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Fisheries Catch Reconstructions : West Africa : Part II Belhabib, Dyhia; Pauly, D. (Daniel) 2015

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ISSN 1198-6727Number2015 VolumeFisheries Centre Research ReportsFisheries catch reconstructions:West aFrica, Part ii23 3ISSN 1198-6727 Fisheries Centre, University of British Columbia, CanadaFisheries Centre Research Reports2015 Volume  Number Fisheries catch reconstructions: West aFrica, Part iiEdited byFisheries Centre Research Reports 23(3)128 pages © published 2015 byThe Fisheries Centre,University of British Columbia2202 Main MallVancouver, B.C., Canada, V6T 1Z4 ISSN 1198-6727 Dyhia Belhabib and Daniel PaulyContentA Research Report from the Fisheries Centre at UBCFisheries centre research rePorts are abstracted in the Fao aquatic sciences and Fisheries abstracts (asFa)issn 1198-6727  Fisheries Centre Research Reports 23(3)128 pages © Fisheries Centre, University of British Columbia, 2015Fisheries Centre Research Reports 23(3)2015Edited byEditors’ Preface iFisheries in troubled waters: A catch reconstruction for Guinea-Bissau, 1950-2010 1Dyhia Belhabib and Daniel PaulyCôte d’Ivoire: fisheries catch reconstruction, 1950-2010 17Dyhia Belhabib and Daniel PaulyThe marine fisheries of Togo, the ‘Heart of West Africa,’ 1950 to 2010 37Dyhia Belhabib, Viviane Kutoub and Daniel PaulyBenin’s fisheries: a catch reconstruction, 1950-2010 51Dyhia Belhabib and Daniel PaulyAn overview of the Nigerian marine fisheries and a re-evaluation of their catch from 1950 to 2010 65Lawrence Etim, Dyhia Belhabib and Daniel PaulyReconstructing fisheries catches for Cameroon between 1950 and 2010 77Dyhia Belhabib and Daniel PaulyGabon fisheries between 1950 and 2010: a catch reconstruction 85Dyhia BelhabibThe implications of misreporting on catch trends: a catch reconstruction for the People’s Republic of the Congo, 1950-2010 95Dyhia Belhabib and Daniel PaulyAn attempt at reconstructing the marine fisheries catches in the Congo  (ex-Zaïre), 1950 to 2010 107Dyhia Belhabib, Sulan Ramdeen and Daniel PaulyRich fisheries and poor data: a catch reconstruction for Angola, 1950-2010, an update of Belhabib and Divovich (2014) 115Dyhia Belhabib and Esther Divovich  Dyhia Belhabib and Daniel PaulyiThis Fisheries Centre Research Report presents reconstruction of the marine fisheries catches of 10 West African countries. Despite their distinctive geographic, historic and cultural features, these countries share a common past in that they were all colonized in the first half of the 20th century, by a motley assemblage of European powers. These were,  from North to South:  Guinea-Bissau by Portugal; Côte d’Ivoire by France; Togo by Germany, then France; Benin by France; Nigeria by the United Kingdom; Cameroon by Germany, then France and the UK; Gabon (by France); Congo (Brazzaville) by France; Congo (ex-Zaire) by Belgium; and Angola by Portugal.The development trajectory upon which these West African countries found themselves when they became independent was strongly shaped by this colonialism, which was harsh and difficult to get rid of - particularly for the ex-Portuguese colonies. Traces of colonialism are thus felt at all levels, notably where the struggle for political and economic ‘agency’ after formal independence plunged these countries into perennial political instability (e.g., Guinea Bissau), or long and murderous civil wars and/or wars over natural resources (e.g., Angola, Congo ex-Zaire). Some other countries transited smoothly into neo-colonies, where development and research institutions fail to play their nation-building role, as they serve mainly to maintain previous colonial ties. This has resulted, particularly in the former French colonies, in a general reluctance to transfer knowledge to local institutions. Neo-colonial ties are also illustrated through the profile of exploitation of natural resources, notably fish stocks, to which the former colonial powers often maintains a privileged access. As a result, West African countries did not develop truly national industrial fisheries, which would have formed an obstacle to the foreign industrial fleets that gradually invaded their Exclusive Economic Zones (EEZ).  As a consequence, in most of their coastal areas, foreign vessels and the stock depletions they cause(d) hinder the development of the artisanal and local industrial fisheries.This has led to growing tensions, which are only partly alleviated by foreign fleets being reflagged to the countries in whose waters they operate, and landing the low-value part of their catch locally.The resolution of these tensions, increased by growing demands for fish by both consumers in Western Europe and East Asia, and the inhabitants of West African countries, will determine whether issues of food security will prevail over the power of international markets. This is the reason why we contrast, for each country, the catches of small-scale fisheries, which mostly enter the local economies, and those of industrial (mostly foreign) fisheries, which tend to hinder their development. The Editors Vancouver, April 2015editors’ PreFaceGuinea-Bissau - Belhabib and Pauly 1Fisheries in troubled Waters: a catch reconstruction For Guinea-bissau, 1950-20101Dyhia Belhabib and Daniel PaulySea Around Us, Fisheries Centre, University of British Columbia, 2202 Main Mall, Vancouver, BC, V6T 1Z4, Canada d.belhabib@fisheries.ubc.ca; d.pauly@fisheries.ubc.caabstractMarine fisheries catches of Guinea Bissau were reconstructed to account for sectors that have never been considered previously. Two main sectors were identified, the large-scale (industrial) sector, which includes foreign industrial catches, the catches of so-called ‘domestic’ vessels, and the discards they both generate. The other main sector consists of the small-scale fisheries, including subsistence, recreational and, most importantly, the artisanal sectors. Catches were estimated at 13 million tonnes between 1950 and 2010, of which 1.6 million tonnes were caught by domestic fisheries. This is much higher than the 207,000 tonnes supplied to the FAO on behalf of Guinea Bissau. A sharp decline in catches is noted over the last decade, probably due to over-exploitation which threatens the food security of the population of Guinea-Bissau. On the other hand, losses due to illegal fisheries are very high, and controlling illegal fishing will go a long way towards improving the status of the fisheries of, and seafood supply to, Guinea Bissau.introductionGuinea Bissau is located at the edge of the Guinea Current Large Marine Ecosystem (LME) and the Canary Current LME between 11°52’N and 15°36’W. Thanks to coastal upwellings and extensive nutrients from river input, the extensive continental shelves off Guinea Bissau – one of the largest in West Africa – within an Exclusive Economic Zone of 106,000 km2 (Figure 1) is home to an estimated one million tonnes of fisheries resources, of which, according to Anon. (2009), 350,000 to 500,000 tonnes could be extracted annually.The history of Guinea Bissau could be described as eventful. Following independence from Portuguese colonial rule in 1974, after a long war of liberation, the first government was overthrown, and it was only twenty years later that the first democratic elections were held. A civil war occurred after a few years, in 1998, followed by a first coup d’état in 1999 and another in 2003. In 2004, the mutiny of a military faction again caused unrest, and eventually led, in 2009, to another coup d’état, after which a new government was elected. The sudden death of the newly elected president in 2012 led to another coup d’état. Unsurprisingly, these events stifled the development, economic and otherwise, of Guinea Bissau, now listed as one of the poorest countries in the world (www.worlbank.org); see also Fernandes (2012).This, along with agricultural resources limited almost exclusively to cashew nuts, left fisheries as one of the few avenues for economy growth and food security (Dia and Bedingar 2001), although the people of Guinea Bissau were seen as “lazy fishers” in colonial times because they lacked a strong fishing tradition (Bordonaro 2006).Yet, although the country’s official statistics show that Guinea Bissau strongly depends on one export commodity – with 99% of the exports, Guinea Bissau is more dependent on cashew nuts than Nigeria is on oil – the fees from foreign fishing access agreements account for 40% of government revenues. This figure, which is among the highest in the world (Anon. 2013), demonstrates how important fishing is to the country’s economy (Anon. 2010).1 Cite as: Belhabib, D. and Pauly, D. (2015) Fisheries in troubled waters: a catch reconstruction for Guinea-Bissau, 1950-2010. pp. 1-16. In: Belhabib, D. and Pauly, D. (eds). Fisheries catch reconstructions: West Africa, Part II. Fisheries Centre Research Reports vol.23(3). Fisheries Centre, University of British Columbia [ISSN 1198-6727].Figure 1.  Map of Guinea-Bissau with its Exclusive Economic Zone (EEZ). 2While legal foreign fishing started in 1978, with the first agreement signed with the former Soviet Union (DINÂMICA 2008), the first management plan ever to be implemented was only promulgated in 1996 (Anon. 2009). Other management plans dealt with capacity limits and total allowable catch, but given the very poor statistics and other constraints, the objectives of the plans were not met (Anon. 2009), repeating the unfortunate experience of fisheries development projects in the 1970s (Bordonaro 2006). Meanwhile, fish biomass in the Exclusive Economic Zone (EEZ) of Guinea-Bissau appears to have declined to at least 50% of its value in 1963, when the first acoustic survey was conducted, by ‘la Rafale’ (Anon. 2009).Official figures indicate that fisheries in Guinea Bissau consist of two main sectors. The artisanal sector relies on dugout canoes called nhominkas, of which about one quarter are motorized, and Senegalese-type pirogues of which 83% are motorized (Anon. 2009). The industrial sector consists of licensed foreign vessels, some of which are chartered and fly the flag of Guinea Bissau (Dia and Bedingar 2001). A thorough literature search revealed, however, the existence of other sectors, i.e., subsistence fishing, conducted mostly by women, and recreational fishing, popular among expatriates in Guinea-Bissau, and occurring in over twenty islands of the Bijago Archipelago. Finally, there are discards generated by the industrial fishing sector, and the illegal foreign fishing sector, as elsewhere in West Africa.There is no regular monitoring system for fisheries in Guinea Bissau, but surveys were conducted by the Department of Fisheries in 1998, 2001 and 2003 (INS 2009), which included the number of pirogues and fishers, and estimates of the artisanal catch. Industrial catches are based on industry declarations and are grossly under-estimated (Dia and Bedingar 2001).The present study presents the first exhaustive and comprehensive estimation of total marine and estuarine fisheries withdrawals from the waters of Guinea Bissau, including all the sectors alluded above for over six decades.methodsArtisanal fishingIn contrast to its neighbours, notably Senegal, Guinea Bissau does not have a long-standing fishing tradition (Campredon and Cuq 2001), and while in the past, nhominkas were commonly used, artisanal fishing by locals started only in the mid-1970s (Tvedten 1990; Chavance 2004). Thus, here the artisanal sector is divided into two categories, distinguished by the craft used, Senegalese nhominka pirogues and local dug-out canoes, or pailão, which have a capacity that is a third of that of the Senegalese nhominka pirogue (Tvedten 1990).Table 1.   Artisanal effort anchor points. Italics indicate interpolations and calculated values. (note that 100%–% nhominka effort =national effort)Year Total effort Source NhominkaEffort % Sourcec1950 195 Chavance (2004) 195 100 Assumption1951 195 Chavance (2004) 195 1001952 215 Chavance (2004) 215 1001953 234 Chavance (2004) 234 1001954 254 Chavance (2004) 254 1001955 273 Chavance (2004) 273 1001956 313 Chavance (2004) 313 1001957 313 Chavance (2004) 313 1001958 313 Chavance (2004) 313 1001959 313 Chavance (2004) 313 1001960 313 Chavance (2004) 313 1001961 313 Chavance (2004) 313 1001962 352 Chavance (2004) 352 1001963 352 Chavance (2004) 352 1001964 352 Chavance (2004) 352 1001965 352 Chavance (2004) 352 1001966 391 Chavance (2004) 391 1001967 352 Chavance (2004) 352 1001968 430 Chavance (2004) 430 1001969 430 Chavance (2004) 430 1001970 391 Chavance (2004) 391 1001971 430 Chavance (2004) 430 1001972 469 Chavance (2004) 469 1001973 547 Chavance (2004) 547 1001974 547 Chavance (2004) 520 95 Tvedten (1990)a1975 547 Chavance (2004) 493 90 Interpolation1976 547 Chavance (2004) 467 85 Interpolation1977 547 Chavance (2004) 440 80 Interpolation1978 547 Chavance (2004) 413 75 Interpolation1979 586 Chavance (2004) 414 71 Interpolation1980 586 Chavance (2004) 385 66 Interpolation1981 586 Chavance (2004) 356 61 Interpolation1982 625 Chavance (2004) 349 56 Interpolation1983 664 Chavance (2004) 339 51 Interpolation1984 625 Chavance (2004) 288 46 Interpolation1985 850 Weber and Durand (1986)350 41 Interpolation1986 664 Chavance (2004) 241 36 Interpolation1987 703 Chavance (2004) 221 31 Interpolation1988 1,094 Chavance (2004) 290 26 Interpolation1989 1,445 Chavance (2004) 312 22 Interpolation1990 1,836 Chavance (2004) 306 17 Tvedten (1990)b1991 1,797 Chavance (2004) 307 17 Interpolation1992 1,836 Chavance (2004) 322 18 Interpolation1993 1,836 Chavance (2004) 330 18 Interpolation1994 1,914 Chavance (2004) 352 18 Interpolation1995 1,914 Chavance (2004) 361 19 Interpolation1996 1,953 Chavance (2004) 376 19 Interpolation1997 1,914 Chavance (2004) 377 20 Interpolation1998 1,953 Chavance (2004) 393 20 Interpolation1999 1,953 Chavance (2004) 402 21 Interpolation2000 2,490 Dia and Bedingar (2001)523 21 Interpolation2001 2,379 Interpolation 512 21 Dia and Bedingar (2001)2002 2,269 Interpolation 466 21 Interpolation2003 2,158 Interpolation 425 20 Interpolation2004 2,048 Interpolation 385 19 Interpolation2005 1,937 Interpolation 347 18 Interpolation2006 1,827 Interpolation 311 17 Interpolation2007 1,716 Interpolation 277 16 Interpolation2008 1,606 Interpolation 245 15 Interpolation2009 1,495 Anon. (2009) 215 14 Anon. (2009)2010 1,495 IRD (2011) 215 14% IRD (2011)a) artisanal national fishing started here;b) Nhominka pirogues represented around 17% of the total in the area sampled;c) the number of pailão canoes is obtained as the difference between the total effort and the nhominka effort.Guinea-Bissau - Belhabib and Pauly 3Three major surveys were conducted in Guinea Bissau to estimate total artisanal effort for 1998, 2001 and 2003 (INS 2009), while the artisanal catch data included only the fish sold through the main market places up to the early 1990s, thus leaving a large part of catches unreported (Tvedten 1990; Kebe et al. 1993). Effort data were scattered across the literature and used unless contradictory; numbers that appeared too low or too high compared to the general average were not used. Total effort, i.e., the number of pirogues, was interpolated to complete the estimate for intervening years (Table 1). Using the few anchor points documenting the effort by category (Table 1), we estimated, and then interpolated the percentage of each category. We obtained the effort per category for the remaining years by multiplying the resulting rates (percentage of nhominka and pailão pirogues over the total) by the total number of pirogues (Table 1).For 1990, Tvedten (1990) estimated a CPUE of 4.16 t∙pirogue-1∙month-1 for 8 months fishing, i.e., 33.2 t∙pirogue-1 for the nhominka pirogues. For 2001, nhominka CPUE was estimated at 150 kg∙pirogue-1∙day-1 for 200 fishing days, i.e., 30 t∙pirogue-1 (Dia and Bedingar 2001). Similarly, Tvedten (1990) documented a 1990 CPUE of 9.6 t∙canoe-1 for the pailão. Assuming the same decreasing trend for CPUEs to 2001, we applied the percentage of change observed for the nhominka CPUE to the pailão CPUE, and estimated the latter at 8.67 t∙canoe-1 for 2001. Given the clear signs of over-exploitation (Anon. 2009), we assumed the CPUE was a conservative 10% higher in 1950 compared to that in 1990. We interpolated to fill the gaps, and extrapolated the trend forwards from 2001 and 2010 to reflect on the decrease of CPUEs. The artisanal catch per category is the product of the effort and the CPUE of each category. Taxonomically, species caught by the artisanal sector are those used for local consumption. They include estuarine species like bonga shad (Dia and Bedingar 2001) and demersal species (Table 2).Migrant fisher catchesMigrant fishers are here defined as foreign artisanal fishers operating on pirogues and landing their catches outside Guinea Bissau. The most common case in Northwest Africa is the Senegalese migrant fishing activity. Their catches were estimated by Belhabib et al. (2014) as the product of the effort (number of Senegalese pirogues x number of trips) by the CPUE per trip. For purposes of the Sea Around Us, these Senegalese catches taken in Guinea Bissau waters are treated as ‘industrial’, despite being of ‘semi-industrial’ or even large ‘artisanal’ nature.Subsistence fishingPrior to the independence of Guinea Bissau from Portugal in 1974, fishing was primarily for subsistence (DINÂMICA 2008). Subsistence fishing is carried out by many people along Guinea Bissau’s coastline (Anon. 2009). Some authors reported that most of the coastal population practices subsistence fishing (Said 2007); others allude to thousands of women and subsistence fishers operating in Guinea Bissau (Garcia 1992) and providing more animal protein than any other sectors for local consumption (Anon. 1994). This is compatible with the observation that almost all the animal protein consumed in Guinea Bissau comes from fish (Anon. 2009).For 1979, Garcia (1992) reported a (survey-based) consumption rate of 28 kg∙person-1∙year-1, relying mostly on artisanal and subsistence catches, complemented by occasional imported fish. By multiplying the per capita fish consumption by the total population of 1,033,000 (Garcia 1992), we estimated a total fish supply of 28,924 t for 1979. We removed that part of industrial catches landed in Guinea, corresponding to 6,303 t∙year-1 (COPACE 1981), the imports (caught outside Guinea Bissau) and exports (unavailable to fish consumers) of 260 t∙year-1 and 4,435 t∙year-1, respectively. Therefore, we estimated a total small-scale catch of 17,661 t∙year-1. Given that a significant part of fish consumption is from subsistence fishing, women in estuarine waters, on beaches, or from household subsistence activities (Garcia 1992), we assumed 40% of the previous small-scale supply was generated by subsistence fishing, i.e., 7,064 t in 1979. We divided this catch by the total population to obtain a per capita consumption supported by subsistence fisheries (6.8 kg∙person-1 for 1979). Given the evidence of a higher consumption rate from subsistence fishing in the past (before independence), when most catches were from the subsistence sector, we conservatively assumed this catch rate was 50% higher in 1950, i.e., 10.2 kg∙person-1, 30% higher in 2000 than in 1979 (8.9 kg∙person-1) due to the decline in artisanal supply during the civil war, and the shift of subsistence fishing to market artisanal fishing during the 1980s and 1990s (Tvedten 1990). Dia and Bedingar (2001) reported a consumption rate of 26 kg∙person-1∙year-1 for the last decade. Thus, by following the same approach as for 1979, but assuming a lower rate for subsistence fishing (35%), and with landings of 6,650 t and imports and exports of 1,456 t and 4,526 t, respectively, we estimated the subsistence catch at 16,735 t for 2010. Table 3 summarizes the methods used. We then interpolated between these estimates to complete the time series.Table 2.   Species composition of the artisanal sector catches in Guinea Bissau. Numbers from 1993 to 2003 converted to percentages and then averaged (ECOST 2007).Scientific name Common name PercentageEthmalosa fimbriata Bonga shad 54Argyrosomus regius Meagre 17Penaeidae Shrimps 10Cynoglossus spp. Soles 9Carlarius heudelotii Smoothmouth sea catfish 6Caranx spp. Carangids (jacks) 2Pomadasys jubelini Sompat grunt 1Table 3.   Summary of the methods used to estimate subsistence catches in Guinea Bissau.Year Population Consumption kg∙person-1 Notes1950 518,888 80% higher than in 1979 10.2 Part of the per capita consumption that comes from subsistence1979 1,033,000 [28 x Population–Landings–(Imports +Exports)] x 0.46.8 Estimated as 40% of the supply from small scale2000 1,241,000 30% increase due to the decrease in artisanal supply8.9 During the civil war, pirogues have been stolen2010 1,515,000 [26 x Population–Landings–(Imports +Exports)] x 0.3511.0 No significant change in fish consumption since 2000 4Taxonomically, catches from mangrove-rich areas and/or the Bijagos Islands constitute a significant part of subsistence fisheries. Therein, molluscs gathered by women, mainly wild oysters (Crassostrea gasar), arks (Anadara senilis) and murex shells (Murex spp.) represent the dominant taxa, assumed here to make up 80% of the catch, divided evenly by the three above taxa. The remaining 20% are assumed to have the same taxonomic composition as the artisanal catches (see Table 2), with shrimp catches (2%) (Failler 2005) consisting mainly of white shrimp (Farfantepenaeus notialis; 73 %) and tiger shrimp (Penaeus monodon; 26%).Recreational fishingSport fishing is apparently a notable segment of tourism in the Bijagos archipelago (Anon. 2010), but little information is available on the number of visitors to the archipelago, or the number of tourists using the services of fishing ‘safaris’. Anon. (2010) reported the total number of international standard beds made available for tourists at 76 daily for 2001, each stay lasting 10 days at average, for 6 days fishing2,3 during a tourist season lasting 6 months, which represents a potential of 1,387 tourists (Table 4). For 2012, the camps established for tourists in Guinea Bissau were visited by 1,200 persons, of which only 50% went fishing. There also were between 150 and 350 fishers (250 on average) for each of 4 other camps, and 500 visitors per year to a near-shore hotel, of which only a minority (20%) went fishing (Pierre Campredon, IUCN Guinea Bissau, pers. comm.). Therefore, the overall number of recreational fishers for 2012 was estimated as the sum of fishers for each camp and/or hotel, i.e., 1,500 fishers. We assumed that recreational fishing began in Guinea-Bissau in the late 1980s, with the emergence of the Bijagos archipelago as a tourist destination (CLPV 2012). Therefore, we assumed the number of recreational fishers was zero in 1988 and filled in the gaps with linear interpolations. We divided the resulting estimate by 2 for the years when there was a coup d’état and/or civil war, i.e., 1998, 2003 and 2009 (Table 4). To estimate the catch per fisher, we collected species and weight catch data from 30 Youtube videos documenting the experience of recreational fishers. From these, we could assemble catch data for 25 tourists and 17 fishing days, and estimated the catch per day per tourist by dividing the resulting total catch by the number of tourists and filtering out the released catch (representing 12%). The CPUE was then estimated at 18.7 kg∙tourist-1∙day-1. The annual catch is the product of the CPUE by the number of tourists per year by the number of days. We also derived the catch composition using visual recognition of species, matched with average weight data from FishBase (www.fishbase.org), which when multiplied by the number of individuals, allowed for the estimation of catch percentage per taxon (Table 5).Industrial fishingIndustrial fishing in Guinea Bissau is conducted by foreign vessels chartered or reflagged to Guinea Bissau, under private or partnership agreements. Although these vessels may fly the flag of Guinea Bissau, they are not considered domestic vessels (Gomes Barbosa 2009). Catches made under these agreement are generally landed elsewhere, notably in the Canary Islands (Spain) and Senegal (Anon. 2009) and are not reported to Guinea Bissau (COPACE 1981; Anon. 2010), nor anywhere else. Even the presence of observers onboard was revealed to be ineffective, including on EU vessels (Anon. 2009). Fleets (or flags) from many countries operated in the waters of Guinea Bissau, notably China, Korea, the EU, Russia, Cyprus, Senegal, Sierra Leone, Panama, Honduras, St Vincent and Grenadine, Morocco and Mauritania (DINÂMICA 2008). However, data on the vessel numbers and other information were scarce and often contradictory.As one source stated that industrial fishing in Guinea Bissau was initiated in the mid-1950s (Chavance 2004), we set its start in 1955, and performed a series of linear interpolations to complete the effort time series for each country (Table 6). We then estimated the CPUE from three different fleet categories when data were available. For 2  http://www.fishipedia.com/destinations/guinea-bissau/ accessed on 17/05/20133  http://www.worldsportfishing.com/by-destination/guinea-bissau/guinea-bissau-prices-details/ accessed on 17/05/2013Table 4.   Estimation of the number of recreational fishers in Guinea Bissau.Year Fishers Event1950-1988 0 See text1989 1051990 2101991 3161992 4211993 5261994 631 First elections1995 7371996 8421997 9471998 526 Civil war1999 1,1572000 1,2622001 1,3682002 1,3802003 696 Coup d’état / Period of unrest2004 1,404 Mutiny of military faction / Period of unrest2005 1,4162006 1,4282007 1,4402008 1,4522009 732 Coup d’état2010 1,4762011 1,4882012 1,500 Death of president / Coup d’étatTable 5.   Taxonomic breakdown for the recreational fishery in Guinea Bissau.Common name Scientific name %Barracudas Sphyraena barracuda 33Carangids or jacks Carangidae 14Cobia Rachycentron canadum 19Crevalle jack Caranx hippos 9Leerfish Lichia amia 6Marine fishes nei - 5Guinean snapper Lutjanus agennes 3Groupers Epinephelus spp. 2Meagre Argyrosomus regius 2Blackchin guitarfish Rhinobatos cemiculus 2Nurse shark Ginglymostoma cirratum 2Sparids Sparidae 1Sharks Selachimorpha spp. 1Requiem sharks Carcharhinus spp. 1Guinea-Bissau - Belhabib and Pauly 5Russia, 68 pelagic trawlers (4,000 to 6,000 GRT) operating between 1981 and 1991 caught around 130,000 t∙year-1 of small pelagics (DINÂMICA 2008), which corresponds to a CPUE of 1,912 t∙vessel-1∙year-1. Given the recent interest in the exploitation of small-pelagics by large trawlers in Guinea Bissau and the absence of evidence of small-pelagic over-exploitation, we assumed a constant CPUE over time between 1950 and 2010. For China, operating cephalopod, shrimps and fish trawlers (Anon. 2013), we estimated from data in Pauly et al. (2013), a CPUE of 1,200 t∙vessel-1∙year-1 between 2000 and 2010. Based on the fact that these stocks are overexploited, we assumed the CPUE was 20% higher in 1950 compared to 2000 and then interpolated linearly. The use of motherships (which Table 6.   Flag composition of the industrial fleet operating in Guinea Bissau, 1950-2010.Year Russiad China Motherships (Korea)Europe Korea Japan Africa References1950-19550 0 0 0 0 0 01956 0 0 0 4 1 0 11957 1 0 0 8 3 1 11958 1 0 0 11 4 1 21959 1 0 0 15 5 1 21960 2 0 0 19 7 1 31961 2 0 0 23 8 2 41962 2 0 0 27 9 2 41963 3 0 0 30 10 2 51964 3 0 0 34 12 2 51965 3 0 0 38 13 3 61966 4 0 0 42 14 3 61967 4 0 0 46 16 3 71968 4 0 0 49 17 3 81969 5 0 0 53 18 4 81970 5 0 0 57 20 4 91971 5 0 0 61 21 4 91972 6 0 0 65 22 4 101973 6 0 0 68 24 5 111974 6 0 0 72 25 5 111975 7 0 0 76 26 5 121976 7 0 0 80 27 5 12 FAO (1979)1977 27 0 0 94 29 6 131978 48 0 0 107 30 6 131979 68 0 0 121 31 6 13 Cissé (1980)1980 68 0 0 123 30 6 13 a1981 68 0 0 124 28 5 131982 68 0 0 126 27 5 141983 68 0 0 127 26 5 141984 68 3 0 129 24 5 14 b1985 68 6 0 130 23 4 14 Weber and Durand (1986)1986 68 9 0 132 21 4 151987 68 11 0 133 20 4 151988 68 14 0 135 18 4 151989 68 17 0 136 17 3 151990 15 20 0 138 16 3 16 Kébé et al. (1993)1991 15 17 0 123 21 3 24 Kébé et al. (1993)1992 15 20 0 79 19 3 14 Kébé et al. (1993)1993 14 20 0 81 20 2 131994 14 21 0 83 22 2 121995 13 21 0 85 24 2 101996 13 21 0 88 25 2 9 Anon. (2009)1997 12 21 0 90 27 2 7 Anon. (2009)c1998 11 22 0 92 29 2 6 Anon. (2009)1999 11 22 0 94 31 1 5 Anon. (2009)2000 10 34 23 109 32 14 3 Anon. (2009), Anon. (2013)2001 5 31 21 101 9 2 3 Anon. (2009), Dia and Bedingar (2001) and Anon. (2013)2002 6 33 20 108 18 7 3 SOFRECO (2002) and Anon. (2013)2003 6 32 18 102 22 9 4 Anon. (2013)2004 5 30 17 91 17 6 4 Anon. (2010) and Anon. (2013)2005 5 25 15 74 34 1 12 Anon. (2009), Gomes Barbosa (2009), Anon. (2013)2006 5 34 13 49 20 3 15 Anon. (2010), Gomes Barbosa (2009), Anon. (2013)2007 5 27 11 59 22 2 17 Anon. (2009), Gomes Barbosa (2009), Anon. (2013)2008 4 19 8 84 12 4 3 Anon. (2009), Anon. (2013)2009 4 19 6 56 10 4 0 Anon. (2009), Anon. (2013)2010 4 19 4 56 10 4 0 Anon. (2013)a) Europe started agreements with Guinea in 1980 (Anon. 2010);b) China started fishing in 1984 (Anon. 2010);c) In 1997, 202 licenses were issued for US $ 16 million; half the licenses went to EU countries, the other half to Senegal, Japan and chartered vessels (Dia and Bedingar 2001);d) The former USSR was Russia (DINÂMICA 2008). 6take small pirogues and artisanal fishers onboard to fish for periods up to 3 months) by Korea in Guinea Bissau started in 2000. These ‘reefers’ were taking up to 40 pirogues of a Senegalese type (Anon. 2013), operating similarly to the artisanal nhominka fleet, with a CPUE of 30 t∙pirogue-1∙year-1 in 2000. However, they were operating only half of the year in Guinea Bissau, i.e., 600 t∙reefer-1∙year-1 when multiplied by the total number of pirogues onboard each vessel. The efficiency and production per boat taken onboard increased during the last decade at an alarming extent (Anon. 2013); therefore we assumed the CPUE increased by 20% in 2010 compared to the CPUE of 2000, i.e., 720 t∙reefer-1∙year-1. For the rest of the fleet, catches were estimated at 60,000 t∙year-1 of mostly demersal species for a total fleet of 145 vessels (Dia and Bedingar 2001), i.e., a CPUE of 414 t∙vessel-1 for 1996. Given the over-exploitation of demersal taxa, we assumed the CPUE was 20% higher in 1950 and 10% lower in 2010, and then interpolated linearly. We then multiplied the effort by the corresponding CPUE to estimate industrial catches per country from the waters of Guinea Bissau between 1950 and 2010.To investigate the real ownership of vessels flying Belizean flags of convenience (FoC), we cross-checked the most recent position of vessels flying Belizean flag listed in www.grosstonnage.com (accessed on 15/05/2013) with the reflagging and ownership history, and inferred the real ownership. Of the total Belize vessels, 16% were Japanese, 6% Norwegian, 15% Spanish, 2% Swedish, 15% Russia, 12% Chinese, 8% Ghanaian, 6% Ukrainian, 2% Italian, and 15% from Iceland, the UK, the United States and others. Only 4% of these vessels, owned by Japanese firms, appear to be operating within the EEZ of Guinea Bissau4. We applied the same method to the flags of Panama, St Vincent and Grenadine, and Honduras, while vessels from Togo were assumed to be of Spanish ownership.5 Twenty-one percent of Panama-flagged vessels were owned by South Korean companies and the remaining was divided between 20 other countries. Assuming that Panama-flagged vessels operating in Guinea Bissau were mostly of South Korean origin aligns well with similar conclusions for neighbouring Guinea (Belhabib et al. 2013). Following the same approach, vessels flagged to St Vincent and Grenadines were assigned predominantly to Russian (30%) and Spanish companies (26%), while Japan and Latvia and others represent 13%, 17% and 13% of the fleet flagged to St Vincent and Grenadine, respectively. However, most of the vessels flagged to Russia were based and/or operating in Namibia; thus, we concluded that vessels flagged to St Vincent and Grenadines operating in Guinea Bissau most likely had a Spanish ownership. For the Honduran flag, most of the fleet is owned by Taiwanese and Chinese companies (71%). Given the diplomatic relations and the history between Guinea Bissau and Taiwan in the past, we assumed that the fleet flying Honduran FoC and operating in Guinea Bissau was from Taiwan (Table 6).To disaggregate catches onto taxa, we used the species disaggregation by Anon. (2009) and subdivided the major categories by the number of taxa represented in each category for African and FoC countries (Table 7). For example, the category ‘mackerel, horse mackerel and sardinella’ (48%) was divided into 3 taxa with 16% each. For Russia, we used the species disaggregation provided by ter Hofstede and Dickey-Collas (2006) and for Europe and Korea (i.e., mostly demersal fleets), we used the species disaggregation provided by Belhabib et al. (2013) for Guinea (Table 8). Similarly, we applied the species breakdown provided by Lesnoff et al. (1999) to Chinese catches.Illegal and unregulated fishingThe number of foreign fishing vessels operating without a license in Guinea Bissau was estimated at 33% of the industrial fleet for 2005 (Agnew et al. 2010), i.e., 47 vessels. For 2007, Anon. (2009) estimated the number of industrial vessels operating in Guinea Bissau at 30, a number that we assumed constant between 2007 and 2010. We interpolated the effort for 2006 (39 vessels), and estimated an industrial CPUE of 573 t∙vessel-1 for 2005, 622 t∙vessel-1 for 2006, 591 t∙vessel-1 for 2007, 538 t∙vessel-1 for 2008, 585 t∙vessel-1 for 2009 and 580 t∙vessel-1 for 2010, by dividing the total industrial catch (legal segment) by the total number of legal vessels per year. We then multiplied these CPUEs by the corresponding number of illegal vessels, and estimated illegal catches between 2005 and 2010. Then we interpolated from zero in 1955, when industrial fishing began in Guinea Bissau to the first estimate in 2005. Catches taken within the EEZ-equivalent 4  Of the total, 21% were located in Dakhla (Western Sahara), 18% in Las Palmas, 14% in Conakry (Guinea), 7% in Côte d’Ivoire, 10% in Ghana, 4% in Cape Town (South Africa), 7% in Namibia, 4% in China, and 4% in Panama. 5  http://www.stopillegalfishing.com/togo.php accessed on 13/06/2013Table 7.  Species disaggregation for industrial catches (in %) by foreign catches in Guinea BissauEnglish name Scientific name %African and Flag of Convenience countriesaMackerel Scomber spp. 16.00Horse Mackerel Trachurus spp. 16.00Sardinella Sardinella spp. 16.00Breams Sparidae 8.00Sweetlips Haemulidae 8.00Croakers Sciaenidae 8.00Catfishes Ariidae 8.00Soles Cynoglossus spp. 8.00Cuttlefish Sepia spp. 3.00Octopus Octopus spp. 3.00Tuna Thunninae 5.00Shrimps Penaeus spp. 1.00Crabs Callinectes spp. 1.00EU and KoreabClupeidae Clupeidae 0.90Croakers Scianidae 40.00Breams Sparidae 6.20Marine fishes nei - 4.00Sharks Selachimorpha 1.70Crabs Callinectes spp. 2.60Shrimps Penaeus spp. 19.00Cephalopods Cephalopoda 25.00Tuna Thoninnae 0.30RussiacCunene horse mackerel Trachurus trecae 3.70Round sardinella Sardinella aurita 63.80Flat sardinella Sardinella maderensis 4.60Chub mackerel Scomber japonicus 9.30European pilchard Sardina pilchardus 12.90Marine fishes nei - 5.70a (Anon. 2009);b (Belhabib et al. 2013);c (ter Hofstede and Dickey-Collas 2006).Guinea-Bissau - Belhabib and Pauly 7waters of Guinea Bissau prior to the EEZ declaration by Guinea Bissau in 1986 are considered ‘unregulated’ but legal. Unregulated activities are conducted mostly by China and Korea, and to a lesser extent by the EU (Italy) (Agnew et al. 2010; Anon. 2013). Therefore, we assumed that between 1955 and 1983, 100% of catches were Korean, and then between 2000 and 2010 Chinese and Korean catches each represented 45% of the illegal catch, and 10% were Italian. We interpolated these percentages and completed the time series. Thereafter, we multiplied these percentages by total estimated illegal and unregulated catches. We used the same species breakdown as for the legal component of the industrial fishery.DiscardsDiscards of the trawl fishery in Guinea Bissau are estimated at 87% of the catch (Kelleher 2004), i.e., 6.7 times the landings for 2004, and between 60 and 62% for 2010 (Anon. 2009), i.e., 1.5 times the landings. While these estimates are strongly divergent, the over-exploitation of fish species might have led to keeping more by-catch, or selling the latter to artisanal fishers, a pattern observed also in Liberia, Senegal and Ghana. Therefore, we conservatively used the latter rates for the demersal fleets. We separated out demersal from pelagic catches to account for the demersal portion of the retained catch, then applied the latter discard rate to demersal catches between 1950 and 2010. The taxonomic composition of the discards was documented by Caverivière and Rabarison Andriamirado (1988) for the southern areas of Senegal as including bigeye grunt (Brachydeuterus auritus), lesser African threadfin (Galeoides decadactylus), Atlantic bumper (Chloroscombrus chrysurus), cuttlefish (Sepia spp.), largehead hairtail (Trichiurus lepturus), catfishes (Arius spp.), croakers (Pseudotholithus spp.), and Guinean tonguesole (Cynoglossus monodi). Given the similar profile of the fleets operating in both countries, we assumed this catch composition also applies to Guinea Bissau discards. We allocated an equal percentage to each of these taxa (i.e., 12.5%).resultsArtisanalTotal catches by the artisanal fleets operating in Guinea Bissau were estimated at 1.06 million t between 1950 and 2010. Catches increased from 7,100 t in 1950 to a peak of 33,000 t in 2000 (Figure 2). The small artisanal sector operating nhominkas between 1950 and the early 1970s caught between 7,100 t in 1950 and 14,000 t in 1970 (Figure 2), while catches by the Bissau-Guinean (pailão) fishers were estimated at 344,000 t between 1974, when they started, and 2010. Bissau-Guinean catches peaked at around 17,000 t in 2000, then declined rapidly to around 11,000 t in 2010 (Figure 2). Total catches landed in Guinea Bissau (alluded herein as catches by the two ethnic craft types, (nhominka and pailão) were lower than catch estimates by Failler (2005) between 1991 and 1997, with an average 25,600 t∙year-1 estimated herein, compared to 34,000 t∙year-1 estimated by that author (Figure 2). Reconstructed catches were thereafter similar to 051015202530351950 1960 1970 1980 1990 2000 2010Catch (t x 103)YearNhominkaPailãoTable 7 cont: Species disaggregation for industrial catches (in %) by foreign catches in Guinea BissauChinadMeagre Argyrosomus regius 0.44Catfishes Ariidae 2.03Triggerfish Balistes spp. 0.10Carangidae Carangidae 0.94Cephalopods Cephalopoda spp. 18.93Herrings Clupeidae 4.75Soles Cynoglossus spp. 1.01Breams Sparidae 2.68African sicklefish Drepane africana 0.43Sharks and rays Elasmobranchii 0.30West African ladyfish Elops lacerta 0.11Groupers Epinephelus spp. 0.35Bonga shad Ethmalosa fimbriata 8.75Southern pink shrimp Farfantepenaeus notialis 0.05Lesser African threadfin Galeoides decadactylus 2.96Sweetlips Haemulidae 2.07Snappers Lutjanus spp. 0.32Marine fishes nei - 18.64Hakes Merluccius spp. 0.13Marine crustaceans nei - 0.05Mullets Mugilidae 0.41Octopus Octopus spp. 0.00Shrimps Penaeus spp. 0.02West African goatfish Pseudupeneus prayensis 0.31Royal threadfin Pentanemus quinquarius 0.18Perch-like fish Perciformes 0.55Flatfishes Pleuronectiformes 0.03Giant African threadfin Polydactylus quadrifilis 0.22Grunts Pomadasys spp. 0.71Croakers Pseudotolithus spp. 9.36European pilchard Sardina pilchardus 0.01Sardinella Sardinella spp. 2.61Tuna Scombridae 9.79Cuttlefish Sepia spp. 2.01Catfishes Siluriformes 1.37Soles Solea spp. 4.34Barracudas Sphyraena spp. 0.68Torpedo (ray) Torpedo spp. 0.50Jack mackerels Trachurus spp. 0.16Largehead hairtail Trichiurus lepturus 0.01Drums Umbrina spp. 0.11d (Lesnoff et al. 1999).Figure 2.  Reconstructed artisanal catches (Nhominka and Pailão) from Guinea Bissau, 1950-2010. 8those provided by Gomes Barbosa (2009) and Anon. (2009) during the 1998-2009 time period (Figure 2). Artisanal catches landed in Guinea Bissau were dominated by bonga (Ethmalosa fimbriata; 50% of artisanal) as well as meagre (Argyrosomus regius; 16.3% of artisanal) and shrimp (Penaeus; 9.3% of artisanal).SubsistenceSubsistence catches totalled 535,000 t between 1950 and 2010, which is the equivalent of around half of the artisanal reconstructed catches landed in Guinea Bissau. Subsistence catches increased from 6,400 t in 1950 to 7,000 t∙year-1 in the late 1970s. Following the first development project, conducted in the Bijagos archipelago, subsistence catches increased at a fast pace, to around 11,000 t in 1999, after the 1998 civil war, which because of the decrease in artisanal catches, resulted in a further increase in subsistence catches to 16,700 t in 2010 (Figure 3). Taxonomically, the species the most commonly eaten in Guinea Bissau are reflected in the subsistence catch, i.e., mostly bivalvia (81%) and bonga (11%).RecreationalRecreational catches increased overall since the introduction of sport fishing to Guinea-Bissau. Catches increased from zero in 1988 to a peak of 166 t in 2010 (Figure 4); catches frequently dropped, along with the numbers of recreational visitors to Guinea Bissau, due to political instability. Recreational catches, mostly from protected areas in the Bijagos archipelago, were dominated by carangids (i.e., jacks), cobias and barracudas (Figure 4).IndustrialIndustrial catches (all assigned to foreign beneficial ownership even if flying domestic flag) were estimated at 11.4 million t between 1950 and 2010, increasing from zero in 1955, when industrial fishing began in Guinea Bissau, to a peak of around 387,000 t in 1989 due to the operation of fleets from the former Soviet Union (Russia), then declined to 73,000 t in 2010.Our estimates were 30% higher than the estimate by Kaczynski (2005) for 1981-1982, 52% lower than the estimate provided by Kaczynski (1989) for 1989, 41% higher than the estimates provided by Fond Africain de Developpement (2001) for 1995, around 30% higher than the estimate by Kaczynski and Djassi (2006) for 2003; 11% higher than the estimate by Gomes Barbosa (2009) for 2005. For 2009, our industrial reconstructed catch was similar to the estimate by Anon. (2009) with less than 1% difference (Figure 5a).Catches by the EU dominated in the past between 1955 and the late 1970s, then started decreasing, and were slowly compensated for by Chinese catches, while the Russian presence was overwhelming between the late 1970s and the early 1990s with 130,000 t∙year-1 on average (Figure 5a). Similarly, given the Russian presence, catches were dominated by small-pelagic species, notably sardinella, pilchards and mackerels in the past (Figure 5b). Conversely, demersal species (cephalopods, shrimps and sciaenids) dominate in more recent years, due to the presence of demersal fleets from South Korea, China and the EU.Migrant fishers catches increased from zero in 1970 to 37,000 t in 1995 (compared to 50,000 t estimated by Anon. 2010), then to 51,000 t in 2005 (compared to 111,000 (Gomes Barbosa 2009)), and finally to 58,000 t in 2010 (Figure 2). Our conservative approach uses migrant catch data mainly from surveys and documented effort, while the approach by the literature is doubtful, non-transparent and resulting catches are highly divergent. Catches by migrant fishers were dominated by smoothmouth sea catfish (Carlarius heudelotii), with around a third of catches, and soles (Cynoglossus spp.), with 20% of catches.0246810121416181950 1960 1970 1980 1990 2000 2010Catch (t x 103 )YearOstreaOthersEthmalosa fimbriataAnadaraMurex0204060801001201401601801950 1960 1970 1980 1990 2000 2010Catch (t)YearSphyraena barracudaOthersCaranx hipposCarangidaeRachycentron canadumLichia amiaFigure 3.  Reconstructed subsistence catches from Guinea Bissau, 1950-2010.Figure 4.  Reconstructed recreational catches from Guinea Bissau, 1950-2010.Guinea-Bissau - Belhabib and Pauly 9Illegal and unregulated catchesIllegal and unregulated catches were estimated at 786,000 tonnes between 1950 and 2010. These catches increased from zero in 1950 to a peak of 27,000 t in 2005 and declined thereafter with slightly better monitoring to around 18,000 t in 2010. Illegal catches are taken mostly by Chinese and Korean vessels, given the assumptions stated above (Figure 6).DiscardsDiscards of both the legal and the illegal unregulated sectors were estimated at 5.2 million tonnes between 1950 and 2010, of which 3.9 million tonnes were generated by the legal industrial sector, about 3.7 times the artisanal domestic catch. Discards increased from zero in 1955 to a peak of 162,000 t in 2000 to decrease thereafter to around 82,000 t in 2010 (Figure 7).Total catchesReconstructed total catches from Guinea Bissau were estimated at 13.0 million tonnes between 1950 and 2010, of which 1.6 million tonnes were generated by Guinea Bissau as a flag state compared to 207,000 tonnes supplied to the FAO during the same time period, and 1.2 million tonnes by migrant fishers’ landing catches in Senegal. Total removals from Guinea-Bissau waters increased from around 13,000 t in 1950 (exclusively by small-scale fisheries) to a first peak of 420,000 t in 1989 (Figure 8a), a second peak of 359,000 t in 2000 and then declined steadily to less than 189,000 t in 2010 (Figure 8a). Domestic catches increased slowly from 13,000 t in 1950 compared to 300 t supplied to the FAO, to a peak of 44,000 t in 2000 compared to 5,300 t supplied to the FAO, and then decreased to around 34,000 t in 2010 despite an increasing fishing effort (Figure 8b).Taxonomically, domestic catches were dominated by bivalves and bonga shad and meagre catches caught mostly by the small-scale sectors. The contribution of fish species such as bonga shad, croakers, sciaenids, threadfins and meagre to the total catch, however, decreased over time and was compensated by increasing catches of bivalve (Figure 8c).discussionTotal removals from Guinea Bissau’s EEZ were reconstructed at 13.0 million tonnes between 1950 and 2010; of this, 1.6 million tonnes were domestic (small-scale) and around 503,000 tonnes caught by Guinea Bissau flagged industrial fleet. Catches by Guinea Bissau as a flag state were 10 times higher than the catch data supplied by the FAO (207,000 tonnes). The under-reporting component was significantly higher in the past, around 44 times as much as supplied to and by the FAO, and then decreased to be around 4 times.Although, this work is the first comprehensive attempt to obtain a realistic estimate of removals from the EEZ of Guinea Bissau between 1950 and 2010, the literature contains earlier, but partial attempts. The estimates by Pires (1999), Failler (2005), IRD (2011) and Anon. (2009) for the artisanal sectors were either higher or similar to the reconstructed artisanal catch estimated herein. Estimates of industrial catches, on the other hand, were generally lower than those presented here and can probably be explained by differences in the methods and definitions previously used, which are often unclear.Catch (t x 10 )301020301950 1960 1970 1980 1990 2000 2010Catch (t x 103 )YearSouth KoreaItalyChinaFigure 5.  Reconstructed industrial catches from Guinea Bissau a) by country, “others” represent 9 additional countries and b) by taxon, 1950-2010. Figure 6.  Reconstructed IUU catches from Guinea Bissau by country, 1950-2010. 