UBC Faculty Research and Publications

Preliminary mass-balance model of Prince William Sound, Alaska, for the pre-spill period, 1980-1989 Dalsgaard, Anne Johanne Tang; Pauly, Daniel; Okey, Thomas Anthony 1997

Your browser doesn't seem to have a PDF viewer, please download the PDF to view this item.

Item Metadata

Download

Media
52383-FCRR_1997_5-2.pdf [ 25.32MB ]
Metadata
JSON: 52383-1.0074775.json
JSON-LD: 52383-1.0074775-ld.json
RDF/XML (Pretty): 52383-1.0074775-rdf.xml
RDF/JSON: 52383-1.0074775-rdf.json
Turtle: 52383-1.0074775-turtle.txt
N-Triples: 52383-1.0074775-rdf-ntriples.txt
Original Record: 52383-1.0074775-source.json
Full Text
52383-1.0074775-fulltext.txt
Citation
52383-1.0074775.ris

Full Text

Fisheries Centre Research Reports 1997 Volume 5 Number 2 Preliminary Mass-Balance Model of Prince William Sound, Alaska, for the Pre-Spill Period, 1980-1989 Fisheries Centre, University of British Columbia, Canada ISSN 198 6727 Preliminary Mass-Balance Model of Prince William Sound, Alaska, for the Pre-Spill Period, 1980-1989 Fisheries Centre Research Reports Preliminary Mass-Balance Model of Prince William Sound, Alaska, for the Pre-Spill Period, 1980-1989 by Johanne Dalsgaard and Daniel Pauly with editorial contributions by Thomas A. Okey Published by The Fisheries Centre, University of British Columbia 2204 Main Mall, Vancouver, B.C. Canada V6T 1Z4 ISSN 1198-6727 iii ABSTRACT A mass-balance model of trophic interactions among the key func-tional groups of Prince William Sound (PWS), Alaska, is presented, based mainly on published data re-ferring to the period from 1980 to 1989, before the Exxon Valdez oil spill. The functional groups explicitly in-cluded in the model are: detritus, phytoplankton, macroalgae, small zooplankton, large zooplankton, epifaunal benthos, infaunal benthos, intertidal invertebrates, demersal fish, herring, salmon fry from hatcheries, wild salmon fry, salmon, other pelagic fishes, birds, sea ot-ters, other resident marine mam-mals, and transient marine mam-mals. Balancing of the model required few steps that went beyond the available data; nevertheless, the model is pre-liminary in that additional ecological information is available on PWS and the functional groups of the organ-isms therein. Much of this informa-tion is not yet incorporated in the model. However, the purpose of this model is to serve as basis for further work, illustrated in two authored appendices, one showing the close match between the trophic levels estimated by the models and esti-mates based on stable isotope ra-tios, and the other documenting how inferences on the dynamics of PWS may be derived from its static representation. v Director's Foreword The first Mass-balance models of marine ecosystems in the North-eastern Pacific, covering the Alaska Gyre, the shelf of southern British Columbia, and the Strait of Georgia, were constructed in November of 1996 at a workshop held at the UBC Fisheries Centre (see Fisheries Cen-tre Research Report 1996, Vol. 4, No 1). The present report extends that work by drawing up a preliminary ecosystem model of Prince William Sound, Alaska, in its most likely form prior to the Exxon Valdez oil spill in 1989. ECOPATH models are forgiving in that they can be im-proved and enhanced using new information without having to be completely reinvented. This report puts forward a preliminary model, based on data from published litera-ture, whose sole purpose is to lead to an improved model based on more complete and more accurate data from the recent intensive work in Prince William Sound. For many years single species stock assessment of fisheries has reigned supreme and separate from main-stream marine ecology, but, for ma-rine conservation, this approach and lack of integration has been con-spicuously unable to answer the crucial questions of our time. These questions include the interplay of predators, competitors and prey with human fisheries, the impact both acute and chronic of marine pollution, and the effects of pro-gressive shoreline development on the stability and value to human society of coastal ecosystems. ECOPATH is a straightforward trophic modeling approach to ecosystems, that balances the budget of biomass production and loss for each com-ponent in the system by solving a set of simultaneous linear equa-tions. The ECOPATH approach is the only ecosystem model to obey the laws of thermodynamics. It is based on pioneering work by Dr Geoffrey Polovina from Hawaii in the early 1980s, and developed by Dr Daniel Pauly when he was at ICLARM, Ma-nila, and Dr Villy Christensen from Denmark. Dr Carl Walters at the Fisheries Centre recently developed ECOSIM a dynamic version of ECOPATH. A Preliminary Mass-Balance Model of Prince William Sound\ Alaska, for the Pre-Oilspill Period, 1980-1989 i s the latest in a series of research re-ports published by the UBC Fisheries Centre. The series aims to focus on broad multidisciplinary problems in fisheries management, to provide an synoptic overview of the founda-tions