10Doubtful biomass estimates in Guinea Bissau’s EEZ show a total of 479,000 t∙year-1 of valuable species, of which 96,000 t∙year-1 could be sustainably exploited (Gomes Barbosa 2009). However, such catch levels were reached, and then exceeded already in the 1970s, with catches reaching a maximum of around 400,000 t∙year-1 in the late 1980s. This can mean two things; (1) maximum sustainable yield and the corresponding biomass are strongly under-estimated and/or (2) the fisheries of Guinea-Bissau are at the edge of collapse as catches are dangerously high. While these two possibilities are not exclusive, declining domestic catches for over a decade despite (or rather because of) an increasing effort are signs of over-exploitation. The other sign is the decrease in the industrial catch, which according to Anon. (2013), declined because of unsustainable exploitation. In all cases, this MSY level appears to be lower than the Total Allowable Catch of small pelagics set at 100,000 t∙year-1 (Anon. 2009).Cyclic political crises in Guinea Bissau, and extreme poverty (Gomes Barbosa 2009) have certainly affected the behaviour of local populations and their interactions with fisheries resources. For example, catches declined significantly immediately after independence from Portugal, and after the 1998 civil-war. Catches increased rapidly with the introduction of motorized pirogues in the late 1980s, after which they stagnated, a sign of failing development projects. On the other hand, poor populations are driven to compensate for the decline in fish supply due to decreasing artisanal catches by increasing subsistence catches, thus illustrating the importance of fish in the national diet and food security of the country. Fisheries, indeed could play a major role in rebuilding the country’s economy, now further distorted by drug-smuggling, as also manifested in the $100,000 cars that the first author recently saw in the capital city of a country that ranks last in human development index in the world.It is thus important to re-iterate the vital role that fisheries play in Guinea Bissau: of the 120,000 people employed by this sector, 52% are women, and all depend on fish as a source of revenue and basic food stable. Moreover, the value lost to Guinea Bissau because of illegal or undervalued foreign fishing (i.e., either by unlicensed vessels, or foreign vessels misreporting, or landing their catches elsewhere) and the discards they generate was here estimated at around $338 million US annually, which is almost as high as the value generated by drug smuggling in the country (Cornwell 2013). It is clear that Guinea Bissau does not have the capacity to process, or even land a large part of these catches in-situ. However, if an inferred 15% is used as the licence fee (Kaczynski 1989) for illegal vessels, this would mean that Guinea Bissau could capture as much as $15 million US annually. Furthermore, the value of catches by the foreign fleets ($238 million US) should be an incentive to impose sanctions on trans-shipping which is already illegal, enhance the level of monitoring, control and surveillance, and increase license fees.0501001502002503001950 1960 1970 1980 1990 2000 2010Catch (t x 103)YearIndustrialSubsistenceIllegalArtisanalFigure 7.  Reconstructed industrial discards from Guinea Bissau, 1950-2010.Figure 8.  Reconstructed total catches (foreign and domestic) by sector from Guinea-Bissau EEZ, 1950-2010. Guinea-Bissau - Belhabib and Pauly 11 acknoWledGementsWe thank the MAVA Foundation for supporting the project “Sea Around Us in West Africa, research and collaboration”, and acknowledge the support of the Sea Around Us, a collaboration supported by the Pew Charitable Trusts and the Paul G. Allen Family Foundation. D.B. thanks the Centre for Applied Fisheries Research of Guinea Bissau (Centro de Investigação Pesqueira Aplicada–CIPA) for their hospitality and transparency during a short visit to Guinea Bissau.reFerencesAgnew D, Walmsley SF, Leotte F, Barnes C, White C and Good S (2010) West Africa regional fisheries project. Estimation of the cost of illegal fishing in West Africa. Final report, MRAG, London. 97 p.Anon. (1994) Planificacao costeira da Guiné Bissau. Relatorio tecnico 1, UICN, Bissau. 150 p.Anon. 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FAO Fisheries Technical Paper 470, FAO, Rome. 134 p.Lesnoff M, Morize E and Traore S (1999) La pêcherie industrielle en Guinée: état et bilan des données disponibles. pp. 175-198 In Domain F, Chavance P and Diallo A (eds.), La pêche côtière en Guinée : ressources et exploitation. Insitut de recherche et de développement, Conakry.Pauly D, Belhabib D, Blomeyer R, Cheung WWWL, Cisneros-Montemayor AM, Copeland D, Harper S, Lam VWY, Mai Y, Le Manach F, Österblom H, Mok KM, van der Meer L, Sanz A, Shon S, Sumaila UR, Swartz W, Watson R, Zhai Y and Zeller D (2013) China’s distant-water fisheries in the 21st century. Fish and Fisheries doi: 10.1111/faf.12032.Pires V (1999) ACP- EU training. Rapport national sur les pêches en Guinée–Bissau. Cours ACP-UE sur la gestion des pêches et de la biodiversité, Dakar, Sénégal, du 12 au 23 avril 1999. EU, Dakar. 5 p.Said AR (2007) Analyse des acteurs de la zone côtière. Le cas de la Guinée-Bissau. Programme « Capacités et connaissances de la FIBA ». FIBA, Bissau. 56 p.Guinea-Bissau - Belhabib and Pauly 13SOFRECO (2002) Diagnostic strategique de filière agro-industrielles. Rapport Guinée-Bissau.765, SOFRECO, Clichy, France. 15 p.ter Hofstede R and Dickey-Collas M (2006) An investigation of seasonal and annual catches and discards of the Dutch pelagic freezer-trawlers in Mauritania, Northwest Africa. Fisheries Research 77(2): 184-191.Tvedten I (1990) The difficult transition from subsistence to commercial fishing. The case of the Bijagos of Guinea-Bissau. MAST 3(1): 119-130.Weber J and Durand H (1986) Le secteur des pêches dans les pays de l’Afrique. Réunion préparatoire pour l’Afrique en vue de la première Consultation sur l’industrie de la pêche, Dakar (Sénégal), 16-19 septembre 1986.86-60897, Organisation des nations unies pour le developpement industriel, Paris. 29 p. 14Appendix Table A1.   FAO landings vs. reconstructed total catch (in tonnes), and catch by sector for Guinea-Bissau, 1950-2010.Year FAO landings Reconstructed total catch Artisanal Subsistence Recreational1950 300 13,500 7,120 6,350 01951 300 13,500 7,110 6,380 01952 300 14,200 7,800 6,400 01953 400 14,900 8,490 6,420 01954 400 15,600 9,170 6,450 01955 600 16,300 9,860 6,470 01956 581 17,800 11,270 6,500 01957 564 17,800 11,250 6,520 01958 456 17,800 11,220 6,550 01959 532 17,800 11,200 6,570 01960 603 17,800 11,170 6,600 01961 587 17,800 11,140 6,620 01962 500 19,200 12,500 6,650 01963 489 19,100 12,480 6,670 01964 637 19,100 12,450 6,700 01965 701 19,100 12,420 6,720 01966 547 20,500 13,760 6,740 01967 523 19,100 12,360 6,770 01968 1,000 21,900 15,060 6,790 01969 1,058 21,800 15,030 6,820 01970 1,087 20,500 13,630 6,840 01971 1,024 21,800 14,950 6,870 01972 1,252 23,200 16,270 6,890 01973 1,284 25,800 18,930 6,920 01974 1,256 25,200 18,230 6,940 01975 1,197 24,500 17,530 6,970 01976 2,920 23,800 16,830 6,990 01977 3,394 23,200 16,140 7,020 01978 2,785 22,500 15,450 7,040 01979 1,584 22,900 15,810 7,060 01980 3,023 22,300 15,080 7,250 01981 1,733 21,800 14,350 7,440 01982 2,684 22,200 14,530 7,630 01983 1,732 22,400 14,610 7,820 01984 1,494 21,000 12,990 8,010 01985 2,141 24,800 16,630 8,200 01986 2,167 20,600 12,180 8,390 01987 2,273 20,600 12,040 8,580 01988 2,897 26,200 17,420 8,770 01989 3,439 30,200 21,280 8,950 121990 3,526 34,000 24,850 9,140 241991 3,262 33,700 24,290 9,330 351992 3,424 34,300 24,780 9,520 471993 3,507 34,500 24,740 9,710 591994 4,097 35,700 25,750 9,900 711995 4,227 35,900 25,710 10,090 831996 4,883 36,500 26,180 10,280 951997 5,378 36,200 25,600 10,470 1061998 5,096 36,800 26,070 10,650 591999 4,773 36,900 26,000 10,840 912000 5,338 44,200 33,070 11,030 1222001 5,430 43,400 31,630 11,600 1542002 6,262 41,800 29,450 12,170 1552003 5,279 40,300 27,450 12,740 782004 5,740 39,000 25,560 13,310 1562005 5,972 37,800 23,740 13,880 1582006 5,510 36,600 21,970 14,450 1592007 5,379 35,400 20,260 15,020 1602008 5,806 34,400 18,610 15,590 1622009 5,902 33,300 17,010 16,160 812010 5,907 33,600 16,670 16,730 166Guinea-Bissau - Belhabib and Pauly 15Appendix Table A2. Reconstructed total catch (in tonnes) by major taxonomic categories for Guinea-Bissau, 1950-2010. ‘Others’ contain 34 additional taxonomic groups.Year Ethmalosa fimbriataArgyrosomus regiusMurex spp. Ostrea spp. Anadara spp.Penaeidae Cynoglossus spp.Others1950 4,540 1,400 1,710 1,710 1,710 712 641 1,0301951 4,540 1,400 1,720 1,720 1,720 711 639 1,0301952 4,910 1,520 1,730 1,730 1,730 780 702 1,1001953 5,290 1,640 1,730 1,730 1,730 849 764 1,1701954 5,660 1,750 1,740 1,740 1,740 917 826 1,2401955 6,030 1,870 1,750 1,750 1,750 986 887 1,3101956 6,800 2,110 1,750 1,750 1,750 1,127 1,015 1,4501957 6,790 2,110 1,760 1,760 1,760 1,125 1,012 1,4501958 6,780 2,100 1,770 1,770 1,770 1,122 1,010 1,4501959 6,770 2,100 1,770 1,770 1,770 1,120 1,008 1,4501960 6,760 2,100 1,780 1,780 1,780 1,117 1,005 1,4501961 6,750 2,090 1,790 1,790 1,790 1,114 1,003 1,4501962 7,480 2,330 1,790 1,790 1,790 1,250 1,125 1,5801963 7,470 2,320 1,800 1,800 1,800 1,248 1,123 1,5801964 7,460 2,320 1,810 1,810 1,810 1,245 1,120 1,5801965 7,440 2,310 1,810 1,810 1,810 1,242 1,118 1,5801966 8,170 2,540 1,820 1,820 1,820 1,376 1,238 1,7101967 7,420 2,300 1,830 1,830 1,830 1,236 1,112 1,5701968 8,880 2,760 1,830 1,830 1,830 1,506 1,356 1,8501969 8,860 2,760 1,840 1,840 1,840 1,503 1,352 1,8401970 8,110 2,520 1,850 1,850 1,850 1,363 1,227 1,7101971 8,830 2,750 1,850 1,850 1,850 1,495 1,346 1,8401972 9,540 2,970 1,860 1,860 1,860 1,627 1,464 1,9701973 10,980 3,430 1,870 1,870 1,870 1,893 1,704 2,2401974 10,610 3,310 1,870 1,870 1,870 1,823 1,641 2,1701975 10,230 3,190 1,880 1,880 1,880 1,753 1,578 2,1001976 9,070 2,820 1,890 1,890 1,890 1,537 1,383 3,3501977 8,480 2,640 1,890 1,890 1,890 1,427 1,284 3,6501978 8,250 2,560 1,900 1,900 1,900 1,384 1,246 3,3401979 8,740 2,720 1,910 1,910 1,910 1,475 1,327 2,8901980 8,040 2,500 1,960 1,960 1,960 1,341 1,207 3,3701981 7,920 2,460 2,010 2,010 2,010 1,316 1,184 2,8801982 7,800 2,420 2,060 2,060 2,060 1,289 1,160 3,3101983 8,180 2,540 2,110 2,110 2,110 1,356 1,221 2,8001984 7,440 2,310 2,160 2,160 2,160 1,215 1,094 2,4501985 9,100 2,830 2,210 2,210 2,210 1,518 1,366 3,3801986 6,730 2,080 2,260 2,260 2,260 1,075 968 2,9201987 6,640 2,050 2,320 2,320 2,320 1,056 950 2,9701988 9,420 2,920 2,370 2,370 2,370 1,566 1,409 3,7701989 11,350 3,530 2,420 2,420 2,420 1,920 1,728 4,4601990 13,280 4,140 2,470 2,470 2,470 2,274 2,046 4,8601991 13,090 4,080 2,520 2,520 2,520 2,235 2,011 4,6801992 13,330 4,150 2,570 2,570 2,570 2,274 2,047 4,8301993 13,300 4,140 2,620 2,620 2,620 2,266 2,039 4,8901994 13,590 4,520 2,670 2,670 2,670 2,315 2,083 5,1901995 13,530 4,440 2,720 2,720 2,720 2,300 2,070 5,3601996 13,500 4,690 2,770 2,770 2,770 2,291 2,062 5,6801997 13,180 4,550 2,830 2,830 2,830 2,228 2,005 5,7301998 13,540 4,650 2,880 2,880 2,880 2,291 2,062 5,6101999 13,670 4,660 2,930 2,930 2,930 2,310 2,079 5,4402000 17,470 5,850 2,980 2,980 2,980 3,011 2,710 6,2502001 16,770 5,600 3,130 3,130 3,130 2,869 2,582 6,1702002 15,290 5,490 3,290 3,290 3,290 2,584 2,325 6,2202003 14,710 4,910 3,440 3,440 3,440 2,464 2,218 5,6502004 13,740 4,580 3,590 3,590 3,590 2,272 2,045 5,6202005 12,810 4,250 3,750 3,750 3,750 2,089 1,880 5,5102006 11,910 3,950 3,900 3,900 3,900 1,912 1,721 5,3802007 11,120 3,670 4,060 4,060 4,060 1,753 1,578 5,1502008 10,180 3,380 4,210 4,210 4,210 1,567 1,410 5,2102009 9,320 3,100 4,360 4,360 4,360 1,397 1,258 5,0902010 9,200 3,060 4,520 4,520 4,520 1,363 1,227 5,170 16Côte d’Ivoire - Belhabib and Pauly 17côte d’ivoire: Fisheries catch reconstruction, 1950-20101Dyhia Belhabib and Daniel PaulySea Around Us, Fisheries Centre, University of British Columbia, 2202 Main Mall, Vancouver, BC, V6T 1Z4, Canada d.belhabib@fisheries.ubc.ca ; d.pauly@fisheries.ubc.caabstractCôte d’Ivoire had a strong industrial fleet both in capacity and reach. Despite the decline of the sector the country still held a particular place within West Africa due to its harbour and shore facilities, which have made Abidjan the second most important fishing port in the region. Its industrial fleets returned to the waters of Côte d’Ivoire after West African countries declared their EEZ which, along with large foreign fleets, contributed to over-exploiting the country’s EEZ. Despite all this, official data suggest catches are increasing, which raises doubts as to their reliability. Moreover, official data do not include a large part of artisanal and subsistence catches, and also omits discards and a relatively important part of the industrial catch. They include, on the other hand, the foreign catches of ‘faux poissons’ from the water of neighboring countries, but labeled domestic fish when landed in Côte d’Ivoire. To estimate total catches and improve their geographical resolution, we reconstructed them by sector, considering effort, catch per effort, and geographical distribution of catches and their taxonomic identity. Total catches from Côte d’Ivoire EEZ were estimated at 7.06 million t between 1950 and 2010, which is 2.67 times the data supplied to the FAO (this accounts for 374,200 t of ‘faux poissons’ in the data supplied to FAO). Domestic catches declined, in contrast to the increase suggested by official data, but the catch of foreign fleets, mostly illegal, increased. Some social consequences for Côte d’Ivoire are outlined.introductionCôte d’Ivoire, with Abidjan, the capital city at 6°51’N – 5°18’W, is located in Sub-Saharan West Africa (Figure 1). The country is bordered by Liberia and Guinea from the West, Mali and Burkina Faso from the North, Ghana from the East and the Atlantic Ocean from the South, making Côte d’Ivoire one of the largest coastal countries of the Gulf of Guinea. The location of Côte d’Ivoire within the Equatorial Savanah of Africa and the Gulf of Guinea is ideal as it experiences seasonal coastal upwelling, strong river flow and discharge into the ocean (Hardman-Mountford 2000). This has contributed to the development of a coffee and cocoa based economy in the 1960s and 1970s as well as further expansion of the fisheries sector.Côte d’Ivoire gained independence from France in 1960; it was, at the time, one of the most prosperous countries of West Africa. This prosperity increased under the rule of president Houphouët-Boigny; the French expatriate community doubled, the country became a world leader in cocoa and coffee production (third after Brazil and Columbia in coffee production), its exports flourished by 40% as its annual economic growth rate stabilized at 10% (the highest of African non-oil exporting countries).The beginning of the economic collapse was triggered in combination of a drought that heavily impacted cocoa plantations and the world economic recession of 1980 that 1 Cite as: Belhabib, D. and Pauly, D. (2015) Côte d’Ivoire: fisheries catch reconstruction, 1950-2010. pp. 17-36. In: Belhabib, D. and Pauly, D. (eds). Fisheries catch reconstructions: West Africa, Part II. Fisheries Centre Research Reports vol.23(#). Fisheries Centre, University of British Columbia [ISSN 1198-6727].Figure 1.  The Côte d’Ivoire’s Exclusive Economic Zone (EEZ) and major coastal lagoons. 18affected cocoa prices on the other. This led to a social crisis that began with protests in 1990. With the death of the former president who had maintained ethnic accommodation, the pseudo-nationalist concept of ‘Ivoirité’ was used to discriminate against the many recent (and not-so-recent) immigrants to the country, who had arrived in colonial time to work in Côte d’Ivoire (Connelly et al. 2013). Along with the devaluation of the currency FCFA (Akindes 1995), the prohibition of immigrant southward migrations within Côte d’Ivoire, the vulnerability of the immigrants to forceful land grabs in the south (Dabalen et al. 2012) and a number of incidents against Ghanaians (Kouadio 2009) were all precursors to a number of coup attempts in the 1990s (Dabalen et al. 2012). These regional disparity were triggers that exploded into a civil war in 2002, ending the long-lived, peaceful political and productive economic conditions in Côte d’Ivoire (Morric MacLean 2004). The situation was exacerbated during the 2000s, as violence heightened (2000 and 2004-2006), instability grew in the North, ‘foreigners’ were increasingly expelled, 500,000 people were internally displaced and 224,000 became refugees (Global Witness 2007). Widespread chaos was fueled by the lack of wealth and income as the number of people living under the national poverty line increased from 10% in 1985 to 45% in 2008 (Global Witness 2007; Connolly et al. 2013).Such historical events, social crisis and natural disasters had a large impact on Côte d’Ivoire fisheries. For example, during the 1958 conflicts between Côte d’Ivoire and Benin, fishers were driven to migrate westwards. Also, at the end of World War II, the number of Ghanaian fishers in Côte d’Ivoire had increased tremendously (Koffie-Bikpo 2012). Similarly, military-political crises since 2002 have negatively affected fisheries (Koffie-Bikpo 2012), e.g., Ghanaians small-scale fishers being expelled from Côte d’Ivoire. After independence (1960), the number of artisanal fishers along the coast increased, due in part to the development of infrastructure, notably a coastal road (Koffie-Bikpo 2012).Fisheries are sensitive to the conditions surrounding them and have high importance for local populations, notably to food security. As poverty increases in the country, fisheries are an alternative way of sustaining livelihood after the collapse of the cocoa and coffee economies. Local populations began to view fisheries as a major asset, which leads them, in the absence of government structures, to manage fisheries on a local scale. For example, in 1982, all foreign artisanal fishers using mainly collective gear were denied access to Ebrié Lagoon, one of the largest lagoons of Côte d’Ivoire (Koffie-Bikpo 2012), leading to an increase in the number of fishers in the neighbouring lagoons (Figure 1).Although these kind of initiatives are common in Côte d’Ivoire, the overexploited state of fisheries, as reported since the 1970s (Cormier 1983; Garcia and Poinsard 1989), raises questions regarding the management of fisheries and the reliability of reported data, particularly during this period of instability. Officially, there are two main sectors in Côte d’Ivoire, artisanal and industrial. The artisanal sector, operating canoes and pirogues, is difficult to assess given the disparity of landing sites, the consumption of a portion of the catches by fishers and their families and the variability of fishing techniques (Cormier 1983). Although field surveys started in 1978, they only included a part of the canoes and pirogues along the coast, and they omitted land-based fishing, resulting in all individual fishing techniques excluded from official reports (Ecoutin 1992). Furthermore, no artisanal fishery data have been collected in recent years and most data failed to reach FAO since 1990 (FAO 2008; 2009). On the other hand, the industrial fishery, which includes trawlers, small-pelagic seiners and tuna purse-seiners “is monitored at the Abidjan fishing port, every day. The entry and exit data of vessels and fish sales slips are collected every two weeks by the research team from the Oceanographic Research Centre (CRO) to estimate the effort and catch per species” (FAO 2009). The foreign industrial fishery of Côte d’Ivoire, however, still remains difficult to assess given their geographical and gear disparity, and few reliable data are made available through logbooks (EU 2008).Given the importance of fisheries for the livelihood and food security of Ivoirians, and the current over-exploitation status of its marine fisheries resources, there is a serious need to address the lack of fisheries catch data in Côte d’Ivoire and analyze the impact of the different fisheries sectors.methodsCoastal populationTotal population was obtained through the WorldBank database (data.worldbank.org [2014]) covering the period between 1960 and 2010 and from Populstat database (www.populstat.com [2014]) for 1950. These data were interpolated to obtain the total population of Côte d’Ivoire between 1950 and 2010. CIESIN (2012) provides coastal rural population estimates (here: rural population living within 10 km from the coast) for 1990, 2000 and 2010. This allowed for the estimation of the coastal population percentage over the total population for Côte d’Ivoire. This was found to be at 1.5% for 1990, 1.9% for 2000 and 2.1% for 2010, which suggest migrations towards the coast, notably to escape conflicts. We assumed this rate was constant between 1950 and 1990 and interpolated linearly to fill in the gaps (Figure 2). Figure 2.  Coastal population in Côte d’Ivoire , 1950-2010.Côte d’Ivoire - Belhabib and Pauly 19Artisanal fisheriesArtisanal catches were mainly lagoon-based prior to 1960. After independence in 1960, the number of artisanal fishers along the coast increased due in part to the development of infrastructures, notably a coastal road (Koffie-Bikpo 2012) along with the opening of the Ebrié Lagoon and the industrialization of lagoon-based subsistence fisheries, which translated into the expansion of fishing grounds to the maritime coast of Côte d’Ivoire. In 1982, foreign artisanal fishers were denied access to Ebrié Lagoon and collective gears, e.g. beach seines, prohibited, which increased the number of foreign fishers in neighboring lagoons (Koffie-Bikpo 2012). Later on, artisanal fishing practiced initially by a few ethnic groups, e.g. Alladians, Keta, Apollonians, but mostly Fanti from Ghana (Delaunay 1992), was heavily impacted by socio-political conditions. For example, the number of Alladian fishers had declined from 1,100 in 1950 (Ecoutin 1992) to 18 in 2010 (Koffie-Bikpo 2012). Conflicts drove Ghanaian fishers to return to Ghana, and the number of Ghanaians in Côte d’Ivoire declined by 20% between 1988 and 1998 (Badmus 2009). Ghanaians had dominated the fishing industry previously(Kouadio 2009), so their departure significantly reduced the number of fishing vessels, similar to the situation in Liberia as a result of the civil war (Belhabib et al. 2013). These fishers, who initially migrated to Côte d’Ivoire because of a crisis in Nigeria and Ghana in the 1970s and 1980s, constituted around 17% of the coastal population of Côte d’Ivoire (Kouadio 2009). Understanding these dynamics and the historical evolution of artisanal fisheries is an important preliminary step to the reconstruction of catches, as it allows for critical evaluation (whether to accept or reject) of the estimates by literature, which appear to be either unreliable, under-estimated or obtained via ad hoc meetings (FAO 1981; FAO 1985, 2008a, 2009). Furthermore, artisanal catch and effort data reported by literature often do not reflect socio-demographic changes alluded above, e.g. the decline of lagoon catches by artisanal fishers in the 1970s, due to the development of industrial fisheries and the departure of Ghanaian (Koffie-Bikpo 2012), does not show in official data. Indeed, it is not even always clear whether these data include lagoon and freshwater catches. For instance, artisanal catches are marked as “unknown” in official reports of the CECAF Working Group between 1963 and 1975 and for 1979 for Sardinella aurita, and are unrealistically low between 1976 and 1978 (FAO 1981); this situation re-appears even after 1981 (Cury and Roy 1987).Landing data were available for the 1980s and 1990s, when the CRO was at its peak activity, and collaborating with the French Institute of Research for Development (IRD); some data from the 2000s are also available. We reconstructed artisanal marine catches based on the number of artisanal boats along with the average catch per unit of effort (CPUE), and we interpolated between the available numbers of artisanal boats, which we used as anchor points (Table 1). We estimated CPUEs based on the catch estimate by Ecoutin (1992), i.e., 35,000 t for 1984, divided by the interpolated number of artisanal marine boats (1,632 boats), i.e., 21.4 t·boat-1·year-1. Considering over-exploitation (Cormier 1983; Garcia and Poinsard 1989) and the increasing capacity of artisanal fishing boats, we assumed the CPUE was 15% higher in 1950 and 15% lower in 2010. We interpolated between the CPUE estimates, then multiplied the latter by the effort to estimated artisanal marine catches between 1950 and 2010.Lagoon catchesThere are three main lagoons in Côte d’Ivoire: Ebrié Lagoon, Aby Lagoon and Grand-Lahou Lagoon. In these lagoons, only collective fisheries are monitored, i.e., cast nets, traps and lines are not included in official statistics, the individual gear being more appropriate for subsistence purposes, and/or yielding a catch sold directly to restaurants (N’Goran 1990). Prior to 1975, lagoon catches were not taken into consideration in official statistics (Kébé et al. 1997). Post-1979, only partial catch and effort data are taken into consideration. If partial effort was examined then partial geographic areas and partial catches were assessed (Doucet et al. 1985).Total lagoon landings were reported between 1994 and 1996 (Kébé et al. 1997) and were herein considered reliable. We estimated total lagoon catches for 2010 by multiplying the CPUE of 3,744 kg·fisher-1·year-1 by the total number of fishers (2,898) provided by Pérez-Ruzafa and Marcos (2012) for 2010. To complete the time series, we estimated lagoon catches separately for the three lagoons mentioned above between 1950 and 1985 for Ebrié and Grand-Lahou Lagoons, 1950 and 1998 for Aby Lagoon, the sum of which represents the annual artisanal lagoon catch.Landings for Ebrié Lagoon were estimated by Cormier (1983) and Ecoutin (1992) between 1975 and 1985 and were considered reliable. The number of fishers using collective gear in Ebrié Lagoon was estimated at 5,300 fishers for 1974 (Ecoutin 1992). Thus, we estimated the number of fishers for 1950 by adjusting the estimate to account Table 1.   Number of artisanal marine pirogues between 1950 and 2010 in Côte d’Ivoire.Year Boats Source1950 1,095 Postel (1950); Cormier (1983);1956 1,000 Lassarat (1958);1964 1,438 2,650 pirogues (Domingo 1980) of which 54% are marine (Gerlotto and Stequert 1978; Cormier 1983);1969 1,500 Gerlotto and Stequert (1978); Cormier (1983);1975 1,574 Total number of artisanal boats averaged between 3,000 and 2,800 (Cormier 1983; Collari 1986) of which 54% were marine (Gerlotto and Stequert 1978);1979 1,638 Over 3,018 artisanal boats (Domingo 1980), 54% of which were marine (Gerlotto and Stequert 1978);1996 1,618 A total of 3,326 artisanal boats (Kébé et al. 1997) of which 48% were active marine boats (Shep et al. 2011; Pérez-Ruzafa and Marcos 2012);1999 1,860 We assumed an increase of 15% of the effort because of increased migrations towards the coast from the lagoons because of political events (new elections and violence);2010 1,372 Shep et al. (2011)  20for changes in coastal population, i.e., we multiplied the number of fishers for 1974 by the rate of change in the coastal population between 1950 and 1975 (Figure 2). We then multiplied the number of fishers by the CPUE of 3,744 kg·fisher-1·year-1 (Pérez-Ruzafa and Marcos 2012). This CPUE was kept constant between 1950 and 2010, assuming that villages adjusted for overexploitation due to non-selective fishing gear and mesh-size (Cormier 1983) by implementing new regulations such as the prohibition of collective fishing gears, e.g., in Ebrié Lagoon (Ecoutin 1983). We interpolated to complete the Ebrié Lagoon catch time series between 1950 and 1985.Collective fishing catches for Aby Lagoon were estimated and reported by different literature sources for the period between 1979 and 1998 (Charles-Dominique et al. 1980; Bayley 1988; Konan 1998), which we considered reliable. The number of fishers was estimated at 1,654 for 1967 (Cormier 1983). We estimated the number of fishers for 1950 by following the same adjustment approach described above using coastal population estimates and estimated a number of 960 fishers for 1950. We multiplied the number of fishers for 1967 and 1950 by a CPUE of 3,744 kg·fisher-1·year-1 (Pérez-Ruzafa and Marcos 2012), and then interpolated to complete the time series between 1950 and 1998.Similarly, catches for Grand-Lahou Lagoon were estimated at 4,140 t for 1969 (Bayley 1988) and 1,500 t for 1985 (Ecoutin 1992). To estimate collective fishing catches in Grand-Lahou Lagoon in 1950, we estimated the number of fishers using the estimate provided for 1969 of 2,995 fishers (Bayley 1988), adjusted by the coastal population, i.e., 1,593 fishers in 1950. We then multiplied the latter by the CPUE provided by Pérez-Ruzafa and Marcos (2012), and interpolated to complete the catch time series for Grand-Lahou Lagoon between 1950 and 1985.We calculated the annual sum of collective fishing catches for the three previous areas between 1950 and 1985 and then interpolated to the first estimate of total lagoon catches for 1994 (Kébé et al. 1997) and then between the estimate for 1996 (Kébé et al. 1997).Subsistence catchesSubsistence fishing in Côte d’Ivoire plays a major role in providing local communities with fish, as households looked for other economic alternatives, particularly after the devaluation of the FCFA (Akindes 1995). Evidence from nearby Liberia and other countries have shown that when communities struggle for food in conflict situations, subsistence activities such as hunting and fishing increases (Foster et al. 2009). Although small-scale fishing in Côte d’Ivoire was mainly subsistence in the past, there has been a certain degree of ‘professionalization’ since the early 1980s, which translated into a decline of individual fishing aimed at subsistence in villages excluded from the ban of collective fishing techniques (Verdeaux 1981). When collective fishing techniques were banned, rather than an increase in the number of individual subsistence fishers, an expansion of the fishing areas occurred (Verdeaux 1981).There are three main types of subsistence fishing in Côte d’Ivoire considered in the present study: (i) fishers using individual gear in the lagoons, (ii) artisanal fishers taking lagoon fish home, and (iii) artisanal fishers taking sea-caught fish home. Item (iii) was restricted in the past to a few species of sparids and groupers being kept for personal consumption, while sardines, sardinellas and sharks were sold in the markets (Koffie-Bikpo 2012). Lagoon fishers use several techniques, the most wide-spread one is the acadja method that is called “tegbe” or “niapra” in Côte d’Ivoire (Verdeaux 1981), in reference to the hollow wood used to form enclosures used to concentrate and catch fish (Durand et al. 1994). Although catches taken using these methods are occasionally sold, we consider it to belong to the subsistence sector.Cast net fishingWe estimated subsistence catches using cast nets separately for Aby and Ebrié Lagoons, and other lagoons, as the product of the catch per fisher and the number of fishers.The number of cast net fishers in Ebrié Lagoon were assessed by Durand et al. (1978) at 3,375 fishers (1972 and 1973), Laë (1992) at 2,160 fishers for 1977, and by Durand et al. (1994) at 2,970 fishers for 1994. To obtain the number of fishers for 1950, we multiplied the mean percentage of cast net fishers over the coastal population of 1973-1977 by the coastal population of 1950. This mean was assumed to be constant between 1950 and the 1970s because of the overall unchanged conditions in the lagoon. The number of cast net fishers increased to 2,932 fishers in 1986 (Laë 1992) partly due to the prohibition of collective fishing techniques in Ebrié Lagoon. To estimate the number of cast net fishers for 2010, we assumed the rate of individual fishers over the coastal population declined by 20% since 1994, due to migrations caused by conflicts, and estimated a percentage of 1% for 2010. By multiplying this percentage by the coastal population for 2010, we obtained the number of cast net fishers for 2010 at 4,118 and interpolated between the previous effort estimates. Catches were assessed for the period between 1975 and 1984 (Durand et al. 1978; Anon. 1981; Laë 1992), which allowed to estimate the CPUE by dividing these catch estimates by the previous effort. We obtained the CPUE for 1950 as the geometric mean of the 1975-1978 CPUEs, given the overall unchanged conditions. On the other hand, the overexploitation of certain species of small pelagic fishes in the early 1980s led to a decrease in CPUE, which remained constant since then, notably because of the high adaptability of fishing villages (e.g., the prohibition of collective fishing gear). Consequently, we obtained the CPUE for 2010 as the geometric mean of the 1982-1984 CPUEs. We interpolated between the CPUE anchor points and then multiplied CPUEs by effort estimates (Table 2).Côte d’Ivoire - Belhabib and Pauly 21Konan (1998) reported the number of cast net fishers at 2,160 for 1996 in Aby Lagoon, which represented 0.8% of the coastal population. Given the decline in subsistence fishing using individual gear in lagoons other than Ebrié Lagoon (Verdeaux 1981), we conservatively assumed that this percentage was 20% higher in 1950 (1 %) and 50% lower in 2010 (0.4%). We then multiplied these percentages by the coastal population of 1950 and 2010 respectively and obtained the number of fishers at 407 (1950) and 1,684 (2010). We interpolated linearly and multiplied the resulting effort by the CPUE estimated previously for Ebrié Lagoon (Table 2).To estimate catches for the Grand-Lahou Lagoon, for which no data on the number of individual fishers were available, we first estimated the average annual catch by square km for the two previous lagoons and then multiplied these by the surface area of Grand-Lahou.Personal consumptionPersonal consumption was estimated by Konan (1998) at 3% of artisanal catches for 1996. We assumed that this consumption rate was constant between 1950 and 1996, and increased it by 30% in 2010, because of the increase of insecurity, which increased informal activities. We interpolated linearly to fill in the gap and then multiplied the resulting rates by the estimated artisanal marine and lagoon catches.Tegbe (acadja) catchesThe number of fishers using the tegbe technique was estimated to be the equivalent of 14% of fishers around lagoons (Verdeaux 1981). We first calculated the total number of fishers in Côte d’Ivoire’s lagoons as the sum of previously estimated number of fishers in each lagoon between 1950 and 1969. We then interpolated to 10,000 fishers in 1979 (Cormier 1983) and to 2,898 fishers in 2010 (Pérez-Ruzafa and Marcos 2012). We interpolated to complete the time series of the total number of lagoon artisanal fishers, and then multiplied the resulting numbers by 14%. Assuming that a tegbe system has a similar production rate than an acadja system, i.e. around 3.4 t·acadja-1·year-1 (Belhabib et al. 2015), we multiplied this rate by the number of fishers (each fishers conservatively using one tegbe) and estimated tegbe catches between 1950 and 2010. Total subsistence catches are calculated as the sum of the three components estimated above.Industrial catchesIndustrial fisheries in Côte d’Ivoire include a domestic component, which in turn, consists of three different categories: (i) tuna purse-seiners, (ii) shrimp and fish trawlers and small pelagic purse seiners, and (ii) foreign fleets including trawlers, but mostly tuna vessels. The Canal of Vridi, opened in 1950, links Ebrié Lagoon to the sea, and led to the creation of the port of Abidjan. By providing good berthing facilities, the new port fostered the development of an industrial fishery (Koffie-Bikpo 2012), which expanded its fishing grounds from the coast of Côte d’Ivoire in the early 1950s to Liberia and Ghana in the early 1960s, and later to Mauritania (Cormier 1983).Trawl landings were recorded by observers since 1966, along with related data on fishing effort, fishing zones and ex-vessel prices. Data on fishing zones and the time spent at sea were collected from the skippers and boat owners themselves; when this information was lacking, it was inferred from vessels of the same size class (Fonteneau and Troadec 1969); such extrapolations were performed for around 30% of the trawl fleet between 1966 and 1978 (Fonteneau and Troadec 1969). Similarly, small-pelagic purse-seine catch data was collected since 1966 by the CRO, and then by the Projet de Développement de la Pêche Pélagique Côtière. Catch data from the marketing services of the landing site and from skippers were collected and then compared and harmonized, while trip durations were obtained using the time of exit and re-entry to port (Fonteneau and Marchal 1970). Between 40% to 50% of the fishing trips were covered by this process (Fonteneau and Marchal 1970). Tuna catch surveys began in the early 1990s by IRD and CRO, but they became reliable only since 1996, when their catches became assessed on deck (Romagny et al. 2000).Table 2.   Effort and CPUE anchor points for the estimation of cast net fishing in Ebrié and Aby Lagoons. Interpolations are indicated by italics. Ebrié Lagoon Aby Lagoon Estimated CPUEYearEffort(fishers) SourceEffort (fishers) SourceCPUE  kg·fisher-1·year-1 Source1950 1,217 Assumed 407 Assumed 810 Geometric mean 1975-1978 CPUE1973 3,375 Durand et al. (1978)1,284 Interpolation 642 Interpolation1974 3,375 Durand et al. (1978)1,322 Interpolation 635 Interpolation1975 2,767 Interpolation 1,360 Interpolation 627 Estimated catch (Durand et al. 1978) by interpolated effort1976 2,159 Laë (1992) 1,398 Interpolation 738 Interpolation1977 2,237 Interpolation 1,436 Interpolation 849 Estimated catch (Anon. 1981) by interpolated effort1984 2,777 Interpolation 1,703 Interpolation 730 Estimated catch (Laë 1992) by interpolated effort1986 2,932 Laë (1992) 1,779 Interpolation 725 Interpolation1994 2,970 Durand et al. (1994)2,084 Interpolation 704 Interpolation1996 3,113 Interpolation 2,160 Konan 1998 698 Interpolation2010 4,118 Assumed 1,684 Assumption 662 Geometric mean 1981-1983 CPUE 22Over 100,000 t of fish are transhipped annually through Abidjan port, which make catch recording very difficult, despite these efforts, the quantities and/or the geographical provenance of these catches is often not available (Chavance et al. 2011). Rather, the spatial resolution and the accuracy of such data are based on the good will and honesty of skippers. Herein, we reconstruct the catches taken within the Exclusive Economic Zone (EEZ) of Côte d’Ivoire, and distinguish them from catches taken outside, but landed/transhipped through Abidjan, in an effort to retrace the history of the domestic fisheries of Côte d’Ivoire and understand the reasons behind their collapse.Domestic fisheriesDomestic catches are defined as catches taken by vessels flagged to Côte d’Ivoire and landed in Côte d’Ivoire. These could be caught within or outside the country’s EEZ.Trawl catchesTotal trawl fish landings by the domestic fleet, taken within or outside the EEZ, were reported by Lassarat (1958) for 1955, Cavérivière (1979) between 1955 and 1968, Cormier (1983); Rey (1993); Kébé et al. (1997) between 1969 and 1995, Coulibaly (2010) between 2000 and 2005 and by Bikbo-Koffie (2010) between 2006 and 2008. On the other hand, landings taken from within Côte d’Ivoire’s EEZ were reported by Cavérivière (1979) and Ménard et al. (2001) between 1955 and 1997. Landings as reported by Cavérivière (1979) under-estimated catches as suggested by Lassarat (1957, 1958). Therefore, we reconstructed catches based on the reported effort and CPUE, then compared these to the landings reported in the literature.The CPUE of trawlers was estimated at 22.36 t·day-1 for 4 units operating 25 fishing days a month (Lassarat 1958), which translates into a CPUE of 1,677 t·trawler-1·year-1 for 1956. The author observed a lower CPUE by experimental trawlers the previous year, i.e., 443 t·trawler-1·year-1. Therefore, we calculated the geometric mean of the CPUEs at 1,060 t·trawler-1·day-1 and assumed the latter was constant between 1950 and 1956. Given the over-exploitation pattern observed in the mid-1980s (Cormier 1983), which included a growing vessel capacity and the retaining of more bycatch species, we assumed the CPUE declined by 5% between 1956 and 1984, i.e., to 1,007 t·trawler-1·year-1. Similarly for 2010, we assumed a decline of 15% and estimated a CPUE of 856 t·trawler-1·year-1, and interpolated to fill in the gaps.The total number of fish trawlers, reported through the 1950-2010 time period (Lassarat 1958; Cormier 1983; Rey 1993; Kébé et al. 1997; Bikbo-Koffie 2010), was completed by a series of interpolations. The number of demersal fish trawlers and their respective GRT was reported by Cavérivière (1979) for the period between 1950 and 1980, when vessels under 300 GRT fished exclusively in Côte d’Ivoire, while trawlers with a GRT between 300 and 600 GRT fished mostly (here assumed to be 70% of the time) in Côte d’Ivoire and at a lesser extent in Sierra Leone, Liberia and Ghana (30%); finally, trawlers of GRT  600 GRT fished between Sierra Leone and Mauritania (Cavérivière 1979). We estimated the number of vessels operating within Côte d’Ivoire between 1950 and 1980 as the total number of vessels under 300 GRT to which are added 70% of the vessels between 300 and 600 GRT. We calculated the percentage of these two categories over the total for 1980, last data point for the GRT categories, and then multiplied this percentage by the total number of fish trawler for the subsequent years, 100% of the first category (300 GRT) and 70% of the second category operated within the Côte d’Ivoire EEZ. We thus obtained the number of vessels operating in Sierra Leone, Liberia and Ghana as 30% of the second category, and obtained the number of vessels operating from Sierra Leone to Mauritania (GRT600) as the difference between the total number of vessels and the sum of the two first GRT categories. To estimate total catches by these two categories, we first estimated the CPUE per GRT by dividing the CPUE per trawler of the first category by 300 GRT between 1950 and 2010 and then multiplied the resulting CPUE (t·trawler-1·GRT·year-1) by 450 (average GRT of the second category), and 600 GRT for the third category. Finally, we multiplied the resulting CPUEs for both categories by their respective effort. We assumed catches by vessels over 300 GRT from outside Côte d’Ivoire started declining since 1984 to zero in 1990, given no indication of access agreements between the Côte d’Ivoire and any other country in Africa, and their declaration of EEZs. [Ghana’s distant-water fleet suffered a similar fate (Atta-Mills et al. 2004)]. The remaining catch was allocated to the Côte d’Ivoire’s EEZ.While Cavérivière (1979) refers to landings from Sierra Leone, Liberia and Ghana for 30% of the vessels ranging between 300 and 600 GRT, the same author, in 1978 reported that landings were taken, between 1966 and 1976, only in Ghanaian and Liberian waters, while Fonteneau and Troadec (1969) reported no landings from Liberia. We calculated the percentage of landings taken from Sierra Leone and Ghana by dividing the landings taken from the EEZ-equivalent waters of each country by the total of the two between 1966 and 1976 and assumed these percentages were constant from then to 1990 (when catches from outside Côte d’Ivoire were zero), and backwards from 1960 to 1966.Catches taken between Sierra Leone and Mauritania, i.e., mainly from Guinea and Senegal (Cavérivière and Marcille 1978), from Guinea Bissau (Cavérivière 1978), and from Gambia and Angola, were only mentioned casually in the 1960s (Fonteneau and Troadec 1969) and made up only 3% of the Ivorian catch in 1969. They were not included in the present study. However, we allocated a third of the catch taken from outside Côte d’Ivoire by trawlers of over 600 GRT to each country’s EEZ (Guinea, Senegal and Guinea Bissau).Côte d’Ivoire - Belhabib and Pauly 23Shrimp trawl catchesShrimp trawl catches were reported from 1969, when the fishery began to 1981, when the fishery collapsed (Cormier 1983; Rey 1993; Kébé et al. 1997). These catches are taken from both Côte d’Ivoire and Nigeria, but catches post-1981, after the economic collapse of Côte d’Ivoire’s industrial fishery in 1978-1979 (Garcia and Poinsard 1989), were likely from Nigeria (FAO 1985). We assumed these catches were reliable given the monitoring system used then, and divided them by the number of shrimp trawl vessels obtained from various sources (Cormier 1983; Rey 1993) to obtain a series of CPUEs averaging at 47 t·vessel-1·year-1. We assumed that this CPUE was constant later on, as vessels adapted to decreasing catches (and ultimately to the collapse of the fishery in Côte d’Ivoire) by fishing in Nigerian waters. We then multiplied this CPUE by the reported number of vessels between 1982 and 2010 (Kébé et al. 1997; Bikbo-Koffie 2010). The number of vessels operating in Nigeria and the number of fishing days between 1970 and 1975 were reported by FAO (1985) along with the catch for 1973 which allowed to estimate the CPUE at 0.27 t·vessel-1·day-1. Assuming a constant CPUE from 1970 to 1975, we estimated catches taken from Nigerian waters for the same time period. We also considered that all catches after 1981 were taken from Nigeria (FAO 1985). The difference between catches taken from Nigeria and total catches represents the catch taken by domestic shrimp trawlers from Côte d’Ivoire.Industrial small-pelagic catchesAlthough the number of small pelagic purse-seiners was documented throughout the 1950-2010 time period (Lassarat 1958; Bouberi 1981; Cormier 1983; Rey 1993; Kébé et al. 1997; Bikbo-Koffie 2010), along with catches for the periods 1967-1995 and 2000-2008 (Cormier 1983; Cury and Roy 1987; Rey 1993; Kébé et al. 1997; FAO 2009; Bikbo-Koffie 2010; Coulibaly 2010), little is known on the geographical distribution of catches beyond the EEZ of Côte d’Ivoire . The few data points illustrating the origin of the purse-seine catch taken from Côte d’Ivoire, Sierra Leone, Senegal, Ghana and Congo covered only years within the period between 1966 and 1979 (Hem 1976; Cavérivière and Marcille 1978; Bouberi 1981, 1984a, 1984b). To complete the time series of total small pelagic catches, i.e. taken within and outside Côte d’Ivoire EEZ, we estimated the average CPUE for the early 1980s based on the effort and the catch documented by Bouberi (1981, 1984b) at 1,345 t·vessel-1·year-1. We assumed the CPUE for 1950 was 30% higher (1,748 t·vessel-1·year-1), thus reflecting in one hand the impact of the collapse of the sardinella fishery of the 1970s and the quota limitations imposed by fishers syndicates in the 1980s (Bouberi 1984a). We multiplied this CPUE by the number of vessels for 1950 and obtained a catch of 3,497 t. Given the decline in CPUE and number of vessels in the 2000s (Pigeaud 2012), we assumed catches declined by 5% between 2008 and 2010. We then interpolated linearly to fill in the gaps between 1950 and 2010.We interpolated catch estimates from zero in 1950 to the first anchor point available for catches taken from Sierra Leone (1967), Senegal (1975), Ghana (1966) and Congo (1974) and then from the last anchor point for Sierra Leone and Senegal (1979), Ghana (1978) and Congo (1975) to zero in 2010 for Sierra Leone and Senegal, and zero in 1979 for Ghana and Congo. The difference between total catches taken within and outside Côte d’Ivoire EEZ and the sum of catches taken from Sierra Leone, Senegal, Ghana and Congo, represents the domestic small pelagic catches taken within Côte d’Ivoire EEZ.Industrial tuna catchesTuna fisheries surveying for foreign vessels began only in 1990 and became efficient in 1996 (Romagny et al. 2000). On the other hand, literature review showed domestic tuna catches as early as 1957 when experimental tuna fishing began (Lassarat 1958), for 1965 (Ecoutin 1992) and between 1970 and 1986 (Cavérivière and Marcille 1978; Cormier 1983; Ecoutin 1992; Rey 1993; Kébé et al. 1997), when domestic tuna seiners stopped operating in Côte d’Ivoire (Rey 1993). These catches included only main species of skipjack (Katsuwonus pelamis) and albacore (Thunnus alalunga). The bycatch, called “faux poissons”2 meaning “false fish”, and which is “a peculiar term for an important by-product of the purse-seine fishery in West Africa and particularly in Abidjan”(Amandè et al. 2010) was not included in official statistics (Cavérivière and Marcille 1978). We completed the time series by interpolating linearly between the anchor points, assuming tuna domestic catches were correctly reported.Foreign catchesDemersal trawl fisheries Herein we reconstruct Chinese trawl catches within Côte d’Ivoire, given the large number of legal Chinese trawlers in the country’s EEZ. FAO (2008b) reported that 9 Chinese trawlers were authorized to fish in Côte d’Ivoire EEZ, with a CPUE of around 415 t·vessel-1 for 2005. Other estimates show a CPUE of 1,252 t·vessel-1·year-1 (Pauly et al. 2013). We assumed that China started fishing in Côte d’Ivoire in 1990, at the time when foreign trawlers were reported for the first time within the Ivoirian EEZ (FAO 2008b), and that the effort was constant between 2005 and 2010; then, we linearly between zero in 1990 and the first data point in 2005. Total Chinese trawl catches from Côte d’Ivoire are calculated as the product of effort and a CPUE of 808 t·vessel-1·year-1, i.e., the mean between values in (FAO 2008a, 2008b; Pauly et al. 2013).2  This sector is treated further below in the section on “faux poissons.” 24Tuna fisheriesScarce documentation is available on foreign tuna fishing in Côte d’Ivoire. When reviews are found, often the geographical allocation of catches remains confusing, as literature refers to landings in “Abidjan” rather than catches from Côte d’Ivoire. A few hints show the number of vessels within Côte d’Ivoire waters, and/or describe the presence or the absence of an agreement for tuna fishing. For example, the first agreement with France was signed right after independence in 1961 (Cormier 1983; Folsom et al. 1993). It is reasonable to assume that Spain and Senegal, for which the number of vessels was reported for 1972 (Cormier 1983), also began fishing in Côte d’Ivoire in 1961, given that Senegalese vessels were mainly from Spanish and French origin (Belhabib et al. 2014). A total number of 270 tuna vessels were reported for 1972, of which 22% were Japanese, 30% French, 18.5% Korean, 18.5% Taiwanese, 6% Spanish, 2% Senegalese and 3% allocated evenly between Yugoslavia, the United States, Canada and Israel (Cormier 1983). We assumed all fleets, excluding those from Spain, Senegal and France, started fishing in 1968, when domestic tuna fishing resumed (Rey 1993). We kept this effort constant in the 4 years from 1972 and 1975, which is the average duration of a fishing agreement. We then interpolated to zero in 1991 for Japan, Korea, Taiwanese, Senegal, Yugoslavia, United States, Canada and Israel, given the absence of any reference indicating an agreement with these countries in the 1990s (in contrast to the agreement with the EU). Similarly, we interpolated data for countries of the European Union (EU), i.e., Spain, France and Portugal for which the effort was indicated in the agreements signed with the EU (Table 3). We completed the effort time series by performing interpolations as needed.The next step was to estimate total catches of these vessels within the EEZ of Côte d’Ivoire or the EEZ-equivalent waters prior to the declaration of the EEZ in 1977. First, we estimated total catches of these vessels within and outside Côte d’Ivoire waters, based on the CPUE of domestic tuna vessels from Côte d’Ivoire. We obtained the latter by averaging the CPUEs obtained by dividing the estimated domestic tuna catch by the domestic effort between 1957 and 1986, i.e., 747 t·vessel-1·year-1. We multiplied this CPUE by the number of vessels assuming that the decrease of the CPUE due to over-exploitation would be compensated by the increase in vessel efficiency and the decrease in vessel number over time. We multiplied the resulting catch by the average percentage of the catch originated from Côte d’Ivoire, i.e., 6% (Menard et al. 2000; European Union 2004). Although these percentages were reported only for the EU fleet, we assumed that it applied to all other fleets, given that they hold agreements with other West African countries, except for Israel, whose entire catch was assumed to be from the Côte d’Ivoire EEZ. Table 3.    Foreign tuna fleet anchor points, 1950-2010. Year Japan France Korea Taiwan Spain Senegal Yugoslavia US Canada Portugal Israeli Reference1960  0   0 0      Assumption1961a             1968 0  0 0   0 0 0  0 Assumption1972 59 81 50 50 16 5 2 2 2  2 Cormier (1983)1973 59 81 50 50 16 5 2 2 2  2 Assumption1974 59 81 50 50 16 5 2 2 2  2 Assumption1975 59 81 50 50 16 5 2 2 2  2 Assumption1978b           0 Lankester et al. (2001)1991-19930 45 0 0 45 0 0 0 0  0 European Economic Community (1990); Folsom et al. (1993)1994-19960 45 0 0 45 0 0 0 0  0 European Economic Community (1990); Folsom et al. (1993)1996 0 45 0 0 45 0 0 0 0 0 0 OECD (2000)1997-19990 25 0 0 30 0 0 0 0 5 0 European Union (2004); OECD (2000)2000 0 30 0 0 36 0 0 0 0 5 0 European Union (2004)2001 0 30 0 0 36 0 0 0 0 5 0 European Union (2004)2002c 30 30 0 0 37 0 0 0 0 5 0 European Union (2004); Oceana (2004)2003 30 30 0 0 37 0 0 0 0 5 0 European Union (2004); Oceana (2004)2004 30 20 0 0 24 0 0 0 0 5 0 eur-lex.europa.eu/Index.do; Oceana (2004)2005 30 20 0 0 24 0 0 0 0 5 0 eur-lex.europa.eu/Index.do; Oceana (2004)2006 30 20 0 0 24 0 0 0 0 5 0 eur-lex.europa.eu/Index.do; Oceana (2004)2007 30 20 0 0 24 0 0 0 0 5 0 eur-lex.europa.eu/Index.do;  EU (2008)2008 30 20 0 0 24 0 0 0 0 0 0 eur-lex.europa.eu/Index.do; EU (2008)2009 30 20 0 0 24 0 0 0 0 0 0  eur-lex.europa.eu/Index.do;  EU (2008)2010 30 20 0 0 24 0 0 0 0 0 0 eur-lex.europa.eu/Index.do;  EU (2008)a) First agreement here with France (Cormier 1983);b) First agreement here, reciprocity not implemented and only Guinea Bissau was fishing in Côte d’Ivoire (Lankester et al. 2001);c) Agreement signed with Japan for 30 vessels but the agreement was never used (European Union 2004).Côte d’Ivoire - Belhabib and Pauly 25”Faux poisson”Chavance et al. (2011) timed the beginning of the ‘faux poissons’ fishery back to the early 1980s, when “the development of the log fishing practice for purse seiners produced quantities of juvenile major tunas, minor tunas or by-catch species that started to be landed in Abidjan for consumption according to a Nigerian (Houssa) recipe, the garba”, a cheap meal that gradually gained popularity (Romagny et al. 2000).Catches of “faux poisson” were grossly under-estimated in the 1980s (Romagny et al. 2000) and are considered absent from more recent official statistics (Amandé et al. 2010). While these were estimated by CRO based on customs reports, the nature of the activity that requires payment allows for a large gap in estimations, a bias that drives catch estimates downwards as fishers would report less to pay less. Also, very often, agents will not report these catches. Estimations by CRO, as opposed to official numbers improved overtime (Amon Kothias 1986; Romagny et al. 2000) from very poor in the early 1980s to relatively better in the late 1990s (Romagny et al. 2000). Catches reported as ‘faux poissons’ by the Department of Fisheries (DAP) in national reports remain relatively low and unreliable when compared to catches estimated more realistically by CRO, as the former were obtained via logbooks while the latter by estimation onsite (Romagny et al. 2000). Even in 2010, accounting for ‘faux poissons’ landings remained informal, and many issues were observed by Chavance et al. (2011), notably regarding the localization of the catch, the gear, and the amount of the catch. The authors noted that the activity remained relatively undeclared in official statistics.While many fleets operate within Côte d’Ivoire EEZ and the Central Eastern Atlantic area, ‘faux poissons’ landings are reported only by European, Japanese, South Korean, Ghanaian and Guinean vessels and vessels flying flags of convenience of countries such as Cambodia (Chavance et al. 2011). We first attributed an underreporting rate of “grossly unreliable/underestimated”, “low reliability” and “good reliability” to CRO estimated catches (Romagny et al. 2000) for the periods considered by the author. We assumed catches were under-estimated by 60% for 1988-1991, 40% in 1991-1994, 30% between 1995 and 1999 and interpolated to 20% (conservatively) in 2010. We first estimated total catches, i.e., added the unreported component for the EU fleets by multiplying the former percentages by the reported catch and then adding it to the reported catch between 1991 and 2010. These estimates include Spain, France and Portugal for the most recent periods. Then, we estimated Spanish, French and Portuguese ‘faux poissons’ bycatch rates by dividing the catch of ‘faux poissons’ by the corresponding total tuna catch, i.e., tuna catches landed in Abidjan regardless of the catch area, between 1991 and 2010, and interpolated from zero in 1981 (Chavance et al. 2011) to the first estimated bycatch rate in 1991, i.e. 35%. Given the similarities between the EU fleets and the Senegalese (mainly French and Spanish based in Dakar) and domestic fleets (given that tuna fishing was introduced to Côte d’Ivoire by France (Lassarat 1957, 1958; Belhabib et al. 2014), we assumed the same bycatch rates and applied them to the estimated tuna catch by the Senegalese and Côte d’Ivoire fleets.Japanese tuna catches were estimated between 1969 and 1990, a period during which Japan had an agreement with Côte d’Ivoire (see foreign tuna catch section), while “faux poissons” catches were only reported for Ghana, also known to have a significant number of Japanese tuna boats flagged to it (Nunoo et al. 2014), and covered only the period between 1988 and 2009 (Chavance et al. 2011). Therefore, we could only estimate bycatch rates for the three overlapping years (1988-1990). We interpolated bycatch rates between zero in 1981 and 29% estimated herein in 1988 and multiplied the resulting time series by Japan’s tuna catch, thus obtaining Japanese “faux poissons” catches landed in Abidjan. Similarly, knowing that Korea also used to reflag its tuna boats to Ghana, we used the same bycatch rates and applied them to the Korean tuna catch between 1981 and 1990, when Korea stopped operating in Côte d’Ivoire as “Korea”. We used these same bycatch rates for the other fleet that had agreements with Côte d’Ivoire and landed their catches in Abidjan, i.e., Israel, Canada, United States, Yugoslavia and Taiwan. For Ghana, Guinea and Cambodia, for which only ‘faux poissons’ catches were reported by Chavance et al. (2011), we calculated the unreported catch by multiplied the reported catch by the underestimation rates alluded above based on the reliability of catch estimates as described by Romagny et al. (2000). Although only 6% of the foreign catches landed in Côte d’Ivoire are taken from the country’s EEZ, the reported landings of ‘faux poissons’ from outside the EEZ were likely included in the data submitted to FAO.Illegal fisheriesWith over 600-700 fishing vessels visiting the ports of Côte d’Ivoire, there are no inspectors responsible for fisheries compliance (SIF 2010). Furthermore as of 2011, Côte d’Ivoire did not have patrol boats and relied on it its navy to monitor fisheries and the Monitoring Control and Surveillance (MCS) unit and Vessel Monitoring System (VMS) were not functional (Manning 2011). This fostered illegal fishing, e.g., by over 40 Chinese trawlers in 2004 and 2005 (Anon. 2007) of which only 8 and 9 vessels were legal, respectively. For 2010, illegal catches were estimated at 55,116 t (Valdmanis and Akam 2010). We multiplied the number of illegal Chinese pair trawlers, i.e., 32 and 31 respectively for 2004 and 2005 by a CPUE of 1,252 t·vessel-1·year-1 (Pauly et al. 2013), slightly higher than the average CPUE estimated for legal trawlers, and then interpolated starting from 0 in 1990, as 1991 coincides with the beginning of Chinese fishing operations in Côte d’Ivoire. 26DiscardsTrawlersDiscard rates observed and reported for Côte d’Ivoire are relatively low, as only a few species are discarded within the EEZ. Furthermore, these low rates have already been declining in recent years reflecting that trawlers keep their fish of lower value (Cavérivière 1983). Discards rate of 15% were reported from 1958 and 1959 (Cavérivière 1983), which we assumed constant for the 1950s. For 1966 and 1967, we used the acoustic trawling survey report by Troadec et al. (1969), which showed that of over about 1,940 kg·h-1 of catch, 1,550 kg·h-1 were commercial species, the remainder being discarded. Thus, relying on the assumption that the survey trawler performed similarly than other trawlers (300 CV and mesh size of trawl 40 mm) over the same fishing grounds, we obtained a discard rate of 20% of total catches, which was kept constant between 1966 and 1969 (Troadec et al. 1969). For 1983, Cavérivière (1983) reported a discard rate ranging between 5% and 30%, which is herein averaged at 18% for demersal trawlers. Knowing that discard rates have been declining (Cavérivière 1983), we assumed a decline of 20% for 2010, i.e., a discard rate of 14%. We applied these discard rates to the estimated domestic trawl catch within and outside Côte d’Ivoire EEZ. For the Chinese legal trawl fleet, we applied a discard rate of 40% (Belhabib et al. 2013), while for the illegal pair trawl fleet, we applied a discard rate of 80% of the trawl catch (Belhabib et al. 2013).Similarly, the discards of the Spanish and French tuna fleet were estimated at 14% for 1998 (Romagny et al. 2000), which we assumed constant between 1998 and 2010 across fleets of different origins. We assumed discards generated by tuna fleets were conservatively 20% higher in 1950 given the decline in tuna discards due to development of a market for “faux poissons” (Romagny et al. 2000; Chavance et al. 2011). We interpolated and applied these discard rates to the estimated tuna catch taken within Côte d’Ivoire by both the domestic and foreign fleets.Cavérivière (1983) observed that around 1% of small pelagic purse-seine catches were discards and were constituted mainly of West African ilisha (Ilisha Africana). We assumed this discard rate was constant between 1950 and 2010 and applied it to the small pelagic domestic purse-seine catch within Côte d’Ivoire.Species disaggregationWe disaggregated subsistence lagoon and artisanal catches using the species composition described by Laë (1992). For industrial catches, we derived a species disaggregation from the reported landings dataset (supplied by the FAO), while for the foreign component, we disaggregated catches based on FAO (2008b). We disaggregated discards based on the description by Cavérivière (1983) and Romagny et al. (2000).resultsArtisanalTotal artisanal catches were estimated at over 2.9 million t between 1950 and 2010, 67% of which were marine. Lagoon artisanal catches were estimated at 982,300 t during the 61 years’ time period. Lagoon catches increased from 14,200 t in 1950 to a peak of 22,000 t in 1979, right before they collapsed due to the decline of the small pelagic catches and the proliferation of collective fishing gear (Figure 3). Lagoon catches varied later on, while increasing toward their second peak of 15,800 t in 1998. They have been declining since, due to increasing migrations towards the coast (Figure 3). Artisanal marine catches decreased slightly in the early 1950s, due to the conflict between Côte d’Ivoire and Benin, which drove fishers from the latter country to leave Côte d’Ivoire. Artisanal catches increased again, to 35,000 t in 1984 and then decreased to 25,000 t in 2010, their minimum since 1957 (Figure 3).0102030405060701950 1960 1970 1980 1990 2000 2010Catch (t x 103 )YearMarineLagoonFigure 3.  Reconstructed artisanal marine and lagoon catches from Côte d’Ivoire EEZ, 1950-2010.Côte d’Ivoire - Belhabib and Pauly 27SubsistenceSubsistence catches were estimated at 523,000 t over the 1950-2010 time period, of which 456,100 t were from the lagoons of Côte d’Ivoire (83%). Lagoon subsistence catches taken mostly by cast nets and tegbe systems increased to a peak of 9,100 t in 1977, and then decreased to less than 6,500 t in 2010 as the use of Tegbe systems fishers migrating towards the coast (Figure 4). Subsistence marine catches, including the catch taken home by artisanal fishers, were estimated at 67,200 t·year-1 between 1950 and 2010, less than 12% of the total subsistence catch, and, overall, remained relatively constant at around 1,000, with slight increases from the 1970s to the 1990s (Figure 4).Industrial domesticTotal industrial domestic catches were estimated at 2.9 million t between 1950 and 2010, around a third of which were taken from outside of Côte d’Ivoire EEZ. Small pelagic purse-seine contributed over half of total domestic catches, followed by demersal catches with around 40% the total domestic industrial catch, while tuna catches including ‘faux poissons’ catches represented only 7%. The latter number is explained by the fact that the domestic tuna fleet operated only between the mid-1960s and the mid-1980s. Total catches increased from around 6,200 t in 1950 to a first peak of around 78,000 t in 1972, corresponding to the peak of demersal and shrimp trawl catches and a second peak of around 80,000 t in 1981 corresponding to the peak of tuna fisheries (Figure 5). Catches remained relatively constant at around 78,000 t·year-1 on average during that time, which corresponds to the period of economic prosperity. Thereafter, catches declined steadily to less than 22,048 t in 2010 (Figure 5).Domestic demersal trawl catches were estimated at 1.5 million t between 1950 and 2010, 20% of which were caught from outside Côte d’Ivoire, but landed in Côte d’Ivoire ports. Catches taken from Côte d’Ivoire EEZ increased from around 2,400 t in 1950 to a peak of 35,600 t in 1966, declined to a minimum of 3,300 t in 1982, increased gradually to a second peak of around 32,900 t in 1996, with increasing number of domestic trawlers returning to fish in Côte d’Ivoire, to decrease thereafter to around 8,800 t in 2010. In contrast, domestic demersal trawl catches taken from outside Côte d’Ivoire EEZ reached their maximum between 1972 and 1980, a period of economic prosperity, before decreasing gradually to zero in 1990 (Figure 6). The decrease of catches taken from the outside coincides with the increase of catches taken from within Côte d’Ivoire EEZ (Figure 6).01020304050601950 1960 1970 1980 1990 2000 2010Catch (t x 103)YearCôte d'IvoireSierra LeoneGhana Guinea BissauGuineaSenegalFigure 4.  Reconstructed subsistence catch from Côte d’Ivoire , 1950-2010.Figure 5.  Total industrial domestic catches of the fleets of Côte d’Ivoire within and outside Côte d’Ivoire EEZ by gear.Figure 6.  Total industrial domestic catches of the demersal trawl fleet within and outside Côte d’Ivoire EEZ..  28The same pattern is observed for shrimp catches, which peaked at around 700 t in 1971 (mostly from Côte d’Ivoire EEZ), and then declined to its peak again in 1988 (330 t) and 1996 (280 t), all of which were caught in Nigeria, before collapsing (Figure 7).Tuna catches (including “faux poissons”) were estimated at 191,400 t between 1950 and 2010. Tuna catches started at around 250 t in 1957 and increased to 20,615 t in 1981, after which ‘faux poissons’ started to be landed in Abidjan by the domestic tuna fleet and increased to a peak of 1,100 t in 1983, corresponding to a tuna catch of 18,100 t (Figure 8). Domestic tuna fisheries collapsed as domestic tuna boats stopped operating in 1987 due to the economic crisis. A small component of ‘faux poissons’ was reported as being domestic, although, a large fraction of it was landed in Abidjan by foreign fleets.Small pelagic purse-seine catches totalled 1.5 million t between 1950 and 2010, most of which was caught within Côte d’Ivoire EEZ. Catches increased from around 3,800 t in 1950 to a first peak of 56,100 t in 1971, decreased to 21,300 t in 1979 due to the decline in the number of boats to increase again to a second peak of 44,400 t in 1982 after catches from outside Côte d’Ivoire EEZ started declining, and then decreased gradually to 13,200 t in 2010 (Figure 9).Industrial foreign catchesTotal foreign catches were estimated at over 989,000 t from 1950 to 2010, 58% of which were caught by illegal trawlers (578,500 t), 32% by the tuna fleets, including ‘faux poissons’ catches within Côte d’Ivoire, with the remainder caught by Chinese legal trawlers.Total catches by the tuna fleet (excluding ‘faux poissons’) increased from around 469 t in 1961, when the fishery began to a peak of 14,000 t·year-1 on average during the early 1970s and then declined to 2,100 t in 2010 (Figure 10). Tuna catches by France and Spain dominated over the 1950s-2010 time period, while catches by Japan, Korea, Taiwan and Israel peaked in the early 1970s to be zero later on Figure 10.‘Faux poissons’ catches were estimated at around 30,300 t between 1950 and 2010, which represented the equivalent of 10% of the tuna catch. ‘Faux poissons’ catches increased from 200 t in 1980 with the introduction of the log fishing practice in the tuna purse-seine fishery, to a peak of around 2,000 t in 1993, and then remained more or less constant thereafter (Figure 10).Legal Chinese trawl catches were estimated at 94,500 t between 1990, when they began, and 2010. Catches increased from zero in 1990 to a maximum of 7,300 t in 2005, then remained relatively constant (Figure 10). Illegal Chinese trawl catches increased from zero in 1990 to over 55,100 t in 2010, and then totalled over 578,500 t.01020304050601950 1960 1970 1980 1990 2000 2010Catch (t x 103 )YearSierra LeoneCote d'IvoireSenegalGhanaCongoFigure 7.  Total industrial domestic catches of the shrimp trawl fleet within and outside Côte d’Ivoire.Figure 8.  Total industrial domestic catches of the tuna fleet and its ‘faux poissons’ bycatch within Côte d’Ivoire EEZ.Figure 9.  Total industrial domestic catches of the tuna fleet and its ‘faux poissons’ bycatch within Côte d’Ivoire EEZ.Côte d’Ivoire - Belhabib and Pauly 29DiscardsDiscards within Côte d’Ivoire waters were estimated at over 777,400 t from 1950 to 2010, most of which were by illegal trawlers operating within Côte d’Ivoire EEZ (60%), followed by the domestic and the foreign fleets with 27% and 14% respectively.Discards by the domestic fleets increased from around 360 t in 1950 to a peak of 7,400 t in 1966 with the peak of industrial trawl catches. Discards by the domestic fleet within Côte d’Ivoire EEZ decreased thereafter, which corresponds with the start of the domestic fleet venturing outside Côte d’Ivoire waters (Figure 11). Domestic discards increased thereafter to a second peak of 5,100 t·year-1 in the mid-1990s to decrease again to around 1,000 t in 2010 (Figure 11).Discards by foreign tuna fleets were estimated at 43,400 t from 1950 to 2010, increasing from 66 t in 1961 to a peak of 2,200 t·year-1 between the early and the mid-1970s, then decreasing to less than 300 t in 2010 (Figure 10). Discards by the legal trawl (China) fleet, on the other hand, increased steadily from 320 t in 1990 to around 4,500 t in 2005, a level at which they remained (Figure 11). Illegal trawl discards represented the overwhelming majority of discards, with over 462,800 t from 1950 to 2010, increasing from around 2,300 t in 1990 to around 44,100 t in 2010 (Figure 11).‘Faux poissons’ from outside Côte d’Ivoire EEZTotal foreign ‘faux poissons’ catches from outside Côte d’Ivoire EEZ landed in Abidjan were estimated at over 599,300 t between 1950 and 2010, of which about 374,200 t (62%) were reported to FAO as Côte d’Ivoire catch. ‘Faux poissons’ catches increased rapidly since the Fish Aggregating Device was introduced in the early 1980s, and peaked twice, in 1993 with around 29,800 t and in 2000 with around 28,600 t (Figure 12). Catches reached a maximum in 2010 (Figure 9). Unreported catches of ‘faux poissons’ declined as reporting improved, from 13,800 t·year-1 on average in the 1980s to less than 5,200 t in 2010 (Figure 12).Total catchesFAO data reported by Côte d’Ivoire include catches of ‘faux poissons’ taken by foreign fleets from outside the EEZ of Côte d’Ivoire which are recorded locally. Similarly, catches taken by Côte d’Ivoire from other countries’ EEZs were reported to the FAO. Total domestic reconstructed catches were estimated at 5.6 million t over the period from 1950 to 2010 of which only 2.6 million t was reported to FAO. Total removals from Côte d’Ivoire EEZ increased from 52,700 t in 1950 compared to 14,600 t reported to FAO to 105,100 t·year-1 on average from the early 1970s through the early 1980s compared to 43,000 t·year-1 reported to the FAO after removing ‘faux poissons’ catches, which started being reported in 1981. Domestic catches within Côte d’Ivoire EEZ declined steadily thereafter to less than 65,500 t in 2010 compared to 56,889 t reported to FAO. It is herein strongly suspected that a large portion of the miscellaneous marine fish component is taken by foreign fleets from EEZs outside of Côte d’Ivoire and landed 02468101214161950 1960 1970 1980 1990 2000 2010Catch (t x 103 )YearFranceJapanChina trawlersIsraelKoreaSpainTaiwanOthers"Faux poissons"01020304050601950 1960 1970 1980 1990 2000 2010Catch (t x 103 )YearCymbiumForeign tunaIllegalDomesticLegal trawlers010203040501950 1960 1970 1980 1990 2000 2010Catch (t x 103 )YearCymbiumReportedUnreportedFigure 10.  Total foreign legal catches from Côte d’Ivoire, 1950-2010.Figure 11.  Total reconstructed discards by domestic and foreign fleets within Côte d’Ivoire EEZ, 1950-2010.Figure 12.  Total ‘faux poissons’ caught by foreign fleets outside Côte d’Ivoire EEZ and landed in Côte d’Ivoire ports, 1950-2010. 30in Abidjan then reported to the FAO as being domestically caught. In fact one strong reason for the increase in reported landings, which doubled in 2010, seems to be due to the reporting of around 15,000 t of ‘faux poissons’. This is supported by the fact that literature refers to a large part of these catches as ‘reported’, while many reports from the CRO include reported ‘faux poissons’ catches. When these are filtered out, catches decline (Figure 13).Overall total removals from Côte d’Ivoire EEZ (domestic and foreign) were estimated at around 7.0 million t between 1950 and 2010. Catches increased and remained relatively constant at 116,000 t·year-1 on average between the mid-1960s when Côte d’Ivoire signed agreements for foreign tuna fishing (mainly), and the early 1980s, when the economy collapsed. Catches decreased slightly in the 1990s and increased again due to increasing illegal catches and be over 167,000 t in 2010.discussionTotal catches in Côte d’Ivoire were estimated at 7.1 million t between 1950 and 2010, of which 5.6 million t were caught domestically within Côte d’Ivoire EEZ. Total reconstructed domestic catches exhibit a constant decline since the mid-1980s due to poor economic conditions and over-exploitation, in contrast to the increasing trend suggested by the data supplied to the FAO. The latter is primarily due to a massive increase in ‘faux poissons’ catches landed by foreign fleets but reported by Côte d’Ivoire. This is dangerous, as it masks the decline in domestic catches from Côte d’Ivoire EEZ. Thus, not only is the over-exploitation problem hidden, but it suggests the sector to be flourishing, while in reality is far from the truth.The symptoms of this decline are further illustrated through a general over-exploitation of the Côte d’Ivoire EEZ (Cormier 1983), the collapse of the shrimp fishery which is believed to be the result of artisanal shrimp fishing in lagoons (Garcia and Fonteneau 1971), the tuna fleet which went “out of business” as early as the late 1980s, the general decrease in the number of boats operating within and outside Côte d’Ivoire and even the proliferation of unwanted species such as triggerfishes in the early 1970s (Troadec and Garcia 1979). Despite this, artisanal fisheries still retain an important role with around 50% of total domestic catches. Indeed, their role has increased as industrial fisheries declined. The constraint to fisheries exacerbated by poor economic conditions, has driven artisanal fishers to adopt diverse adaptation strategies to avoid suffering a similar fate. For example, Ecoutin (1992) shows that the pirogues of Côte d’Ivoire have evolved in size, capacity and motorization from those described by Lassarat (1958), thus increasing their reach and fishing grounds, a pattern also observed elsewhere, e.g. Senegal (Belhabib et al. 2014). This is further illustrated by the disappearance of motors with low power (Ecoutin 1992). Fishers also adapted to other conditions; for example, droughts in the 1970s and 1980s in Niger delta in Mali drove fishers to migrate to the Côte d’Ivoire fishing grounds (Njock and Westlund 2010). Another condition that strongly impacted the fisheries of Côte d’Ivoire is related to conflicts and the migrations they incur. The Ebrié Lagoon which was once “filled with fish” (Chenery 1875) has witnessed changes in the populations through migrations from the conflicted areas of the North, which translated into increasing catches. Later on, these catches decreased due to over-exploitation and conflicts that again drove fishers to migrate towards the already overexploited coastal marine fisheries. This describes a chaotic situation where artisanal fishers of Côte d’Ivoire become trapped between socio-political conflicts, the desire for a better life and over-exploitation triggered in part by the large number of illegal fishing vessels operating in Côte d’Ivoire.Another effect of the collapsing economy was the devaluation of the Franc CFA, which has increased the price of fish and thus reduced fish consumption (Akindes 1995). The increase of post-conflict consumption of fish (Dabalen and Saumik 2013) is due in part to the increase in informal food business (Akindes 1995), i.e, subsistence fishing through the use of cast nets as documented herein. Furthermore, the role of fish in post-conflict diets appears to have increased (Kouame and Enoh 2011), thus giving fish an even greater weight in the balance of food security and poverty alleviation in the country.Catch (t x 10 )3Figure 13.  Reconstructed total catch for Côte d’Ivoire EEZ, 1950-2010, by a) sector with official reported data overlaid as a line graph and b) taxon with “Others” consisting of 78 additional taxonomic categories.Côte d’Ivoire - Belhabib and Pauly 31Despite multiple efforts, notably to tackle the issue of the non-reporting of ‘faux poissons’ (which are now being reported as part of Côte d’Ivoire catches, the objectives of fishery development in Côte d’Ivoire are questionable. First, reporting ‘faux poissons’ in FAO datasets and using these for fishery analysis masks the declining trend of fisheries and jeopardizes the movement towards sustainable fisheries. Furthermore, to counter the effect of over-exploitation and declining supplies, Ivoirian fisheries planners consider modernizing and/or replacing of aging vessels in order to “increase efficiency”, which however, will increase fishing effort on overexploited resources and further reduce catches. Finally, while they assert that they want to increase protein supply for domestic consumption as a first objective, they also plan to promote fish exports (Mabawonku 1990).The important economic role that fisheries play in Côte d’Ivoire is undisputedly due to the small scale fisheries (Diaby 1996; Golé Bi Golé et al. 2005). Yet, while the dependence of small scale communities upon fish increases in the face of conflicts (see UNDP 2011), catches that decline, jeopardizing the livelihoods as poverty increases. 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FAO landings vs. reconstructed total catch (in tonnes), and catch by sector with discards shown separately, for Côte d’Ivoire, 1950-2010.Year FAO landings Reconstructed total catch Industrial Artisanal Subsistence Discards1950 14,600 52,700 5,900 41,200 5,200 3561951 14,223 54,100 7,200 41,000 5,500 4811952 18,263 57,300 9,900 40,900 5,700 8401953 17,902 61,300 13,400 40,700 5,900 1,3191954 17,535 66,600 18,000 40,500 6,100 1,9641955 17,412 67,800 18,800 40,400 6,300 2,2951956 20,847 70,000 21,000 40,200 6,500 2,3031957 26,521 72,600 21,600 41,800 6,800 2,3431958 26,174 77,200 24,100 43,300 7,100 2,6651959 29,780 86,500 30,700 44,800 7,300 3,6251960 34,123 88,200 30,500 46,400 7,600 3,7321961 35,283 98,000 37,200 47,900 7,800 5,1371962 36,427 101,500 38,600 49,300 8,100 5,4211963 36,729 102,300 37,600 50,800 8,300 5,4661964 45,386 105,200 38,600 52,300 8,600 5,7501965 47,197 107,200 39,400 52,800 8,800 6,2071966 44,535 121,200 51,100 53,300 9,000 7,8001967 44,545 120,100 50,000 53,700 9,200 7,1681968 47,819 119,200 48,900 54,500 9,400 6,4421969 43,117 113,400 41,400 55,200 9,500 7,2841970 38,948 105,500 34,500 55,700 9,700 5,6311971 51,714 119,400 48,600 56,100 9,800 4,8721972 48,436 125,100 52,800 56,600 9,900 5,8111973 36,667 111,700 38,500 57,100 10,000 6,1651974 44,555 113,500 40,700 57,500 10,100 5,2891975 37,524 111,700 38,900 58,000 9,700 5,2011976 57,043 114,600 42,600 57,100 9,700 5,1521977 42,921 124,500 51,300 56,600 10,300 6,2541978 43,169 120,400 45,200 57,500 11,600 6,0561979 44,078 111,100 36,500 57,900 11,200 5,5141980 35,707 116,300 50,200 52,100 8,200 5,7841981 38,249 122,300 62,800 46,400 7,600 5,4661982 36,932 121,500 62,300 44,700 9,300 5,1801983 40,110 125,400 60,100 51,100 9,200 5,0111984 39,778 87,800 26,200 48,300 9,800 3,4781985 60,636 110,500 46,400 50,300 9,800 4,0081986 61,152 108,200 45,100 49,500 9,800 3,7921987 61,718 104,500 42,200 48,800 9,700 3,8421988 50,602 95,200 33,700 48,100 9,500 3,8531989 59,767 98,800 38,300 47,300 9,400 3,7441990 67,057 107,100 47,300 46,600 9,300 3,9181991 54,813 110,800 48,600 45,900 9,200 7,0591992 65,109 127,500 62,700 45,100 9,100 10,5991993 50,244 124,400 57,500 44,400 9,000 13,4851994 52,496 125,000 56,900 43,700 8,900 15,5241995 53,306 130,700 58,500 45,100 8,900 18,2451996 55,793 144,300 65,100 48,900 9,000 21,2221997 50,349 147,600 65,600 49,900 9,000 23,1741998 55,587 152,400 67,300 50,900 8,900 25,3331999 63,524 157,200 69,000 51,900 8,900 27,5062000 66,031 160,100 71,200 50,300 8,800 29,7632001 62,055 161,000 71,600 48,800 8,700 31,9432002 44,969 148,800 58,800 47,400 8,600 34,0162003 44,407 146,200 56,500 45,900 8,400 35,3612004 47,344 150,600 60,100 44,400 8,300 37,7872005 27,615 155,300 65,500 43,000 8,200 38,6522006 46,769 148,300 58,900 41,500 8,100 39,8592007 42,965 151,900 61,400 40,100 7,900 42,4512008 44,818 155,800 64,300 38,700 7,800 45,0152009 38,119 159,700 67,200 37,300 7,700 47,6102010 56,889 167,400 73,800 35,900 7,600 50,205 36Appendix Table A2. Reconstructed total catch (in tonnes), by major taxa for Côte d’Ivoire, 1950-2010. ‘Others’ contain 78 additional taxonomic categories.Year Ethmalosa fimbriataSardinella auritaBrachydeuterus auritusSardinella maderensisScombroids Balistes Pentheroscion mbiziPteroscion peliElops lacertaOthers1950 18,300 18,000 0 0 0 98 79 79 2,640 13,5001951 18,700 18,300 0 0 0 131 109 109 2,710 14,1001952 18,700 18,700 0 0 0 223 197 197 2,790 16,5001953 19,800 20,300 0 0 0 344 316 316 2,860 17,4001954 21,200 22,400 0 0 0 507 475 475 2,930 18,6001955 21,300 22,100 0 0 0 591 556 556 3,010 19,7001956 19,800 23,100 0 0 0 595 557 557 3,080 22,4001957 21,100 20,600 794 0 0 596 555 555 3,160 25,1001958 22,300 22,300 856 0 0 677 633 633 3,240 26,5001959 24,500 22,600 1,740 0 0 918 870 870 3,320 31,6001960 24,400 21,400 1,531 0 0 945 895 895 3,400 34,7001961 25,800 24,800 2,481 0 403 1,281 1,227 1,227 3,480 37,3001962 26,000 24,700 3,300 0 807 1,336 1,279 1,279 3,560 39,2001963 25,200 23,400 3,114 0 1,210 1,332 1,272 1,272 3,630 41,9001964 29,600 24,700 2,632 0 1,614 1,388 1,325 1,325 3,710 38,8001965 28,600 21,500 6,046 0 2,017 1,487 1,421 1,421 3,790 41,0001966 32,200 20,500 4,668 0 2,420 1,882 1,780 1,780 3,860 52,1001967 29,400 22,700 3,898 0 2,824 1,714 1,591 1,591 3,930 52,5001968 28,500 17,600 1,113 0 3,227 1,516 1,387 1,387 4,030 60,4001969 25,700 20,000 2,551 0 5,959 1,591 1,506 1,506 4,140 50,4001970 23,500 10,500 349 12,080 8,691 1,062 985 985 4,200 43,1001971 22,700 10,400 427 18,440 11,423 748 607 607 4,260 49,8001972 23,300 7,700 1,080 15,020 14,155 828 688 688 4,320 57,3001973 24,400 2,200 603 13,410 14,155 884 816 816 4,380 50,0001974 23,400 1,200 623 15,200 14,155 608 525 525 4,430 52,8001975 25,300 0 887 18,710 14,155 458 393 393 4,420 46,9001976 21,600 2,400 3,052 14,750 12,115 453 370 370 4,140 55,3001977 26,000 1,200 4,891 19,110 11,587 530 440 440 4,270 56,1001978 26,300 3,700 6,238 11,810 11,060 499 433 433 4,550 55,4001979 25,400 800 3,563 14,790 10,532 468 427 427 4,510 50,2001980 23,500 2,000 4,214 9,520 10,004 522 421 421 3,340 62,4001981 19,600 10,200 4,327 10,820 9,476 407 245 245 2,520 64,5001982 19,100 14,500 3,858 5,750 8,949 362 197 197 2,540 66,0001983 22,900 19,000 2,169 4,780 8,421 423 260 260 3,410 63,8001984 19,200 8,000 1,733 4,340 7,893 448 395 395 3,140 42,3001985 19,000 25,300 1,349 5,520 7,365 577 442 442 3,440 47,1001986 19,000 28,100 1,922 2,580 6,838 761 618 618 3,360 44,3001987 18,800 23,600 2,091 3,370 6,310 789 664 664 3,280 44,9001988 19,700 13,400 3,325 4,110 5,782 790 709 709 3,200 43,4001989 20,100 12,000 432 4,450 5,254 793 691 691 3,110 51,3001990 21,700 14,900 7,192 7,370 4,727 875 737 737 3,030 45,9001991 20,700 21,900 7,730 2,370 4,199 1,901 1,761 1,761 2,950 45,5001992 21,500 28,300 7,530 1,970 4,199 3,033 2,839 2,839 2,860 52,5001993 20,200 19,500 7,599 4,420 4,199 3,962 3,792 3,792 2,780 54,1001994 19,600 14,700 8,562 6,390 4,199 4,704 4,510 4,510 2,690 55,2001995 19,900 14,700 8,912 3,780 4,199 5,611 5,403 5,403 2,920 59,9001996 21,000 22,700 9,334 3,080 4,199 6,591 6,352 6,352 3,480 61,2001997 22,900 13,700 10,747 2,810 2,831 7,363 7,093 7,093 3,420 69,7001998 21,400 13,800 6,902 2,280 2,831 8,139 7,837 7,837 3,360 78,1001999 22,400 13,800 9,943 2,050 2,831 8,917 8,583 8,583 3,300 76,9002000 20,300 20,600 11,584 2,510 3,350 9,698 9,332 9,332 3,230 70,1002001 19,500 20,500 8,505 3,040 3,350 10,475 10,085 10,085 3,160 72,4002002 19,100 8,400 10,530 5,260 3,397 11,192 10,839 10,839 3,090 66,2002003 15,300 8,600 10,053 3,040 3,397 11,766 11,376 11,376 3,020 68,2002004 12,400 10,600 10,885 8,910 2,312 12,648 12,223 12,223 2,940 65,4002005 7,700 13,400 14,850 4,650 2,312 12,834 12,422 12,422 2,870 71,9002006 6,700 8,300 12,126 3,420 2,312 13,370 12,933 12,933 2,500 73,7002007 7,300 8,300 11,836 4,570 2,312 14,252 13,790 13,790 2,720 73,0002008 6,600 5,900 12,200 4,450 2,076 15,137 14,648 14,648 2,450 77,8002009 6,900 4,700 12,754 4,470 2,076 16,021 15,505 15,505 2,570 79,2002010 3,200 9,600 13,072 4,730 2,076 16,904 16,362 16,362 1,030 84,100Togo - Belhabib et al. 37the marine Fisheries oF toGo, the ‘heart oF West aFrica,’ 1950 to 20101Dyhia Belhabiba, Viviane Kutoubb and Daniel Paulyaa Sea Around Us, Fisheries Centre, University of British Columbia2202 Main Mall, Vancouver, V6T 1Z4, CanadabUSAID, Dakar, Senegald.belhabib@fisheries.ubc.ca; koutubviviane@gmail.com; d.pauly@fisheries.ubc.caabstractFisheries catches in the Togolese Exclusive Economic Zone were reconstructed including small scale marine and lagoon fisheries, commercial large scale fisheries, illegal foreign fisheries and discards by both the domestic and foreign sectors. In the last two decades, total domestic catches showed a decrease, in contrast to the positive trend observed in the data supplied to FAO. Moreover, with a total of 2.3 million tonnes compared to 560,000 tonnes between 1950 and 2010, domestic catches were 4.1 times the catch supplied to FAO. This study also shows higher foreign fisheries removals than what is officially reported, with the foreign legal and illegal catch representing almost a quarter of the total reconstructed catch. These catches are masked by the reflagging practices of Togo and the lack of fisheries monitoring and enforcement, which illustrates a general laisser faire in the Togolese fisheries policy, and threatens poverty alleviation strategies and food security within local communities trapped between the over-exploitation of fisheries and the anticipated effects of climate change.introductionTogo, a small West African country stretching 600 km from the edge of the Sahel in the North to the coast of the Gulf of Guinea in the South, where it has a width of 56 km, consequently has an extremely small Exclusive Economic Zone (EEZ), and an even smaller shelf (Figure 1).Unmonitored and uncontrolled, freshwater and coastal lagoon fisheries of Togo generate relatively high yields, but remain largely understudied. Marine fisheries, which apparently generate higher yields, are given more importance in the few studies that are available for Togo. In fact, these fisheries, similar to those of Benin, are mostly mentioned en passant in reviews of the Gulf of Guinea fisheries (Écoutin et al. 1993; Guiffre 1993; Horemans 1993, 1994, 1995).Here, we try to overcome this by assembling all the information that we could obtain on the Togolese fisheries, and particularly on their catches since 1950, using early ‘grey literature’ gathered during a short stay in that country (by DP in Oct. 1971), as well as from the more recent peer-reviewed and report literature, both on and offline, with particular emphasis to colonial and ‘development’ sources in German and French.Togo, was known under various names highlighting a rich historical past. Its coast, used as a slave trading platform, earned Togo the name of ‘Slave Coast’; as a German colony from 1884 to 1918, it became ‘Togoland’, before it was transferred to France as part of the French colonial empire in West Africa, to finally gain independence in 1960.1 Cite as: Belhabib, D., Kutoub, V. and Pauly, D. (2015) The marine fisheries of Togo, the ‘heart of West Africa,’ 1950 to 2010. pp. 37-50. In: Belhabib, D. and Pauly, D. (eds). Fisheries catch reconstructions: West Africa, Part II. Fisheries Centre Research Reports vol.23(3). Fisheries Centre, University of British Columbia [ISSN 1198-6727].Figure 1.  a) Map of Togo showing the Exclusive Economic Zone of Togo, and b) showing the coastal lagoons of Togo. 38However, the ties which Togo retained to Germany where instrumental for the decade-long marine fisheries development project initiated in the mid-1960s, which brought industrial fishing, specifically bottom trawling, onto the Togolese shelf (Karger and und Steinberg 1969).This development was meant to complement the existing small-fisheries, but these were soon seen as competitors to the trawl fisheries, if mainly because their beach seines and other gear tended to exploit the juvenile stages of species potentially exploitable as adults further offshore by the newly supplied trawler (Beck 1974, 1977). These dynamics still exists, in Togo and elsewhere, though as rather typical competition between foreign trawlers and local small-scale fishers (Pauly 2006), the implantation of a locally-based industrial fishery having failed. These dynamics, and the foreign element that they entail, are also the reason why the catches of the marine fisheries of Togo, despite their small size, are difficult to disaggregate into subsectors.methodsThe majors sources of information used here are peer reviewed and grey literature along with media reports; the data they contained we analyzed using the catch reconstruction methods in (Zeller et al. 2007), which, in the main, consists of:1) Using the available catch estimate as ‘anchor points’, between which linear interpolations were used to provide preliminary catch estimates for years without data;2) Using demographic data to extrapolate estimates of small-scale fisher numbers (incl. beach seine operators) to years for which such estimates were lacking; and3) Generally: provide (conservative) estimates where there was evidence of a non-zero catch.The procedure used for the various subsectors was a follows:Small-scale fisheriesSmall scale fisheries include two major sectors, subsistence fisheries operated in (brackish-water) coastal lagoons (freshwater fisheries are not considered here), and marine artisanal fisheries conducted from beaches (beach seines and set nets) or by pirogues.Lagoon subsistence fisheriesThe statistics on lagoon fisheries are included in the continental water component, and the fisheries are not monitored (FAO 2007). Thus the catch data supplied to FAO pertains mostly to freshwater species. Most lagoon fishery catches in Togo are for personal consumption and are not marketed (Laë 1992), which differs from neighboring Ghana, where the catch of lagoon fishers are mostly sold (Pauly 1976). They are operated by mostly occasional and seasonal fishers who practice agriculture at the same time (Laë 1992). Therefore, this fishery is considered a subsistence fishery. Coastal lagoons in Togo, as elsewhere along the gulf of Guinea are exploited either traditionally or by means of extensive ranching systems called acadjas.Traditional fishingThe mapping by Weigel (1985) for Lac Togo, which despite its name is a coastal lagoon, in 1960 revealed 19 villages over a total of 37, where 700 pirogues are active operated by 2.5 fishers at average (de Surgy 1966; Bama 1984). Considering a total of 37 villages and 5,300 permanent fishers (Alsopp 1966), i.e., 51 pirogues per villages and 143 fishers, the remaining 18 villages not covered by Weigel (1985) would shelter 2,574 fishers and 918 additional pirogues in 1960. Thus the total number of fishers for 1960 is estimated at 4,324 fishers. These numbers are conservative because they do not include part time and seasonal fishers, and children (de Surgy 1966). For 1978, Dioury (1983) estimated the number of pirogues at 2,000, with 2.5 fisher per pirogue (Bama 1984), i.e., a total of 5,000 fishers. Laë (1992) reported a total number of 1,800 fishers in 1984 for 33 villages, i.e., 2,372 fishers in 37 villages in total. The number of pirogues was estimated at 1,000 in 1985 (Weigel 1985), 1,100 in 1989 (Sedzro and Kusiaku 1999), 793 in 2007 (IRD 2011) and assumed constant thereafter. Assuming a constant number of fishers per pirogue at 2.5, we estimated the number of fishers at 2,500 in 1985, 2,750 in 1989, 1,586 in 2007 onwards, then we performed a series of linear interpolations to complete the time series. The CPUE per fisher declined from 1.7 t∙year-1∙fisher-1 in the mid-1960s to 0.53 t∙year-1∙fisher-1 in the mid-1980s (Laë 1997). Given the strong decline in lagoon catches and the over-exploitation already reported in the 1960s (de Surgy 1966), we assumed the CPUE in 1950 was 20% higher than in 1965 (2.05 t∙year-1∙fisher-1). Pérez-Ruzafa and Marcos (2012) estimated a CPUE of 0.59 t∙year-1∙fisher-1 in 2012. Thus we interpolated linearly CPUE estimates and multiplied these by the total number of fishers to estimate the traditional lagoon catch in Togo from 1950 to 2010.Togo - Belhabib et al. 39Acadja catchesAcadjas are extensive ranching techniques that rely on wild fish being concentrated in “dense masses of branches planted in the muddy bottom” (Welcomme 1972), in which they find shelter and food. Acadjas were introduced in Togo in the mid-1950s (King 1993), and because of their uncontrolled proliferation, which created conflicts between traditional fishers and fishers using this new technique, and also because of the deforestation they induce, they were prohibited in 1975 (Weigel 1985). However, the higher productivity (Kapetsky 1981) and the lack of control is undoubtedly encouraging an illegal use that is still common in Togolese lagoons (SOFRECO 2011). Weigel (1985) estimated a total number of 133 acajda systems in Togo of 0.7 ha each and a productivity of 5 t∙ha-1 from 1969 to 1972. The resulting catch would be the product of the number of acadja systems, the average surface and the productivity, i.e., 451 t from 1969 to 1972. We assumed catches induced by acadjas in 2010 were half the catch of 1972, i.e., 226 in one hand because of the unenforced prohibition but mostly because of over-exploitation and pollution. We interpolated catches from 0 t in 1954 right before the introduction of the Acadja technique to Togo, to 451 t in 1969 and then from 541 t in 1972 to 226 t in 2010.Traditional lagoon and acadja catches are overwhelmingly dominated by the blackchin tilapia Saratherodon melanotheron and the Guinean tilapia Tilapia guineensis (50-70%), the rest consisting of a near equal mix of coastal marine and continental (freshwater) species (Laë 1994). We applied the species disaggregation provided by Laë (1994) to traditional and acadja lagoon catches (Table 1).Artisanal marine fisheryLand based fishingCoastal population data was extracted from the Center for International Earth Science Information Network (CIESIN 2012) for 1990, 2000 and 2010 (Table 2) within a range of 10 km of the coast from, and total population data was extracted from Populstat (www.populstat.info [2012]) and the Worldbank (www.worldbank.org [2012]) databases from 1950 to 2010 (Table 2). We estimated the proportion of coastal population over the total population at 19% for 1990, 2000 and 2010. We assumed this rate was constant from 1950 to 2010, and thus could estimate the annual coastal population in Togo (Table 2). In 1965, fishers used 345 cast nets the majority of which were operated by individual land-based fishers (80%), 135 beach seines, half of which uses at average 30 fishers on land and 36 handlines (de Surgy 1966). Thus the total number of land-based fishers in 1965 was estimated at 2,334 permanent land based fishers, and 2,000 seasonal land-based fishers (de Surgy 1966) working 42% less (Laë 1992), which translates to 1,164 permanent working fishers. The total number of land based fishers is the sum of the two categories (3,170 in 1965). This number represented 1.08% of the coastal population in 1965. Using the same method, based on the data by IRD (2011), 208 handlines, 2,146 nets of which we conservatively assumed 20% were operated from land by individual fishers, 62 beach seines, i.e., 930 land based fishers. Thus the total number of land-based fishers for 2010 was estimated at 1,567, i.e., 0.14% of the coastal population. We assumed the rate was constant from 1950 to 1965 and interpolated from 1.08% in 1965 to 0.14% in 2010. Then we applied these rates to the coastal population data per year and estimated the number of artisanal land-based fishers from 1950 to 2010 (Table 2). We assumed the CPUE per fishers working on a pirogue was similar to the CPUE of a land based fisher since the two categories operate in similar areas and use similar gears. The number of fishers per pirogue increased from an average of 4.75 in the 1950s and 1960s (de Surgy 1966) to 8.43 fishers per pirogue in 2010 based on the estimates of the number of pirogues and the number of pirogue based fishers by (IRD 2011). We performed a linear interpolation and estimated the land based catch as the product of the CPUE per fishers, i.e., CPUE per pirogue (estimated in artisanal fishing above) divided by the number of fishers per pirogue, and the total number of land based fishers.A detailed analysis of the catch composition of the beach seine catch in 1973 was presented by Beck (1974, 1976), documenting a catch consisting of most of the groups making up the “shallow water” community, dominated by croakers (Family Sciaenidae; Longhurst and Pauly 1987, p151). We used this description to break down land based catches onto taxonomic groups (Table 3).Table 1.   Species composition of lagoon catchesScientific name Common name %Clarias gariepinus North African catfish 2.3Heterotis niloticus African bonytongue 0.5Parachanna obscura African snakehead 0.8Hepsetus odoe Kafue pike 0.2Schilbe mystus African butter catfish 0.1Pellonula leonensis Smalltoothed pellonula 0.4Chrysichthys spp. Bagrid catfishes 14.0Gerres spp. Silver biddies 1.4Hemichromis fasciatus Banded jewelfish 1.3Sarotherodon melanotheron Blackchin tilapia 57.9Tilapia guineensis Guinean tilapia 7.6Ethmalosa fimbriata Bonga shad 1.2Liza falcipinnis Sicklefin mullet 1.9Pomadasys jubelini Sompat grunt 0.1Elops lacerta West African ladyfish 0.4Polydactylus quadrifilis Giant African threadfin 0.1Callinectes amnicola Bigfisted swimcrab 7.6Farfantepenaeus notialis Southern pink shrimp 2.1 40Pirogue fishingThe number of pirogues was documented since 1962, and remained relatively constant since then (Table 4). We assumed conservatively that the number of pirogues was 20% lower in 1950 than in 1962 (Table 4), since evidence suggests the number of pirogues increased slightly to ‘chase’ sardinella and sardine stocks going further from the coast, migration caused by industrialization and over-exploitation of coastal areas (Welcomme 1972). Thereafter, we interpolated the number of pirogues between the anchor points from 1950 to 2010 (Table 4). As for the catch per unit of effort, in 1978, based on a catch of 12,003 t∙year-1 and an effort of 346 pirogues (Amégavie 1979), we estimated a CPUE of 34.69 t∙year-1∙boat-1. Because of the over-exploitation pattern of coastal areas in Togo, constrained by a higher motorization rate in 2010, we assumed the CPUE in 2010 was 10% lower than the CPUE in the mid-1970s. Similarly in 1950, because of a consequent lower motorization (0%; Welcomme 1972), we assumed the CPUE in 1950 was 20% lower than in 1983. We then interpolated linearly from 27.75 t∙year-1∙boat-1 in 1950 to 34.69 t∙year-1∙boat-1 in 1978, and then to 31.22 t∙year-1∙boat-1 in 2010. Thereafter, we multiplied the yearly number of pirogues by the corresponding CPUE to estimate the pirogue based marine artisanal catches in Togo from 1950 to 2010.We applied a species disaggregation using the 1991-1995 catch data from Denke (1997) converted to rates, then averaged (Table 5) and then applied on the artisanal catches from 1950 to 2010.Table 2.   Total population, coastal population and land based fishers estimates in Togo. Interpolations are italicized.Year Total population (x 103)Coastal population (x 103)Land based fishers as percentage of coastal population (%)Number of land based fishers1950 1,212 230 1.08 2,4881951 1,241 236 1.08 2,5481952 1,267 241 1.08 2,6011953 1,291 245 1.08 2,6501954 1,316 250 1.08 2,7021955 1,343 255 1.08 2,7571956 1,372 261 1.08 2,8161957 1,404 267 1.08 2,8821958 1,437 273 1.08 2,9501959 1,450 276 1.08 2,9771960 1,444 274 1.08 2,9641961 1,482 282 1.08 3,0421962 1,520 289 1.08 3,1201963 1,613 306 1.08 3,3111964 1,655 314 1.08 3,3971965 1,704 324 1.08 3,4981966 1,760 334 1.06 3,5401967 1,822 346 1.04 3,5921968 1,889 359 1.02 3,6491969 1,955 371 1.00 3,6981970 1,962 373 0.97 3,6331971 2,013 382 0.95 3,6481972 2,066 393 0.93 3,6611973 2,119 403 0.91 3,6711974 2,174 413 0.89 3,6801975 2,231 424 0.87 3,6871976 2,289 435 0.85 3,6921977 2,348 446 0.83 3,6941978 2,409 458 0.81 3,6941979 2,473 470 0.79 3,6931980 2,554 485 0.77 3,7131981 2,615 497 0.74 3,6971982 2,770 526 0.72 3,8061983 2,890 549 0.70 3,8561984 2,960 562 0.68 3,8311985 3,028 575 0.66 3,7991986 3,144 597 0.64 3,8191987 3,248 617 0.62 3,8161988 3,381 642 0.60 3,8371989 3,507 666 0.58 3,8411990 3,638 694 0.56 3,8551991 3,761 717 0.53 3,8341992 3,899 744 0.51 3,8191993 4,026 768 0.49 3,7831994 4,010 765 0.47 3,6071995 4,085 779 0.45 3,5111996 4,230 807 0.43 3,4671997 4,345 829 0.41 3,3871998 4,458 850 0.39 3,2971999 4,567 871 0.37 3,1952000 5,019 951 0.35 3,2902001 5,153 977 0.32 3,1742002 5,051 958 0.30 2,9102003 5,170 980 0.28 2,7732004 5,288 1003 0.26 2,6262005 5,408 1025 0.24 2,4712006 5,530 1048 0.22 2,3072007 5,653 1072 0.20 2,1332008 5,777 1095 0.18 1,9512009 5,902 1119 0.16 1,7582010 6,028 1143 0.14 1,567Togo - Belhabib et al. 41Recreational fisheriesWhile growing up in Togo, V.K did not observe significant recreational fishing activities; however a few recreational fishing clubs were created by expatriates, notably during the last 16 years. Three clubs were documented, the first in 1997, the second in 2004 and the third in 2007 (FAO 2007)1. These clubs often sell their catches to restaurants. We assumed that the number of fishers per club was 20, i.e., that they was a total of 20 fishers in 1997, 40 fishers in 2004 and 60 fishers in 2007. We extrapolated the trend and estimated the number of recreational fishers at 68 for 2010. We assumed the number of trips to be 4 per month (i.e., one day per week end) during six months of the year corresponding to the dry season (24 trips∙fisher-1∙year-1). We estimated the CPUE based on four YouTube videos posted by recreational fishers/clubs from Togo, which showed the species caught and the number of recreational fishers (5). We approximated the weight for each species, then estimated the mean CPUE as 13.6 kg∙fisher-1∙trip-1. We multiplied the number of fishers by the number of trips and the CPUEs and obtained a catch of 6.5 t for 1997, 13.1 t for 2004, 19.6 t for 2007 and 22.2 t for 2010. We interpolated linearly assuming recreational fishing began after the last coup d’état in 1967, which was followed by a certain political stability. We obtained the species breakdown by averaging the total catch by species by the total for all species (by all fishers), i.e., 515 of wahoo (Acanthocybium solandri), 21% of groupers (Fam. Serranidae), 7% of Carangidae, 7% of Muraenidae, 7% of dolphinfish (Coryphaena hippurus) and 7% of other species.Large-scale fisheriesIndustrialIndustrial fishing in Togo is conducted by visibly reflagged fleets to Togo (mostly), vessels under joint ventures, and vessels operating under agreements. Thus here, the ‘Togolese’ fleet is comprised of ostensibly Togolese vessels, i.e., vessels whose origin we couldn’t trace. The number of industrial vessels in Togo was reported by different sources (Table 6), and the origin of vessels was reported in a few instances (Table 6); thus using these numbers, we performed a series of linear interpolation and completed the effort time series per country of origin, the difference between the total number of industrial vessels as documented by the literature and the sum of the interpolated effort per country of origin, is in the category other origin (Table 6). The CPUE was estimated by Beck (1976) at 235 t∙year-1∙boat-1 in 1973 and we assumed this CPUE was constant since the introduction of industrial fishing to Togo in 1965. In the 2000s, vessels were larger, with 1,416 GRT (www.grosstonnage.com) on average compared to around 200 GRT in the 1970s (Beck 1976), i.e., increased by a factor of 7. We assumed the CPUE increased proportionally however at a lower extent given evidence of over-exploitation, i.e., by a factor of 5, resulting in a CPUE of 1,175 t∙year-1∙boat-1. We performed a linear interpolation to complete the CPUE time series and multiplied the CPUEs by the estimated effort per country.Table 3.   taxonomic composition of the beach seine (land-based) fishery (Beck 1976)Scientific name Common name %Albula vulpes Bonefish 0.1Ilisha africana West African ilisha 1.4Sardinella rouxi Yellowtail sardinella 5.1Sardinella aurita Round sardinella 0.9Sardinella maderensis Madeiran sardinella 40.7Engraulis encrasicolus European anchovy 4.3Lagocephalus laevigatus Smooth puffer 0.1Hemirhamphus balao Balao halfbeak 1.4Sphyraena afra Guinean barracuda 4.8Galeoides decadactylus Lesser African threadfin 3.6Lutjanus fulgens Golden African snapper 0.1Pomadasys jubelini Sompat grunt 0.1Brachydeutrerus auritus Bigeye grunt 16.2Gerres melanopterus Flagfin mojarra 1.0Pteroscion peli Boe drum 0.2Pseudotolithus senegalensis Cassava croaker 0.3Trachinotus ovatus Pompano 0.1Uraspis secunda Cottonmouth jack <0.1Decapterus punctatus Round scad 1.1Selar crumenophtalmus Bigeye scad 1.2Caranx hippos Crevalle jack 0.2Caranx crysos Caranx crysos 2.2Caranx senegalus Senegal jack 0.2Chloroscombrus chrysurus Atlantic bumper 11.2Vomer setapinnis Atlantic moonfish 2.4Pseudupeneus prayensis West African goatfish 0.2Sparus ehrenbergi Pagrus caeruleostictus 0.1Orcynopsis unicolor Plain bonito 0.5Solea spp. Soles 0.1Cephalopoda Cephalopods 0.1Penaeus spp. Shrimps 0.1Table 4.   Anchor points of artisanal pirogues and the corresponding CPUE, italics indicate interpolations. Data were interpolated for the missing years.Year Number of piroguesMotorized (%)Reference CPUE(t∙year-1∙boat-1)1950 370a - - 27.75b1962 463 - Alsopp (1966) 30.741966 255 23 Amégavie (1979) 31.731967 388 16 Amégavie (1979) 31.981968 386 24 Amégavie (1979) 32.231969 416 24 Amégavie (1979) 32.471970 237 41 Amégavie (1979) 32.721971 545 24 Amégavie (1979) 32.971972 559 28 Amégavie (1979) 33.221973 550 31 Amégavie (1979) 33.471974 540 41 Amégavie (1979) 33.711975 603 42 Amégavie (1979) 33.971976 218 62 Amégavie (1979) 34.211977 409 79 Amégavie (1979) 34.461978 346 85 Amégavie (1979) 34.69c1979 603 70 Dioury (1983), Bama (1984) 34.601992 510 Horemans (1994) 33.191996 403 45 Sedzro and Kusiaku (1999) 32.752002 407 40 Segniagbeto and Waerebeek (2010) 32.102003 400 Anon. (2010) 31.992007 407 IRD (2011) 31.562010 407 Assumed constant 31.22da) assumed to be 20% lower than the number of pirogues in 1962, year of first survey;b) assumed to be 20% of the CPUE in 1978;c) based on the estimate of the catch and effort by Amégavie (1979);d) assumed to be 10% lower than the CPUE in 1978. 42The catch composition of trawlers (Table 7) provided by Beck (1977) is dominated by species of the shallow water Haemulidae-dominated community (reaching down to about 40 m) and represented by the bigeye grunt Brachydeuterus auritus and of the species from bellow the thermocline, i.e., the species of the Sparidae community (Longhurst and Pauly 1987). While pelagic catches were assumed to include 70% of Sardinella and 30% of other unidentified taxonomic groups, since seiners in Togo target mostly sardinellas (Bama 1984).DiscardsTo estimate discards by the domestic fleet, we used the average discard rate between the neighbouring Ghana and Benin, i.e., 0.9% of landed catches (Kelleher 2005). This low rate is explained by the use of bycatch for ‘African mix’, a popular product in West Africa; thus the low-value bycatch is landed and transformed. Using the same source, we estimated an average discard rate of 14.9% of the landed catch between Spain (30%), Ghana (1.3%), Greece (32.8%), Cyprus (0.1%), and Guinea (0.5%), which we applied on the catch by each foreign country operating in Togo.Discarded species include mostly undersized commercial species and other species not identified. Therefore, we applied the same species disaggregation than for the trawl catches.Illegal industrial fisheriesIllegal catches are catches by unauthorized foreign vessels in the Togolese EEZ. MRAG (2005) estimated the Illegal Unregulated Unreported (IUU) catch as 32% of the total catch in Togo in the 2000s, consequently we interpolated from zero in 1985 prior the declaration of the EEZ to 32% of the total catch (47% of the reconstructed catch) from 2005 to 2010. We then applied these rates to the reconstructed catch including industrial and small-scale marine catches. We then applied the same species disaggregation as for the legal fishery, assuming the same countries’ contributions. Although rates of illegal fishing were documented, countries responsible for illegal fishing in Togolese waters were not always identified. In two instances, we found media reports of trawlers as being “mostly from Asia” (Anon. 2012a), China based in Ghana and Ghanaian canoes operating illegally (Anon. 2012b). Ghanaian canoes, although artisanal in nature, due to their size can travel long distances for fishing2. Therefore, we assumed illegal catches to be 70% Chinese (more efficient industrial vessels) and 30% by Ghanaian canoes, which are here considered ‘industrial’ because they operate internationally. We then applied the same species disaggregation than for industrial legal fleets.2  Given the definitions built in the database of the Sea Around Us, Ghanean Fanti canoes are labelled as ‘industrial’ because they operate outside their own national waters, i.e., Ghana’s EEZ.Table 5.   Catch composition of the artisanal pirogue fishery in TogoScientific name English name Local name %Engraulis encrasicolus Anchovy Anchois 68.41Sardinella spp. Sardinella Sardinelle 5.75Sardinella maderensis Madeiran sardinella Hareng 2.38Scomber japonicus Chub mackerel Maquereau 1.50Carangidae Jacks and pompanos Chinchard 1.90Caranx hippos Crevalle jack Carangue 4.85Euthynnus alletteratus Little tunny Bonite 2.66Pagellus bellottii Red pandora Pageot 1.21Ilisha africana West African ilisha Rasoir 0.84Sphyraena spp. Barracuda Brochet 0.64Selene dorsalis African moonfish Vomer 0.06Tylosurus crocodilus crocodilus Hound needlefish Orphie 0.28Boops boops Bogue Bogue 0.29Galeoides decadactylus Lesser African threadfin Hormose 0.29Drepane africana African sicklefish Disque 0.05Trichiurus lepturus Largehead hairtail Ceinture 0.04Dactylopterus volitans Flying gurnard Poisson volant 1.29Hemiramphus balao Balao halfbeak Demi-bec 0.01Elops lacerta West African ladyfish Faux mulet 0.04Pseudotolithus Croakers Bar 0.47Xiphias gladius Swordfish Espadon 0.13Brachydeuterus auritus Bigeye grunt Friture 0.42Centrophorus granulosus Gulper shark Requin 0.08Scombridae Tunas Thon 0.34Lutjanus spp. Lutjanus (Snappers) Lutjanus 1.03Dentex spp. Dentex Dorade rose 1.23Lethrinus atlanticus Atlantic emperor Dorade grise 0.11Epinephelus spp. Grouper Merou 0.45Pomadasys jubelini Sompat grunt Pristipoma 0.03Coryphaena equiselis Pompano dolphinfish Cameleon 0.03Palinurus spp. Spiny lobster Langouste 0.01Penaeus spp. Shrimps Crevette 0.01Umbrina spp. Drums Ombrine 0.02Raja spp. Rays Raie 0.08Polydactylus quadrifilis Giant African threadfin Capitaine 0.09Balistes capriscus Grey triggerfish Baliste 0.02Pseudupeneus prayensis West African goatfish Rouget 0.03Solea spp. Sole Sole 0.04Psettodes belcheri Spottail spiny turbot Turbot <0.01Sepia spp. Cuttlefish Seiche 0.12Dentex macrophthalmus Large-eye dentex Gros yeux 0.01Carlarius heudelotii Smoothmouth sea catfish Poisson chat <0.01Paraconger notialis Guinean conger Congre <0.01Lagocephalus laevigatus  Smooth puffer Peroquet 0.01Marine fishes not identified Marine fishes not identified Divers 2.74Togo - Belhabib et al. 43resultsSmall-scale catchesSmall-scale catches, including artisanal marine and subsistence lagoon catches, totalled 2.24 million tonnes between 1950 and 2010. Catches increased slightly from 33,200 t in 1950 to a peak of 48,700 t in 1975, and then decreased to less than 19,700 t in 2010 (Figure 2).Artisanal catchesArtisanal catches increased from 24,816 t in 1950 to a peak of 43,100 t in the 1975 and then decreased again to be at 18,600 t in 2010, their historical minimum (Figure 3). Artisanal marine catches totalled 1.97 million tonnes between 1950 and 2010, of which over half (56%) was generated by marine land-based fisheries, i.e., 1.1 million tonnes Table 6.   Number of pelagic and demersal fishing vessels in Togo by country of origin. Interpolation are indicated in italics. Country of origin Pelagic SourceYear Total Togo Germany Greece Italy Cyprus Spain Guinea Ghana Othera, b China Togo1950-19640 0 0 0 0 0 0 0 0 0 0 01965 2 0 2 0 0 0 0 0 0 0 0 0 Beck (1974)1966 2 0 2 0 0 0 0 0 0 0 0 11967 2 0 2 0 0 0 0 0 0 0 0 11968 2 0 2 0 0 0 0 0 0 0 0 21969 2 0 2 0 0 0 0 0 0 0 0 31970 2 0 2 0 0 0 0 0 0 0 0 31971 2 0 2 0 0 0 0 0 0 0 0 41972 2 0 2 0 0 0 0 0 0 0 0 41973 2 0 2 0 0 0 0 0 0 0 0 5 Beck (1976)1974 2 0 2 0 0 0 0 0 0 0 0 61975 2 0 2 0 0 0 0 0 0 0 0 61976 7 0 0 0 0 0 0 0 0 7 0 7 Bama (1984)1977 4 0 0 0 0 0 0 0 1 2 0 10 Dioury (1983), Bama (1984)1978 10 1 0 1 0 0 0 0 2 7 0 11 Bama (1984)1979 12 1 0 1 0 0 0 0 2 8 0 11 Dioury (1983)1980 2 1 0 1 0 0 0 0 3 0 0 4 Bama (1984)1981 3 1 0 1 0 0 0 0 3 0 0 13 Bama (1984)1982 7 1 0 1 0 0 0 0 4 1 0 11 Dioury (1983), Amégavie (1986)1983 5 2 0 2 0 1 0 0 4 0 0 4 Amégavie (1986)1984 1 1 0 3 0 1 1 0 4 0 0 4 Amégavie (1986)1985 4 1 0 3 1 1 1 0 3 0 0 4 Amégavie (1986)1986 4 1 0 3 1 1 2 0 3 0 0 41987 5 1 0 3 1 1 2 0 3 0 0 31988 5 0 0 2 1 1 2 0 3 0 0 31989 5 0 0 2 1 1 3 0 3 0 0 31990 6 0 0 2 2 1 3 1 3 0 0 31991 6 0 0 2 2 1 4 1 3 0 0 31992 6 0 0 2 2 1 4 1 2 0 0 3 Oceana (2011)1993 7 0 0 2 2 1 4 1 2 0 0 3 Oceana (2011)1994 7 0 0 2 2 1 4 1 2 0 0 2 Oceana (2011)1995 7 0 0 2 2 1 4 1 2 0 0 2 Oceana (2011)1996 8 0 0 2 2 1 4 1 2 0 0 2 Oceana (2011)1997 8 0 0 2 2 1 4 1 2 0 0 2 Oceana (2011)1998 9 0 0 2 2 1 4 1 2 0 0 2 Oceana (2011)1999 9 1 0 2 2 0 4 1 1 0 0 2 Segniagbeto and Waerebeek (2010), Oceana (2011)2000 9 1 0 2 2 0 4 1 1 0 0 1 Oceana (2011)2001 10 1 c 0 2 2 c 0 4 c 1 1 0 0 12002 10 1 c 0 2 2 c 0 4 c 1 1 0 0 12003 11 1 c 0 2 2 c 0 4 c 1 1 0 0 12004 11 1 c 0 2 2 c 0 4 c 2 1 0 4c 12005 12 1 c 0 2  2 c 0 4 c 2 1 0 4c 12006 12 1 c 0 2 2 c 0 4 c 2 0 1 4c 12007 13 1 c 0 2 2 c 0 4 c 2 0 1 4c 02008 13 1 c 0 2 2 c 0 4 c 2 0 2 4c 02009 13 1 c 0 2 2 c 0 4 c 2 0 2 4c 02010 14 1 0 2 2 0 4 c 2 0 3 4c 0 IRD (2011), SOFRECO (2011)a) France and Switzerland are among the unidentified flags;b) Represents the difference between the sum of trawlers and the total provided by the literature. When the estimated total number of trawlers was higher than the estimate given by the literature, we assumed these vessels were simply not reported by the literature since a number of trawlers using the Togolese flag in the Togolese EEZ were not reported by the literature (Segniagbeto and Waerebeek 2010);c) assumed constant.Table 7.   Catch composition of the industrial trawl fishery in Togo (Beck 1976)Scientific name Common name %Pagellus coupei Red pandora 10Dentex spp. Dentex 10Lethrinus atlanticus Atlantic emperor 10Brachydeuterus auritus Bigeye grunt 29Trachurus trecae Cunene horse mackerel 2Caranx hippos Crevalle jack 4Chloroscombrus chrysurus Atlantic bumper 2Pseudupeneus prayensis West African goatfish 7Epinephelus aeneus White grouper 3Pomadasys jubelini Sompat grunt 2Pseudotolithus spp. Croakers 2Marine fishes not identified Marine fishes not identified 20 44(Figure 3). Land based fisheries represented over 60% of the total artisanal marine catch between the 1950s and the late 1970s, then declined to represent 32% of the total artisanal marine catch in 2010 (Figure 3).Lagoon subsistence fisheriesLagoon catches totalled 271,000 tonnes between 1950 and 2010 (Figure 4a), which is the equivalent of 14% of the artisanal marine catch. Lagoon catches, mostly tilapias (Figure 4b) and considered here subsistence, increased slightly from 8,400 t in 1950, to around 9 ,100 t in 1963 of which 300 t were generated in the acadja systems. Lagoon catches declined rapidly to 2,000 t in 1983, with the acadja systems contributing to around 400 t, the kept on decreasing but with a lower slope to 1,100 t in 2010 when the catch generated by the acadja systems was estimated at 230 t (Figure 4).Recreational catchesRecreational catches were estimated at 287 t between 1950 and 2010. Recreational catches increased from zero in 1967 to 22 t in 2010 and included mostly wahoo, carangids and groupers (Figure 5).Industrial catchesDomestic catchesIndustrial domestic catch for Togo was estimated at 101,496 t between 1966, when the domestic industrial fishery was launched and 2010. Of these catches, 81% were captured by the pelagic fleet (81,925 tonnes) (Figure 6). Industrial catches by Togo increased rapidly since their introduction from zero in 1965 to 6,100 t in 1982, then decreased to less than 1,200 t in 2010 (Figure 6).Foreign trawl catchesForeign catches started at low levels when the trawl fishery was introduced by Germany in Togo in the mid-1960s, 540 t∙year-1, and picked up in 1978 with the increase in the number of trawlers (Figure 7). Catches increased thereafter, to reach at average 15,000 t∙year-1 in the early 1990s, and then increased rapidly with the introduction of the agreement between Togo and China in the 2000s to a historical maximum catch of around 41,000 t in 2010, of which a quarter was Chinese (Figure 7). Of a total industrial trawl catch estimated at 678,000 tonnes between 1950 and 2010, 13.7% was Spanish, 36.4% was Chinese, 9.6% was Greek, 20.9% was caught by the neighbouring Ghana, 7.8% by Italy, 5% by Guinea, 2.2% by Cyprus, 1% by Germany in the 1970s, and the remaining by other countries including Portugal and Russia (Figure 7).DiscardsDiscard were estimated at 38,500 tonnes between 1950 and 2010. Discards by the trawl fleet increased following the same pattern than industrial trawl catches increasing from 70 t in 1965, when industrial fishing begun, to a historical maximum of around 2,300 t in 2010 (Figure 8), twice, the Togolese domestic industrial catch.Catch (t x 10 )3C0246810Catch (t x 103 )a)02468101950 1960 1970 1980 1990 2000 2010Catch (t  x 103 )YearSarotherodon melanotheronFarfantepenaeus notialisCallinectes spp.Tilapia guineensisChrysichthys spp.Liza spp.Othersb)Figure 2.  Estimated small scale catches for Togo, 1950-2010.Figure 3.  Estimated artisanal catches for Togo, 1950-2010.Figure 4.  Estimated lagoon catches for Togo (a) subsistence sector and (b) by major taxonomic group, 1950-2010.Togo - Belhabib et al. 45Illegal catchesIllegal catches increased from zero in 1985 at the declaration of the Togolese EEZ –unregulated catches already considered in legal catches – to a peak of 20,300 t in 2005, then decreased slightly to about 19,300 t in 2010 (Figure 9). Illegal catches totalled around 289,500 tonnes in less than 30 years which was the slightly higher than the legal (but not all reported) industrial catch.Total catchesThe total marine extractions from the Togolese EEZ were here estimated at over 3 million tonnes between 1950 and 2010 including 2.3 million tonnes from domestic catch and 678,000 tonnes from foreign and visible reflagged vessels. This is compared to the total of 563,400 tonnes supplied to the FAO on behalf of Togo during the same period (Figure 10). Total domestic catches increased from around 33,200 t in 1950 compared to 1,900 t supplied to FAO, to a peak of 51,600 t in 1979, eleven times the catch supplied to FAO, then gradually decreased to be 20,900 t in 2010, compared to 20,000 reported to the FAO (Figure 10). Although this is slightly lower than the data supplied to the FAO, the latter includes catches by foreign vessels landed in Togo, which when considered as domestic resulted in higher catches comparatively to the landing data supplied to the FAO. Foreign (reflagged, joint venture and under agreement) catches increased from 540 t in 1965 to 5,436 t in 1979, the increased constantly to 41,533 t in 2010 (Figure 10).discussionThe present report presents a historical overview of the Togolese fisheries catch for the 61 years since 1950. It shows reconstructed catches 4 times higher than the figures supplied to the FAO by Togo, with over 3 million tonnes reconstructed compared to 563,000 tonnes supplied to FAO. Artisanal catches represented the bulk (72%) of the reconstructed catch. The pirogue-based artisanal fisheries, dominated by Ghanaian migrant fishers, were driving the variation of domestic catches, also strongly influenced by the political history of Togo. A few examples of inter-annual variations could be related to political-historical events in Togo, like the coup d’état of 1963 when, because of the prevailing insecurity, artisanal fishing effort and consequently catches declined. The ‘Aliens Compliance Order’ decree by the government of Ghana in 1969–forcing all immigrants without proper documentation to leave Ghanaian towards Togo and other neighbouring countries (Bump 2006)–certainly generated an increase in artisanal fishing in Togo, reflected in an increase in artisanal catches in 1970. Another example is provided by the sharp decline in the artisanal catch in the mid-1970s, when the ‘Togoland Liberation Movement’ and the ‘National Liberation Movement for Western Togoland’ were seeking separation from Ghana, and threatened it with a guerilla war. This has contributed to increasing insecurity of migrant fishers notably from Ghana, and thus reduced artisanal fishing and catches.Subsistence lagoon catches represented 10% of the total reconstructed catch. Although subsistence catches do not seem to be high, they contribute towards supplying around 20% of the Togolese population with around 8 kg per capita per year. This further highlights the importance of small-scale fisheries, forgotten by official data, to coastal populations and for food security. Indeed, Togo has been struggling to meet its fish protein demand, with around 65% of the fish supply supplied by imports (FAO FishStat).Figure 5.  Estimated recreational catches for Togo, 1950-2010.Figure 6.  Reconstructed total domestic industrial catch in Togo EEZ, 1950-2010.Figure 7.  Reconstructed total foreign industrial catch in Togo’s EEZ, 1950-2010. 46On the other hand, the large scale sectors, including industrial legal fisheries and illegal fisheries generated only 8% and 9% of the catch respectively, and discarded 1% of the total catch. The industrial sectors, particularly the foreign fleets show a sharp increase, which contrasts with the pronounced decline of the small-scale fisheries. This further highlights the negative link between industrial (trawl) sectors and small-scale fisheries and questions the usefulness of exclusive ‘artisanal fishing zones’ in a country where monitoring is barely existent. This adds to the problems of subsistence fishers and poor communities where fishing remains the last resort for poverty alleviation, especially because agriculture is facing increasing climatic challenges (Njock and Westlund 2010).The decrease in the domestic catch has been compensated by the reflagging practices of Togo since the late 1970s, keeping the total catch in the Togolese EEZ relatively constant since then, at an average of around 48,000 t∙year-1 ± 2,000 t∙year-1 despite the increasing effort, particularly by the industrial fleet. This trend is very different from the increasing catch trend shown by the data supplied to FAO, and is explained by an over-exploitation by both the lagoon fisheries (de Surgy 1966; Weigel 1985; Laë 1992) and the artisanal and demersal fisheries (FAO 2006). Since the mid-1970s, droughts constitute another aspect of the decline in the Togolese fishery, because they increase the pressure by farmers who are shifting their activities to fishing, a pattern occurring in many countries (Pauly 2006).The decrease of domestic industrial catches is due to the collapse of the industrial companies launched in the early 1970s, and the common reflagging practices of Togo here considered in the foreign segment of industrial catches. The so-called ‘Togolese fleet’ includes vessels from Guinea and Cyprus, vessels from Spain, Italy, China, Ghana, Portugal and Germany in the earlier time periods. Herein, catches by France, Switzerland and other unknown countries where not included, implying that our reconstruction is a conservative, but realistic estimate of catches in Togolese waters. Rather than investing in a truly Togolese fleet, Togo–a Flag of Convenience (FoC) country and also ‘a cheap registry that does not require VMS (EJF 2012)–offers the Togolese flag to an increasing number of foreign fleets, and gains a fairly high compensation when doing so (Österblom et al. 2010). For example during the last decade, 7 to 15 vessels flagged to Togo (mostly of Spanish origin) were operating in the area covered by the Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR) area illegally and in Australian, Malaysian and French waters (Gianni and Simpson 2005). And thus, as Real (2013) points out, with a lack of control over these ‘domesticated’ fleets from the EU, Togo was recently classified in the EU blacklist of the countries fishing irresponsiblyacknoWledGmentsThis is a contribution of the Sea Around Us, as scientific collaboration between the University of British Columbia, The Pew Charitable Trusts and the Paul G. Allen Family Foundation.CC0204060Catch (t x 103 )ArtisanalIndustrialSubsistence supplied to FAOa)02040601950 1960 1970 1980 1990 2000 2010Catch (t x 103)YearEngraulis encrasicolusBrachydeuterus auritusSarotherodon melanotheronSardinella  spp.OthersChloroscombrus chrysurusb)Figure 8.  Estimated industrial discards in Togo EEZ, 1950-2010.Figure 9.  Estimated illegal catches by the foreign fleet from Togo EEZ, 1950-2010.Figure 10.  Reconstructed total catch for Togo for 1950 to 2010, by a) sector, with official reported data overlaid as line graph, and b) by major taxa, with ‘Others’ consisting of 103 additional taxonomic categories.Togo - Belhabib et al. 47reFerencesAlsopp WHL (1966) Rapport au Gouvernement du Togo sur le développement et l’organisation de l’industrie des pêches. 2148, FAO, Rome. 19 p.Amégavie K (1979) Rapport sur la pêche togolaise. In COPACE (ed.) Rapport du groupe de travail spécial sur l’évaluation des stocks démersaux du secteur Côte d’Ivoire–Zaïre. 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Fishery Bulletin 105(2): 266-277.Togo - Belhabib et al. 49Appendix Table A1: FAO landings vs. reconstructed total catch (in tonnes), and catch by sector with discards shown separately for Togo, 1950-2010.Year FAO landings Reconstructed total catch Industrial Artisanal Subsistence Recreational Discards1950 1,900 33,200 0 24,800 8,400 0 01951 1,900 33,900 0 25,600 8,310 0 01952 1,900 34,600 0 26,400 8,210 0 01953 1,800 35,300 0 27,100 8,120 0 01954 1,800 35,900 0 27,900 8,030 0 01955 1,900 36,700 0 28,700 7,960 0 01956 1,900 37,400 0 29,500 7,900 0 01957 2,300 38,300 0 30,400 7,830 0 01958 1,800 39,100 0 31,300 7,770 0 01959 1,800 39,700 0 32,000 7,700 0 01960 1,900 40,100 0 32,400 7,640 0 01961 2,300 41,500 0 33,400 8,130 0 01962 2,300 43,000 0 34,400 8,600 0 01963 2,500 43,400 0 34,300 9,060 0 01964 3,000 42,500 0 33,600 8,950 0 01965 3,700 41,700 0 32,900 8,830 0 01966 4,800 40,100 156 31,400 8,520 0 01967 5,000 44,400 305 35,900 8,210 0 01968 7,000 44,400 455 36,100 7,900 0 01969 7,001 45,500 604 37,300 7,600 0 01970 6,614 38,900 754 30,900 7,270 1 01971 7,923 48,900 903 41,000 6,940 1 01972 7,944 49,200 1,053 41,500 6,610 1 01973 8,334 48,700 1,203 41,300 6,290 1 01974 8,151 48,400 1,527 40,900 5,970 2 01975 11,421 50,600 1,889 43,100 5,640 2 01976 9,471 37,600 2,357 29,900 5,320 2 01977 7,497 45,100 3,696 36,400 5,000 2 11978 12,014 43,300 4,452 34,200 4,680 2 21979 4,597 51,600 4,861 42,700 4,030 3 21980 5,634 47,700 2,148 42,100 3,430 3 31981 6,826 50,900 6,660 41,300 2,890 3 41982 11,031 49,800 6,095 41,300 2,400 3 51983 11,058 46,100 3,230 40,900 1,950 3 101984 11,048 44,500 2,809 40,200 1,560 4 51985 12,045 43,800 2,867 39,300 1,620 4 51986 11,325 43,300 2,771 38,800 1,660 4 41987 11,676 42,600 2,709 38,200 1,690 4 41988 11,956 42,100 2,629 37,700 1,720 5 31989 11,946 41,400 2,531 37,100 1,750 5 21990 10,880 40,700 2,414 36,600 1,720 5 11991 7,605 39,900 2,280 35,900 1,680 5 01992 5,252 39,200 2,198 35,300 1,650 5 01993 10,965 37,700 2,151 33,900 1,620 6 01994 8,054 35,600 2,095 31,900 1,580 6 01995 7,206 33,900 2,029 30,300 1,550 6 01996 10,101 32,400 1,954 28,900 1,510 6 01997 9,293 31,700 1,869 28,300 1,480 7 01998 11,659 30,900 1,775 27,700 1,440 7 01999 17,926 31,100 2,696 27,000 1,410 8 92000 17,279 31,200 2,614 27,200 1,370 9 92001 18,165 30,400 2,522 26,500 1,330 10 102002 15,947 28,900 2,421 25,200 1,300 11 102003 22,487 27,800 2,311 24,200 1,260 12 102004 23,013 26,900 2,192 23,500 1,220 13 112005 22,745 25,900 2,011 22,700 1,190 15 112006 19,879 24,900 1,830 21,900 1,150 16 112007 14,905 23,900 1,650 21,200 1,110 20 112008 18,500 22,900 1,469 20,300 1,110 20 112009 20,604 21,700 1,175 19,400 1,110 20 112010 19,729 20,900 1,175 18,600 1,100 22 11 50Appendix Table A2: Reconstructed total catch (in tonnes) by major taxa, for Togo, 1950-2010. Others contain 104 additional taxonomic categories.Year Engraulis encrasicolusSardinella spp.Sarotherodon melanotheronBrachydeuterus auritusChloroscombrus chrysurusOthers1950 8,270 7,620 5,140 2,210 1,500 8,4701951 8,510 7,870 5,080 2,290 1,560 8,6201952 8,740 8,100 5,020 2,370 1,610 8,7601953 8,810 8,450 4,970 2,450 1,660 8,9101954 9,050 8,690 4,910 2,520 1,710 9,0501955 9,360 8,900 4,870 2,590 1,760 9,1801956 9,600 9,160 4,830 2,680 1,820 9,3501957 10,130 9,320 4,790 2,730 1,850 9,4301958 10,040 9,760 4,750 2,870 1,950 9,7301959 10,290 9,940 4,710 2,930 1,990 9,8601960 10,590 9,970 4,670 2,930 1,990 9,9001961 11,130 10,180 4,970 3,000 2,040 10,2301962 11,400 10,510 5,260 3,110 2,110 10,6401963 10,440 11,130 5,540 3,290 2,240 10,7501964 9,360 11,150 5,470 3,340 2,280 10,9101965 8,750 11,120 5,400 3,370 2,300 10,7401966 8,040 10,920 5,210 3,230 2,210 10,4801967 10,670 11,530 5,020 3,320 2,260 11,5801968 11,080 11,560 4,830 3,130 2,130 11,7001969 11,740 11,850 4,650 3,170 2,160 11,9001970 7,920 10,660 4,440 2,970 2,040 10,8801971 14,160 11,940 4,240 3,070 2,080 13,3701972 14,510 12,070 4,040 3,170 2,080 13,3301973 14,430 12,000 3,850 3,070 2,040 13,3601974 14,410 12,240 3,650 3,010 2,040 13,0801975 16,130 12,470 3,450 2,760 1,860 13,9601976 7,340 10,320 3,250 2,530 1,720 12,4501977 9,600 11,760 3,060 2,960 1,990 15,7601978 9,150 10,670 2,860 2,430 1,620 16,5901979 14,780 13,810 2,470 3,320 2,190 15,0101980 15,640 11,430 2,100 3,250 2,100 13,1601981 15,840 14,220 1,770 3,210 1,990 13,8901982 17,730 13,390 1,470 2,790 1,770 12,6601983 17,500 10,310 1,190 2,900 1,770 12,4601984 18,460 10,060 950 2,700 1,710 10,6601985 18,320 9,490 990 2,540 1,590 10,9001986 13,500 9,730 1,010 2,550 1,610 14,8701987 16,650 9,390 1,030 2,450 1,550 11,5301988 18,070 8,900 1,050 2,340 1,510 10,2001989 17,040 8,730 1,070 2,260 1,470 10,8401990 16,620 9,000 1,050 2,310 1,510 10,2501991 14,670 9,760 1,030 2,480 1,650 10,3101992 14,150 10,040 1,010 2,620 1,750 9,5801993 15,880 8,110 990 2,060 1,360 9,3001994 12,890 8,320 970 2,130 1,410 9,8601995 12,670 8,020 950 2,060 1,380 8,7901996 13,460 6,930 920 1,690 1,150 8,2501997 11,560 7,160 900 1,690 1,140 9,2401998 12,110 6,150 880 1,400 940 9,4301999 10,630 4,370 860 1,540 550 13,2002000 11,170 4,540 840 1,900 600 12,1702001 10,020 3,760 820 1,860 500 13,4302002 10,670 3,730 790 2,210 520 11,0102003 12,300 1,490 770 820 120 12,3002004 7,420 1,400 750 1,900 50 15,3802005 6,560 800 730 1,110 30 16,7102006 8,020 2,290 700 1,310 120 12,5002007 5,970 2,020 680 1,790 300 13,1902008 3,820 740 680 2,150 100 15,4102009 2,620 30 680 2,210 0 16,2102010 4,600 20 680 1,210 730 13,640Benin - Belhabib and Pauly 51benin’s Fisheries: a catch reconstruction, 1950-20101Dyhia Belhabib and Daniel PaulySea Around Us, Fisheries Centre, University of British Columbia2202 Main Mall, Vancouver, BC, V6T 1Z4, Canadad.belhabib @fisheries.ubc.ca; d.pauly @fisheries.ubc.caabstractTotal marine fisheries catches from the Exclusive Economic Zone of Benin and its coastal lagoons were estimated between 1950 and 2010. The reconstruction considered artisanal and industrial sectors and their discards, subsistence fisheries from the marine and lagoon waters including those generated by women for the first time. Small-scale catch estimates were obtained using catch per unit of effort and per capita catch estimates alongside with the number of fishers and the number of pirogues, while industrial catches were estimated by country using the number of industrial vessels and their catch per unit of effort. Total catches were estimated at 4.0 million t between 1950 and 2010 of which 3.9 million t were domestic (and mainly from lagoon areas) compared to 1.7 million t of catch data supplied to the FAO. Catches showed a decreasing pattern in contrast to the increase observed in official data, which puts in jeopardy the livelihoods of the many fishers relying solely on fisheries.introductionBenin (capital city; Cotonou, 6°28′N 2°36’E) is a small country of Central West Africa with a coast on the Gulf of Guinea, one of the smallest coastlines of Africa (the Gulf of Benin). The country is bordered by Nigeria on the East, Niger and Burkina Faso on the North and Togo on the West.Historically, Benin held a major role in the slave trade, and hence its previous name of ’Slaves Coast’, following the European colonial habit of naming areas of Africa after their major resources, such as the “Pepper Coast” for Côte d’Ivoire (itself another resource name, ivory), or the “Gold Coast” for Ghana (Bouche 1885). The country, known as Dahomey during the French colonization and shortly after independence in 1960, went through a period of political unrest and a major coup d’état in 1972, which triggered the establishment of a Marxist regime. The newly formed government renamed the country the People’s Republic of Benin and started a multitude of politically driven initiatives such as nationalization of industries, and taking nuclear waste from the former Soviet Union and France. Ill-founded policies, conflicts and a badly managed economy governed under the “poverty is not fatality” motto contributed to Benin acquiring the reputation of being the “sick child of Africa” (Atti-Mama 1998).The availability of fisheries resources within Benin’s many lagoons and coastal areas contributed to the importance of this industry as it is the second major source of employment for coastal populations following agriculture (Bouche 1885). Benin has a well-established tradition of fishing as fish was then caught for personal consumption (Bouche 1885).The absence of major upwelling phenomenon in Benin inshore waters (Djiman 1996; FAO 2007), the short coastline and the large size of the estuarine systems drove the growth of Benin’s mostly lagoon-based fisheries, which are small-scale, largely subsistence operations conducted from small canoes. Artisanal and industrial marine fisheries operate in Benin’s waters only since the early 1950s. They include small pelagic fisheries, operated by Fanti type pirogues and pelagic trawlers, cephalopod fisheries by industrial vessels flagged to Benin which land their catches in Benin, a demersal fish sector operated either by industrial trawlers reflagged to Benin or artisanal boats which land their catches in Benin (Senouvo 1990b; Chaboud and Charles-Dominique 1991; Ecoutin et al. 1993), and a shark fishery (Anon. 2010).1 Cite as: Belhabib, D. and Pauly, D. (2015) Benin’s fisheries: a catch reconstruction, 1950 to 2010. pp. 51-64. In: Belhabib, D. and Pauly, D. (eds). Fisheries catch reconstructions: West Africa, Part II. Fisheries Centre Research Reports vol.23(3). Fisheries Centre, University of British Columbia [ISSN 1198-6727].Figure 1.  Map of Benin with Exclusive Economic Zone (EEZ). 52Although new fisheries regulations were introduced in the 1990s, they faced serious challenges in effectively regulating these fisheries sectors, particularly in the face of the well-established implemented traditional system such as the one found in lagoons (Stoop et al. 2013).Traditional systems of fisheries management built around animist beliefs (‘Voodoo’) were efficient in the past as fishers adhered to fishing rules, as they were those of their own villages and/or communities. For example, violation of fisheries regulations set up by villages was considered a sacrilege and therefore an animal sacrifice was required at the cost of the offender (Iroko 2005). Voodoo sanctions ranged from fines and confiscation of fishing gear to public flagellation and even death sentences (Briones Alonso et al. 2013). Measures to prevent overfishing or to allow fish to multiply went from prohibiting breastfeeding women and women having their periods to approach the water (Iroko 2005) to ‘quotas’. Interestingly in Benin, even today, these quotas, i.e., definite quantities of fish to be taken, as set by villages, are traditionally defined by the customs of the two ethnic groups Houedah and the Xwlâ, exist. Although they have no scientific basis, and are based exclusively on tradition, they are believed to be efficient. Some other measures included fishing bans, release of bycatch and a feast day for the deities of the sea, when fishing was forbidden (Vogt et al. 2010). These rules are now slowly disappearing from among young fishers (Vogt et al. 2010) and destructive fishing techniques are increasingly used as the traditional system loses power to ‘modern’, but ineffective systems. Ironically, as noted by Vogt et al. (2010), while artisanal fishers observe strict rules, the ‘deities’ of the sea, a.k.a., illegal fishing vessels, are feasting upon the fish which small-scale fishers allow to rest, which creates more conflicts between the small-scale sector and the industrial sector.Benin lacks the capacity to monitor its fisheries effort and catches, which often results in a lack of data and a lack of scientific knowledge leading to inadequate management (FAO 2007). However, data wise, the sampling techniques that were used were described as “efficient”–at least in the past for part of the fishing industry, at the dawn of FAO development projects in the 1970s (FAO 2007). On the other hand, some authors argue that large fractions of the catch were never registered, and that those that were recorded are unreliable. Furthermore “it has to be noted that even the national fishing authority does not have data on fishing quantities at its disposal.” (Vogt et al. 2010). For example, industrial catches are unreliable as the FAO data for the industrial sector was in the past significantly higher than the national data presented by the Direction de Programmation et de Prospective (DPP), the latter likely being under-estimated given the high number of trawlers (Vogt et al. 2010).Fisheries in Benin shifted from a time of abundance, waste and carelessness when “dried fish was even used to replace the cattle cake normally used in making fire” (Iroko 2005), to fisheries depletion, social disparities created by the use of ‘acadja’ systems (see below), as early as the 1960s (Iroko 2005) and raising conflicts with the industrial marine fleet, which ultimately led to piracy.Herein, we reconstruct Benin marine and lagoon fisheries catches to have a realistic idea of total fisheries removals from Benin in contrast to officially ill-documented data.methodsData on fisheries landings are collected and compiled by the Centre de Recherche Halieutique et Océanographique du Benin (Fisheries and Oceanographic Research Centre of Benin, CRHOB); these are then submitted to the Fisheries Directorate. Monitoring of marine artisanal fisheries is based on ARTFISH stratified sampling technique, which was introduced by FAO in 1976 at the launch of the Technical Cooperation Programme (TCP). Between 1987 and 2002, the Fisheries Directorate counted daily the number of dugout canoes in the port of Cotonou. Monitoring decreased after 2003 for economic reasons. One of the particularities of Benin however, is that marine fishers were actively involved in data collection as they received a financial compensation from the Fisheries Directorate for their work. The program stopped in 2007 and fisheries monitoring shrunk again to cover only the Port of Cotonou (FAO 2007). The industrial fleet is dominated by foreign vessels, notably bottom trawlers, onboard of which no observers were taken. Similarly, there is hardly any control on the mesh size or the fishing grounds of these fleets (FAO 2007).Herein we reconstruct total catches from Benin EEZ for the artisanal marine and lagoon sectors notably catches taken by acadja systems, subsistence fisheries catches, domestic and industrial foreign catches and their discards (including legal and illegal sectors).Coastal populationCoastal population, i.e., rural and urban population living within the 10 km strip of the coast was given for 1990, 2000 and 2010 (CIESIN 2012). We extracted total population estimates from the WorldBank database (www .worldbank.org) from 1960 to 2010, and completed these using data from www .populstat.com from 1950 to 1960. We divided the coastal population estimate for 1990 by the total population estimate for the same year and obtained a percentage of coastal population for 1990. We assumed this percentage was constant between 1950 and 1990 and multiplied it by the total population for the same time period to obtain coastal population of Benin between 1950 and 1989. We interpolated between coastal population estimates between 1990 and 2010 to fill in the gaps (Figure 2). Figure 2.  Total and coastal population of Benin, 1950-2010.Benin - Belhabib and Pauly 53Artisanal catchesAlthough artisanal catches in Benin are relatively unknown, they seem to be important particularly in the lagoons (Boëly and Fréon 1979). Data are often referred to as “patchy” which is explained by the fact that to the 80 landing sites are difficult to monitor properly (Turay and Verstralen 1997).Marine catchesTo reconstruct artisanal marine catches, we multipled the catch per unit of effort by the effort (number of pirogues). Literature documented the number of marine pirogues for a certain number of years for the years 1983, 1985, 1986, 1987, 1988, 1992, 1993, 1994, 1997 and 1999 (Senouvo 1990a, 1990b; Ssentongo 1990; Gbaguidi and Meyizoun 1994; Horemans and Jallow 1997; Turay and Verstralen 1997; FAO 2007) and the number of marine fishers for the early 1980, 1983, 1992, 1993, 1994, 1997, 1999 and 2010 (Chaboud and Charles-Dominique 1991; Ecoutin et al. 1993; Horemans 1994; Horemans and Jallow 1997; Turay and Verstralen 1997; FAO 2007; Njock and Westlund 2010; Dessouassi 2011) (Table 1). We estimated the number of pirogues for 1980 by multiplying the number of fishers (2,500) by the number of fishers per pirogue obtained from the first available anchor point documenting both the number of pirogues and the number of fishers, i.e., around 5 fishers per pirogue in 1983. The total number of coastal fishers (lagoon and marine) was estimated at 15,300 for 1960 (Anon. 1964), thus to estimate the number of marine artisanal fishers among these, we first obtained the number of lagoon fishers using the ratio lagoon fishers estimated at 11,000 (Lemasson 1961): Coastal population for 1955 (Figure 2), i.e., 3%, multiplied by the coastal population for 1960 and obtained a number of lagoon fishers of 11,939 for 1960. The difference between the total number of coastal fishers and lagoon fishers is the number of artisanal marine fishers for 1960, i.e., 3,361 for 639 pirogues (assuming 5 fishers per pirogue). Similarly, we obtained the total number of coastal fishers as 4% of the coastal population within the primary sector (80% of the coastal population) as documented by Anon. (1964) for 1950, i.e., 11,925 fishers. We then estimated the number of lagoon fishers for 1950 at 10,061 using the proportion of lagoon fishers for 1955, i.e., 11,000 (Lemasson 1961) over the coastal population for 1955, then multiplied by the coastal population for 1950. We then estimated marine artisanal fishers by subtracting the number of lagoon fishers from the total estimated for 1950 (Table 1), which was then divided by 5 to estimate the number of pirogues. We interpolated to fill in the gaps.Surveyed catches by gear type and the number of artisanal boats were obtained from Turay and Verstralen (1997) for 1995 and 1996, which were used to calculate an average CPUE of 14.26 t·pirogue-1·year-1 for 1995 and 1996. Given the over-exploitation pattern (Stoop et al. 2013), we assumed this CPUE was slightly higher (10%) in 1950, and lower in 2010 (10%). We interpolated and then multiplied the estimated number of pirogues by the CPUE.Table 1.   Artisanal fishing effort in the marine waters of Benin and its lagoons. Italics indicate interpolations. Marine effort Lagoons fishersYear Pirogues Fishers Source Total Sources Using acadjas1950 354 1,864 Estimated 10,061 Estimated 2,5151955 496 2,613 11,000 Lemasson (1961) 2,7501956 525 2,762 11,000 Lemasson (1961) 2,7501957 553 2,912 11,000 Lemasson (1961) 2,7501958 582 3,062 10,000 Buffe (1958) 2,5001960 639 3,361 Estimated 14,455  3,6141969 565 2,974 34,500 Welcomme 2003 8,6251977 500 2,629 38,300 Dioury 1983 7,2951980 475 2,500 Estimated based on the number of fishers (Chaboud and Charles-Dominique 1991)38,545  7,6861987 477 4,000 39,117 Turay and Verstralen (1997) 8,6151988 654 3,840 42,619 Turay and Verstralen (1997) 9,5131989 657 3,680 45,292 Turay and Verstralen (1997) 10,2451990 660 3,520 50,284 Turay and Verstralen (1997) 11,5231991 662 3,360 50,470 Turay and Verstralen (1997) 11,7161992 665 3,200 Horemans (1994) 47,672 Turay and Verstralen (1997) 11,2091993 731 3,237 Horemans and Jallow (1997) 50,014 Turay and Verstralen (1997) 11,9081994 731 3,237 Horemans and Jallow (1997) 48,874 Turay and Verstralen (1997) 11,7821995 786 3,357 48,895 Turay and Verstralen (1997) 11,9331996 840 3,476 Turay and Verstralen (1997) 48,947  12,0911997 840 3,596 Turay and Verstralen (1997) 49,000 Turay and Verstralen (1997) 12,2501999 816 4,345 FAO (2007) 52,600  13,1502002 804 4,524  58,000 FAO (2007) 14,5002003 800 4,583 Njock and Westlund (2010) 57,949  14,4872006 860 4,762  57,796 Ahouandjogbe et al. (2013) 14,4492009 919 4,940  58,000 Anon. (2010) 14,5002010 939 5,000 Estimated based on the number of fishers (Dessouassi 2011)59,217  14,8042012    61,650 Ahouandjogbe et al. (2013)   54Lagoon catchesNon-acadja catchesThere are three main lagoons in Benin, Porto Novo, Lake Aheme and Lake Nokoué, which in contrast to what their names suggest, are two of the most important lagoon systems in Benin. Literature suggests Benin lagoons contribute the most to artisanal fisheries in the country (Iroko 2005; FAO 2007). Data on the number of artisanal fishers were available and completed by a series of linear interpolations (Table 1). Some of these fishers use acadjas, i.e., “artificial systems aimed at enhancing fish production by providing additional substrata for development of plants and animals upon which the fish will feed” (Niyonkuru and Lalèyè 2010), to aggregate, then catch fish. Since these systems are well documented, we reconstructed their catches separately. We first estimated the number of fishers not using acadjas by subtracting the number of those using acadjas from the total number of artisanal lagoon fishers. We obtained the proportion of fishers using acadjas over total lagoon fishers by dividing the number of fishers using this technique for Lake Aheme and Porto-Novo Lagoon (3,500) by the total number of fishers provided for both lagoons for 1997 (14,025), i.e., 25% (Turay and Verstralen 1997; SOFRECO 2002). Given that acadjas are mainly on inheritance basis and new entries are restricted (Vogt et al. 2010), we assumed the rate remained constant over time except for the time when the acadjas were prohibited in Lake Aheme between 1970 and 1976. Thus, we assumed the proportion of acadja fishers over total number of fishers for 1976 was 25% lower than that of 1997, i.e., 9%. We assumed this proportion was 25% between 1950 and 1970, when acadjas were prohibited in Lake Aheme, interpolated to 9% in 1976, and then interpolated to 25% in 1997, kept constant thereafter. We multiplied these rates by the total number of lagoon fishers (Table 1) and then subtracted the result from the total number of lagoon fishers to obtain the number of lagoon fishers not using acadjas (Table 1).We estimated the CPUE using the total non-acadja observed catch divided by the number of fishers for 1960, i.e., 22,500 t by 11,000 fishers (Lemasson 1961), and we assumed that this CPUE was constant between 1950 and 1960. We divided the CPUE by 2 for 1983 (Dioury 1983). Similarly, we estimated the CPUE based on catch and effort data by Turay and Verstralen (1997) at 1.1 t·fisher-1·year-1. Ahouandjogbe et al. (2013) surveyed lagoon catches per trip, the number of trips and the number of pirogues by lagoon in Benin for 2012, which allowed to estimate a weighted average CPUE for all coastal lagoons, and excluded 25% of it as being taken by acadjas, i.e., 1.65 t·pirogue-1·year-1 or 1.2 t·fisher-1·year-1 (with 1.37 fishers per pirogue). Pérez-Ruzafa and Marcos (2012) estimated a lower CPUE of 0.99 t·fisher-1·year-1 for the same year, of which we removed 25% as taken from acadja systems and obtained 0.74 t·fisher-1·year-1. We averaged the previous CPUE estimates and obtained 0.98 t·fisher-1·year-1 for 2012. Anon. (2010) documented that the CPUE declined by a third during the last 20 years. Therefore, we assumed the CPUE in 1989 was 33% higher than the CPUE in 2012, i.e., 1.3 t·fisher-1·year-1. These declines of CPUE are illustrated throughout the literature and surveys, where catches per trip and fish sizes were declining (Atti-Mama 1998; Niyonkuru and Lalèyè 2010), and fish stocks decreasing (Stoop et al. 2013) in lagoons which were previously known to be abundant in fish (Bouche 1885). We interpolated between the CPUE estimates and multiplied the resulting annual values by the estimated number of fishers to obtain lagoon non-acadja catches.Acadja catchesAcadjas were introduced in Benin through Lake Nokoué and Porto Novo lagoons in the beginning of the 20th century (Lalèyè 2000). They quickly became an effective way of aggregating and catching large amounts of wild fish within lagoons. However, this technique is controversial since it tends to aggregate wild fish otherwise caught by non-acadja users. Furthermore, the area occupied by acadjas is often high enough, i.e., 35% of Lake Nokoué for example, to produce spatial conflicts (Niyonkuru and Lalèyè 2010). These conflicts and inequalities have led to a moratorium in 1970 in Aheme lagoon (Weigel 1985; Dangbégnon 2000; Cofad and Gut 2002). The total surface area of acadjas was estimated at 433 ha in 1959 (Welcomme 1972), 156 ha after the prohibition in 1970 (Welcomme 1972) and at 6,691 ha for 1996 (Gbaguidi and Djanato 1997). We estimated the surface areas of acadjas for 1950 at 414 ha (by estimating the surface area per fisher for 1959 obtained by dividing the surface area by the estimated number of acadja fishers; Table 1). We applied the same method to estimate the surface area between 1960 and 1969, prior to the prohibition acadjas in Lake Aheme and assumed the surface area was constant between 1971 and 1976 because of the prohibition in place. We estimated the surface area of acadjas for 2010 by dividing the surface area for 1996 by the number of fishers for the same year, then multiplying the resulting rate by the number of acadja fishers for 2010 and obtained a surface area of 8,192 ha for 2010. We interpolated between the estimates to fill in the gaps.Catches per hectare were obtained from Buffe (1958) for the period between 1955 and 1958, Welcomme (1972) for 1959 and 1970 and Lalèyè (2000) for 1980 and 1998. We also estimated the CPUE for 1994 based on the survey by Anon. (1994) estimating the catch for 12 ha of different acadjas, over 93 fishing days and 33 fishers, at 13.8 kg·ha-1·day-1, i.e., 4.14 kg·ha-1·year-1 assuming 300 fishing days. We assumed the CPUE was constant between 1950 and 1955 and that it declined by 10% between 1998 and 2010 to account for overexploitation despite an increase in catches since 1976 (Ajao 1999). We interpolated between the CPUE estimates and multiplied them by the surface area of acadjas to obtain total artisanal acadja catch.Benin - Belhabib and Pauly 55Subsistence catchesAcadja catchesAcadja catches per trip were surveyed by Anon. (1994) and accounted for commercial catches, consumption, donations and stolen fish. These would not be landed and therefore not accounted for in artisanal catches or surveys targeting artisanal catches. Consumption (including personal consumption, donations and stolen fish) was estimated at 1.5 kg·fisher-1·day-1, i.e., 451 kg·fisher-1·year-1 for 1994. We assumed this consumption was 20% higher between 1950 and 1969 prior to the prohibition of acadjas in Lake Aheme. Given evidence of a decrease of retained catches for personal consumption (Vogt et al. 2010), we assumed consumption in 2010 was 15% lower than that of 1994. Similarly, we assumed consumption during the acadja prohibition period (between 1970 and 1976) was 15% lower than in 1994. We interpolated and multiplied the estimated consumption by the number of fishers using acadjas.Other marine and lagoon subsistence catchesSubsistence marine catches were estimated as the equivalent of 17% of artisanal catches for 2010, part of which is the taken home portion of the artisanal catch (Vogt et al. 2010), i.e., 1,939 t·year-1 for 2010. This converts into a consumption rate of around 48 kg·capita-1·year-1 for fishers and their households of 8 members (Ijff and Tempelman 1990). For 1990, Ijff and Tempelman (1990) estimated a consumption from subsistence fishing of 54 kg·capita-1·year-1 which, when multiplied by the number of fishers and their households, provides a subsistence catch of 1,521 t·year-1 for 1990. Given the evidence of declining subsistence consumption (Vogt et al. 2010), we extrapolated the previous consumption rates per capita backwards and estimated a consumption rate of 65.1 kg·capita-1·year-1 for 1950, i.e., 970 t·year-1 when multiplied by the number of marine artisanal fishers and their household in 1950. We then interpolated linearly between the three anchor points and estimated marine subsistence catches.We applied the same method for lagoon non-acadja subsistence catches, where for 2010 the equivalent of 17% of artisanal catches were for subsistence (Vogt et al. 2010), i.e., 7,476 t·year-1 or 21.04 kg·capita-1·year-1, and for 1990, a consumption rate of 38.33 kg·capita-1·year-1 was estimated (Ijff and Tempelman 1990), i.e., a catch of 11,884 t·year-1. We extrapolated the previous consumption rates backwards and estimated a consumption rate of around 73 kg·capita-1·year-1 for 1950, i.e., 4,401 t·year-1. We interpolated linearly lagoon non-acadja subsistence catches.Table 2.   Reconstructed number of industrial fishing vessel operating in Benin per country (Dioury 1983; Ssentongo 1990; Turay and Verstralen 1997; SOFRECO 2002; Anon. 2010). Interpolations are indicated in italics. Year Total Benin Nigeria Cameroon Sudan Greece China Spain France Italy Portugal1950-1957  - - - - - - - - - - -1958 1 - - - - - - - - 1 -1959 1 - - - - - - - - 1 -1960 2 - - - - - - - - 1 11961 2 - - - - - - - 1 1 -1962 2 - - - - - - - 1 1 -1963 3 - - - - - - - 1 1 11964 6 - - - - 1 - - 1 2 21965 6 - - - - 1 - - 1 2 21966 5 - - - - 1 - - 1 2 11967 7 1 - - - 1 - - 2 2 11968 7 1 - - - 1 - - 2 2 11969 7 1 - - - 1 - - 2 2 11970 9 2 - - - 1 - - 3 2 11971 11 2 - - - 1 - - 3 3 21972 12 3 - - - 1 - - 3 3 21973 11 2 - - - 1 - - 3 3 21974 19 3 - - - 1 - - 10 3 21975 8 2 - - - 1 - - 2 2 11976 6 2 - - - 1 - - 2 1 -1977 6 2 - - - 1 - - 2 1 -1978 4 1 - - - 1 - - 1 1 -1979 4 1 - - - 1 - - 1 1 -1980 16 3 1 1 1 1 - 1 4 2 21981 9 2 1 1 1 1 - 1 2 1 11982 1 1 - - - - - - - - -1983 1 1 - - - - - - - - -1984 5 1 - 1 1 - - - - - -1985 6 1 1 2 1 - - - - - -1986 6 2 1 1 1 - - - - - -1987 7 2 1 1 1 1 - 1 1 - -1988 7 2 1 1 1 1 - 1 1 - -1989 8 2 1 1 1 1 - 1 1 - -1990 8 3 1 2 1 1 - 1 1 - -1991 9 3 1 2 1 1 - 1 1 - -1992 9 3 1 2 1 1 - 1 1 - -1993 10 3 1 2 1 1 - 1 1 - -1994 9 3 1 2 1 1 - 1 1 - -1995 7 3 1 1 - - - 1 1 - -1996 7 3 1 1 - - - 1 1 - -1997 7 3 1 1 - - - 1 1 - -1998 9 3 1 1 - - 1 1 1 - -1999 10 3 1 2 1 - 3 1 1 - -2000 12 2 1 2 1 1 4 1 1 - -2001 13 2 1 3 1 1 5 1 1 - -2002 15 2 1 3 2 1 7 1 1 - -2003 14 3 1 2 1 1 6 1 1 - -2004 13 3 1 2 1 1 6 1 1 - -2005 12 4 - 1 1 - 5 1 - - -2006 11 4 - 1 - - 5 1 - - -2007 10 5 - - - - 4 1 - - -2008 14 4 1 1 1 1 6 1 1 - -2009 18 3 1 1 2 1 8 1 1 - -2010 20 3 8 - - - 8 - - - - 56Women catchesLiterature documenting women fishing in Benin is scarce, most reviews refer to their role in fish processing. Yet, to improve their financial situation, women along the coast tend to have other activities such as financing fishing gear, or fishing for crabs and oysters along the lagoons (Gnakadja 2000). In Benin, these women fish for cash sale (Trottier 1987). Capo-Chichi (2006) estimated the number of these women at 9,724 for 2006, which is the equivalent of 16% of the total number of male lagoon fishers. Since these women are most likely relatives of male fishers themselves and directly or indirectly related to them, we assumed this percentage was constant over the 1950-2010 time period and multiplied it by the total number of lagoon male fishers to obtain the total number of female fishers. We assumed the same CPUE than for the acadja subsistence catch and multiplied the CPUE by the number of female fishers.IndustrialMost of the industrial fleet that is operating and holds legal agreements to fish within Benin is either foreign owned, foreign flagged or under joint venture and thus based in Benin (Dioury 1983). This situation did not change over time as in the 2000s, and most vessels operating within Benin legally were foreign owned, targeting demersal stocks notably shrimps (Turay and Verstralen 1997; FAO 2007). It is also widely recognized that industrial foreign vessels do not land their catches in Benin (Allegre and Dupret 2010), nor do they have observers onboard and therefore their catches, reflected by low numbers in official data, are mostly unknown. This situation worsened after the 1972 coup d’état, when French, Italian and Greek fishing vessels based in Cotonou left Benin ports because of the fear of nationalization (NOAA 1981), which makes catch data collection even more difficult. We reconstructed the total number of industrial shrimp trawlers within Benin using different literature sources and then allocated these number to a nationality based on the available literature (Table 2). For example, the Chinese fleet, particularly the Kelly fleet (see below), operate in Benin since 2002 and has been increasingly reflagging to the country since then (Vogt et al. 2010). The number of these boats was given at –at least – 4 for 2007, and therefore we assumed the number of Chinese vessels in the following years was at least 4 plus part of the number of vessels flagged to Benin. CPUEs estimated were given by the literature from 1958 to 1988 (Dioury 1983; Ssentongo 1990). We performed a linear extrapolation to model the CPUE between 1950 and 2010, then multiplied the resulting CPUE estimates by the estimated number of boats per country.DiscardsThe discard rate for the domestic fleet was estimated by Kelleher at 0.5% for 2005, a low rate that is due to increasing retention and landing of bycatch by the domestic demersal fleets. This rate was assumed constant between 2005 and 2010. In the early 1960s, trawl surveys within fishing areas revealed that over the total catch, 15% of species were non-commercial and thus discarded species (Crosnier and Berrit 1964). We assumed this percentage was constant between the 1950s and 1969 and then interpolated to 0.5% in 2005. We multiplied discard rates by the domestic catch to obtain discarded bycatch.To estimate foreign discards, we used the percentage of discards provided by Kelleher (2005) for Spain (30%) and Greece (32%) between the 1950s and 2010 and then applied them to Spanish and Greek catches. We averaged the previous discard rates and applied them to the industrial catch by France, Portugal, Italy and China. For Nigeria, Cameroon, and Sudan, we applied the domestic discard rates given that these fleets are likely landing their bycatch for local markets.IllegalIllegal fishing in Benin is operated by Nigerian flagged Chinese vessels and particularly the ‘Kelly Company’s fleet’, whose incursions to the artisanal fishing area often results in loss of gear and conflicts with artisanal fishers (Vogt et al. 2010). MRAG (2005) estimated illegal, unreported and unregulated catches to be the equivalent of 12% of the legal reported catch, but it is unclear to which category these catches belong. The available information suggests that illegal tuna fishing was most likely offshore (FAO 2007). Trawl illegal fishing referred to in the literature considers the unregulated activities of the Kelly fleet and vessels that are Nigerian flagged holding legal right to operate in Benin, but use illegal mesh size and often operate within areas reserved for artisanal fishers. Herein, we did not reconstruct illegal catches as these might be already included in the industrial component.Table 3.   Artisanal marine catch composition (Ssentongo 1990; Djiman 1996) in %.Percentage of total catch 20 80Pseudotolithus spp. 13.7 9.7Galeoides decadactylus 13.9 7.3Pentanemus quinquarius 0.1 -Arius spp. - -Brachydeuterus auritus 0.4 -Drepane africana 0.5 -Belonidae 2.4 -Chloroscombrus chrysurus 14.3 -Trichiurus lepturus 3.4 -Others 51.3 -Dentex spp.  - 2.5Sphyraena spp.  - 6.2Lutjanus spp.  - 2.9Illisha africana  - 50.0Pomadasys spp.  - 0.8Polydactylus quadrifilis  - 0.6Pagellus spp.  - 0.3Sardinella spp.  - 8.6Scombromorus tritor  - 11.2Benin - Belhabib and Pauly 57Species disaggregationTo disaggregate artisanal and subsistence marine catches we combined the taxonomic breakdown by Ssentongo (1990), who provided the species disaggregation for demersal catches, i.e., 20% of total catches, and Djiman (1996), who documented the species breakdown for the rest of the catch (Table 3).Similarly, we used the species breakdown provided by (Ssentongo 1990) and Djiman (1996) between 1965 and 1993, completed with a series of linear interpolations and assuming that the same species breakdown since 1993.It should be noted that the Sea Around Us is solely focused on marine and brackishwater fisheries catches. Therefore, once the species disaggregation of the lagoon catches was complete, the catch of purely freshwater species was removed and all analysis was performed on marine and brackish water species only. Herein, artisanal and subsistence lagoon catches refer exclusively to the marine/brackish water species estimates.resultsArtisanal catchesArtisanal catches from the marine and estuarine waters of Benin were estimated at about 3.1 million t between 1950 and 2010, mainly taken from lagoons (81.6%). Artisanal marine catches increased from 5,600 t·year-1 in 1950 to a first peak of around 10,000 t·year-1 in 1960 and then decreased after independence due to a series of socio-political events to their historical minimum of 6,200 t·year-1 in 1985 then increased to a peak of 12,000 t·year-1 in 1996 to remain relatively constant despite an increase in the effort later on (Figure 3).Artisanal lagoon catches increased from 15,400 t in 1950 to a first peak of 35,000 t in 1969, to decrease thereafter to 28,000 t·year-1 in the mid-1970s after the 1972 coup d’état that triggered insecurity (Figure 3). Catches increased thereafter to their historical maximum of 67,000 t in 1993, before declining to 58,000 t·year-1 in the late 2000s and then remaining relatively constant despite an increasing number of fishers (Figure 3). The data set does not separate artisanal catches into acadja/non-acadja catches.Subsistence catchesSubsistence catches were estimated at around 800,000 t between 1950 and 2010, most of which taken from the lagoons (538,000 t). Subsistence marine catches increased with the coastal population from around 1,000 t·year-1 in 1950 to around 2,100 t·year-1 in 2010 (Figure 4). The lagoon subsistence catches of male fishers increased from around 4,400 t·year-1 in 1950 to a peak of 12,000 t·year-1 in 1990, mainly taken as consumption from the acadja fishery (60%), before declining to 8,100 t·year-1 in 2010 (Figure 4). Women catches increased from 1,000 t·year-1 on average in the 1950s to a peak of around 3,000 t·year-1 in 1969 right after decreasing because of increasing insecurity in the early 1970s (Figure 4). Catches increased gradually thereafter to reach a peak of 4,100 t·year-1 in 2002, before decreasing to around 3,800 t·year-1 in 2010 (Figure 4).0204060801950 1960 1970 1980 1990 2000 2010Catch (t x 103 )YearLagoonArtisanal catches supplied to FAOMarine0481216201950 1960 1970 1980 1990 2000 2010Catch (t x 103 )YearWomen gleaningacadjamarinenon-acajdaFigure 3.  Artisanal reconstructed catches within marine and lagoon waters of Benin, 1950-2010. Black line indicating FAO reported values has been adjusted to remove freshwater catches from lagoons.Figure 4.  Subsistence reconstructed catches within coastal and lagoon waters of Benin, 1950-2010. 58Industrial catchesIndustrial domestic catches increased from 240 t in 1959 to a first peak of 1,100 t·year-1 in 1974 and declined rapidly to less than 400 t·year-1 in the late 1970s (Figure 5). Industrial catches peaked again in 1980 at 1,100 t·year-1 before declining to less than 400 t·year-1 in 1984. Industrial catches varied later on but reached a peak of 1,600 t·year-1 in 2007 before declining drastically due to the decline in the number of industrial domestic vessels (Figure 5).Foreign catches, on the other hand, reached a historical peak of around 7,800 t·year-1 in 1974, after which the departure of vessels from Benin translated into a drastic decline in industrial foreign legal catches, dropped to around 1,100 t·year-1 in 1978, mostly by French, Italian, Greek and Sudanese vessels (Figure 5). Catches peaked again in 1980 with the increase in the number of industrial vessel at 5,900 t, before declining to very low levels in 1982 (0 from 1982-1983) (Figure 5). Catches increased again thereafter to reach a peak of 2,500 t·year-1 in the early 1990s, when industrial fleets were dominated by African flagged vessel (Cameroon, Nigeria, Sudan) and European vessels (Figure 5). Catches increased to around 5,800 t·year-1 in 2002, dominated by Chinese catches, decreased slightly before reaching 5,900 t·year-1 in 2010; they were dominated by China and Greece (Figure 5).DiscardsDiscards were estimated at around 29,100 t between 1950 and 2010. Discards increased gradually from low levels in the mid-1950s to a peak of 1,900 t·year-1 in 1974, due to high discarding rates. Discards lowered with the decline of the industrial fleet to low levels in 1983 before increasing gradually to around 800 t·year-1 in 2010 (Figure 6).Reconstructed total catchesTotal removals from Benin waters were estimated at 4.0 million t between 1950 and 2010, of which 76 % were taken from the lagoons of Benin, and less than 4 % by the foreign fleets operating in Benin. Domestic catches were estimated at 3.8 million t, of which only 1.7 million t were reported to FAO2 on behalf of Benin. Domestic catches increased to 26,900 t in 1950 compared to 9,200 t reported to FAO, to 56,900 t in 1969, contrasted to the 31,000 t reported to FAO. Catches declined during the 1970s before increasing to a peak of over 94,000 t·year-1 in the early 1990s, almost three times what was reported to the FAO (Figure 7a). Catches decreased thereafter to 85,000 t in 2010, while landing data reported to FAO increased to 35,000 t (Figure 7a).Taxonomically, blackchin tilapia (Sarothoredon melanotheron) dominates catches with approximately a third of total reconstructed catches (38%) followed by Perciforms (11.5%). However the contribution of the two previous taxa to total catches has been declining and slowly replaced by bonga shad (3.8%) in the most recent periods (Figure 7b). ‘Others’ contain 91 additional categories and composed 25.7% of reconstructed total catches.discussionDomestic and foreign fishing fleets caught around 4.5 million t between 1950 and 2010. Only 41% of the catches taken domestically were reported to the FAO on behalf of Benin. The under-reporting component remained relatively constant over time and then increased during the recent time periods, which shows a lack of improvement in the monitoring system. Furthermore, while official data shows stagnation to a slight increase in the recent years, the 2  1.7 million t represents the adjusted FAO baseline, after the removal of freshwater species.0121950 1960 1970 1980 1990 2000 2010Catch (t x 103 )YearForeignDomestic01234567891950 1960 1970 1980 1990 2000 2010Catch (t x 103)YearBeninChinaFranceGreeceCameroonItalyPortugalSudanSpainNigeriaFigure 5.  Industrial domestic and foreign reconstructed catches from Benin, 1950-2010.Figure 6.  Industrial domestic and foreign reconstructed discards from Benin, 1950-2010.Benin - Belhabib and Pauly 59reconstructed data suggest catches are decreasing despite (or rather because of) an increase in effort, which explains over-exploitation perceived by small-scale fishers. This overexploitation causes increasing conflicts with industrial fishing fleets. Furthermore, marine catches including artisanal, industrial catches and the discards they generate are above Maximum Sustainable Yield (MSY), estimated to be between 8,000 and 10,000 t·year-1 (Anon. 2010).The decline of fisheries and the increasing number of conflicts (Vogt et al. 2010) threatens small-scale fishers’ livelihoods. Indeed, more than a tradition, fisheries are often in Benin the only available occupation for a large number of people as it remains a more profitable activity than agriculture (Atti-Mama 1998). Yet, the economic situation of fishers is increasingly deteriorating (Vogt et al. 2010), which suggests increasing presence of industrial vessels and increasing use of acadjas. Although some authors argue that acadjas contribute to increasing fish sizes and repopulating lagoons (Atti-Mama 1998), these large brush parks remain controversial since they “physically impede fishing in the waters they occupy and, as they attract fish from a wider area, they also reduce the stocks available to capture fisheries to some extent” (Cofad and Gut 2002).Fisheries are also affected by socio-political conditions. For example, the 1972 coup d’état triggered insecurity in the country which resulted in a decline in small-scale catches on one hand, and the departure of formerly Benin-based foreign fleets fearing nationalization (NOAA 1981) by the newly implemented Marxist regime, on the other hand. As a result, when the livelihoods of fishers are threatened, the traditional rules aimed at the sustainable use of fisheries resources via bans, periods of rest, restricted gear and entry to the fishery, are overcome by short term high yields (Vogt et al. 2010), resulting in further over-exploitation of fisheries. This decline is also shown by the decrease in discarding rates leading to previously discarded species and juvenile fish increasingly appearing in local markets (Vogt et al. 2010). This, along with climate-change induced sea level rise and a low adapting capacity (Dossou and Gléhouenou-Dossou 2007) dangerously challenges of the management approaches aimed at development in Benin.Another dangerous aspect of the decline in Beninese fisheries is that 90% of fisheries and related activities involve “the exchange of sexual favors or transactional sex which is highly related to HIV and AIDS” (Allison and Seeley 2004). The decline in fisheries may have severe implications for exacerbating the HIV/AIDS pandemic.As fish catch decline, the growing desperation of fishers could intensify catch effort and capacity, hence placing additional pressures on both marine and lagoon resources. The expansion of fishing territory, which further increases competition (Vogt et al. 2010) and the lack of management measures to control foreign industrial fleets, have led to the increasing spread of piracy and violence in the Gulf of Guinea. This was prevalent in 2007, when Chinese trawlers sailing under the Benin flag were attacked by local fishers (Gletton-Quenum 2010). By reconstructing the total marine catches of Benin, the severity of the current state of the fisheries and the stark implications for Benin fishers becomes apparent.acknoWledGementsWe acknowledge the support of the Sea Around Us, a scientific collaboration between the University of British Columbia, The Pew Charitable Trusts and the Paul G. Allen Family Foundation.020406080100Catch (t x 103 )Artisanalsupplied to FAO SubsistenceIndustriala)0204060801001950 1960 1970 1980 1990 2000 2010Catch (t x 103)YearSarotherodon melanotheronOthersSiluriformsIllisha africanaTilapia guineensisEthmalosa fimbriataSarotherodon galilaeusPerciformesb)Figure 7.  Reconstructed total catches from Benin EEZ by a) sector, with the solid line representing the adjusted FAO reported baseline after the removal of freshwater species; and b) by taxonomic composition, 1950-2010. ‘Others’ contain 91 other taxonomic categories. 60reFerencesAhouandjogbe S, Didavi Y, Gangbazo K and Gnitassoun D (2013) Rapport National. Enquête cadre en pêche continentale 2012. Ministère de l’Agriculture, de l’Elevage et de la Pêche, Cotonou. 124 p.Ajao E (1999) Sustainable management of water bodies for small-scale fisheries resorces research and development, 13th Annual Conference of the Fisheries Society of Nigeria (FISON), 3-8 November 1996. 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FAO, Rome.Turay F and Verstralen K (1997) Costs and Earnings in Artisanal Fisheries: Methodology and Lessons Learned from Case Studies. Technical Report 100, DIPA, Cotonou. 60 p.Vogt J, Teka O and Sturm U (2010) Modern issues facing coastal management of the fishery industry: A study of the effects of globalization in coastal Benin on the traditional fishery community. Ocean & Coastal Management 53(8): 428-438.Weigel J (1985) Traditional management of some lagoons in the Gulf of Guinea (Ivory Coast, Ghana, Togo and Benin). FAO Fish. Circ. 790, FAO, Rome. 29 p.Welcomme R (1972) An evaluation of the acadja method of fishing as practiced in the coastal lagoons of Dahomey (West Africa). I. Fish Biol. 4: 39-55. 62 Appendix Table A1.  Adjusted FAO landings vs. reconstructed total catch (in tonnes), and catch by sector with discards shown separately, for Benin, 1950-2010.Year FAO landings1 Reconstructed total catch Industrial Artisanal Subsistence Discards1950 9,190 26,900 - 20,600 6,290 -1951 9,190 27,800 - 21,300 6,500 -1952 9,190 28,800 - 22,000 6,710 -1953 9,190 29,700 - 22,800 6,920 -1954 14,280 30,600 - 23,500 7,130 -1955 14,280 31,600 - 24,200 7,340 -1956 19,370 33,800 - 26,200 7,530 -1957 19,370 36,400 - 28,700 7,720 -1958 19,370 33,200 - 25,400 7,800 -1959 21,190 35,300 240 26,800 8,250 -1960 22,190 39,300 300 30,300 8,700 -1961 24,010 42,100 360 32,600 9,150 -1962 25,650 44,600 360 34,600 9,600 -1963 21,010 46,700 180 36,500 10,050 -1964 22,010 48,900 240 38,200 10,500 -1965 17,100 50,900 240 39,700 10,950 -1966 16,080 52,600 228 41,000 11,400 -1967 30,160 54,300 336 42,100 11,850 -1968 30,460 55,700 354 43,000 12,300 -1969 31,160 56,900 396 43,700 12,740 -1970 37,100 53,500 499 41,200 11,780 -1971 37,670 54,300 606 41,700 11,980 -1972 37,680 54,800 666 41,900 12,190 -1973 35,250 52,100 749 39,000 12,390 -1974 34,070 51,600 1,119 37,900 12,600 -1975 32,290 50,500 743 37,000 12,800 -1976 31,890 49,700 740 35,900 13,000 -1977 31,390 51,800 737 37,800 13,270 -1978 30,880 53,200 367 39,400 13,500 -1979 30,770 55,100 365 41,000 13,740 -1980 32,780 58,000 1,091 42,900 13,970 381981 32,790 60,100 724 45,100 14,210 181982 32,650 62,200 361 47,400 14,440 -1983 30,250 64,600 359 49,600 14,680 -1984 30,910 65,400 352 50,100 14,910 161985 32,250 66,700 420 51,100 15,150 181986 34,690 71,400 709 55,300 15,390 171987 34,090 77,700 756 61,300 15,620 181988 31,290 84,700 803 67,700 16,170 181989 34,660 90,000 850 72,400 16,650 191990 31,630 94,600 896 76,300 17,340 191991 29,070 94,200 942 76,000 17,230 191992 26,750 91,300 987 73,500 16,840 191993 32,900 95,900 1,031 77,900 16,930 181994 33,750 94,800 1,027 77,000 16,700 171995 36,630 93,000 1,022 75,500 16,490 151996 34,710 90,600 1,018 73,300 16,280 141997 36,350 86,500 1,013 69,400 16,070 131998 34,690 83,600 941 66,600 16,010 111999 32,820 84,200 868 67,300 15,950 102000 25,980 84,400 797 67,700 15,890 82001 31,290 86,000 729 69,400 15,820 72002 33,560 87,000 660 70,600 15,750 62003 34,560 86,800 854 70,500 15,510 32004 33,380 86,500 1,046 70,200 15,280 22005 26,350 85,700 1,237 69,400 15,040 12006 35,720 86,200 1,425 70,000 14,800 -2007 30,720 86,100 1,612 69,900 14,570 -2008 31,830 85,500 1,283 69,900 14,340 12009 33,660 84,700 958 69,600 14,120 22010 34,690 85,300 953 70,300 13,980 131 For the purposes of Sea Around Us, freshwater species catch have been removed from reported FAO landings, yielding an adjusted baseline.Benin - Belhabib and Pauly 63Appendix Table A2. Reconstructed total catch (in tonnes) by major taxa for Benin, 1950-2010. ‘Others’ contain 91 additional taxonomic categories.Year Sarotherodon melanotheron Perciformes Sarotherodon galilaeus Ilisha africana Ethmalosa fimbriata Siluriformes Tilapia guineensis Others1950 12,300 317 3,210 2,620 189 569 1,300 6,3401951 12,600 329 3,350 2,800 193 587 1,330 6,6601952 12,800 341 3,490 2,980 196 605 1,350 6,9901953 13,100 353 3,620 3,150 200 623 1,380 7,3101954 13,300 365 3,760 3,330 204 641 1,400 7,6301955 13,500 377 3,900 3,510 207 659 1,430 7,9501956 14,800 394 4,030 3,680 227 699 1,560 8,3501957 16,500 413 4,170 3,860 253 747 1,730 8,7801958 13,400 410 4,310 4,030 206 693 1,410 8,6901959 14,300 425 4,440 4,210 218 725 1,500 9,4801960 16,800 448 4,580 4,380 257 795 1,770 10,2501961 18,800 468 4,720 4,330 287 852 1,980 10,6401962 20,600 487 4,850 4,280 315 906 2,180 10,9501963 22,300 506 4,990 4,220 341 957 2,360 11,0601964 23,800 524 5,120 4,170 364 1,005 2,520 11,4001965 25,200 541 5,260 4,120 385 1,049 2,670 11,6701966 26,400 558 5,400 3,960 403 1,089 2,800 12,0201967 27,500 574 5,530 3,830 418 1,127 2,910 12,4501968 28,300 589 5,670 3,850 432 1,160 3,010 12,6101969 29,100 603 5,810 3,840 443 1,191 3,090 12,8301970 19,100 8,568 5,940 2,290 290 2,778 2,030 12,5701971 18,500 8,576 6,080 2,140 282 2,778 1,970 13,9201972 17,900 8,585 6,220 2,200 273 2,778 1,910 14,8701973 17,500 8,592 6,350 1,870 259 2,765 1,810 12,9801974 16,900 8,600 6,490 2,220 244 2,752 1,710 12,6701975 16,300 8,607 6,630 2,850 230 2,738 1,610 11,5001976 15,700 8,616 6,760 3,110 214 2,725 1,500 11,0701977 17,400 8,639 6,900 3,160 232 2,756 1,620 11,0701978 18,900 8,658 7,040 3,210 246 2,780 1,710 10,6601979 20,500 8,681 7,170 3,240 259 2,804 1,800 10,6201980 20,500 10,694 7,310 3,160 253 3,002 1,750 11,3501981 22,100 10,717 7,450 3,280 265 3,022 1,830 11,4301982 23,700 10,735 7,580 3,410 277 3,041 1,910 11,5001983 25,400 10,753 7,720 3,690 288 3,059 1,980 11,8001984 27,000 10,756 7,860 3,060 299 3,074 2,050 11,2401985 28,700 10,777 7,990 2,740 308 3,088 2,110 10,9501986 30,400 10,791 8,130 2,590 318 3,100 2,170 13,8301987 27,400 11,034 8,270 2,570 4,336 3,291 1,900 18,9101988 35,800 9,214 8,400 3,590 2,569 5,096 2,390 17,5801989 39,300 10,027 8,540 1,680 2,840 3,269 2,540 21,7901990 44,200 9,342 8,680 2,010 2,681 3,136 2,770 21,7801991 45,300 8,605 8,510 2,180 2,483 2,936 2,750 21,3401992 43,900 8,263 8,350 2,620 2,371 2,808 2,580 20,4701993 43,100 11,054 8,190 3,020 2,462 2,665 2,460 22,9101994 42,400 11,070 8,030 3,070 2,440 2,419 2,340 22,9901995 39,400 12,519 7,870 3,490 2,272 3,291 2,110 22,0701996 37,100 12,281 7,710 3,820 2,182 3,019 1,930 22,5101997 33,700 12,252 7,550 3,560 2,097 2,771 1,700 22,8201998 31,600 12,228 7,390 3,570 2,023 2,532 1,550 22,7101999 32,600 12,365 7,230 3,420 2,028 2,341 1,540 22,6702000 36,400 10,318 7,070 3,990 1,744 2,082 1,650 21,1302001 36,100 11,602 6,910 3,020 1,936 2,248 1,570 22,6202002 37,400 11,592 6,740 2,130 1,945 2,217 1,570 23,3902003 37,400 11,577 6,580 1,550 1,933 2,183 1,500 24,0802004 38,300 10,827 6,420 2,080 1,838 2,049 1,470 23,5402005 24,300 9,069 6,260 2,740 10,622 1,733 1,490 29,4102006 6,800 13,564 6,100 2,820 17,300 2,268 1,270 36,0402007 6,700 14,181 5,940 3,980 16,751 2,352 1,240 34,9302008 6,600 14,163 5,780 3,370 16,665 2,337 1,230 35,2902009 6,500 14,783 5,620 3,500 15,983 2,422 1,210 34,6302010 6,600 15,079 5,460 4,120 15,979 2,458 1,230 34,340 64Nigeria - Etim et al. 65an overvieW oF the niGerian marine Fisheries and a re-evaluation oF their catch From 1950 to 20101Lawrence Etima, Dyhia Belhabibb and Daniel Paulyba Department of Fisheries and Aquatic Environmental Management, University of Uyo, Akwa Ibom State, Nigeriab Sea Around Us, Fisheries Centre, University of British Columbia,  2202 Main Mall, Vancouver, BC, V6T 1Z4, Canada lawrenceetim @uniuyo.edu.ng ; d.belhabib @fisheries.ubc.ca ; d.pauly @fisheries.ubc.caabstractNigeria, with more than 250 ethnic groups and a current population of about 170 million inhabitants is the most populous African country. With a crude oil production of 2.5 million barrels per day, Nigeria also ranks as the largest producer of crude oil in Africa and the sixth largest producer in the world. The fisheries sector, which is also important, has grown considerably since the country gained independence from the United Kingdom in 1960. However, government fisheries departments lack officers responsible for field data collection; consequently, catch data are often exaggerated or un-reported. Using standard procedures, we re-estimated (i.e., reconstructed) the Nigerian marine fisheries catches from 1950 to 2010 to account for likely under-reporting and non-reporting of the catch of fish and shrimps trawlers, artisanal and subsistence fishers, foreign legal and illegal fleets and discards. This led to catches of about 34,000 t in 1950, 540,000 t in 2005 and 490,000 t in 2010. Reconstructed domestic catches were about twice the data supplied to the FAO. Taxonomically, sardinellas (Sardinella spp.) represented the largest contribution to domestic catches, followed by bonga shad (Ethmalosa fimbriata) and croakers (Pseudotolithus spp.). Under-reporting is becoming more pronounced over time, thus debunking the myth of massive over-reporting by Nigeria. Increasing illegal and unreported catches by foreign vessels constitute a growing threat to the sustainability of the stocks. In all, while catches are under-reported, the marine fisheries of Nigeria are overexploited.introductionFishing activities in the Nigerian marine fisheries sector may be classified into coastal small-scale (artisanal and subsistence), inshore industrial and offshore (distant water) industrial fisheries. The coastal small-scale fishery operates within 5 nautical miles from the coastline and also in estuaries, creeks and lagoons. To reduce conflicts between the industrial and the artisanal sectors, the Nigeria Sea Fisheries (Fishing) Regulation of 1972 assigns exclusive right to the artisanal canoe fisheries to exploit this inshore area. The species exploited include pelagic and demersal fishes such as clupeids, croakers, soles, threadfins, catfishes, sharks, penaeid shrimps, crabs, etc. The artisanal fishery is labour intensive and employs small, traditional and sometimes un-motorized craft and hand-operated gears although planked and dug-out canoes (3 to 13 m long) powered by outboard engines ranging from 15 to 25 hp are increasingly common. Generally, this fishery, which has low capital outlays, employs simple technology and its catches are sold mostly in the local markets. Set gillnets and cast nets are the major fishing gears. The fishery is open access and unregulated (Panayotou 1982).The inshore industrial fishery operates from about 5 nautical miles off the coast to the edge of the continental shelf (Figure 1). This industry employs bottom or mid-water trawlers to catch and land a variety of species including croakers (Pseudotolithus spp.), soles (Cynoglossus spp.), groupers (Epinephelus spp.), snappers (Lutjanus spp.), bigeyes (Brachydeuterus spp.), threadfins (Polydactilus spp.), baraccudas (Sphyraena spp.), jacks (Caranx spp.), horse mackerels (Trachurus spp.) and cutlass fishes (Trichiurus spp.). The industrial fisheries are capital intensive and utilize large fishing vessels with in-board engines 1 Cite as: Etim, L., Belhabib, D. and Pauly, D. (2015) An overview of the Nigerian marine fisheries and a re-evaluation of its catch data for the years 1950-2010. pp. 66-76. In: Belhabib, D. and Pauly, D. (eds). Fisheries catch reconstructions: West Africa, Part II. Fisheries Centre Research Reports vol.23(3). Fisheries Centre, University of British Columbia [ISSN 1198-6727].Figure 1.  Nigeria’s Exclusive Economic Zone (EEZ; 217,000 km2) and shelf area (to 200 m depth). 66and mechanically operated winches (Ekpo and Etim 1989). They employ small- to medium-sized trawlers ranging in size from 9 to 25 m Length Over All (LOA). About 40 trawling companies, with an average fleet size of four, operate in Nigeria and most are members of the Nigerian Trawlers Owners’ Association. Companies with fleet size of more than four are likely to be in partnership with foreign investors (Falaye 2008). Ganapathiraju and Pitcher (2006) noted that there are 36 fishing companies operated in the country, out of which 14 were foreign-owned.According to FAO (2000), Nigerian flag-registered fishing vessels are allowed to operate in the waters of other African countries under the terms of the bilateral fishing access agreements between Nigeria and the countries in question, or under privately arranged agreements, which must be seen by the Nigerian Federal Department of Fisheries (FDF) as “just and equitable”. All the fish catch must be landed at a Nigerian port. The fishing licence issued to such Nigerian-registered flag vessels is classified as Distant-Water Fishing Licence (Category A). Category B license is for vessels which are foreign flag-registered, but are chartered by Nigerian companies or individuals for fishing in the waters of foreign countries. Category C is Distant-Water Fishing Licences usually issued to reefer vessels bringing in frozen fish to Nigeria. Such vessels may be Nigerian or foreign-flag registered.Falaye (2008) stated that FDF makes about 250,000 US dollars annually from the registration of industrial trawlers, but that the sector contributes less than 5% to total marine fish catches in the country. A salient aspect of this subsector is that parts of its catch, notably shrimps, are exported, which brings in about 20 million US dollars annually to the Nigerian economy (Falaye 2008).Offshore marine fisheries exploit resources between the continental shelf area and the 200-mile EEZ. Tuna and billfishes are the main target species. The vessels are generally more than 25 m LOA and greater than 150 gross registered tonnage (GRT). Vessels are all wholly owned by Nigerians. The inability of Nigeria to attract foreign investors may be due its non-membership in the International Commission for the Conservation of Atlantic Tunas (ICCAT).The history of systematic, country-wide fisheries data collection in Nigeria is rather short, as it started in the early 1970s (Ajayi 1991; Etim 1992). Etim (1992) pointed out that the accuracy and authenticity of data collated by FDF is usually doubted by independent authors (e.g., Ssentongo et al. 1983; Everett 1986; Ssentongo et al. 1986; Anon. 1988). Much of the inaccuracies and deficiencies in the FDF’s data are consequences of the inherent bureaucratic problems in government ministries, the fisheries sector and the difficult politics of the country. The various fisheries departments are grossly under-staffed with field officers who are not replaced by new employees upon their retirements. Thus, fewer field officers continue to collect data from an increasing number of landing sites and beaches.Without adequate funding, they are unable to cover all the landing sites assigned to them and they end up guessing part, or maybe even all, of the data they submit. Indeed, scarcity of operating funds is considered by the Directors of Fisheries to be their greatest problem. The decline in government funding, as the only source of funds, to ministries implies that it is politically more expedient for government to direct scarce funds to community development projects and poverty alleviation programmes than to fix fisheries data collection issues whose usefulness is not immediately visible. Politicians are re-elected based on the “development projects” they can take credit for, and not on the quality of statistical data their ministries compile. Without funds, it is difficult for field officers to reach the numerous fishers scattered in remote villages.There are inherent competitive tendencies among the states as they try to surpass or even outdo each other as the best producer of one commodity or the other. This explains the suspected or alleged tendencies by state ministries to inflate their production figures to the FDF. According to the Directors of Fisheries of several states, the final data published by FDF are often higher than the ones they submitted. With no vessels, the monitoring and surveillance unit of the FDF suffers from a total lack of vessel monitoring opportunities; the unit is handicapped as it is expected to depend on other agencies (e.g., the Nigeria Navy) for their monitoring and surveillance activities.Thus, it is clear that fisheries data collection in Nigeria, as in many other developing countries, is fraught with difficulties that make such data deficient, biased or incomplete (Etim 1992; Zeller et al. 2007; Zeller and Pauly 2007; Jacquet et al. 2010). This is compounded by the multi-gear nature of the fisheries, which makes computation and inter-comparison of some indices (e.g., CPUE) across a range of gears difficult.A ‘catch reconstruction’ approach for addressing the anomalies in such data was developed (Zeller et al. 2007) and successfully implemented for many countries, e.g., Mozambique and Tanzania (Jacquet et al. 2010), Colombia (Wielgus et al. 2010) and the US flag-associated islands in the Pacific (Zeller et al. 2007). Within this context and in the light of the aforementioned problems, we reconstructed the marine fisheries catches of Nigeria for the years 1950 to 2010, to obtain time series likely to be more complete, comprehensive and hopefully less biased than the extant data.Nigeria - Etim et al. 67methodsThe catch reconstruction procedure used in this work entails six basic steps (Zeller et al. 2007): i) Identifying of and sourcing for existing reported catch time series, catch per effort, number of fishers;ii) Identifying of sectors, time periods, species, gears, etc., not covered by (i) above; that is missing catch data via extensive literature searches;iii) Search for available alternative information sources to supply the missing catch data in (ii) through extensive literature searches (peer reviewed publications, gray literature and technical reports) and consultations. The first author consulted in-country experts in academia and federal and state government officials, notably, the Directors of Fisheries in all the maritime states, who were either visited or contacted;iv) Developing of data anchor points in time for missing data items,v) Interpolation of time periods between data anchor points for total catch, andvi) Estimation of final total catch time series estimates for total catch, combining reported catches in (i) with interpolated, missing data series in (v) above.FAO and other dataThe Nigerian marine fish catches between 1950 and 2010, as published by FAO on behalf of Nigeria, was extracted from FAO FishstatJ after filtering out unwanted information related to turtles, marine mammals, etc. We carried out extensive literature searches including peer reviewed publications, technical reports and other grey literature2.Reconstructed total catchThe catch per unit of effort (CPUE) and the active fishing days were extracted from the relevant literature or obtained from in-country experts. The reconstructed catch data have the following components: a) fish trawl catches, b) shrimp trawl catches, c) artisanal shrimp catches, d) artisanal fish catches, e) shrimp trawl discards, f) subsistence catch by fishers and their families, and g) illegal and unreported foreign fish catches and illegal and unreported foreign shrimp catches. These are addressed individually.a) Fish trawl catchesThe total catch from the marine sector was computed from CPUE and fishing effort. The CPUE was estimated at 639 kg∙boat-1 for 300 fishing days for 1991 (Löwenberg and Künzel 1991), i.e. 110.7 t·boat-1·year-1. We assumed the CPUE was 20% lower in 1950 due to lower capacity and boat size, and 5% lower in 2010 due to prevailing overexploitation (Akankali and Jamabo 2011) but also increasing piracy, which led to an overall decline of the fishing activity (Perouse de Montclos 2012). The number of finfish trawlers was reconstructed from various sources (Table 1), then interpolated to fill in the gaps. We multiplied the interpolated CPUEs by the number of finfish trawlers and estimated their total catches between 1950 and 2010. We then disaggregated catches based on the species composition provided by Ssentongo et al. (1986).b) Shrimp trawl catchesWe reconstructed the number of boats between 1950 and 2010 based on various sources (Table 2). Given the the lack of independent empirical scientific reports on the 2  Some of the earlier reports from the 1960s were obtained during a summer 2013 visit by DP to Alan Longhurst, who has retired in the South of France, but was based in Lagos in the early 1960s, and very active in early Nigerian fisheries research.Table 1.   Reconstruction of the number of finfish trawlers operating in Nigeria, 1950-2010.Year Number of trawlersReference1950 7 Assumed half of the number in 19711971 13 Ssentongo et al. (1986)1976 26 Ssentongo et al. (1986)1982 52 Ssentongo et al. (1986)1984 53 Ssentongo et al. (1986)1992 58.2 One fifth of the total trawl fleet (Okon 2010) 2003 50 One fifth of the total trawl fleet (Okon 2010)2007 38.2 One fifth of the total trawl fleet (Okon 2010)2008 35 FDF (2008)2010 30 One fifth of the total trawl fleet (Perouse de Montclos 2012)Table 2.   Reconstruction of the number of shrimp trawlers operating in Nigeria, 1950-2010.Year Number of shrimpersReference1950 5 Assumed to be 20% of the 1971 effort1971 26 Ssentongo et al. (1986) 1972 29 Ssentongo et al. (1986)1973 30 Ssentongo et al. (1986)1974 39 Ssentongo et al. (1986)1975 30 Ssentongo et al. (1986)1976 29 Ssentongo et al. (1986)1977 36 Ssentongo et al. (1986)1978 49 Ssentongo et al. (1986)1979 48 Ssentongo et al. (1986)1980 45 Ssentongo et al. (1986)1981 36 Ssentongo et al. (1986)1982 34 Ssentongo et al. (1986)1983 39 Ssentongo et al. (1986)1984 37 Ssentongo et al. (1986)1992 233 See Table 11995 235a -1997 197a -2003 200 See Table 12010 120 See Table 1a http://www.fcwc-fish.org/about-us/member-countries/81-nigeria  68shrimp trawl fisheries, we calculated the CPUE by dividing the catch estimated by FDF (2008) by the corresponding effort, i.e., 1,123 t·boat-1·year-1 for the 2008-2010 time period (see Table 2 for effort). An assessment by Ssentongo et al. (1986) based on reported catch data by shrimping companies allowed to estimate the CPUE of shrimpers at 188.27 t·boat-1·year-1 for the early 1980s. Although this value is much lower than that for the late 2000s, increasing shrimper capacity and efficiency, and the increase in the number of their fishing days (Perouse de Montclos 2012), makes such an increase possible. We assumed the CPUE was 20% lower in 1950 to account for increasing capacity. We interpolated linearly the CPUE estimates, then multiplied the latter by the number of shrimpers between 1950 and 2010. We interpolated the resulting catch to fill in the gaps. Shrimp trawler catches consisted of 6% shrimps, 81% croakers, 2% soles, 3% rays, 4% sea catchfishes and 5% other species (Ssentongo et al. 1986).c) Artisanal shrimp catchesThe number of artisanal fishing boats was provided by Ssentongo et al. (1986) for the period between 1971 and 1984, and the number of full time artisanal fishers was given in FDF (2008). The latter are given for the entire country rather than by sector. Published studies do not contain information by sector either; this may be because local authors consider enumeration of boats and fisher numbers a ‘sociological’ study, while calculation of CPUE, etc., is ‘scientific’ and thus worth their while. From the total number of artisanal fishers given in FDF (2008), the number of artisanal boats in the country was estimated at about 45,200, assuming 6 fishers per boat (Uwe-Bassey 1988; Enin et al. 1991; Enin 1994). Assuming a 3.5 to 1 ratio between artisanal fishing and artisanal shrimping boats, there were about 35,200 artisanal fishing boats and about 10,000 artisanal shrimping boats in 2008-2010. We kept this ratio constant and disaggregated the total number of artisanal boats (see above) to fish and shrimp boats between 1979 and 1984. We also assumed that the number of artisanal boats in 1950 was 80% of that of 1971. We interpolated linearly the number of boats to complete the time series.An average CPUE of 75.9 kg∙boat-1∙day-1 (Enin et al. 1991) and an active number of fishing days of 200 (Enin 1994) allowed to estimate an annual CPUE of 15.18 t·boat-1 for 1991. We assumed this CPUE was 20% higher in 1950 and 5% lower in 2010 for two main reasons: first, the size and motorization rate of the fleet grew only slightly between 1950 and 1991; and second, over-exploitation should have resulted in declining catch per boat between 1991 and 2010. We multiplied the interpolated CPUE by the interpolated fishing effort and estimated total catches by the artisanal shrimp fleet.d) Artisanal fish catchA mean CPUE of 36 kg∙day-1 (Udolisa and Solarin 1979) and an average number of active fishing days of 160 (Uwe-Bassey 1988) allowed to estimate an annual CPUE of 5.76 t∙boat-1 for 1979. We applied the same method as for artisanal shrimp fisheries described above.e) Shrimp trawl discardsDuring their field investigation, Ayaji and Adetayo (1982) observed that fish discards from shrimp trawlers constituted about 43.7% of the total catch of the shrimp trawler in question. Thus, we computed the yearly quantity of discards as 43.7% of the annual total trawled shrimp landings as reported by the FDF.f) Subsistence catchesFish is a staple in the diets of Nigerian fishers; consequently, the total amount of fish they consumed is likely to be higher than the national mean. Nevertheless, we assumed a per capita fish consumption of 9.7 kg∙person-1∙year-1 (Ekpo and Etim 1989; FDF 2008), which is the national average. We assumed this consumption rate was 20% higher in 1950 compared to the 2000s and interpolated linearly. We also assumed an average fishing family size of six and an average six crew per boat (Uwe-Bassey 1988; Enin et al. 1991; Enin 1994). The product of these figures, jointly with our estimated total number of artisanal boats gave an estimate of the total unreported weight of fish consumed by the fishers (crews) and their families. Thus, here we only estimate take-home catch by artisanal fisheres as subsistence catches, and do not account for the potentially large number of non-fishers that may also enage in subsistence fishing.g) Illegal foreign fish and shrimp catchesAccording to Falaye (2008), about 30 million dollars’ worth of fish is taken from the Nigerian marine waters by illegal activities of foreign fishing vessels. First, we assumed that two-third of this value (i.e., 20 million dollars) is finfish. From the market survey that we conducted, we estimated a mean price of 3.8 USD per kg in Nigerian coastal markets, and estimated the corresponding tonnage at 5,263 t·year-1, which represented 2% of reported catch data. We applied this rate to total reported catches between 1950 and 2010. It is worth noting that such catches were ‘unregulated’ rather than illegal before the 1982 declaration of the EEZ by Nigeria.From the 10 million dollars assumed in term of illegal shrimp catch (see above), and a mean price of 15 USD∙kg-1, we inferred a shrimp catch of 667 t∙year-1, which represented 0.22% of total reported catches. We then applied the same method as for illegal fish catches (see above).Nigeria - Etim et al. 69resultsIndustrial catchesIndustrial catches increased from around 1,800 t∙year-1 in the early 1950s to a peak of 200,000 t in 2003 (Figure 2). Industrial catches decreased after that to 141,000 t in 2010 (Figure 2) due to over-exploitation and increasing piracy, which led to the decrease in the number of industrial vessels. The sharp rise, which happened in 1980, is attributed to the creation of the Nigerian Shrimping Company and the expansion of the Nigerian economy as a consequence of the increase in crude oil prices.Artisanal catchesArtisanal catches averaged around 32,000 t∙year-1 in the early 1950s, and increased gradually to 36,000 t in 1970 (Figure 3). Artisanal catches increased rapidly in the early 1970s, which coincided with the onset of the rapid expansion in Nigerian economy as a consequence of the jump in crude oil prices. Artisanal catches increased with the increase in the number of boats and reached a plateau of around 340,000 t∙year-1 in the mid-2000s (Figure 3).Subsistence catchesSubsistence catches followed the same pattern as artisanal catches (Figure 4). Subsistence catches averaged around 1,200 t∙year-1 in the early 1950s, and gradually increased to around 2,500 t in 1974 (Figure 4). Thereafer, they increased to plateau at of over 13,200 t∙year-1 in the mid 2000s (Figure 4).DiscardsDiscards increased from around 232 t∙year-1 in the early 1950s to a first peak of 2,200 t in 1990, declined to 1,400 t in 1993 before increasing again to a plateau of 3,100 t in 2001 (Figure 5).Illegal foreign catchesIllegal catches (considered ‘unregulated’ before the declaration of the Nigerian EEZ in 1982) increased from 400 t in 1950 to a pleateau of around 3,000 t∙year-1 between the 1970s and the mid-1980s. Illegal catches increased to a peak of 6,000 t∙year-1 in the late 1990s, near which they remained (Figure 6).Figure 2.  Reconstructed industrial catches from the EEZ of Nigeria, 1950-2010.Figure 3.  Total reconstructed artisanal catches from the EEZ of Nigeria, 1950-2010.Figure 4.  Total reconstructed subsistence catches from the EEZ of Nigeria, 1950-2010. 70Total reconstructed catchesTotal reconstructed domestic catches were estimated at around 34,000 t in 1950 compared to 22,000 t reported to the FAO on behalf of Nigeria (Figure 7a). Catches increased rapidly in the early 1970s to around 150,000 t∙year-1 due to (a) the expansion of industrial fisheries, notably those that targeted shrimp and (b) the distant water fishing fleet. Catches increased to a peak of 540,000 t in 2005 compared to 285,000 t reported to the FAO before declining to 490,000 t in 2010. Overall total reconstructed catches were twice as high as the data supplied to the FAO; however under-reporting was higher in the late time periods, which might be due to increasing piracy.Taxonomically, around 70 taxa are caught within the Nigeria waters; however, catches include mainly croakers (15.4%), sardinellas (11.2%), Bonga shad (6.9%) and scianids (4.1%) (Figure 7b).discussionA large part of the catches from the Nigerian marine waters is either poorly accounted for or not accounted for at all. For example, there are at least four categories of fisheries data which are not mentioned at all in the FDF and FAO official statistics, which resulted in our reconstructed catch being twice as high as the catch data supplied to the FAO.Three historical events in Nigeria translated in a most direct way into downward trends in domestic fish production in the country. These are activities of militants and pirates in the Niger Delta, government economic reform programmes (e.g., the Structural Adjustment Programme, or SAP) and the Nigerian Civil War (1967-1970).The destructive and violent activities of the pirates in the Niger Delta region (eastern part of Nigeria) exerted a negative impact on fish production in the country. Over a period spanning many years, these militants had consistently and persistently carried out attacks on oil installations mostly in the Niger Delta area with the aim of ensuring that a greater part of Nigeria’s petroleum oil revenue goes to the impoverished people of the Niger Delta region from whose lands the oil was taken. The militants engaged in activities like sabotage, theft, property destructions, arson, bombings, guerrilla warfare and kidnapping. The decrease in fish landings, caused by the activities of the militants in the Niger Delta, reached what the FDF (2008) described as an “alarming situation” which resulted in the decline of the number of industrial vessels operating in Nigeria (Perouse de Montclos 2012).Another event was the implementation of the IMF/World Bank-supported SAP in July 1986. The main components of the SAP entailed the devaluation of the local currency, removal of subsidies on petroleum, liberalization of trade and elimination of price controls (e.g., by scrapping commodity marketing boards), deregulation of bank interest rates and the privatization of government enterprises. The negative impacts of these activities precipitated an uncontrolled inflation, especially as a consequence of currency devaluation. The inflationary rise in cost of fishing inputs (gears, crafts, etc.) together with the increase in pump price of petrol due to subsidy removal had meant that most fishers could not buy new crafts and gears. They also could not service the old ones, nor replace their worn out gears and vessels. This resulted in the decrease in distant water fishing activities by Nigeria.According to Ekpo and Etim (1989), Nigeria’s government fisheries policy objectives could be summarized as follows: (a) increasing domestic fish production, (b) earning foreign exchange through fish exports, (c) developing fishery-based industries, (d) rational management and conservation of the fisheries resources, (e) encouraging local manufacturing of fish products, (f) providing employment, (g) increasing income of local fishers. Measures put in place by government for the realization of these objectives can be grouped into (i) institutional development policy, (ii) direct production policy, (iii) credit policy, (iv) research policy, (v) infrastructure policy, (vi) input provision policy, and (vii) allocation policy. The Federal Government of Nigeria has difficulties implementing these policies, which is not surprising, as several of them are mutually incompatible.Figure 5.  Total reconstructed shrimp trawl discards from the EEZ of Nigeria, 1950-2010.Figure 6.  Total reconstructed illegal catches from the EEZ of Nigeria, 1950-2010.Nigeria - Etim et al. 71Institutional development policy is vital in enhancing domestic fish catches and ensuring their sustainability. Apart from the Nigerian Institute for Oceanography and Marine Research, which is a federal government agency mandated to conducted research in marine sciences, there is one federal and one state-owned university in each of the maritime states, all of which have a mandate to focus on marine science and fisheries research. However, these institutions are not well funded.Between 2004 and 2007, there was no budgetary allocation for capital projects in the fisheries subsector by the federal government. The allocation declined from 1.16 billion Naira in 2010 to 750 million Naira in 2012 (1 NGN = 0.006 USD). As observed by Ekpo and Etim (1989) Federal government budgetary allocation to capital projects in fisheries had always been inadequate even in the late 1970s and early 1980s.The federal government no longer extend credit facilities to fishers because of the policy of discontinuing direct financing of agricultural production. Artisanal fishers lack the necessary collateral to obtain credit from commercial banks. Only owners of commercial trawlers are able to access credit facilities from banks.Except with hook and line and other highly selective gears, by-catch is a natural moiety in fisheries. In some cases, a part or all of the by-catch are thrown back to the sea as discards (Ayaji and Adetayo 1982; Ambrose 2005). In many cases, all the by-catches are sold either separately or as part of the original catch (Löwenberg and Künzel 1991). By-catch is a general problem of shrimp fisheries. Ayaji and Adetayo (1982) observed in commercial shrimp trawlers off Lagos coast (western part of Nigeria) that fish “shovelled overboard measured 18.0 cm or less in total length” and “amounted to 43.68% of the total catch” of the trawler in question. Ambrose (2005) demonstrated that an experimental by-catch reduction device was able to exclude 61% (belonging to length class 4 – 10 cm) and retain 39% (belonging to length class 11–30 cm). Enin et al. (1991) and Enin (1994) noted in artisanal shrimp fisheries that by-catch fish ( 10 cm) and squids constituted approximately 8.5% by weight and 4.7% by number in the sample. These are small compared to 43.7% (Ayaji and Adetayo 1982) and 61% (Ambrose 2005) in trawl shrimp fisheries. Thus, the problem of by-catch in artisanal shrimp fisheries is not as serious as in the trawl fisheries. In Nigeria, by-catch from the artisanal shrimp fisheries is not discarded; all the catches (the targeted shrimps and the fish by-catch) are smoked-dried together and marketed as “crayfish”. Nowadays and especially in the eastern part of Nigeria, itinerant buyers use speed boats to follow shrimp trawlers and buy from them whatever would have been discarded. According to E.Ambrose (pers. comm.), who is the pioneer researcher in TED (Turtle Exclusion Device) and BRD (By-catch Reduction Device) in Nigerian marine waters, now “all trawlers carry TED and BRD”, but “at sea, 10% use them.” Definitely, this is an improvement in the Nigerian fisheries management. Nevertheless, there is still need for a more stringent enforcement of the law.There are many, though unsubstantiated reports on the illegal activities of foreign vessels in Nigerian waters. Some vessels suspected to belong to China, Korea, Italy, Greece, Russia, Japan, Cameroon and Togo fish in Nigerian waters undeterred (Ganapathiraju and Pitcher 2006; Falaye 2008; Pauly et al. 2014). These illegal activities take advantage of the poor monitoring and “lax policing situation (in Nigeria) and land shrimp, lobster, and snapper (among other valuable species) worth over $10,000 per boat per day” or about “30 million US dollars per annum” (Falaye 2008). This is a huge amount compared to about 20 million US dollars per annum which is the amount realized from shrimp as the major fisheries export from Nigeria. In our interview with the Deputy Director of Fisheries in charge of monitoring and surveillance, we learnt that the lack of effective monitoring and policing is because the department has no vessels and fast boats of its own, and is expected to depend on the goodwill of the Nigerian Navy for vessels. Consequently, the department has not been successful in apprehending vessels involved in illegal activities. As pointed out by Falaye (2008), illegal activities are not restricted to Nigeria alone but “continue unabated and unchallenged” throughout the West African region “due to the lack of an adequate monitoring, control and surveillance structure with regards (sic) to both equipment and management systems.”It remains to consider the state of exploitation of the marine fisheries resources in Nigeria vis-à-vis its potential yield. Ajayi and Talabi (1984) gave the potential yield of the Nigerian marine fish resources between 70,000 and 90,000 tonnes, while Ssentongo et al. (1986) put the maximum potential yield at “about or slightly less than 150,000 t.” Within this context and with a total annual catch of about 390,686 tonnes, the Nigerian marine fisheries resource is overexploited. This is not a new finding: several authors e.g. Nsentip (1983), Moses (1989), Ajayi (1991), Ganapathiraju and Pitcher (2006) and Falaye (2008) had already pointed this out previously.0100200300400500600Catch ( t x 103)IndustrialFAOSubsistenceArtisanalDiscardsDWF catchesa)01002003004005006001950 1960 1970 1980 1990 2000 2010Catch (t x 103 )YearPseudotolithus spp.CynoglossidaeCarangidaeAriidaespp.SciaenidaeEthmalosa fimbriataSardinella spp.OthersSharks, rays and chimaerasb)SphyraenaFigure 7.  Total reconstructed domestic by Nigeria, by a) sector, with data as reported by FAO overlaid as line graph; and b) taxon, 1950-2010. Distant water fleet (DWF) catches refer to those catches reported to the FAO by Nigeria but that were taken from outside Nigeria within the area comprised between Benin and Cameroon. DWF catches are not included in the taxonomic breakdown. 72The challenges this posed are acknowledged by the new Director of the Nigerian Institute for Oceanograpy and Marine Research (NIOMR) Dr. Gbola Akande, who wrote (pers. comm to D.P.) that NIOMR “is also very much into [food security] research nowadays [which is understandable] when you consider the need for the Government to feed a population close to 170 million people. Fish food security is our priority especially in the artisanal fisheries and aquaculture. The industrial fisheries of course are also in the reckoning, but the first two contributes far more to our national fish production than the industrial fisheries. The justification for procuring the new vessel, RV Bayagbona is essentially to tap into the resources of the deep waters in our 200 mile Exclusive Economic Zone. Our inshore coastal water is currently under pressures with well over 150 fishing/shrimping trawlers struggling to catch from an environment already depleted due to overfishing over the years.”acknoWleGementsThe work of DB and DP was supported by the Sea Around Us, a collaboration supported by The Pew Charitable Trusts and the Paul G. Allen Family Foundation.reFerencesAjayi TO (1991) Highlights of achievements in the last 30 years by the Nigerian Institute for Oceanography and Marine Research and its parent research division of the Federal Department of Fisheries, Lagos, 1960-1990. Nigerian Institute for Oceanography and Marine Research (NIOMR), Lagos, Nigeria. 23 p.Ajayi TO and Talabi SO (1984) The potential yield and strategies for optimum utilization of the fisheries resources of Nigeria. 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African Journal of Marine Science 32(2): 197-206.Löwenberg U and Künzel T (1991) Investigations on the trawl fishery in the Cross River estuary, Nigeria. Journal of Applied Ichthyology 7: 44-53.Moses BS (1989) The status of artisanal fisheries and fish resources conservation in south eastern Nigeria. Nigerian Society for Biological Conservation, University of Cross River State, Uyo, Nigeria. 22 p.Nsentip UN (1983) A review of the commercially exploited marine fishery resources in Nigeria. pp. 35-57 In Anon. (ed.), Proceedings of the Second Annual Conference of the Fisheries Society of Nigeria. Fisheries Society of Nigeria (FISON), Calabar, Nigeria, 25-27th January, 1983Okon EE (2010) Integrating climate change into conservation and management of marine fisheries resources: A study of the sustainable development of marine fisheries in Nigeria. PhD thesis, Aberystwyth University, Department of Law, Aberystwyth, United Kingdom. 308 p.Nigeria - Etim et al. 73Panayotou T (1982) Management concept for small scale fisheries: economic and social aspects. FAO Fisheries Technical Paper 228, Rome. 53 p.Pauly D, Belhabib D, Blomeyer R, Cheung WWL, Cisneros-Montemayor A, Copeland D, Harper S, Lam V, Mai Y, Le Manach F, Österblom H, Mok KM, van der Meer L, Sanz A, Shon S, Sumaila UR, Swartz W, Watson R, Zhai Y and Zeller D (2014) China’s distant water fisheries in the 21st century. Fish and Fisheries 15: 474-488.Perouse de Montclos MA (2012) Maritime piracy in Nigeria: Old wine in new bottles? Studies in Conflict & Terrorism 35: 531-541.Ssentongo GW, Ajayi T and Ukpe ET (1983) Report on a resource appraisal of the artisanal and inshore fisheries of Nigeria. FAO/UNDP/FNDP/NIR/77/001, Rome. 43 p.Ssentongo GW, Ukpe ET and Ajayi TO (1986) Marine fishery resources of Nigeria: a review of exploited fish stocks. CECAF Series 86/40, Food and Agriculture Organization of the United Nations (FAO), Rome. 62 p.Udolisa REK and Solarin BB (1979) Design characteristics of cast nets and gillnets in Lagos Lagoon, Nigeria. Nigerian Institute of Oceanography and Marine Research Occasional Paper 31: 24.Uwe-Bassey BU (1988) The catch structure of the artisanal gillnet fishery of the lower Cross River. MSc thesis, University of Calabar, Calabar, Nigeria. 105 p.Wielgus J, Zeller D, Caicedo-Herrera D and Sumaila UR (2010) Estimation of fisheries removals and primary economic impact of the small-scale and industrial marine fisheries in Colombia. Marine Policy 34: 506-513.Zeller D, Booth S, Davis G and Pauly D (2007) Re-estimation of small-scale fishery catches for U.S. flag-associated island areas in the western Pacific: the last 50 years. Fishery Bulletin 105(2): 266-277.Zeller D and Pauly D, editors (2007) Reconstruction of marine fisheries catches for key countries and regions (1950-2005). Fisheries Centre Research Reports 15(2), University of British Columbia Fisheries Centre, Vancouver. 163 p. 74Appendix Table A1.   FAO landings vs. reconstructed total catch (in tonnes), and catch by sector with discards shown separately for Nigeria, 1950-2010.Year FAO landings Reconstructed total catch Industrial Artisanal Subsistence Discards1950 22,000 34,400 1,359 31,700 1,170 2181951 22,000 34,900 1,575 31,900 1,180 2251952 22,000 35,300 1,791 32,100 1,200 2321953 22,000 35,700 2,008 32,300 1,210 2391954 25,000 36,200 2,224 32,500 1,220 2471955 25,000 36,600 2,440 32,700 1,230 2541956 25,000 37,000 2,656 32,900 1,240 2611957 25,000 37,500 2,873 33,100 1,250 2681958 25,000 37,900 3,089 33,300 1,260 2751959 25,000 38,300 3,305 33,500 1,260 2831960 33,500 38,700 3,521 33,600 1,270 2901961 30,000 39,100 3,738 33,800 1,280 2971962 35,200 39,600 3,954 34,000 1,290 3601963 36,200 40,100 4,170 34,200 1,300 4231964 41,345 41,800 4,535 35,500 1,310 4861965 41,742 42,300 4,758 35,700 1,320 5491966 42,136 42,700 4,981 35,800 1,330 5591967 42,525 43,100 5,204 36,000 1,340 5701968 42,911 43,500 5,427 36,100 1,350 5811969 43,292 43,900 5,650 36,300 1,360 5921970 43,670 44,300 5,873 36,400 1,370 6031971 44,044 44,700 6,096 36,600 1,370 6891972 55,144 55,900 6,969 46,400 1,750 7751973 63,087 63,900 7,478 53,600 2,020 8611974 79,229 80,200 9,483 67,200 2,540 9471975 80,987 82,000 8,130 70,200 2,660 1,0331976 111,281 112,400 8,271 99,200 3,770 1,1191977 116,742 117,900 10,133 102,700 3,910 1,2051978 101,007 102,300 13,150 84,600 3,230 1,2911979 118,817 120,200 13,519 101,400 3,880 1,3771980 127,279 128,700 13,490 109,600 4,190 1,4631981 148,317 181,200 24,221 149,600 5,920 1,5321982 154,066 199,300 35,412 156,100 6,180 1,6001983 152,119 214,500 46,212 160,200 6,340 1,6691984 150,062 226,800 57,012 161,600 6,390 1,7381985 154,464 246,500 67,474 170,500 6,740 1,8071986 161,243 266,200 77,936 179,300 7,080 1,8761987 155,079 285,800 88,398 188,000 7,420 1,9451988 167,951 305,300 98,860 196,700 7,760 2,0141989 185,019 324,800 109,322 205,300 8,100 2,0831990 217,365 344,200 119,785 213,900 8,430 2,1521991 174,421 363,300 130,247 222,400 8,770 1,9061992 208,046 385,300 143,516 231,100 9,100 1,6601993 142,783 402,200 151,696 239,700 9,420 1,4141994 162,403 419,600 159,877 248,300 9,750 1,6191995 231,579 436,800 168,057 256,900 10,070 1,8251996 248,472 449,400 171,622 265,400 10,390 2,0311997 294,279 462,000 175,188 273,900 10,710 2,2371998 324,004 474,600 178,753 282,300 11,020 2,4421999 316,235 487,100 182,318 290,800 11,330 2,6482000 309,063 499,500 185,884 299,100 11,640 2,8542001 297,971 511,900 189,449 307,500 11,950 3,0602002 293,814 524,100 193,015 315,800 12,250 3,0642003 300,194 536,200 196,580 324,000 12,560 3,0682004 282,987 538,300 190,095 332,300 12,860 3,0722005 285,131 540,300 183,610 340,500 13,150 3,0762006 328,928 533,100 177,125 339,700 13,150 3,0812007 303,313 525,900 170,640 339,000 13,150 3,0852008 296,955 518,700 164,132 338,300 13,150 3,0892009 312,439 504,800 151,025 337,600 13,150 3,0932010 323,599 491,000 137,917 336,800 13,150 3,093Nigeria - Etim et al. 75Appendix Table A2. Reconstructed total catch (in tonnes) by major taxonomic categories for Nigeria, 1950-2010. ‘Others’ contain 64 additional taxonomic groups.Year Pseudotolithus spp.Sardinella spp.Ethmalosa fimbriataSciaenidae Sphyraena spp.Ariidae Sharks or rays and chimaerasCynoglossidae Carangidae Others1950 4,610 0 1,750 1,570 3,390 11 1,520 2,340 1,070 18,1001951 4,680 0 1,750 1,620 3,390 14 1,520 2,340 1,100 18,4001952 4,740 0 1,750 1,660 3,390 17 1,520 2,340 1,140 18,7001953 4,810 0 1,750 1,710 3,390 20 1,520 2,350 1,170 19,0001954 5,450 0 1,750 1,380 3,850 18 1,750 2,690 940 18,3001955 5,510 0 1,750 1,430 3,850 21 1,750 2,690 970 18,6001956 5,570 0 1,750 1,470 3,850 24 1,750 2,700 1,000 18,9001957 5,630 0 1,750 1,520 3,850 27 1,750 2,700 1,030 19,2001958 5,700 0 1,750 1,560 3,850 30 1,750 2,700 1,060 19,5001959 5,770 0 1,750 1,600 3,850 33 1,750 2,700 1,090 19,8001960 6,920 0 2,690 610 5,150 11 2,340 3,510 420 17,1001961 6,520 0 2,350 1,080 4,580 24 2,110 3,180 740 18,6001962 7,230 0 2,690 500 5,380 9 2,460 3,750 340 17,2001963 7,430 0 2,690 430 5,500 7 2,580 3,870 290 17,3001964 8,150 0 2,860 0 6,250 0 2,860 4,340 0 17,4001965 8,280 0 2,900 0 6,320 0 2,900 4,350 0 17,5001966 8,380 0 2,960 0 6,410 0 2,960 4,440 0 17,6001967 8,480 0 2,980 0 6,480 0 2,980 4,470 0 17,7001968 8,570 0 3,010 0 6,540 0 3,010 4,510 0 17,9001969 8,660 0 3,080 0 6,570 0 3,080 4,580 0 17,9001970 6,180 0 3,090 0 6,360 247 2,960 4,320 0 21,1001971 8,890 0 2,250 0 4,920 1,093 1,740 3,190 0 22,7001972 9,120 0 3,060 0 6,730 1,368 2,370 4,340 0 28,9001973 10,010 0 3,460 0 7,610 1,502 2,680 4,910 0 33,8001974 12,630 0 4,500 0 9,850 1,895 3,530 6,380 0 41,4001975 12,870 0 4,630 0 10,140 1,931 3,700 6,570 0 42,2001976 17,400 0 4,870 0 12,490 2,610 13,690 11,100 0 50,2001977 18,130 0 5,200 0 13,350 2,719 14,650 10,740 0 53,2001978 15,520 0 4,540 0 11,710 2,328 12,730 9,530 0 45,9001979 17,840 0 5,380 0 13,810 2,676 15,140 12,270 0 53,1001980 20,150 0 25,750 0 10,040 3,022 20,150 6,620 0 43,0001981 26,230 0 30,850 4,550 15,860 3,625 11,690 8,370 2,840 77,2001982 28,730 0 30,460 6,000 16,280 4,898 13,950 8,630 3,740 86,6001983 32,740 0 34,900 7,930 11,610 629 13,960 12,530 4,950 95,2001984 36,640 0 34,080 9,330 6,120 9,681 14,770 13,560 5,820 96,8001985 55,330 0 41,680 10,880 4,380 1,641 16,990 8,520 6,790 100,3001986 54,280 5,130 30,740 12,090 2,490 1,873 13,190 9,220 7,540 129,6001987 39,070 5,060 52,110 14,710 1,440 3,464 12,890 6,570 9,170 141,3001988 54,520 5,000 51,490 15,150 1,420 3,612 12,740 6,480 9,450 145,5001989 70,230 4,600 55,290 15,150 4,020 3,762 3,830 10,920 9,450 147,6001990 58,470 16,200 20,350 13,570 4,160 1,730 7,530 8,440 8,460 205,3001991 70,860 83,090 13,690 19,810 3,130 2,733 3,920 7,110 12,360 146,6001992 70,230 54,810 42,530 18,280 4,510 8,140 7,200 3,640 11,410 164,6001993 85,480 28,520 26,600 26,440 5,370 3,937 5,130 1,070 16,490 203,2001994 90,190 29,050 28,850 26,040 5,670 11,541 6,690 1,040 16,250 204,2001995 71,810 89,650 17,640 20,760 3,790 17,853 3,280 2,300 12,950 196,8001996 75,530 115,810 5,260 20,420 4,030 17,402 4,850 1,660 12,740 191,7001997 60,810 104,400 30,050 17,190 5,590 17,575 4,100 1,570 10,720 210,0001998 59,330 107,370 33,970 15,530 8,630 14,403 7,410 2,140 9,690 216,1001999 64,430 92,520 20,510 17,620 11,610 21,324 8,580 4,370 10,990 235,1002000 68,590 94,380 20,500 19,650 12,600 20,152 8,730 8,400 12,260 234,3002001 78,200 72,150 22,190 22,080 12,750 22,404 8,480 7,930 13,780 252,0002002 78,280 65,090 24,090 23,820 12,150 26,557 7,880 8,400 14,860 263,0002003 80,690 70,640 22,580 24,490 11,430 22,609 8,940 7,420 15,280 272,2002004 85,060 77,810 16,050 27,000 10,080 25,994 6,930 6,930 16,840 265,6002005 78,490 70,380 21,130 27,530 10,490 26,142 9,990 9,570 17,180 269,4002006 65,160 79,250 24,610 22,350 12,150 28,259 8,620 8,810 13,940 269,9002007 66,330 72,170 23,750 24,590 13,250 22,766 10,070 9,950 15,340 267,7002008 66,130 69,610 24,260 24,770 12,750 25,621 9,590 8,210 15,450 262,3002009 53,670 73,570 25,520 22,050 14,620 22,308 11,670 6,960 13,760 260,7002010 43,350 73,330 26,850 19,680 16,780 20,518 14,420 8,970 12,280 254,800 76Cameroon - Belhabib and Pauly 77reconstructinG Fisheries catches For cameroon betWeen 1950 and 20101Dyhia Belhabib and Daniel PaulySea Around Us, Fisheries Centre, University of British Columbia 2202 Main Mall, Vancouver, BC, V6T 1Z4, Canadad.belhabib @fisheries.ubc.ca; d.pauly @fisheries.ubc.caabstractTotal catches for Cameroon, West Africa, are reconstructed to include sectors that were unaccounted or not properly accounted for, i.e., parts of the artisanal sector, the subsistence sector, bycatch and discards of the industrial sector, as well as illegal foreign fisheries. Reconstructed catches were estimated at 15,000 t in 1950 (compared to 12,000 t reported by the FAO on behalf of Cameroon), increased to a first peak of 89,300 t in 1977, declined to 61,900 t in 1986, then increased again to reach a peak of 115,000 t in 2003 (FAO: 62,800 t), before declining to 80,100 t in 2010 (around 15,100 t higher than the data supplied to the FAO). Overall, there are two main discrepancies between reconstructed data and the data supplied to the FAO: the former are 40% higher than the latter and the trend of the former is consistent with an over-exploitation status of marine fisheries resources of Cameroon, while the FAO data, which shows a pattern of increasing catches, are not. Artisanal fisheries, and thus fish species that are consumed locally, such as sardinellas and bonga shad make up for most catches. This further denotes the relatively important role fisheries play for food security in Cameroon.introductionCameroon is located in central West Africa, bordered by Nigeria from the north, the Central African Republic and Chad from the east, Gabon from the south and the Atlantic Ocean from the west (Figure 1). The geographic location of Cameroon, facing Bioko Island (Equatorial Guinea) from the West, makes its EEZ relatively small (14,693 km2), smaller than even the tiny EEZs of Benin and Togo. This, despite a relatively large continental shelf, limits economic maritime activities in the country.Cameroon was colonized by Germany, then, following WWI, by both the U.K. and France. In 1960, ‘French’ Cameroon obtained its independence, later joined by ‘British’ Cameroon. Thus, the Federal Republic of Cameroon was born, which, however, maintained strong political and economic ties with France. A civil war gave birth to a repressive dictatorship by the first president of Cameroon, which lasted 22 years, soon followed by a military coup in 1984. The first elections, marred by electoral fraud, were held in 1992 and 1997. Despite major apparent political improvements, there are disputes between the English-speaking southwest region of the country and the French speaking majority in the rest of Cameroon, a colonial legacy that continues to cause problems.Cameroon economy relies heavily on extractive industries (oil) and agriculture (cocoa, coffee and cotton). Despite good agricultural conditions and abundant oil reserves, which make Cameroon one of the best primary-commodity economies of Sub-Saharan Africa, political conflicts have contributed to decreasing the GDP by 60% from the mid-1980s to the mid-1990s. Recent reforms, notably in the agriculture and some industrial sectors, have contributed to increasing the GDP. However, many issues still hobble the country, and affect both the general population and the economy, notably major electricity deficits and limited access to safe drinking water (OECD 2007). These issues are amplified by high corruption and rampant abuse of human rights (OECD 2007), which increase the food insecurity of Cameroon’s population.1 Cite as: Belhabib, D. and Pauly, D. (2015) Reconstructing fisheries catches for Cameroon between 1950-2010. pp. 77-84. In: Belhabib, D. and Pauly, D. (eds). Fisheries catch reconstructions: West Africa, Part II. Fisheries Centre Research Reports vol.23(3). Fisheries Centre, University of British Columbia [ISSN 1198-6727].Figure 1.  Map of Cameroon and its Exclusive Economic Zone (EEZ). 78Fisheries in Cameroon play an important role as fish represents 25.5% of animal protein consumption (Anon. 2009). Moreover, artisanal fisheries alone generate over 119 Billion CFA (240 million USD) per year (Ngok et al. 2005). Surprisingly, despite this important role, the fisheries sector is neglected. Indeed, currently in Cameroon there is no data collection system for fisheries. “Existing statistics in the artisanal sector are just vague estimations and extrapolations and the actual volume of fish production in this sector is unknown” and “bycatch […] is not taken into account in the national statistics, due to lack of log books on vessels.” (ENVIREP-CAM 2011). This low monitoring performance is illustrated by the fact that artisanal catches (marine, continental and aquaculture) were reportedly unchanged from 1999 to 2010 (Nnana Noah 2010). The lack of knowledge of the fisheries sector performance and removals has resulted in a severe over-exploitation, documented since the mid-1980s, yet fishing effort has increased drastically since then (Djama and NNa Abo’o 1999). Here, we attempt to address this lack of knowledge by reconstructing catch data for Cameroon, based on a detailed analysis of the existing literature on Cameroon’s fisheries.methodsTotal and coastal populationTotal population of Cameroon was extracted from the World Bank database (www .worldbank.org) between 1960 and 2010 and completed using data from www .populstat.info. Coastal population data, i.e. rural population living within 5 km from the coast, for 1990, 2000 and 2010 were obtained from CIESIN (2012), which allowed estimating a percentage of 1.13% of Cameroon’s population as coastal. We assumed this percentage for 1950 and obtained the coastal population for the same year. We interpolated to fill in the gaps (Figure 2).Subsistence catchesLagoin and Salmon (1970) documented a survey-based estimate of fish consumption rate ranging between 30 and 48 kg·person-1·year-1, i.e. 39 kg·person-1 for 1961. In 1967, 3,048 t were caught and consumed by subsistence fishers. We assumed the consumption rate was constant between 1950 and 1961. We multiplied the consumption rate for 1950 by the coastal population estimated for 1950 and obtained a subsistence catch of 2,178 t. Similarly, we assumed the previous consumption rate from subsistence fishing declined by 70% in 2010, i.e. 11.7 kg·person-1 due to increasing fish availability from artisanal fisheries, and we multiplied this rate by the coastal population for 2010. We then interpolated between the previous estimates to complete the time series between 1950 and 2010.The catch composition of subsistence catches is given as a list with no further indication of the percentage (ENVIREP-CAM 2011): marbled swim crab (Callinectes marginatus), African ghost crab (Ocypoda ippeus), common cuttlefish (Sepia officinalis), sea snail (Mytilus tenuistriatus), oysters (Crassostrea gasar, Cypraecassis rufa), mudskipper (Periopthalmus hoelferi), African sicklefish (Drepana africana), groupers (Epinephelus spp.), Alexandria pompano (Alectis alexandrina), Blue runner (Caranx crysos), Atlantic bumper (Chloroscombrus chrysurus), round scad (Decapterus punctatus), bigeye scad (Selar crumenophthalmus), greater amberjack (Seriola dumerili), African moonfish (Selene dorsalis), pompano (Trachinotus ovatus), barracudas (Sphyraenidae), bigeye tuna (Thunnus obesus), West African Spanish mackerel (Scomberomorus tritor), Dasyatidae, brown ray (Raja miraletus), and flathead grey mullet (Mugil cephalus). In the absence of detailed information, we allocated the same percentage to every taxon.Artisanal catchesThere is no licensing system for artisanal fisheries in Cameroon despite the high percentage (85%) of foreign artisanal fishers (ENVIREP-CAM 2011). This also applies to monitoring of artisanal catches, which is virtually absent (Kamgaing 2009). Estimates of artisanal catch were available through different literature sources for 1967 and 1970 (Laure 1972), 1980 (Ssentongo and Njock 1987), 1987 (Seck 1987), 1990 (Bamou 1997), 2003 (Nnana Noah 2010), 2009 (ENVIREP-CAM 2011) and 2012 (Anon. 2013). We assumed artisanal catches in 1950 were 20% lower than the catch in 1967, given the documented increasing pattern of catches (Lagoin and Salmon 1970). We then interpolated to fill in the gaps between 1950 and 2010. We summed artisanal and industrial landings (see below for industrial landings), and adjusted artisanal landings upwards whenever FAO data were higher than the sum, based on the assumption that the difference is due to under-reporting of artisanal catches.To disaggregate catches taxonomically, we assumed the same species composition as in the landing statistics presented by FAO on behalf of Cameroon, and disaggregated the “marine fishes nei” group using the species list provided above (see subsistence catches section).0Figure 2.  Cameroon’s rural population living within a range of 5 km from the coast, 1950-2010.Cameroon - Belhabib and Pauly 79Industrial catchesWhile industrial fishing in Cameroon began with a failed attempt by a German company in Douala in 1912, it was only in 1951 that first successful industrial fishing operation was conducted (Laure 1972). Industrial fishing in Cameroon is carried out by nationally flagged vessels, mostly targeting demersal resources (Anon. 2010). The main highlights of the industrial fisheries of Cameroon are the shrinking of fishing area when Gabon declared national waters in 1970 (Laure 1972), along with a significant increase in vessel efficiency and size since the 1950s (ENVIREP-CAM 2011) to counter the effects of over-exploitation. We assumed the contribution of catches from Gabon increased linearly from 30% in 1960 to 80% in 1970 before collapsing to zero in 1973. Industrial catch data are collected from Douala port by the National Institute of Statistics (Institut national de la statistique du Cameroun). These data presented on the website of the organization are incomplete.2 Furthermore, they do not include catches that are exported at sea, landed in Nigeria or those landed in Cameroon’s military port of Tiko (ENVIREP-CAM 2011).We interpolated landings data provided by different literature sources between 1950 and 2010 (Laure 1972; Ssentongo and Njock 1987; Bamou 1997; Djama and NNa Abo’o 1999; Nnana Noah 2010; ENVIREP-CAM 2011). These data serve as a baseline for estimating the under-reported component.For every kg of shrimp caught by shrimp trawlers there is around 8 kg of bycatch (46% of fish for 6% of shrimp) (ENVIREP-CAM 2011). Although shrimp fishery bycatch are not reported, we herein conservatively assume that only half of the fish bycatch is not reported, i.e., 4 kg of fish for every 1 kg of shrimp. This approach is very conservative since it assumes all shrimp catch by shrimp trawler is reported and all fish catch by demersal trawlers is reported. Similarly, crab catches represent 1.33 times the shrimp catch. We applied this rate to shrimp catches and estimated unreported crab catches.The demersal fleet of Cameroon comprises Chinese reflagged vessels since the early 2000s, 11 vessels were licenced in 2003 and 8 vessels between 2006 and 2007, which we conservatively assumed constant between then and 2010 (Pauly et al. 2013). We estimated the CPUE of demersal boats operating in Cameroon between 2000 and 2010 based on the estimated catch (all trawlers together) and the number of fishing boats provided by the literature (Nnana Noah 2010; ENVIREP-CAM 2011), then we multiplied these by the interpolated number of Chinese vessels to estimate that part of the demersal catch which ownership could be allocated to China. We used data in Lagoin and Salmon (1970) to taxonomically disaggregate the unreported component of industrial catches (Table 1).DiscardsAround 25% of shrimp trawl catches are discarded (ENVIREP-CAM 2011), i.e. 33% of landings. Herein, we multiplied the estimated industrial shrimp catches by 33% to estimate discards from 1950 to 2010. For demersal trawl, Kelleher (2005) estimated that 0.6% of demersal trawl catches were discarded. Thus demersal trawl discards range between 0.6% and 33%, i.e. 16.8%. We applied this rate to the estimated demersal trawl landings between 1950 and 2010. We assumed the same species disaggregation than for bycatch above.Illegal catchesAlthough Cameroon declared an EEZ as late as 2000, there were already “illegal” fishing vessels in 1989, when Cameroon arrested 9 vessels fishing illegally fishing within their waters (ENVIREP-CAM 2011). We assumed that  this number corresponded to the number of vessels fishing illegally in Cameroon for that year and multiplied it by a CPUE of 258 t·boat-1·year-1 obtained by dividing the total legal industrial (demersal trawl) catch (9,020 t·year-1) by the number of legal boats for the same year, i.e. 35 (Bamou 1997). Chinese illegal vessels caught an estimated 9,500 t in 2009 (Pauly et al. 2013). We interpolated to fill in the gaps.As for the nationality of illegal fishing vessels, we relied upon the profile of illegal fleets from the country that is immediately adjacent to Cameroon, i.e., Equatorial Guinea’s Bioko Island. In Equatorial Guinea, illegal catches were taken by Russian fleets between 1980 and 1989 and Chinese fleet between 1985 and 2010 (Belhabib et al. 2014). We assumed proportionality and applied the disaggregation to illegal catches from Cameroon waters. We assumed the same species disaggregation than for domestic industrial fisheries above.2  http://www.statistics-cameroon.org/manager.php?id=9&id2=53&link=6 Table 1.   Composition of the catch of Cameroon’s industrial fisheries (Lagoin and Salmon 1970).Common name Scientific name %Bigeye grunt Brachydeuterus auritus 40.5Croaker Pseudotolithus spp.* 31.9Claroteid catfishes Chrysichthys spp. 6.0Giant African threadfin Polydactylus quadrifilis 5.1Tongue soles Cynoglossus spp. 4.6Rays Raja and other genera 2.7African sicklefish Drepane africana 2.3Shrimps Peneidae 1.8Canary drum Umbrina canariensis 1.1Marine fishes nei - 4.0* including P. senegalensis and P. typus (see Djama 1988; Djama and Pitcher 1989)012341950 1960 1970 1980 1990 2000 2010Catch (t x 103)YearFigure 3.  Reconstructed subsistence catches from Cameroon, 1950-2010. 80resultsSmall scale catchesSubsistence catches increased from around 2,200 t in 1950 to 3,000 t in 1967 and then decreased to 2,600 t in 2010 (Figure 3).Estimated artisanal catches varied between 1950 and 2010, however with a distinct increasing pattern until the mid-2000s. Artisanal catches increased from 12,300 t in 1950 to a peak of 93,200 t in 2003, passing by periods of decline notably between 1958 and 1966 and between 1980 and 1987 dominated by political instability within the country (Figure 4). Catches declined to less than 59,300 t in 2010 (Figure 4).Industrial catchesEstimated industrial catches increased from 70 t in 1951 to a peak of around 39,000 t in 1971, declined rapidly between then and the early 1980s when the offshore fleet stopped operating in Gabon. Catches kept on declining, although less rapidly, to around 18,000 t in 2010. Chinese reflagged vessels caught less than 600 t in 2001, around 1,000 t in 2008 and less than 1,000 t in 2010 (Figure 5).DiscardsEstimated discards increased from around 10 t in 1951 to a peak of 7,900 t in 1977 following increasing industrial catches from Cameroon, then declined rapidly to 1,500 t in 2010 (Figure 6).Illegal catchesEstimated illegal catches (considered unregulated until 2000) increased from low levels in the mid-1980s to 2,300 t in 1989 to 9,500 t∙year-1 in the late 2000s. Illegal catches, as reconstructed here, were overwhelmingly taken by Chinese vessels, with the remainder taken by Russian vessels.Total catchesTotal domestic (and reflagged) catches were estimated at 14,500 t in 1950 compared to 12,000 t reported to the FAO. Catches increased to a first peak of 89,300 t in 1977, following agriculture development policy in Cameroon, and then declined to 61,900 t in 1986 marking a period of political instability in the country. Catches increased later to reach a peak of 115,000 t in 2003 compared to 62,800 t reported to the FAO, before declining to 80,000 t in 2010, around 15,000 t higher than the data supplied to the FAO (Figure 8a). There is also a net discrepancy in trends between the reconstructed data and the data supplied to the FAO. The reconstructed catches shown a steady declining pattern compared to the FAO data, which were relatively constant since the mid-2000s (Figure 8a).Overall, 68 taxa are caught within Cameroon waters (and caught in Gabon’s EEZ, but landed in Cameroon). The artisanal sector dominates with over 71% of total catches and industrial contributing 21% (Figure 8a). Catches include mainly bonga shad (25%) and a declining catch of sardinella (19%), which were previously the prime focus of the little attention Cameroonian fisheries biologists could afford to give to their marine resources (Djama et al. 1989a; 1989b; 1990).0204060801001950 1960 1970 1980 1990 2000 2010Catch (t x 103 )Year0102030401950 1960 1970 1980 1990 2000 2010Catch (t x 103 )YearCameroon EEZGabon EEZChina reflagged to CameroonUnreported024681950 1960 1970 1980 1990 2000 2010Catch (t x 103 )Year02468101950 1960 1970 1980 1990 2000 2010Catch (t x 103 )YearChinaRussiaFigure 4.  Reconstructed artisanal catches from Cameroon, 1950-2010.Figure 5.  Cameroon reconstructed industrial landings from Cameroon and Gabon EEZs by the domestic and reflagged fleets, 1950-2010. Catches from the Gabonese EEZ were taken by the real domestic fleet of Cameroon and landed in Cameroon.Figure 6.  Reconstructed discards from Cameroon, 1950-2010.Figure 7.  Reconstructed (unregulated and) illegal catches from the waters off Cameroon, 1950-2010.Cameroon - Belhabib and Pauly 81discussionTotal catches from the EEZ of Cameroon were marked by two main cycles; catches increased to a first peak in the 1970s following main agricultural reforms and development projects focusing on the primary sector industry, before decreasing rapidly following a period of instability; the second cycle was marked by the highest peak of catches which reached over 109,000 t·year-1 in the early 2000s, which were highly divergent with the data supplied to the FAO in amount and trend. Overall, reconstructed total catches were about 50% higher than the data supplied to the FAO. Although this discrepancy is not negligible, it is much smaller than the West African average.The taxonomic separation between the industrial and small-scale fisheries suggested by the catch composition data presented above probably does not occur in reality, as the over-exploitation of the small EEZ of Cameroon forces small-scale fishers to shift to estuarine species (such as estuarine shrimps) to maintain their catches. Thus, the decline in under-reporting, rather than being a sign of improvement, probably reflects decreasing catches. This is masked by a false increasing trend in the official data, likely due to improved monitoring.This study demonstrates that there is much room for improvement in Cameroon’s statistical system. For example, the registration system for artisanal fisheries is virtually inexistent. Thus, accounting for catches is merely occasional, and occurs mainly when fisheries scientist require data for their research. Also, landing operations and reporting by industrial fleets are hardly controlled. Ironically, a part of the (unreported) industrial catches are landed in the only military port of the country. Moreover, management of Cameroon fisheries is a recent initiative, as the first fishery policy document for Cameroon was formulated in 2011 (ENVIREP-CAM 2011).acknoWledGementsThis is a contribution from the Sea Around Us, a collaboration supported by The Pew Charitable Trusts and the Paul G. Allen Family Foundation.reFerencesAnon. (2009) Evaluation de l’impact de la hausse des prix des denrées alimentaires sur la securité alimentaire des ménages dans les villes de Bamenda, Douala, Maroua et Yaoundé au Cameroun. United Nations World Food Programme, Yaoundé. 70 p.Anon. (2010) Cameroun. ACPFish II. Available at: http://acpfish2-eu.org/index.php?page=cameroon-fr [Accessed: 12/08/2014].Anon. (2013) Pêche : Le Cameroun perd plus de 10 milliards par an. La Tribune du Citoyen, Yaoundé. Available at: http://tribune.tmp38.haisoft.net/index.php?option=com_content&view=article&id=447:peche—le-cameroun-perd-plus-de-10-milliards-par-an&catid=6:economie&Itemid=6 [Accessed: 12/08/2014].Bamou E (1997) Impact des incitations économiques sur la pêche au Cameroun: simulations à l’aide d’un MCEG Document de Travail 12, Réseau de Recherche sur les Politiques Industrielles en Afrique, Yaoundé. 70 p.Belhabib D, Hellebrandt D, Edward E and Pauly D (2015) Equatorial Guinea: a catch reconstruction (1950-2010). Fisheries Centre Working Paper #2015-71, University of British Columbia, Vancouver, 24 p.CIESIN (2012) National Aggregates of Geospatial Data Collection: Population, Landscape, and Climate Estimates, Version 3 (PLACE III). Center for International Earth Science Information Network (CIESIN)/Columbia University, Palisades, NY. Available at: http://sedac.ciesin.columbia.edu/data/set/nagdc-population-landscape-climate-estimates-v3. [Accessed: Nov 21, 2012].Djama T (1988) Estimation of growth parameters and mortality of longnect croaker (Pseudotolithus typus) in Cameroon. pp. 153-170 In Venema S, Möller-Christensen J and Pauly D (eds.), Contributions to tropical fisheries biology: papers by the participants of FAO/DANIDA follow-up training courses. Fisheries Report No. 389. FAO, Rome.Djama T, Gabche C and Njifonju O (1989a) Growth of Sardinella maderensis in the Lobe Estuary, Cameroon. Fishbyte – Newsletter of the Network of Tropical Fisheries Scientists 7(2): 8-10.020406080100120Catch (t x 103) IndustrialDiscardsSubsistencesupplied to FAOArtisanala)0204060801001201950 1960 1970 1980 1990 2000 2010Catch (t x 103)YearEthmalosa fimbriataSciaenidaeBrachydeuterus auritusOthersspp.b)SardinellaFigure 8.  Reconstructed total catches by a) sector as compared to FAO with solid line indicating data supplied to FAO, and b) taxonomic group from Cameroon’s EEZ, 1950-2010. ‘Others’ consist of 64 additional taxonomic categories. 82Djama T, Gabche C and Youmbi-Tienctheu J (1989b) Comparison of the growth of West African stocks of Sardinella maderensis with emphasis on Cameroon. Fishbyte – Newsletter of the Network of Tropical Fisheries Scientists 7(3): 13-14.Djama T, Nkumbe L and Ikome F (1990) Catch assessment of Sardinella maderensis in the Ocean Division, Cameroon. Fishbyte–Newsletter of the Network of Tropical Fisheries Scientists 18(1): 6-7.Djama T and NNa Abo’o P (1999) Aperçu de la pêche camerounaise. Cours ACP-EU sur la gestion des pêches et de la biodiversité, Dakar, Sénégal, du 12 au 23 Avril 1999. FishBase, Dakar. Available at: http://fishbase.us/Training/CountryReports/Dakar/Cameroon.htm [Accessed: 06/08/2014].Djama T and Pitcher T (1989) Comparative stock assessment of two sciaenid species, P. typus and P. senegalensis off Cameroon. Fisheries Research 7(111-125).ENVIREP-CAM (2011) Overview of Management and Exploitation of the Fisheries Resources of Cameroon, Central West Africa. Institut de Recherche Agricole pour le Développement, Yaoundé. 70 p.Kamgaing S (2009) Rapport Panorama I sur les statistiques agricoles et alimentaire. FAO, Rome. 78 p.Kelleher K (2005) Discards in world’s marine fisheries, an update. FAO Fisheries Technical Paper 470, FAO, Rome. 131 p.Lagoin Y and Salmon G (1970) Etude Technique et Economique comparée de la distribution du poisson de mer dans le pays de L’Afrique Centrale Atlantique1. Secretériat d’état aux affaires étrangères chargé de la coopération. 500 p.Laure J (1972) Vingt ans de pêche industrielle au Cameroun. Extrait de La Pêche Maritime 136, ORSTOM. 4 p.Ngok E, Ndjamen D and Dongmo Jiongo V (2005) Contribution économique et sociale de la pêche artisanale aux moyens d’existence durables et à la réduction de la pauvreté. Rome, Programme pour des Moyens d’Existence Durables dans la pêche (PMEDP), Yaounde. 41 p.Nnana Noah A (2010) Législation et réglementation de l’inspection des produits de la pêche au Cameroun : étude et propositions d’amélioration. EISMV, Douala. 200 p.OECD (2007) Cameroon. African Economic Outlook, OECD. 14 p.Pauly D, Belhabib D, Blomeyer R, Cheung WWWL, Cisneros-Montemayor AM, Copeland D, Harper S, Lam VWY, Mai Y, Le Manach F, Österblom H, Mok KM, van der Meer L, Sanz A, Shon S, Sumaila UR, Swartz W, Watson R, Zhai Y and Zeller D (2013) China’s distant-water fisheries in the 21st century. Fish and Fisheries: n/a-n/a.Seck P (1987) Catalogue des engins de pêche artisanale maritime du Cameroun. COPACE/PACE Series 87/43, FAO, Rome. Available at: http://www.fao.org/docrep/003/s5831f/S5831F00.htm#TOC [Accessed: 06/08/2014].Ssentongo G and Njock J (1987) Marine fishery resources of Cameroon: a review of exploited fish stocks. CECAF/ECAF Series 87/44, FAO, Rome. Available at: http://www.fao.org/docrep/003/s4639e/S4639E00.htm#TOC [Accessed: 07/08/2014].Cameroon - Belhabib and Pauly 83Appendix Table A1.  FAO landings vs. reconstructed total catch (in tonnes), and catch by sector with discards shown separately, for Cameroon, 1950-2010.Year FAO landing Reconstructed total catch Industrial Artisanal Subsistence Discards1950 12,000 14,500 0 12,300 2,180 01951 12,000 14,800 60 12,500 2,200 101952 12,000 15,000 120 12,700 2,220 201953 12,300 15,700 480 12,900 2,240 811954 19,100 21,600 1,500 17,600 2,260 2521955 23,800 26,500 2,500 21,300 2,280 4201956 25,400 28,200 2,750 22,700 2,300 4621957 26,500 29,300 2,553 23,900 2,320 4291958 30,600 33,400 2,610 28,000 2,340 4381959 20,200 23,000 2,860 17,300 2,360 4801960 20,734 23,500 2,254 18,500 2,390 3791961 25,195 28,000 2,514 22,700 2,410 4221962 26,047 29,100 3,302 22,700 2,510 5551963 26,240 29,600 4,276 22,000 2,620 7181964 26,031 29,500 4,308 21,700 2,730 7241965 21,772 25,300 4,187 17,600 2,830 7031966 21,419 25,200 5,058 16,400 2,940 8501967 21,562 25,400 4,720 16,800 3,050 7931968 22,063 27,100 4,653 18,600 3,040 7821969 22,728 32,800 6,621 21,800 3,030 1,3761970 22,876 43,300 12,259 25,000 3,020 3,0261971 22,076 52,400 16,751 28,000 3,010 4,6181972 25,242 58,300 18,728 31,000 3,000 5,5661973 37,600 74,700 30,184 34,000 2,990 7,4891974 35,736 75,800 28,991 37,000 2,980 6,8801975 46,280 78,000 28,512 40,000 2,970 6,5291976 50,397 82,800 29,973 43,000 2,960 6,8771977 50,167 89,300 32,407 46,000 2,950 7,9441978 48,867 80,600 23,648 49,000 2,940 4,9781979 61,214 79,300 20,358 52,000 2,930 3,9821980 61,045 79,100 17,878 55,000 2,920 3,2781981 59,761 75,200 17,264 51,800 2,910 3,2471982 63,012 72,500 17,486 48,600 2,900 3,5171983 57,277 68,200 16,584 45,400 2,890 3,3821984 55,299 66,500 17,073 42,800 2,880 3,7481985 53,969 63,700 15,563 41,900 2,870 3,2921986 51,981 61,900 15,434 40,400 2,860 3,2091987 50,637 62,600 16,659 39,500 2,850 3,5571988 50,800 67,000 17,683 42,700 2,840 3,7921989 48,830 78,300 18,633 52,800 2,830 3,9781990 48,743 87,800 18,238 63,000 2,820 3,7341991 47,319 89,200 17,626 65,300 2,810 3,4081992 49,975 88,300 15,346 67,600 2,800 2,4801993 42,258 90,800 15,577 70,000 2,790 2,4581994 52,021 93,800 16,133 72,300 2,780 2,5521995 64,132 96,700 16,640 74,600 2,770 2,6301996 63,530 99,200 16,876 76,900 2,760 2,6091997 62,001 101,200 16,760 79,300 2,750 2,3981998 61,801 103,700 17,007 81,600 2,740 2,3171999 60,001 108,900 19,252 83,900 2,730 2,9572000 57,110 109,400 17,408 86,200 2,720 2,9922001 68,531 111,400 17,649 88,600 2,710 2,4332002 65,135 113,300 17,541 90,900 2,700 2,1952003 62,802 115,400 17,288 93,200 2,690 2,2142004 64,001 110,600 20,192 84,900 2,680 2,8192005 67,346 96,500 15,681 76,600 2,660 1,5682006 62,233 85,300 13,263 68,300 2,650 1,0702007 64,233 86,400 21,234 60,000 2,640 2,5642008 64,501 85,500 19,391 61,400 2,630 2,0272009 65,001 86,100 18,672 62,900 2,620 1,8952010 65,001 80,100 16,758 59,300 2,610 1,461 84Appendix Table A2. Reconstructed total catch (in tonnes) by major taxonomic groups for Cameroon, 1950-2010. “Others” contain 64 additional taxonomic categories.Year Ethmalosa fimbriata Sardinella spp. Brachydeuterus auritus Sciaenidae Others1950 3,700 4,000 1,000 1,000 4,8001951 3,700 4,000 1,000 1,000 5,0701952 3,700 4,000 1,000 1,000 5,3401953 4,000 4,000 1,000 1,000 5,6601954 5,000 6,000 3,000 2,000 5,6101955 7,000 7,400 3,500 2,500 6,1001956 7,000 7,300 4,000 3,000 6,8601957 7,000 7,400 4,000 3,000 7,8501958 8,000 8,000 5,000 4,000 8,3801959 6,000 7,000 400 2,400 7,2501960 5,730 5,730 3,340 1,720 6,9701961 6,660 7,040 3,800 2,850 7,6801962 6,490 7,420 4,630 2,780 7,8001963 6,430 7,140 4,460 3,390 8,1601964 6,290 6,990 4,370 3,490 8,3401965 5,420 5,420 4,170 2,500 7,7901966 5,430 5,430 3,880 2,330 8,1401967 5,690 5,690 3,800 2,280 7,9401968 6,230 6,230 3,660 2,200 8,7501969 6,870 6,870 4,070 2,060 12,9601970 5,900 4,960 6,210 1,770 24,4601971 5,560 5,560 8,010 1,520 31,7201972 6,250 6,250 10,490 1,730 33,5801973 10,000 10,000 12,950 2,370 39,3401974 10,000 10,000 10,440 3,220 42,1901975 15,000 15,000 9,170 4,540 34,3101976 15,000 15,000 9,120 8,000 35,6901977 15,000 15,000 11,690 5,660 41,9401978 15,000 15,000 8,310 4,650 37,6001979 18,000 18,000 7,260 6,670 29,3301980 18,000 18,000 6,700 6,770 29,6001981 18,000 18,030 8,120 6,540 24,5201982 18,000 18,060 7,340 8,800 20,2701983 18,000 18,030 5,620 6,520 20,0301984 18,000 18,070 6,610 5,330 18,4901985 18,000 18,050 5,260 4,740 17,6001986 18,000 18,000 4,280 3,670 17,9501987 18,000 18,000 5,510 2,360 18,7101988 18,000 18,000 5,910 2,360 22,7001989 18,000 18,000 6,200 2,620 33,4501990 18,000 18,000 5,980 2,620 43,1801991 17,480 17,490 5,500 2,560 46,1301992 16,000 16,010 1,140 6,050 49,0801993 16,000 16,010 1,130 2,300 55,3501994 18,600 18,600 1,280 3,000 52,2801995 24,000 24,000 1,410 3,680 43,5701996 24,000 24,000 1,410 3,540 46,2401997 23,500 23,500 1,090 3,500 49,5801998 23,000 23,000 940 3,500 53,2101999 23,500 23,500 1,720 3,500 56,6302000 21,610 21,610 1,720 3,260 61,1602001 21,640 21,640 1,400 2,400 64,2702002 21,780 22,540 1,010 1,950 66,0402003 20,230 21,760 1,310 1,560 70,5502004 30,800 11,800 1,730 800 65,4602005 41,700 1,810 690 40 52,2902006 41,590 2,100 620 20 40,9502007 41,490 2,100 1,130 20 41,6902008 41,400 2,100 730 20 41,2302009 41,400 2,100 850 20 41,6902010 41,400 2,100 580 20 35,980Gabon - Belhabib 85Gabon Fisheries betWeen 1950 and 2010: a catch reconstruction1Dyhia BelhabibSea Around Us, Fisheries Centre, University of British Columbia, 2202 Main Mall, Vancouver, BC, V6T 1Z4, Canadad.belhabib @fisheries.ubc.caabstractFisheries removals from Gabon were reconstructed to include small-scale artisanal, subsistence catches and foreign industrial catches. Total removals from the Gabonese EEZ were estimated at less than 5,000 t in 1950, constituted mostly of small-scale catches, increased gradually to a peak of 242,000 t in 2000 and then decreased to 161,000 t in 2010. Domestic fisheries catches of Gabon were estimated to be 2.5 times the data reported by the FAO on behalf of Gabon; however, under-reporting decreased in the last few years, suggesting improvements in fisheries catch statistics. Artisanal fisheries represented 73% of total domestic removals from the Gabonese EEZ, which highlights the importance of small-scale fisheries to the local economy and domestic food security.introductionGabon (Figure 1), a country on the equator, is located in Sub-Saharan West Africa and is bordered by the Congo from the east and south, Cameroon and Equatorial Guinea from the north and the Atlantic Ocean from the west.Gabon obtained independence from France in 1960, and has been considered one of the most prosperous economies of West Africa, thanks to a number of factors including low population, forest resources and abundant oil resources. The economy of Gabon relies mostly on extractive activities, notably timber, manganese, uranium and oil. After the 1973-1974 spike in oil prices, the dependence of Gabon on the oil industry grew strongly, which made it one of the wealthiest countries in Africa. However, the sharp decline in oil prices in 1986 resulted in a decline in the GDP by 43% between 1985 and 1987, threatening the local economy, despite Gabon having the highest human development index of Africa. This led the Gabonese government to diversify the economy and invest in other extractive sectors such as fisheries (Ijiff 1991).As reported by the government, fisheries in Gabon include two main sectors. One is the industrial sector operated mainly by foreign vessels and joint ventures, including reflagged vessels often referred to as “domestic”, but essentially remaining mainly under foreign beneficial ownership (Ekouala 2013). The other is the artisanal sector, which is operated mainly by migrant fishers, a distinguishing feature of Gabonese fisheries (Haakonson 1992). Artisanal fisheries in Gabon are the main source of domestic fish landings, and are characterized by the “weakness of its production tool and the supremacy of migrant fishermen” (Bignouma 2011). The informal nature of this sectors makes it difficult to monitor in terms of fisheries statistics (Bignouma 2011).Total biomass estimates show an increase over time (Kébé et al. 1996); in contrast, catches show a decline. With over-exploitation being considered an issue, this does question the quality of data that are available officially. Furthermore, up to the mid-1990s, only 35% of the industrial fleet landed their catches in Libreville (Gabon); thus, official industrial statistics only account for that part of industrial catch that is landed in Libreville, and the remaining vessels’ effort and catch data are unknown (Kébé  et al. 1996). Moreover, non-commercial subsistence fisheries are not included in official statistics, and neither are discards and illegal fisheries.1 Cite as: Belhabib, D. (2015) Gabon fisheries between 1950-2010: a catch reconstruction. pp. 85-94. In: Belhabib, D. and Pauly, D. (eds). Fisheries catch reconstructions: West Africa, Part II. Fisheries Centre Research Reports vol.23(3). Fisheries Centre, University of British Columbia [ISSN 1198-6727].Figure 1.  Map of Gabon with Exclusive Economic Zone (EEZ). 86Catch data have to be improved in order to better grasp the impacts of investments in fisheries (Kébé  2011). Therefore, the purpose of this report is to provide an alternative and comprehensive estimate for catches from the Gabonese Exclusive Economic Zone (EEZ) from 1950 to 2010, using the ‘reconstruction’ method developed by Zeller et al. (2007).methodsTotal and coastal population of GabonTotal population data were extracted from www .populstat.info (2014) for the period from 1950 and 1959 and from the World Bank database (www .worldbank.org) for 1960 and 2010. Coastal rural and urban population living within a range of 5 km from the coast was extracted from CIESIN (2012) for 1990, 2000 and 2010, then expressed as a percentage of total population, i.e., 33% for 1990, 43% for 2000 and 30% for 2010. We assumed coastal population represented 33% of the total population in 1950 and thus estimated coastal population for the same year at around 153,000 persons (Figure 2).Subsistence catchesA household survey conducted in the early 1960s estimated fish consumption from non-commercial activities (subsistence fishing) at 23.5 g·person-1·day-1, i.e. 8.6 kg·person-1 for 1963. This estimate was multiplied by the estimated coastal population, resulting in estimated subsistence catches of 1,944 t for 1963. Total subsistence catches were assumed to be 30% higher in 1950 compared to 1963. A more recent household survey estimated fish consumption per adult male equivalent (AME) at 200 g·AME-1·day-1 from commercial small-scale and non-commercial sources (Wilkie et al. 2005), i.e., 150 g·person-1·day-1 (1 AME is equivalent to 0.75 person) and 55 kg·person-1·year-1. The latter estimate was multiplied by the coastal population, then artisanal catches (estimated below) were subtracted, and the remainder treated as subsistence catches. Imports and exports extracted from the United Nations Food and Agriculture database for 2005 were also used to balance internal consumption. The same operation was performed for 2010, assuming the same consumption rate. We interpolated linearly to complete the estimates.Artisanal catchesThe number of artisanal canoes was provided by different sources for 1967, 1974, 1983, 1990, 1996, 2008, 2009, 2010 (Table 1). Given the evidence of a lower effort in the early 1950s (Lagoin and Salmon 1970), it was assumed that the number of canoes in 1950 was half of that of 1967; intermediate values were interpolated (Table 1). The catch per unit of effort (CPUE) was averaged at 294 kg·canoe-1·day-1 from Kébé et al. (1996) for 1995 and at 55.1 kg·canoe-1·day-1 from Badjina Egombengani (2011) between 2008 and 2010. Fishers noted a strong decrease in daily CPUE between the mid-1960s and the 1990s (Ijiff 1991); therefore, the CPUE in 1965 was set 20% higher than the CPUE in 1995. Similarly, given lower rates of motorization, and relatively smaller boats in the 1950s compared to later time periods, when migrant fishers introduced bigger boats, the CPUE in 1950 was set 50% lower than the CPUE in 1965, and intermediate values were interpolated (Table 1). The number of fishing days for 1,000 canoes were estimated at 99,744 days for 1995 and for 1,600 canoes at 157,510 days for 1999 (Ekouala 2013), i.e. 99 fishing days∙canoe-1∙year-1 between 1995 and 1999. The number of fishing days per canoe for 2010 was obtained by dividing the 26,710 fishing days by the 176 canoes estimated as fishing in 2010 (Badjina Egombengani 2011). The latter was obtained by dividing the number of fishers (230 fishers) by the average number of fishers per canoe (1.3 fishers∙canoe-1) estimated from the total number of fishers and the total number of canoes surveyed by Badjina Egombengani (2011). The pattern of increasing number of fishing days suggests declining resources (Ijiff 1991); thus, this pattern was projected backward, i.e., the number of fishing days in 1950 was assumed to have been 40% lower than in 1995, i.e. 40 days·canoe-1·year-1. The days fished were then interpolated to fill in the gaps. Total artisanal catches were then obtained as the product of the number of canoes, the CPUE and the number of fishing days.Table 1.   Number of artisanal fishing canoes and corresponding CPUE in Gabon, 1950-2010. Values in italics are interpolated.Year Canoes Source CPUE Source1950 275 Assumption 176.0 Assumption1965 518 Interpolation 353.0 Assumption1967 550 Lagoin and Salmon (1970) 349.0 Interpolation1974 600 Everett (1976) 335.0 Interpolation1983 1,800 Haakonson (1992) 318.0 Interpolation1990 1,110 Ijiff (1991) 304.0 Interpolation1995 1,435 Interpolation 294.0 Kébé et al. (1996)1996 1,500 Kébé et al. (1996) 276.0 Interpolation2008 2,824 Kébé (2011) 55.1 Badjina Egombengani (2011)2009 3,000 Kébé (2011) 55.1 Badjina Egombengani (2011)2010 3,000 Assumed constant 55.1 Badjina Egombengani (2011)0Figure 2.  Coastal population of Gabon, 1950-2010.Gabon - Belhabib 87Industrial catchesDomestic catchesThe domestic industrial fishing fleet in Gabon includes vessels of foreign origin and majority foreign beneficial ownership, mainly from China. We first reconstructed total ‘domestic’ industrial catches, then allocated the catch to ‘real domestic’ and joint venture fleets. The first industrial trawler operated in Gabon in 1948, and it persisted into the 1950s (Haakonson 1992). Catches were low due to the experimental nature of the fishery, with about 60 t for 1956 and 101 t for 1957 (Haakonson 1992). It was assumed that catches were constant between 1950 and 1956. The number of boats was reported at 5 trawlers for 1967 (Lagoin and Salmon 1970) and 10 trawlers for 1974 (Everett 1976). The number of ‘domestic’ vessels was compiled by Ekouala (2013) for the period between 1979 and 2007, during which (in 1985) China entered the fishery through a joint venture with Gabon. The number of boats for the later years was provided by the Department of Fisheries and Aquaculture for 2008, 2009, 2010, showing both domestic and foreign vessels by name, flag, gear type, number of months fishing, and licence fees paid by each vessel (Anon. 2009, 2010, 2011). Kébé et al. (1996) reported a shrimp trawl CPUE of 300 kg·boat-1·day-1, while Ekouala (2013) estimated that catches were, in reality, 5 to 10 times higher than reported landings per boat, i.e. 7.5 times higher, as trawlers usually report only target species. Thus, the shrimp trawler total CPUE was estimated at 2,250 kg·boat-1·day-1 (or 720 t·boat-1·year-1), assuming 320 fishing days per year for 1996 (based on the duration of fishing licences). Similarly, Kébé et al. (1996) reported 1,600 kg·boat-1·day-1 for demersal trawlers. As shrimp trawlers are known to generate higher by-catch amounts, we assumed under-reporting was 50% lower for demersal trawlers. Therefore, the demersal trawler CPUE is estimated to be 3.25 times higher than the reported CPUE, i.e., 1,872 t·boat-1 for 1996. This yielded an average CPUE estimate of 1,296 t for 1996. It was assumed that the CPUE would have been 50% higher in 1950 and 10% lower in 2010; an interpolation was then performed to fill in the gaps, which the resulting trend corresponding to the drastic decline in CPUE documented since the 1960s (Ekouala 2013). The ‘domestic’ industrial catches from 1967 to 2010 were obtained by multiplying the number of ‘domestic’ industrial vessels by the estimated CPUE, then interpolating to the 1950, 1956 and 1957 catch estimates to complete the time series. To filter out ‘real’ domestic from joint venture catches, it was assumed that the officially reported industrial catch was that of vessels landing catches at ports of Gabon (Haakonson 1992; Kébé 2011; Ekouala 2013; Barretta and Houston 2014). Although, a few of these vessels might have been of Chinese origin as well, it is more likely that under-reporting is due to Chinese vessels landing their catch elsewhere, rather than being due to vessels based and landing in Gabon ports.Foreign legal catchesThe number of foreign fishing vessels, i.e., vessels that are flagged to and have majority beneficial ownership in countries other than Gabon, was gathered from different sources for 1965, 1974, 1979 and between 1991 and 2010 (Kébé et al. 1996; Anon. 2009, 2010, 2011; Ekouala 2013). Interpolations were performed back to 1965, which was deemed the start date of foreign fishing in Gabon waters. The foreign fishing effort was multiplied by the previously estimated CPUE (see above). Under-reporting by foreign vessels is likely higher as vessels are generally based in foreign ports, and their catch and effort data are not recorded by Gabon (Kébé et al. 1996). There are over twenty foreign countries operating under different types of access agreements in Gabon, flying a range of flags (real nationality in brackets): Angola, Belize (China), Belize (France), Belize (Spain), Cape Verde (China), Cameroon (China for bottom trawlers), China, Congo (China), France, Korea, Ghana, Guatemala, Guinea (China), Indonesia, Japan, Madagascar, Namibia, Netherlands Antilles (unknown), Nigeria (China), Philippines, Sao Tome and Principe, Togo (Spain), Spain, Portugal, and Panama (Korea) (Anon. 2009, 2010, 2011; Mallory 2013). The number of vessels per fishing entity was reported for the period between 2007 and 2010 (Anon. 2009, 2010, 2011). It was assumed that vessels flagged to African countries (except those of Chinese origin) and those that are European, but flagged to other countries such as Belize and Korea, started fishing when the foreign fishery began, given their documented presence in neighbouring countries. Japan started fishing in the early 1980s (Belhabib 2015); EU countries under the EU-Gabon fishing agreement started fishing at the beginning of the first agreement in 1998; China started fishing in Gabon in 1985 (Kébé 2011); Chinese vessels flying the Congolese flag started operating in Gabon in the early 2000s when China started reflagging to Congo (Belhabib and Pauly this volume); vessels from the remaining countries, mainly flag-of-convenience countries were assumed to have begun fishing in Gabon in 2000. We converted the number of vessels per country to percentages between 2007 and 2010, then we carried these percentages backwards to 2000 for all countries which began fishing in 2000, and to 1998 for fleets operating under the EU-Gabon agreement. For the remaining time period, we allocated catches evenly between countries documented within a similar time span.Foreign illegal catchesIllegal fishing is widespread, but only partly controlled in Gabon. When foreign vessels are incriminated, foreign pressure is usually applied on local officials, such as to assist the foreign crew (Ekouala 2013). In 2010, six trawlers were caught fishing illegally during 17 days of patrol (Ekouala 2013). This number was extrapolated to the entire year, which led to an estimate of 21 vessels fishing illegally, which, when multiplied by the above-estimated CPUE, gives an estimate of 25,000 t·year-1 of illegal catch. For 2005, illegal catches were equivalent to 19% of the total legal catch (MRAG 2005). Thus, this estimate was multiplied by the reconstructed total catch by legal foreign fleets, which yielded an illegal catch of 14,356 t·year-1. We assumed illegal fishing, mainly by Chinese operators, began when Chinese fleets started operating in Gabon waters, i.e., in 1985, and interpolated. 88DiscardsThe data submitted by fishing vessels to the Department of Fisheries showed an average discard rate of 2% (Anon. 2009), which was applied across all trawl fleets between 1950 and 2010. This is likely an underestimate. For tuna vessels, i.e., those operating under the flag of Guatemala, Belize, Ghana, EU countries, Japan, Netherlands, Antilles and Cape Verde, discard rates from Romagny et al. (2000), and Chavance et al. (2011) summarized in Belhabib and Pauly (2015) were applied to the tuna catches by these vessels.Species disaggregationTo disaggregate subsistence and artisanal catches, the species composition for 2000s (Badjina Egombengani 2011) and 1967 (Lagoin and Salmon 1970) were interpolated for each species/taxon. The catch composition was assumed constant between 1950 and 1967. Trawl catch composition between 2005 and 2009 was available from the Department of Fisheries reports (Anon. 2009) and for 1967 by Lagoin and Salmon (1970). For the tuna catch disaggregation, catch descriptions by Failler et al. (2013) and Anon. (2004) were used, from which discarded tuna by-catch composition was extracted.resultsSubsistence catchesSubsistence catches decreased slightly from 2,500 t in 1950 to around 2,000 t in 1963, then increased to a peak of over 8,200 t in 2005, before decreasing again, to less than 4,000 t in 2010 (Figure 3).Artisanal catchesArtisanal fisheries catches witnessed changes over time as they increased slowly from 2,000 t in 1950 to 56,500 t in 1983 (due to the increase in fishing effort), then decreased to around 37,000 t in 1990 (Figure 4). Catches increased to a second peak of 60,000 t in 2004, before decreasing rapidly to around 28,400 t in 2010, mainly driven by over-exploitation.Industrial catchesIndustrial ‘domestic’ catches (i.e., ‘Gabon’ in Figure 5) increased from 60 t in 1950 to about 8,600 t in 1967, and remained around that level until 1984, when China entered the fishery under Gabon’s flag (Figure 5). Overall ‘domestic’ catches, Gabon and China reflagged to Gabon, increased rapidly to a first peak of 44,300 t in 1985, and a second peak of 53,000 t in 1994 (Figure 5), the latter due to the increase in the number of fishing vessels. Catches declined thereafter to approximately 18,000 t in 2010, of which 14,600 t were taken by Chinese vessels reflagged to Gabon (Figure 5).Foreign industrial catches (excluding China flagged as ‘Gabon’) increased from 9,000 t in 1965, when foreign fishing was deemed to have started, to around 74,000 t in 1979, after which they remained relatively constant until the early 1990s (Figure 6). Industrial foreign catches varied later-on due to changes in the number of legal foreign fishing vessels, and peaked at 104,000 t in 2000 and 101,000 t in 2008, before decreasing to 71,000 t in 01234567891950 1960 1970 1980 1990 2000 2010Catch (t x 103)Year01020304050601950 1960 1970 1980 1990 2000 2010Catch (t x 103)Year01020304050601950 1960 1970 1980 1990 2000 2010Catch (t x 103 )YearGabonChina reflagged to GabonFigure 3.  Reconstructed subsistence catches in Gabon, 1950-2010.Figure 4.  Reconstructed artisanal catches in Gabon, 1950-2010.Figure 5.  Reconstructed industrial ‘domestic’ catches including those by vessels of Chinese origin in Gabon, 1950-2010.Gabon - Belhabib 892010. Foreign legal fisheries were dominated by trawl catches prior to the mid-2000s and by tuna catches thereafter (Figure 6). Illegal foreign catches increased from less than 1,000 t in 1986 to over 23,000 t in 2010 (Figure 6).African countries catches represented the bulk of catches with around 47% of foreign catches from the Gabonese EEZ, while EU countries represented less than 20% and China slightly over 20%. However, the contributions of China and the EU to total foreign catches has increased over time.DiscardsDiscards increased from around 550 t·year-1 in the late 1960s to around 5,000 t·year-1 between the early 1980s and the mid-1990s, before increasing to a first peak of 10,000 t in 2000, and then a second peak of 13,000 t in 2008 (Figure 7).Total catchesTotal domestic catches, including artisanal, industrial, and subsistence catches, as well as discards were estimated at around 4,600 t in 1950 compared to 2,400 t reported to the FAO, increased to a peak of 63,000 t in 1994 compared to 26,500 t reported to the FAO, and then decreased to less than 36,000 t in 2010 compared to 22,000 t reported to the FAO (Figure 8a). Overall, total catches were 2.5 times the data supplied to the FAO. However, under-reporting was at its maximum during the first years of industrial fisheries, and underreporting has declined considerably in the most recent time period (Figure 8a).Taxonomically, domestic catches included around 70 groups. However, the bulk of the catch consisted of bonga shad (Ethmalosa fimbriata) and West African croakers (Pseudotolithus spp.) (Figure 8b).Total foreign catches (legal, illegal and discards) were estimated at around 9,000 t in 1965, increased to a peak of 120,000 t in 1994 and a second peak of 176,000 t in 2008, before decreasing to 126,000 t in 2010 (Figure 10).discussionTotal domestic removals from the Gabonese EEZ were estimated at less than 5,000 t in 1950, constituted mostly of small-scale catches, increased gradually to a peak of 82,000 t in 2004 and then decreased to less than 36,000 t in 2010. Although the last figure triples when foreign catches are added, small-scale fisheries still constitutes on average 60% of the total legal catch. This highlights  the importance of small-scale fisheries to the population of Gabon, which remains the second most practiced activity in rural areas of the country (Badjina Egombengani 2011).  Although domestic catches were strongly under-reported, the relative decrease of the under-reported component indicates an improvement in catch statistics. This improvement is observed since the early 2000s herein and indicated by literature since 2003 (Badjina Egombengani 2011).0204060801001201401601950 1960 1970 1980 1990 2000 2010Catch (t x 103 )YearTrawlIllegal trawlTuna024681012141950 1960 1970 1980 1990 2000 2010Catch (t x 103 )YearTunaTrawl0102030405060708090Catch (t x 103) Industrialsupplied to FAOSubsistenceArtisanala)01020304050607080901950 1960 1970 1980 1990 2000 2010Catch (t x 103)YearEthmalosa fimbriataPolydactylus quadrifilisDentex spp.spp.Pseudotolithus spp.ShrimpsOthersb)SphyraenaFigure 6.  Reconstructed total foreign catches from Gabon, 1950-2010.Figure 7.  Reconstructed industrial discards from Gabon by gear, 1950-2010.Figure 8.  Reconstructed total domestic catches a) by sector from Gabon, 1950-2010, with solid line as data supplied to FAO. Discards plotted but cannot be seen on graph; b) by taxonomic composition from Gabon, 1950-2010. ‘Others’ consist of 55 additional taxonomic categories. 90Illegal catches were estimated to have been the equivalent of 1% of legal catches in the past, and around 50% today, indicating an alarming increase in less than 25 years, which may partially explain the problem of over-exploitation in the waters of Gabon. Furthermore, of the around 80 taxa caught by the legal fisheries of Gabon, 40 taxa are also taken by illegal fisheries, indicating an overlap of 50% in taxa targeted or caught. Economically, illegal fisheries are estimated to have extracted over $207 million US in 2010 from the waters of Gabon that could have been extracted by legal fisheries, assuming a price of $8.3 US·kg-1 (RFI 2012). Thus, the net loss to the total Gabonese economy, if we could assume complete landings and processing within Gabo, using an economic multiplier of 2.95 (Dyck and Sumaila 2010), would be equivalent to $610 million US per year. The legal fisheries contribute $1.3 billion US to the Gabonese economy, i.e., around 9% of the Gabonese GDP in 2010, while small-scale fisheries alone contribute $800 million US of the total economy, i.e., 5% of the GDP, a clear indication of their importance to both the economy and food security.Small-scale fisheries in Gabon, the main source of animal protein, are threatened by increasing illegal fishing, combined with a low monitoring, control and surveillance capacity (Barretta and Houston 2014) and other threats, such as increasing migrations towards the coast. Although fisheries statistics have improved over time, there is still room for effort to refine the catch statistics, notably through a separate accounting of small-scale and industrial fisheries. Most important, however, is the enforcement of fisheries legislations, notably against foreign vessel incursions.acknoWledGementsThis is a contribution from the Sea Around Us, a collaboration supported by The Pew Charitable Trusts and the Paul G. Allen Family Foundation.reFerencesAnon. (2004) Framework contract for performing Evaluations, Impact Analyses and Monitoring Services in the context of Fisheries Partnership Agreements concluded between the Community and Non-Member coastal states. Sao Tome and Principe. Report to the European Commission by Oceanic Développement, Poseidon Aquatic Resource Management Ltd, and MegaPesca Lda., Concarneau, France. 126 p.Anon. (2009) Annuaire statistique 2009. Direction Généale de la Statistique, Libreville. 245 p.Anon. (2010) Publication du registre des licences de pêches. Situation au 1er semestre 2010. 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Institut de recherche pour le developpement, Institut français de recherche pour l’exploitation de la mer, Ecole nationale supérieure agronomique de Rennes 38. Editions Quae.Wilkie DS, Starkey M, Abernethy K, Effa EN, Telfer P and Godoy R (2005) Role of Prices and Wealth in Consumer Demand for Bushmeat in Gabon, Central Africa. Conservation Biology 19(1): 268-274.Zeller D, Booth S, Davis G and Pauly D (2007) Re-estimation of small-scale fishery catches for U.S. flag-associated island areas in the western Pacific: the last 50 years. Fishery Bulletin 105(2): 266-277. 92Appendix Table A1.  FAO landings vs. reconstructed total catch (in tonnes), and catch by sector, with discards shown separately for Gabon, 1950-2010.Year FAO landings Reconstructed total catch Industrial Artisanal Subsistence Discards1950 2,400 4,580 60 2,000 2,530 11951 2,400 4,860 60 2,320 2,480 11952 2,400 5,170 60 2,670 2,440 11953 3,000 5,520 60 3,070 2,390 11954 3,000 5,900 60 3,490 2,350 11955 4,000 6,320 60 3,960 2,300 11956 4,000 6,780 60 4,460 2,260 11957 4,500 7,360 101 5,040 2,210 21958 5,000 9,590 940 6,470 2,170 161959 5,000 11,870 1,780 7,940 2,120 301960 5,000 14,190 2,620 9,450 2,080 441961 5,500 16,560 3,459 11,010 2,030 591962 5,700 18,980 4,299 12,620 1,990 731963 5,700 21,450 5,138 14,280 1,940 871964 5,700 24,160 5,978 15,990 2,090 1011965 6,700 26,920 6,817 17,750 2,240 1151966 6,700 29,290 7,656 19,110 2,390 1301967 6,500 31,660 8,496 20,490 2,530 1441968 7,500 32,150 8,491 20,830 2,680 1441969 7,500 32,640 8,485 21,180 2,830 1441970 8,200 33,130 8,480 21,530 2,980 1441971 8,200 33,630 8,475 21,880 3,130 1431972 8,200 34,120 8,469 22,230 3,280 1431973 10,200 34,620 8,464 22,580 3,430 1431974 10,200 35,120 8,459 22,940 3,570 1431975 13,100 38,690 8,453 26,370 3,720 1431976 13,020 42,350 8,448 29,890 3,870 1431977 12,210 46,090 8,443 33,480 4,020 1431978 16,000 49,890 8,437 37,140 4,170 1431979 19,200 53,760 8,432 40,860 4,320 1431980 18,000 57,710 8,427 44,670 4,470 1431981 18,346 61,730 8,421 48,550 4,620 1431982 18,805 65,810 8,416 52,490 4,770 1421983 17,649 69,960 8,411 56,490 4,920 1421984 19,200 67,910 8,405 54,300 5,070 1421985 19,153 65,800 8,400 52,050 5,220 1421986 18,244 62,030 7,600 48,940 5,370 1291987 20,286 58,390 6,900 45,860 5,520 1171988 20,191 58,400 8,022 44,580 5,670 1361989 18,601 50,770 5,400 39,460 5,810 911990 18,000 48,190 5,300 36,840 5,960 901991 20,000 50,240 5,200 38,840 6,120 881992 22,000 54,340 6,100 41,880 6,270 1031993 28,290 58,680 7,120 45,030 6,420 1201994 26,515 63,100 8,140 48,250 6,570 1381995 32,777 67,460 9,159 51,430 6,720 1551996 36,045 68,060 12,518 48,500 6,870 1721997 34,073 68,640 10,738 50,710 7,020 1771998 44,556 75,920 13,949 54,570 7,170 2361999 40,453 69,400 11,353 50,530 7,320 1932000 36,937 73,740 11,849 54,230 7,470 1992001 32,482 71,670 12,844 51,050 7,620 1602002 31,136 75,880 11,804 56,120 7,770 1862003 34,576 79,270 12,648 58,490 7,920 2112004 37,423 81,790 13,453 60,040 8,070 2282005 33,727 73,310 11,619 53,270 8,220 1972006 31,765 63,260 9,785 45,980 7,330 1662007 28,374 50,420 7,016 36,850 6,430 1192008 31,702 40,240 5,860 28,740 5,530 992009 21,457 36,780 3,696 28,380 4,640 632010 21,457 35,880 3,696 28,380 3,740 63Gabon - Belhabib 93Appendix Table A2. Reconstructed total catch (in tonnes) by major taxonomic category for Gabon, 1950-2010. ‘Others’ contain 55 additional taxonomic category.Year Ethmalosa fimbriata Pseudotolithus spp. Sphyraena spp. Dentex spp. Polydactylus quadrifilis Shrimps Others1950 3,190 347 148 159 96 0 6471951 3,500 440 187 201 122 0 4101952 3,680 491 209 225 136 0 4331953 4,100 467 199 214 129 0 4131954 4,300 527 224 241 146 0 4641955 4,990 437 186 200 121 0 3841956 5,240 508 216 232 141 0 4461957 5,540 597 253 273 165 0 5351958 6,860 855 356 391 232 1 8981959 7,970 1,197 494 547 322 1 1,3361960 9,110 1,546 635 706 414 2 1,7801961 10,140 1,889 763 861 497 3 2,4111962 11,230 2,244 899 1,022 586 4 2,9901963 12,400 2,611 1,045 1,189 681 5 3,5121964 13,600 3,006 1,193 1,368 777 6 4,2071965 15,610 3,285 1,319 1,496 859 5 4,3411966 16,420 3,606 1,419 1,639 925 8 5,2731967 17,230 3,929 1,520 1,783 990 10 6,2061968 18,500 3,907 1,553 1,777 1,014 10 5,3961969 18,770 3,989 1,586 1,813 1,038 12 5,4381970 20,020 3,960 1,618 1,805 1,058 9 4,6591971 20,290 4,040 1,651 1,840 1,081 10 4,7131972 20,560 4,119 1,684 1,876 1,104 12 4,7671973 21,560 3,969 1,622 1,807 1,064 13 4,5821974 21,830 4,049 1,655 1,842 1,087 14 4,6401975 22,330 5,571 1,723 2,289 1,125 10 5,6481976 24,300 6,106 1,968 2,541 1,286 31 6,1161977 26,680 6,346 2,261 2,731 1,479 223 6,3711978 26,860 7,558 2,289 3,076 1,492 1,409 7,2031979 27,310 9,098 2,351 3,528 1,527 1,506 8,4371980 30,010 9,293 2,683 3,723 1,746 1,608 8,6531981 31,960 9,735 2,926 3,948 1,905 2,108 9,1451982 33,880 10,743 3,165 4,330 2,060 1,710 9,9211983 36,650 11,065 3,509 4,565 2,286 1,630 10,2591984 34,860 11,163 3,287 4,499 2,140 1,637 10,3281985 34,920 9,990 3,128 3,715 2,041 1,701 10,3131986 33,220 9,316 2,948 3,637 1,919 1,906 9,0881987 31,680 8,602 2,698 3,233 1,765 2,114 8,3001988 31,670 8,484 2,696 3,293 1,769 1,373 9,1151989 28,780 6,879 2,336 2,758 1,530 1,348 7,1391990 26,980 7,222 2,225 2,668 1,428 825 6,8461991 26,820 8,454 2,273 2,965 1,431 939 7,3551992 28,450 8,458 2,513 3,488 1,545 966 8,9241993 30,100 9,540 2,709 3,485 1,646 540 10,6611994 33,310 9,535 3,072 3,674 1,925 661 10,9181995 34,030 9,692 3,181 3,787 1,819 898 14,0531996 29,970 9,907 3,159 3,083 1,371 956 19,6091997 33,520 9,331 3,222 3,039 1,524 2,250 15,7571998 36,260 11,205 3,347 3,320 1,377 2,666 17,7501999 34,540 10,487 3,102 2,725 1,394 1,278 15,8782000 35,600 10,202 3,562 3,153 1,685 2,456 17,0872001 33,270 9,748 4,189 3,245 1,663 1,947 17,6072002 34,990 10,670 4,308 3,707 2,538 1,833 17,8312003 35,420 11,564 4,452 3,707 3,880 3,544 16,6992004 34,310 14,156 4,552 3,839 5,102 2,394 17,4382005 31,000 12,722 3,791 3,595 3,534 1,920 16,7542006 28,590 10,180 2,837 2,872 2,586 2,207 13,9902007 24,220 7,509 2,145 2,372 2,505 550 11,1182008 20,100 6,167 1,849 1,786 2,155 163 8,0112009 18,670 5,636 1,888 1,883 1,875 102 6,7282010 18,200 5,498 1,830 1,820 1,837 102 6,600 94Congo (Brazzaville) - Belhabib and Pauly 95the imPlications oF misrePortinG on catch trends: a catch reconstruction For the PeoPle’s rePublic oF the conGo, 1950-20101Dyhia Belhabib and Daniel PaulySea Around Us, Fisheries Centre, University of British Columbia,  2202 Main Mall, Vancouver, BC, V6T 1Z4, Canadad.belhabib @fisheries.ubc.ca; d.pauly @fisheries.ubc.caabstractThe official fisheries statistics for the People’s Republic of the Congo, also known as ‘Congo (Brazzaville)’ feature increasing landings, despite current, if anecdotal evidence of over-exploitation. This reconstruction brings to light that strong under-reporting in the past masked a massive exploitation and thus biased the trends of reported data. Reconstructed domestic catches within Congo (Brazzaville)’s EEZ increased from 7,110 t in 1950 to a peak of 99,300 t in 1977, declined to 30,500 t on average during the 1990s and then increased slowly to 45,000 t in 2010. Reconstructed total catches from the Congo within its EEZ were on average 2.8 times the data supplied to the FAO. As opposed to official statistics, which may have justified the licensing of an over-capitalized foreign industrial fleet, the reconstructed catch confirms fishers’ accounts of declining catches and resources availability. This situation threatens the livelihoods of the coastal population of the Congo, which faces increasing resource scarcity and poverty.introductionThe People’s Republic of the Congo, or ‘Congo (Brazzaville)’, thus named after its capital to avoid confusion with the ‘Congo (ex-Zaïre)’, is located in central West Africa (Figure 1). The relatively narrow coast opens to the Atlantic Ocean on the west, and ranges from Angola (Cabinda) in the South to Gabon in the North.The first steps toward independence from France began with a strong nationalist movement as early as 1926, due mainly to mistreatment of the Congolese by the French administration (Bernault 1996). The Congo became an autonomous republic in 1958, followed by a series of upheavals in 1959 and finally independence in 1960. Although the Congo may be considered peaceful when compared to its neighbours in the South, it remains a good example of how the democratization process can trigger a series of conflicts (Bazenguissa-Ganga 1999). Due to deteriorating economic conditions and a high unemployment rate (Bernault 1996), this led to a revolution in 1963 and a coup d’état in 1968. This period of instability eventually ended when an army colonel assumed the Presidency, and led the country into re-establishing its relations with France, and notably the French state oil company, Elf. This also involved a political conflict in 1993-2000 which ended in a civil war (www .ucdp.uu.se) that killed over 18,000 people between 1993 (3,000) and 1997 (15,000). The conflict further exacerbated with greater casualties in 1999, in addition to over 20,000 women raped (Yengo 2006) and between 100,000 to 300,000 people displaced (Bazenguissa-Ganga 1999). However, the security in the country has improved significantly since 2002, when groups of armed fighters were disbanded. Economically, the Congo relies mainly on minerals, agriculture and the oil sector which represents around 65% of the GDP. Despite a prevailing oil sector and an average GDP per capita of $3,800, which is relatively high compared to the rest of Africa, poverty and child malnutrition still prevail, particularly in rural areas (The World Bank 1997). With over a third of monthly expenses dedicated for bushmeat 1 Cite as: Belhabib, D. and Pauly, D. (2015) The implications of misreporting on catch trends: a catch reconstruction for the People’s Republic of the Congo, 1950-2010. pp. 95-106. In: Belhabib, D. and Pauly, D. (eds). Fisheries catch reconstructions: West Africa, Part II. Fisheries Centre Research Reports vol.23(3). Fisheries Centre, University of British Columbia [ISSN 1198-6727].Figure 1.  Map of Congo (Brazzaville) with Exclusive Economic Zone (EEZ). 96and fish, animal protein intake is a household priority (The World Bank 1997; Fa et al. 2003). Indeed, with some 4.2% of the Congo households fishing (Anon. 2006), fish contributes over 50% of the animal protein intake (Anon. 2011b) and around 2 to 3% of the national GDP (Horemans and Kebe 2006; COREP 2012). However, with declining fisheries resources (Nguinguiri and Katz 1996) due in part to overexploitation by foreign fleets, notably those from China, a complete lack of transparency and a high level of corruption (Transparency International 2010), which led to licenses being awarded to some 70 foreign vessels despite the sustainable level being much lower (Maloueki 1999, 2005), coastal populations find themselves trapped between increasing poverty and limited choices of livelihood (Brugère et al. 2008).Official catch statistics reported by the Food and Agriculture Organization (FAO) on behalf of the Congo exhibit a continuous increasing trend, which in the light of the above issues, appears to be highly dubious. Although, there have been a great effort by the Office de la recherche scientifique et technique d’outre-mer (ORSTOM, now IRD) as early as 1981 to collect artisanal and industrial (small-pelagic) fishing data, “catch statistics for the 1970s are virtually non-existent” (Jul-Larsen 1994a). In addition to industrial trawl and artisanal fisheries being under-estimated given their scattered nature (as industrial fleets operate in other countries’ Exclusive Economic Zones (EEZ) and artisanal are dispersed across the entire coast of the Congo), discards and foreign catches are also largely unknown. Herein, we reconstruct fisheries catch data between 1950 and 2010, by making coherent and compatible what little is known of the marine fisheries of the Congo, and thus generating what we hope are realistic fisheries catch trends.methodsCoastal populationThe total population was obtained from the database of the World Bank (www.worldbank.org) for the period between 1960 and 2010 and from Populstat (www.populstat.org) from 1950 to 1959. Coastal rural and urban population estimates for 1990, 2000 and 2010 were extracted from CIESIN (2012), then expressed in percent of total population. We extrapolated backwards the rural and urban population percentage and completed the time series by a series of linear interpolations. We then multiplied the resulting percentages by the total population to obtain the coastal rural and urban population of Congo (Figure 2)Subsistence fisheriesIn the past small-scale fisheries were directed mainly for personal consumption and canoe (villi)-type fisheries were described to be for subsistence (Le Gall 1975). Herein, we consider subsistence fishing, anything that is taken by non-artisanal fishers for household consumption, including children (Vennetier 1968)2; thus the part that is taken home by artisanal fishers is considered as a fraction of the artisanal fishery. Households in the Congo can consume fish as much as 5.8 times a week on average as revealed by a survey sampling 70 households in Pointe-Noire (Le Gall 1975). In the Pointe-Noire area, fish consumption ranged between at least 65 kg·capita-1·year-1 (Lagoin and Salmon 1970) and 85 kg·capita-1·year-1 (Cayre and Fontana 1977). These numbers are likely too high for the rest of the Congolese coast; however, they give a clear indication of the importance of fish consumption to Congolese households.Dhont (1963) estimated a per capita consumption rate for the country as a whole of 500 g·capita-1·week-1 for 1957 and 1 kg·capita-1·week-1 for 1962, equivalent to 24 kg·capita-1·year-1 and 48 kg·capita-1·week-1 respectively. Lagoin and Salmon (1970) reported a higher consumption rate for 1967 of 55 kg·capita-1·week-1. For 2005, we converted the per capita calories intake from different kinds of fish and processed seafood products (Anon. 2006; Backiny-Yetna and Zodon 2009) to weight of the processed product, then to live weight using conversion factors from FAO (FAO 2000). We reached a consumption rate of 93.2 g·capita-1·day-1, i.e. 34 kg·capita-1·year-1 for 2005. We assumed the consumption rate was constant between 1950 and 1957, between 2005 and 2010, and then interpolated linearly to fill in the gaps.In inland fisheries, 35% of the fish caught by households is kept for personal consumption (Béné 2008). Assuming the same rate applies to coastal fisheries, 35% of the fish consumed by the coastal rural populations of the Congo would be caught by the household itself. Therefore, we multiplied the previous consumption rates by 35% and then by the rural coastal population, thus obtaining subsistence catches from the coastal waters of the Congo.2  The author suggests in his description of subsistence fisheries that “all children” in coastal Congo are fishing.0Figure 2.  Coastal population of the Congo, 1950-2010, adapted from www.worldbank.org and www.populstat.org (see text).Congo (Brazzaville) - Belhabib and Pauly 97Artisanal fisheriesArtisanal catch data collection was conducted by ORSTOM scientists since the early 1980s at 4 landing sites of the Congo (Kebe and Njock 1995), mainly monitoring sardinella (Sardinella spp.) catches. We assume that previously, catches were not monitored. The two types of canoes operating along the coast of the Congo have different capacity and therefore are treated separately in the present reconstruction. The first type includes the motorized and un-motorized Congolese (villi) pirogues, also called ‘bouatou’ (Dhont 1963), whose length is less than 6 m for the un-motorized ones and between 7 and 8 m for those with motors of 6.5 to 25 hp (Kebe and Njock 1995; Maloueki 1999). Villi fishers use gill-nets and hand lines (Tvedten 1990) and take onboard 1 to 2 fishers. The second type includes the Ghanaian pirogue-type used by the Popo ethnic group from Benin (Maloueki 1999). Their length reaches 14 to 18m and their engine power 25-40 hp (Tvedten 1990; Kebe and Njock 1995; Maloueki 1999) taking onboard 5 to 7 fishers (Mandilou 2010). These boats can carry from 4 t of fish every trip (Kebe and Njock 1995) to “tons of fish… every week”(Tvedten 1990).Although the villi were not considered active fishers in the 1940s and the 1950s when the Popo seemed to have a monopoly (Vennetier 1968), a relatively large number of villi-type canoes was reported as early as 1962, which suggest that a strong villi fishery already in place the 1950s and the 1960s (Dhont 1963; Lagoin and Salmon 1970). This is supported by further evidence suggesting that this fishery was mainly for personal consumption prior to the 1970s (Le Gall 1975), which might be a reason why it is not considered in economic surveys of Congolese fisheries.Table 1.   Reconstructed artisanal fishing effort by ethnic group in the CongoYear Total canoes Reference Villi canoes Reference Popo canoes Reference1950  -  - 178 Assumed the effort in 1950 was half of that of 19623 Assumed constant1955  -  - 252 Interpolation 3 Gobert (1985)1958  -  - 297 Interpolation 16 Gobert (1985)1960  -  - 326 Interpolation 24 Jul-Larsen (1994a, 1994b)1962 356 Dhont (1963); Lagoin and Salmon (1970)356 Dhont (1963); Lagoin and Salmon (1970)38 Interpolation 1963  -  - 373 Interpolation 45 Jul-Larsen (1994a, 1994b)1966  -  - 423 Interpolation 120 Jul-Larsen (1994a, 1994b)1967 460 Lagoin and Salmon (1970) 440 Subtraction 20 Lagoin and Salmon (1970)1970  -  - 414 Interpolation 24 Jul-Larsen (1994a, 1994b)1975 500 Le Gall (1975) 370 Interpolation 102 Interpolation 1976  -  - 361 Interpolation 117 Jul-Larsen (1994a, 1994b)1977 469 Fontana (1980) 352 Subtraction 117 Jul-Larsen (1994a, 1994b)1978  -  - 362 Interpolation 59 Reduced by halfa1980 600 Chaboud and Charles-Dominique (1991) 382 Interpolation 84 Interpolation 1982 -  402 Interpolation 110 Jul-Larsen (1994a, 1994b)1983 542 Nguinguiri (1991) 412 Subtraction 130 Jul-Larsen (1994a, 1994b)1986  -  - 381 Interpolation 109 Jul-Larsen (1994a, 1994b)1987 513 Barro et al. (1989) 371 Barro et al. (1989) 142 Barro et al. (1989)1988 550 Kébé and Njock (1995) 401 Kébé and Njock (1995) 149 Jul-Larsen (1994a, 1994b)1989 515 Kébé and Njock (1995) 355 Kébé and Njock (1995) 160 Kébé and Njock (1995)1990 520 Kébé and Njock (1995); Bazon and Ngouembe (1995)360 Kébé and Njock (1995); Bazon and Ngouembe (1995)160 Kébé and Njock (1995)1991 500 Kébé and Njock (1995) 380 Kébé and Njock (1995) 120 Jul-Larsen (1994a, 1994b)1992 530 Kébé and Njock (1995) 395 Interpolation 120 Interpolation 1993 490 Kébé and Njock (1995) 410 Interpolation 120 Interpolation 1994 545 Kébé and Njock (1995); Jul-Larsen (1994a)425 Kébé and Njock (1995); Jul-Larsen (1994a)120 Kébé and Njock (1995); Jul-Larsen (1994a)2000 518 Koumba (2012) 336 Koumba (2012) 182 Koumba (2012)2001 532 Koumba (2012) 343 Koumba (2012) 189 Koumba (2012)2002 720 Koumba (2012) 464 Koumba (2012) 256 Koumba (2012)2003 506 Kibelolo (2003)b 594 Interpolation 180 Koumba (2012); Kibelolo (2003)2004 506 Koumba (2012)b 724 Interpolation 180 Koumba (2012)2005 588 Anon. (2011a)c 853 Interpolation 254 Koumba (2012)2006 1199 Anon. (2011a) 983 Anon. (2011a) 216 Koumba (2012)2007 1173 Anon. (2011a); InfoPeche (2008) 919 Anon. (2011a) 254 Koumba (2012)2008 1171 Anon. (2011a) 811 Anon. (2011a) 360 Koumba (2012)2009 1193 Anon. (2011a) 929 Anon. (2011a) 264 Koumba (2012)2010 1193 Anon. (2011a) 929 Anon. (2011a) 264 Koumba (2012)a ‘Foreign’ fishers were expelled (i.e., fishers of irregular status in the Congo) since 1960 until 1977, and fishers migrated again to Congo in 1979 (Gobert 1985); After the death of President Marien Nhouabi in May 1977, around 4/5 of the Popo community were repatriated and 166 outboard engines confiscated (the fishers had no residence permits, and their engines no import permits). The government also decided that the remaining Popo should “refrain from fishing” unless it was for subsistence (Jul-Larsen 1994a);b This number was not taken into consideration as it was too low compared to the previous and later years;c This number was adjusted upwards as a total of 1,347 pirogues was reported by Bignouma (2010) of which 254 are Popo. 98The effort time series for both fisheries, expressed in number of canoes, was rebuilt using different literature sources (Dhont 1963; Lagoin and Salmon 1970; Le Gall 1975; Fontana 1980; Gobert 1985; Barro et al. 1989; Chaboud and Charles-Dominique 1991; Nguinguiri 1991; Jul-Larsen 1994a, 1994b; Kébé and Njock 1995; Kibelolo 2003; Anon. 2011a; Koumba 2012) and adjusted when necessary3 (Table 1). We interpolated linearly to fill in the gaps.The catch per unit of effort was provided by Dhont (1963) at 750 kg·canoe-1·month-1 for the villi canoes for around 11.5 days fishing per month (Gobert 1985, 1986), i.e., 65.2 kg·canoe-1·day-1 for 1958. Similarly, the author provided a CPUE of 66.7 kg·canoe-1·day-1 for the dry season and 44.4 kg·canoe-1·day-1 for the wet season, i.e. 55.6 kg·canoe-1·day-1 for 1962 on average. For 1993, we estimated the CPUE of the villi at 84.3 kg·unit-1·day-1 by calculating the weighted average of the CPUE of motorized and unmotorized pirogues provided by Kébé and Njock (1995). We assumed the CPUE remained relatively constant between 1950 and 1958, and that it decreased linearly by 30% between 1993 and 2003 to reflect the over-exploitation, declining catches and declining fish sizes (Fontana 1980; Nguinguiri 1991; Nguinguiri and Katz 1996). We then interpolated linearly to fill in the time series of villi-type canoes CPUE.Similarly, the CPUE of Popo-type canoes was estimated by dividing the total observed catch for the Popo-type canoes by the number of these canoes (Kebe and Njock 1995), i.e. 387 kg·canoe-1·day-1 for 1993. Popo fishers observed that the time spent fishing increased because of declining catches; they catch in the 1990s the same amount of fish in one night than what they used to catch in 2 hours in the 1960s (Nguinguiri and Katz 1996). Moreover, although fishers used more rudimentary fishing gear in the 1960s, they used to catch more fish than today, even with increasing fishing net sizes (Nguinguiri and Katz 1996). This translates into the CPUE of 1960 being 6 times higher than the CPUE of 1990s, i.e. 2,322 kg·canoe-1·day-1 for 1960, which is still below the capacity of a typical Popo-type canoe. We assumed the CPUE declined by 15% between 1993 and 2010 and then filled in the gaps by performing a series of linear interpolations.We obtained vili and Popo catches by multiplying the number of canoes of each type by their respective CPUE.Artisanal catches included mainly sardinellas (Sardinella aurita, S. maderensis) and bonga shad (Ethmalosa fimbriata) (Anon. 2011b), with the remaining evenly distributed between Southern meager (Argyrosomus holopedium), chub mackerel (Scomber japonicus) and Atlantic bumper (Chloroscombrus chrysurus) (Fontana 1980).Industrial domestic fisheriesIndustrial fishing in Congo began (in Pointe Noire) as early as the 1940s (Vennetier 1968), with the first industrial trawlers arriving in 1948 (Dhont 1963; Fontana 1980).The number of shrimp trawlers, other demersal trawlers and small-pelagic purse-seiners were obtained from different literature sources which retrace the fishing effort between 1950 to 2010 (Dhont 1963; Crosnier and Tanter 1968; Vennetier 1968; Lagoin and Salmon 1970; Fontana 1980; Bazon and Ngouembe 1995; Kébé and Njock 1995; Cochrane and Tandstad 2000; Binet et al. 2001; InfoPêche 2008; Anon. 2011a, 2011b; Koumba 2012). Reported landings were often reported by the same sources as an aggregate of all industrial fishing segments and/or separated into demersal, shrimp and small-pelagic (Sardinella spp.) landings (Le Gall 1975; Cayre and Fontana 1977; Fontana 1980; COREP 2012).Since ORSTOM staff started monitoring sardinella catches as soon as the fishery began (Fontana 1980), we assumed sardinella catches were reported properly and added 4% for the by-catch.On the other hand, given the scattered nature of the demersal and shrimp trawl fisheries, operating between Gabon and Angola (Crosnier and Tanter 1968; Cochrane and Tandstad 2000), we reconstructed catches using a different method relying on the CPUE and the number of boats for every segment.The CPUE for shrimp trawlers was estimated using the observed catch data by Fontana (1980) provided by kg·hour-1 for target species: deep-water rose shrimp (Parapenaeus longirostris), striped red shrimp (Aristeus varidens) and the deep-water shrimp (Plesiopenaeus edwardsianus), converted to catch per day using the conversion rate provided by the author, and estimated a CPUE of 5.85 t·boat-1·day-1 of retained species and 4.27 t·boat-1·day-1 of discarded species for 1975. Bazon and Ngouembe (1995) estimated a CPUE of 1 t·boat-1·day-1 for 1986 and 0.4 t·boat-1·day-1 for 1993. Given evidence of declining trawler CPUE (Bazon and Ngouembe 1995) , we assumed the CPUE in 1950 was 30% higher than in 1975, and that of 2010, 15% lower than the CPUE of 1993. Similarly, Bazon and Ngouembe (1995) estimated a CPUE of 4.5 t·boat-1·day-1 for demersal trawlers for 1971, 3.7 t·boat-1·day-1 for 1979, 2.4 t·boat-1·day-1 for 1982 and 1 t·boat-1·day-1 for 1990, we assumed that the CPUE in 1950 was 30% higher than the CPUE of 1971, and that of 2010, 15% lower than that of 1990. We interpolated linearly between the CPUE estimates and multiplied them by the respective number of boats.In 1967, fishing in Angola declined because of its declaration of territorial waters (12 miles zone). On the other hand, in 1970, fishing by Congolese boats in Gabonese waters was prohibited; it was only in 1972 that an access agreement allowed Congolese trawlers to operate again in Gabon, if to a smaller extent. Maps included in the study of Fontana (1980) suggest a third of trawl catches landed in Congo were taken from Angola, a sixth from the democratic Republic of the Congo (ex-Zaïre), another sixth from Gabon up to 1974; then, their operation shifted North to Gabon and Congo, up to 1980 (Fontana 1980). The domestic industrial fleets targeting mainly shrimp (Crosnier and Tanter 1968; Cochrane and Tandstad 2000) reduced its fishing zone from Angola and Gabon in the 1980s to only Congo today (Nguinguiri and Katz 1996).3  Some references reported very low effort numbers in contrast to some others, in which case the highest number was taken into consideration as the effort was actually observed.Congo (Brazzaville) - Belhabib and Pauly 99We assumed 70% of the shrimp catch was taken from Angola, the remaining distributed evenly between Gabon, the Congo (ex-Zaire) and the Congo between 1950 and 1967 when Angola claimed its territorial waters. In 1974, a third of shrimp trawl catches were taken from Angola and 17% from the Democratic Republic of the Congo (ex-Zaïre), 17% from Gabon and the remaining from the Congo. For 1980, when fishing in Angola ceased, we allocated 50% of the catch as taken from the Congo and 50% from Gabon, which were then kept at zero from 1989 on.Reported catches often include only the targeted groups such as penaeid shrimps, crabs and other high value species for shrimp trawlers. Therefore, using the bycatch data provided by the authors (Fontana 1980), catches must be corrected.The number of Chinese vessels is often included in the ’total’ number of domestic vessels, thus causing a large increase in the latter. China started fishing in the Congo in 2000 (Kibelolo 2003). In 2006, 26 Chinese bottom trawlers were operating in the Congo (Anon. 2011a, 2011b; Koumba 2012). We obtained the number of Chinese vessels operating for the later years by subtracting the number of domestic demersal trawlers from the total provided in the literature (InfoPeche 2008; Anon. 2011a; Koumba 2012). We interpolated linearly to fill in the gaps and multiplied the effort by the CPUE calculated for demersal trawlers for 300 days, which we then adjusted by +20% for the difference in efficiency.Between 1958 and 1961, other trawlers operated in Congo, but statistics were available (Poinsard 1969); thus, any estimate generated based on a CPUE and effort, as is the case here, is likely to be conservative.We disaggregated shrimp trawl catches using the catch description of target species by Fontana (1980) and demersal trawl catches by combining the species disaggregation provided by different references (Poinsard 1969; Lagoin and Salmon 1970; Chardy and Le Guen 1971; Cayre and Fontana 1977; Fontana 1980). We assumed the species composition provided by Poinsard (1969) remained unchanged between 1950 and 1963, and similarly for that provided by Fontana (1980) from 1980 and 2010, and interpolated between them.Illegal fisheries“Unregulated and unsustainable industrial fisheries are the most significant threat. Increasing numbers of domestic and foreign fishing boats venture into coastal waters to fish illegally. Fish are caught at unsustainable levels” (WCS 2011). Chinese boats are often accused of illegal fishing in Congo; thus we assume illegal fishing by China began around the time China started operating in the area. Specifically, assumed that illegal Chinese catches started at zero in 2000, increased to 58% of the legal catch (MRAG 2005) in 2005 and further increased by 20% in 2010, given the evidence of an increasing pattern of illegal catches (MRAG 2005).DiscardsAlthough sharks were targeted for their fins for over 20 years (since the fishery began until the fishery was prohibited in the early 2000), discards were minimal because the carcasses were also used in local markets (Maloueki 2005).Discards by the shrimp fleet were between 1,500-2,000 t∙year-1 (Bazon and Ngouembe 1995), which is equivalent of 3.43 times the landed (estimated catch) for 1993. For 1975, using the data on non-target species catch provided by Fontana (1980), which was equivalent of 73% of landings. We assumed discards were constant between 1950 and 1975, and decreased by 50% between 1993 and 2010, to reflect upon over-exploitation which might have led vessels to increasingly keep by-catch. We then multiplied the resulting rates by the estimated shrimp trawl catch.Documents assessing discards by demersal fish trawlers in the waters of the Congo were not available. Therefore, to estimate domestic discards, we used the discard rate estimated by (Belhabib et al. 2014b) for the Congo (ex-Zaire) of 1.8% for domestic demersal trawl and 66% of landed catches for foreign discards.Discards include soles (Cynoglossus spp.), porgies (Pagellus spp., Pagrus spp. and Dentex spp.), i.e., fishes that are not appreciated by Congolese consumers (Poinsard 1969). Shrimp discards were disaggregated using the data presented by Fontana (1980) for the contribution of non-targeted species to the shrimp trawl catch.Figure 3.  Reconstructed total subsistence catches from the Congo, 1950-2010. 100resultsSubsistence fisheriesSubsistence catches were estimated at 950 t·year-1 on average from 1950 to 1957 (Figure 3). Subsistence catches increasing since the early 1960s to a peak of 5,600 t in 2000, followed by a slight decrease to 5,400 t in 2010 (Figure 3).Artisanal fisheriesArtisanal catches were estimated at around 6,600 t·year-1 on average in the 1950s, before they increased drastically to a peak of 52,300 t in 1966 driven by increasing Popo fisher catches and migrations into the Congo (Figure 4). Artisanal catches collapsed to less than 13,000 t in 1967 mainly due to the major decrease in Popo catches as fishers were expelled and their fishing gear confiscated (Figure 4). Catches increased thereafter to 37,300 t in 1976 and then increased again with the Popo fishers returning to the Congo (Figure 4). Catches declined slowly since the 1980s to less than 18,000 t in 2001 and then increased slightly with the increasing number of canoes to around 32,400 t in 2008 before they decline to 27,600 t in 2010 (Figure 4).Industrial domestic fisheriesIndustrial catches from the EEZ of the Congo increased from 2,300 t in 1950 to a peak of around 38,400 t in 1975 driven by increasing shrimp trawl catches and a high number of shrimp trawlers (Figure 5). Industrial catches from the coast of the Congo decreased thereafter, with a decreasing catch to less than 11,000 t in 2010, dominated by purse-seiners catches (Figure 5). In contrast, Congolese catches from outside the Congolese EEZ increased to a peak of around 37,400 t in 1968 before declining to very low levels by the late 1980s (Figure 6), after which the fleet operated mainly within Congolese waters.Domestic discardsDiscards by the Congolese fleets followed the same pattern than demersal and shrimp trawl catches, increasing from low levels in the 1950s to a peak of around 62,000 t in 1980, and then matching the decline of the demersal and shrimp trawl fisheries, and reaching less than 1,100 t in 2010 (Figure 7).Industrial foreign catches (China)Industrial catches by the Chinese fleet unauthorized to operate in Congo increased from low levels when the fishery began in 2001 to around 14,800 t in 2010 (Figure 8). Similarly, legal catches by China, i.e., catches by vessels authorized to operate within the Congolese EEZ, and discards increased from low levels in 2001 to around 21,200 t and 13,900 t in 2010 respectively (Figure 8).Figure 6.  reconstructed total industrial catches by EEZ of the Congolese shrimp trawl fleet, 1950-2010.Figure 5.  Reconstructed total industrial catches by gear type from the Congo.Figure 4.  Reconstructed total artisanal Popo and villi catches from the Congo, 1950-2010.Congo (Brazzaville) - Belhabib and Pauly 101Reconstructed total catchReconstructed total domestic catches from the Congolese EEZ increased from around 7,100 t in 1950 compared to 5,000 t reported to the FAO to a peak of 99,300 t in 1977 compared to around 15,400 t reported to the FAO, driven by high shrimp and demersal trawl catches (Figure 9a). Catches declined thereafter to remain relatively constant at 30,500 t·year-1 on average during the 1990s and then increased slowly to 45,000 t in 2010 compared to around 34,700 t reported to the FAO (Figure 9a). Overall reconstructed domestic catches from the Congolese EEZ illustrate a declining pattern as opposed to increasing reported landings illustrated by the FAO data (Figure 9a).Taxonomically, African spider shrimp (Nematocarcinus africanus; 13%) and other crustaceans (13%) along with sardinella spp. (25%) represented most of the catch in the past. More recently, sardinella spp. still compose a high proportion of the catch along with some other 70 demersal and small pelagic species (Figure 9b).discussionReconstructed total catches from the Congo within its EEZ were on average 2.8 times the data supplied to the FAO. Under-reporting was at its highest in the 1970s and 1980s, before the creation of the catch statistics division by ORSTOM. Clearly, this under-reporting contributed to biasing the trend illustrated by official data which showed continuous increase in catch, despite major signs of over-exploitation (WCS 2011).Indeed, while migrant fisheries catches (mainly by ethnic Popo fishers) were limited by governmental restrictions and entry permits, the size of migrant pirogues has shown a steady increase from around 8 m in the mid-1950s, to 9.3 m in the mid-1970s and 11.35 m in the early 1980s, along with the generalization of the motorization in 1960 for migrant pirogues (Gobert 1985, 1986). This is a common strategy used by fishers to expand their fishing grounds and capacity, as it also occurs elsewhere in West Africa (Belhabib et al. 2014a). Similarly, the length of the fishing net increased from 135 m in the mid-1950s to 275 m in the 1972 to around 1,000 m today (Gobert 1985). This extension is an adaptation to decreasing catches (Kibelolo 2003; InfoPêche 2008; Anon. 2011b). Despite expanding effort, artisanal fisheries in Congo are facing reduced catches per fisher and shrinking fish sizes (Nguinguiri and Katz 1996). Moreover, finding new fishing grounds today is very difficult because of coastal development and oil production facilities (Watson and Morato 2013), which reduced the exploitable areas by 2/3 (Maloueki 2005). This certainly contributes to the unsustainable levels of small-scale fisheries resources that the Congo face today (WCS 2011). Not only does this raise concerns for Congolese fisheries management, but it also place additional pressures on other food alternatives as people seek to replace seafood in their diet, i.e., people find alternatives in bush-meat, they put “additional pressure on hippopotamus, crocodiles, turtles and dolphins” (WCS 2011).020406080100Catch (t x 103)Industrialsupplied to FAOSubsistenceDiscardsArtisanala)0204060801001950 1960 1970 1980 1990 2000 2010Catch (t x 103)YearSardinella spp.OthersPseudotolithus spp.CrustaceanNematocarcinus africanusb)Figure 8.  Reconstructed total industrial foreign catches by China in the EEZ of Congo, 1950-2010.Figure 7.  Reconstructed discards by the Congolese fleet, 1950-2010.Figure 9.  Reconstructed total catches for the Congo a) by sector and b) major taxa, 1950-2010. 102Industrial fisheries, notably foreign Chinese fleets operating in the Congo, are often regarded as culprits when discussing issues of over-exploitation. This goes in hand with anecdotal evidence that the industrial effort is too high in the Congo. While the number of industrial domestic vessels and their capacity remains within the boundaries established for sustainable industrial fisheries, i.e., less than 30 vessels (Maloueki 2005), China deploys on average 70 fishing vessels (legally) in Congolese EEZ, which may render moot the management strategy for sustainable fisheries in the Congo. Indeed, industrial fisheries along with climate change are likely to be the strongest challenge for Congolese fishers in the next few years (Bassi and Lombardi 2013) and efforts to control are required.The small-scale fisheries of the Congo operate within the context of strong traditional beliefs, which contribute to reshaping the fishing effort of the migrant artisanal fishers (Boungou 1986). Yet, despite strong traditional regulations aimed at maximizing fisheries output while maintaining the resource and continuous adaptive efforts, artisanal fishing households are among the poorest in the Congo (Brugère et al. 2008). Moreover, declining fisheries put further pressure on education and health of children in the Congo, in spite of fishmongers (mainly women) putting a particular focus on their children’s education (Tati 2005) and health (Horemans and Kebe 2006).It is perhaps encouraging that alternative livelihoods, as perceived by the most vulnerable fishing coastal households all exclude fishing (Brugère et al. 2008), as it may allow for moving excess fishers onto non-fishing activities. But the main task for Congolese fisheries management is to control foreign industrial fishing remains, without which all their other efforts will be in vain.acknoWledGementsThis is a contribution of the Sea Around Us, a scientific collaboration between the University of British Columbia and the Pew Charitable Trusts.reFerencesAnon. (2006) Enquête congolaise auprès des ménages pour l’evaluation de la pauvreté (ECOM 2005). Ministère du Plan, de l’Aménagement du Territoire et de l’Integration économique, Brazzaville, Congo. 141 p.Anon. (2011a) Annuaire statistique du Congo 2009. Ministère de l’Economie, du Plan, de l’Aménagement du Territoire et de l’Intégration, Pointe-Noire, Congo. 414 p.Anon. (2011b) Opportunités et obstacles au commerce durable intra et extra régional des produits de la pêche maritime et continentale en Afrique Centrale. European Union, Brussels. 103 p.Backiny-Yetna P and Zodon Q (2009) Profil et perceptions de la pauvreté en République du Congo en 2005. 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The so-called «popo» fishermen. pp. 283-296 In Haakonson J and Diaw C (eds.), Fishermen’s migrations in West Africa 36. IDAF, Cotonou.Nguinguiri V and Katz E (1996) Perception de l’impact de l’homme sur les ressources naturelles chez les vili du Congo. pp. 143-154 In Baudot P, Bley D, Brun B, Pagezy H and Vernazza-Licht N (eds.), Impact de l’homme su les milieux naturels, Perceptions et mesures. Editions de Bergier, Chateauneuf de Grasse.Poinsard F (1969) La pêche au chalut à Pointe-Noire. pp. 381-390 In UNESCO (ed.), L’océanographie et les ressources halieutiques de l’Atlantique tropical. UNESCO, Paris.Tati G (2005) Entrepreneurial African female migrants at the informal-formal interface of the urban economy: Are gender asymmetries modified by entrepreneurship?, University of Western Cape, Bellville, South Africa. 16 p.The World Bank (1997) Congo, poverty assessment. The World Bank. 58 p.Transparency International (2010) Indice de perception de la corruption 2010. Transparency International, Berlin. 12 p.Tvedten I (1990) The difficult transition from subsistence to commercial fishing. The case of the Bijagos of Guinea-Bissau. MAST 3(1): 119-130.Vennetier P (1968) Pointe-Noire et la facade maritime du Congo-Brazaville. ORSTOM, Pointe-Noire, Congo. 485 p.Watson RA and Morato T (2013) Fishing down the deep: Accounting for within-species changes in depth of fishing. Fisheries Research 140: 63-65.WCS (2011) Best of the wild: wildlife conservation society and the Congo basin coast. Wildlife Conservation Society, Bronx, New York. 18 p.Yengo P (2006) La guerre civile du Congo-Brazzaville, 1993-2002:» chacun aura sa part». Karthala Editions. 104Appendix Table A1.  FAO landings vs. reconstructed total catch (in tonnes), and catch by sector (with discards shown separately) for the Republic of Congo, 1950-2010.Year FAO landings Reconstructed total catch Industrial Artisanal Subsistence Discards1950 5,000 7,110 2,340 3,820 907 421951 5,000 7,290 2,310 4,020 916 421952 5,000 10,960 5,720 4,210 928 1031953 5,500 12,250 6,790 4,400 940 1221954 5,500 13,520 7,830 4,600 953 1411955 6,000 14,760 8,850 4,790 967 1591956 6,000 17,920 9,840 6,920 982 1771957 7,000 21,050 10,800 9,050 998 1941958 7,000 24,350 11,740 11,190 1,216 2111959 7,500 22,240 7,130 13,140 1,444 5211960 7,500 26,680 8,890 15,090 1,756 9381961 7,500 31,980 10,620 17,990 2,024 1,3461962 8,600 36,030 11,290 20,710 2,305 1,7271963 8,500 41,030 12,950 23,530 2,432 2,1181964 9,600 53,720 14,950 33,700 2,565 2,5001965 9,500 64,270 15,420 43,290 2,705 2,8561966 9,700 74,190 15,830 52,300 2,851 3,2041967 9,100 35,500 16,010 12,940 3,003 3,5431968 9,100 41,140 19,760 13,180 3,054 5,1491969 8,900 43,590 20,540 13,380 3,106 6,5701970 9,401 48,000 23,250 13,540 3,161 8,0471971 10,013 57,570 26,350 18,420 3,219 9,5751972 17,527 69,510 32,150 22,940 3,279 11,1511973 15,204 78,230 35,030 27,090 3,340 12,7721974 15,719 85,600 36,900 30,870 3,401 14,4371975 15,104 91,950 38,390 34,280 3,460 15,8161976 17,870 97,830 37,580 37,330 3,519 19,4071977 15,365 99,300 36,960 35,900 3,577 22,8601978 16,297 85,850 36,260 19,920 3,634 26,0361979 19,630 93,090 38,060 22,550 3,692 28,7831980 20,966 95,700 36,140 24,890 3,751 30,9211981 17,665 92,440 31,960 26,920 3,812 29,7431982 18,836 87,210 27,500 28,660 3,874 27,1741983 21,708 82,400 23,550 31,490 3,936 23,4161984 19,308 71,030 19,650 28,640 3,997 18,7501985 16,340 59,520 15,950 25,940 4,056 13,5751986 17,993 48,560 12,650 23,400 4,114 8,3971987 22,469 53,040 12,040 30,600 4,169 6,2271988 22,378 44,210 9,210 26,950 4,224 3,8251989 21,708 38,680 7,480 25,610 4,277 1,3041990 21,954 36,520 6,710 23,890 4,328 1,5981991 18,371 30,860 6,230 18,370 4,442 1,8151992 18,944 29,500 5,730 17,290 4,556 1,9331993 18,899 28,400 5,750 16,200 4,671 1,7771994 17,913 28,700 5,870 16,230 4,790 1,8151995 18,965 29,260 5,970 16,530 4,912 1,8471996 19,600 29,790 6,080 16,800 5,040 1,8711997 19,095 30,290 6,180 17,050 5,173 1,8901998 17,500 30,760 6,270 17,280 5,307 1,9021999 18,241 31,180 6,350 17,480 5,438 1,9072000 20,520 31,570 6,430 17,660 5,564 1,9072001 22,729 32,900 7,230 17,940 5,506 2,2282002 22,433 38,830 7,410 23,870 5,440 2,1092003 22,683 34,570 6,750 20,610 5,370 1,8412004 26,686 37,950 9,320 22,250 5,304 1,0802005 22,116 42,120 7,960 28,370 5,243 5532006 28,082 38,040 4,280 27,560 5,275 9292007 29,096 38,840 4,270 28,390 5,313 8682008 24,742 42,960 4,430 32,360 5,350 8172009 32,833 41,060 6,040 28,120 5,380 1,5162010 34,686 44,960 10,870 27,620 5,401 1,068Congo (Brazzaville) - Belhabib and Pauly 105Appendix Table A2. Reconstructed total catch (in tonnes) by major taxonomic group for the Republic of Congo, 1950-2010. “Others” contain 57 additional taxonomic categories.Year Sardinella spp. Nematocarcinus africanus Crustacean Pseudotolithus spp. Others1950 4,910 0 1 1,060 1,1401951 5,080 0 1 1,070 1,1401952 5,700 0 4 2,150 3,1101953 6,080 0 5 2,470 3,6901954 6,330 0 6 2,840 4,3501955 6,610 0 6 3,240 4,9001956 8,520 0 7 3,660 5,7301957 10,760 0 8 3,960 6,3201958 12,930 0 9 4,330 7,0801959 14,640 381 588 2,640 3,9901960 17,010 755 1,161 2,990 4,7601961 20,230 1,121 1,722 3,350 5,5501962 23,240 1,480 2,270 3,420 5,6301963 26,240 1,830 2,808 3,760 6,3901964 36,560 2,173 3,334 4,270 7,3801965 44,320 2,509 3,848 4,570 9,0301966 53,120 2,836 4,350 4,610 9,2701967 15,650 3,156 4,839 4,420 7,4401968 17,310 4,658 7,137 4,440 7,5901969 16,550 5,987 9,172 4,530 7,3601970 15,120 7,368 11,287 5,800 8,4201971 21,530 8,797 13,476 5,140 8,6301972 28,380 10,272 15,733 6,140 8,9901973 34,790 11,791 18,054 4,960 8,6401974 38,040 13,349 20,443 4,700 9,0701975 40,490 14,641 22,420 5,050 9,3501976 42,600 18,003 23,072 4,880 9,2701977 40,730 21,236 23,459 4,790 9,0801978 21,900 24,210 23,552 6,050 10,1301979 28,280 26,782 23,318 5,160 9,5601980 26,680 28,800 22,735 6,060 11,4301981 31,260 27,719 20,077 5,140 8,2301982 34,410 25,337 16,933 3,630 6,9001983 35,560 21,828 13,573 3,580 7,8501984 33,760 17,470 10,183 3,360 6,2501985 30,890 12,635 6,958 2,220 6,8201986 27,940 7,797 4,098 1,980 6,7401987 34,700 5,774 2,908 2,420 7,2401988 29,610 3,534 1,676 2,690 6,6901989 24,970 1,181 577 3,380 8,5601990 22,200 1,466 718 3,340 8,7901991 18,500 1,674 1,034 2,600 7,0601992 16,830 1,789 1,064 2,570 7,2501993 15,360 1,637 980 2,640 7,7801994 18,760 1,668 672 1,230 6,3701995 19,500 1,692 999 1,000 6,0701996 19,340 1,710 1,288 1,000 6,4601997 19,600 1,722 1,048 1,060 6,8601998 20,070 1,728 1,176 1,150 6,6301999 20,130 1,728 1,155 1,170 7,0002000 19,790 1,722 1,333 1,180 7,5402001 17,980 2,008 1,572 2,080 9,2602002 21,490 1,912 1,733 3,130 10,5602003 15,240 1,653 1,820 4,400 11,4602004 21,200 941 1,327 3,430 11,0502005 24,000 446 1,181 4,340 12,1602006 18,270 843 2,089 3,460 13,3802007 17,130 795 1,490 3,140 16,2802008 28,370 747 1,769 2,670 9,4002009 19,700 1,401 2,269 3,470 14,2202010 18,050 982 2,630 4,170 19,130 106Congo (ex-Zaïre) - Belhabib et al. 107an attemPt at reconstructinG the marine Fisheries catches in the conGo  (ex-Zaïre), 1950 to 20101Dyhia Belhabib, Sulan Ramdeen and Daniel PaulySea Around Us, Fisheries Centre, University of British Columbia,2202 Main Mall, Vancouver, BC, V6T 1Z4, Canadad.belhabib @fisheries.ubc.ca; s.ramdeen @fisheries.ubc.ca; d.pauly @fisheries.ubc.caabstractThe catches of the marine fisheries of the Democratic Republic of the Congo ‘DRC’, formerly known as Zaïre (here: ‘Congo (ex-Zaïre)’, were estimated, in spite of low availability of quantitative data and pertinent literature. Reconstructed total catches were estimated to be at least twice as much as the data supplied to FAO on behalf of the Congo (ex-Zaïre), with around 764,000 tonnes between 1950 and 2010 compared to 338,000 tonnes reported to the FAO on behalf of the Congo (ex-Zaïre), of which about 70% were taken by the small-scale fisheries. The reconstructed catches illustrate the fact that while political turmoil caused the nascent industrial fisheries to fold, wars and other conflicts contributed to increasing the contribution of small-scale fisheries to total fisheries removals, thus demonstrating the resilience of small-scale fisheries and their crucial role in contributing to the food security of coastal communities.introductionThe Democratic Republic of The Congo (here alternatively referred to as ‘DRC’ and ‘Congo (ex-Zaïre)’ is located in West central Africa, bordered by nine countries: the Republic of the Congo, the Central African Republic, Southern Sudan, Uganda, Rwanda, Burundi, Tanzania, Zambia and Angola, with Lake Tanganyika, the second largest freshwater lake in the world, forming its eastern border. Although Congo (ex-Zaïre) is one of the largest countries of Africa, its coastline is extremely narrow, with a straight-line extent of 40 km from North to South.Historically, the Congo (ex-Zaïre) suffered from a succession of political disasters; repression, corruption, and violence are words that occur commonly when retracing the history of the country. Much of this sad story is yet another case of the ‘curse’ affecting countries rich in natural resources, in this case minerals such as diamonds and rare earths, as required in computer manufacturing. Since independence (in 1960), the country changed its name four times, suffered two major wars and a multitude of lesser, but still violent conflicts2. As a result, nearly 2 million people were displaced; over 5 million people alone died due to the prolonged conflict between 1998 and 2007, described as the deadliest conflict after World War II, and one that involved thousands of child soldiers (Weijs et al. 2012). The “debrouillez-vous” (approx. “you-are-on-your-own”) policy declared by president Mobutu in response to his government’s inability to pay public salaries, and who redirected public funds to pay off his cronies during his long tenure (1960 to 1997), led to a tremendous growth of the informal economy.The decline of the formal economy and increase of poverty coincided with the “Zaïrianization” of the country in the 1970s, where many industries collapsed. In spite of a recent slight improvement, around 71% of the population still lives under the poverty threshold of 1 US$ per day, which is far behind the level of 1960 when the country gained independence from Belgium (Weijs et al. 2012). The country today ranks 168 over 169 in the human development index (UNDP 2010). Most of the economy, being informal, is undocumented, and this applies to fishing as well 1 Cite as: Belhabib, D., Ramdeen, S. and Pauly, D. (2015) An attempt at reconstructing the marine fisheries catches in the Congo (Ex-Zaïre), 1950-2010. pp. 107-114. In: Belhabib, D. and Pauly, D. (eds). Fisheries catch reconstructions: West Africa, Part II. Fisheries Centre Research Reports vol.23(3). Fisheries Centre, University of British Columbia [ISSN 1198-6727].2  http://www.ucdp.uu.se/gpdatabase/gpcountry.php?id=38&regionSelect=2-Southern_Africa [Accessed on 22/10/2013].Figure 1.  Map of Congo (ex-Zaïre) and its Exclusive Economic Zone (EEZ). 108(Muzigwa Kashema 2006), although fishing ranks second in household activities, right after agriculture (Weijs et al. 2012). Weijs et al. (2012) write on this: “With regards to data availability and quality: this investigation finds a strong bias towards humanitarian issues and eastern DRC, a lack of studies that aim to bring underlying structures and dynamics into the picture, as well as a lack of focus on local needs. Additionally, there is little centralised data collection and exchange of findings, critical appraisal of available data, and a lack of methodologically sound, robust scholarly research. Local research capacity is lacking, there is a gap between research and policy… The reliability of official figures is questionable, but there are few alternatives.”The present reconstruction is proposed as a complement to official data, which fail to document the contribution of coastal fisheries, often overlooked, to food security in the DRC. This is viewed as particularly important as Congo (ex-Zaïre) remains “chronically” food insecure (OCHA 2011).methodsOften the few literature sources describing the fisheries Congo (ex-Zaïre) refer to the two main sectors, industrial and artisanal fisheries. However, subsistence fishing is mentioned by numerous sources, notably when describing the livelihood strategies of coastal communities and/or bushmeat surveys (Lagoin and Salmon 1970; de Merode et al. 2004; Weijs et al. 2012). Due to the narrowness of the DRC’s coastline, and thus its small Exclusive Economic Zone (EEZ), foreign fishing fleets are relatively small. However, their presence cannot be overlooked, as the impact of foreign fishing in the EEZ of other West African countries – even small ones, such as The Gambia – is extremely important.Farming and related activities constitute the main livelihood activities for 97% of the population in the Bas Congo, a province bordered by the Congo River and the Atlantic coast, of these farming and related activities 20% is fishing (Weijs et al. 2012).. Although there is a large overlap between artisanal and subsistence fisheries in the DRC, we rely on the nature of the craft to identify ‘artisanal’ fishing, whose main purpose is to catch fish for sale, as opposed to subsistence fishing, whose main purpose is household consumption. Thus here, fisheries involving canoes are considered artisanal, while all land-based fishing is considered subsistence fishing.Artisanal catchesThe marine artisanal fisheries of the Congo (ex-Zaïre) are not well monitored and reported upon in official statistics (Weijs et al. 2012), and thus, their catches are here estimated indirectly. The artisanal catch per unit of effort was estimated by dividing an observed localized catch of 150 tonnes (Lagoin and Salmon 1970) by the number of units involved, i.e., 20 canoes, i.e., 7.5 t∙canoe-1 for 1967. We assumed this CPUE was constant between 1950 and 1967, and 10% lower in 2010 compared to the 1967 CPUE given the high fishing pressure by the many small-scale boats operating in the small EEZ of the DRC. We interpolated linearly CPUE estimates to complete the time series. Effort estimates were available for 1967 (588 canoes, Lagoin and Salmon 1970), 1994 (800 canoes, Horemans 1996) and an estimated 3,230 fishers along the Atlantic coast, which translates into 1,615 canoes (assuming two fishers per canoe) for 2008, of which only 5% are motorized (Mavinga Ngembo 2008). We assumed the effort was 10% lower in 1950 relative to 1967, given a lower numbe