and themes of current re-search, to report on work-in-progress, and to identify the next steps and ways that research may be improved. Edited reports of the workshops and research in progress are published in Fisheries Centre Research Reports and are distrib-uted to all project or workshop par-ticipants. Further copies are avail-able on request for a modest cost-recovery charge. Please contact the Fisheries Centre mail, fax or email to 'office@fisheries.com'. Tony J. Pitcher ? Professor of Fisheries Director, UBC Fisheries Centre vi Table of Contents A B S T R A C T D I R E C T O R ' S F O R E W O R D V I T A B L E O F C O N T E N T S VII LIST O F EXHIBITS VIII I N T R O D U C T I O N 1 PRINCE WILLIAM SOUND 1 THE ECOPATH APPROACH AND SOFTWARE 3 P R E L I M I N A R Y M O D E L I N P U T S 5 PHYTOPLANKTON 5 MACROALGAE 6 DETRITUS 7 ZOOPLANKTON 7 BENTHIC INVERTEBRATES 8 INTERTIDAL INVERTEBRATES 9 DEMERSAL FISH , 1 0 HERRING 1 1 SALMON FRY 1 1 ADULT SALMON 1 2 MISCELLANEOUS SMALL PELAGIC FISHES 1 3 BIRDS 1 3 SEA OTTERS 1 6 OTHER MARINE MAMMALS 1 6 B A L A N C I N G T H E M O D E L 1 7 R E S U L T S A N D D I S C U S S I O N 2 1 A C K N O W L E D G E M E N T S 2 5 R E F E R E N C E S .. . . . . . 2 6 A P P E N D I X 1 3 2 A P P E N D I X 2 3 3 vii List of exhibits Box 1. Basic equations and assumptions of the Ecopath approach 4 Figure 1. Map of Prince William Sound, Alaska 2 Figure 2. Simplified flowchart of Ecopath model of PWS 22 Figure 3. Mixed trophic impacts of groups in the PWS ecosystem model 23 Figure 4. Results of an Ecosim run of the PWS file generated by Ecopath 24 Table 1. Macroalgae biomass estimates for different PWS habitats... 6 Table 2. Mean Settled zooplankton volume in upper 20m 7 Table 3 a. Estimated biomass of benthic infauna, in PWS 8 Table 3b. Estimated biomass of benthic epifauna, PWS 9 Table 4. Q/B estimates and diet matrix (% weight) of PWS zoobenthos 9 Table 5. Estimated biomass of demersal fish species in PWS, 1989 10 Table 6. Mean demersal fish catch from PWS, 1987-1988 10 Table 7. Average harvest of herring in PWS from 1980 to 1988 11 Table 8. Characteristics of wild salmon fry, and hatchery released fry 12 Table 9. Harvest of salmon in PWS, 1980 to 1989 12 Table 10. Estimated standing stock of salmon in PWS 13 Table 11. Instantaneous oceanic mortality rates (Z) for salmon 13 Table 12. Population statistics of ducks overwintering in PWS 14 Table 13. Estimation of duck biomass in PWS, by season 14 Table 14. Diet matrix for selected ducks in Prince William Sound 14 Table 15. Seabird densities in PWS 15 Table 16. Diet matrix for the seabirds of PWS 15 Table 17. Diet composition of sea otters in Montague Strait, PWS 16 Table 18. Population statistics of marine mammals in PWS 17 Table 19. Basic statistics for transient marine mammals in PWS 17 Table 20. Basic statistics for resident marine mammals in PWS 17 Table 21. Basic statistics for pinnipeds in PWS 18 Table 22. Diet matrix for the marine mammals of PWS 18 Table 23. Basic estimates and trophic levels of groups in PWS model 19 Table 24. Diet matrix of trophic interactions in PWS 20 viii INTRODUCTION Prince William Sound Prince William Sound (PWS), located near the northern apex of the Gulf of Alaska and renown for its wildlife and once pristine environment, be-came the center of the world's atten-tion on March 24, 1989, when the supertanker Exxon Valdez ran aground on Bligh Reef, in the North-eastern part of the Sound (Fig.l), spilling over 40 million liters of crude oil - the largest oil spill in United States history. During the first two weeks following the spill, the oil was transported the south-west through the western part of PWS, and into the Gulf of Alaska, along the Kenai Peninsula, killing thousands of seabirds, marine mammals and vast numbers of fish and invertebrates (Loughlin 1994). Early assessments of the impact of the Exxon Valdez oil spill (EVOS) were presented in the proceedings, edited by Rice et al. (1996), of a symposium held from February 2 to 5, 1993. Major efforts have been made since, under the guidance of the Exxon Valdez Oil Spill Trustee Council, to study the long-term ef-fects of the EVOS, and a second gen-eration of assessments is now emerging which will address ques-tions left open at the 1993 sympo-sium. The present report is designed to support these efforts by presenting a preliminary version of what will be more precise and realistic models of trophic interactions among the ma-jor functional groups of PWS, for the periods before and after the spill. These models will incorporate as much of the relevant data from both periods as possible, for a large number of functional groups. However, the model presented herein, and the assumptions used for its construction are prelimi-nary. We are aware of the exis-tence of better data for most of the functional groups in the model. A primary goal of the current effort is a collaborative partnership among PWS experts to incorporate these better data thereby maximiz-ing the usefulness of the more de-tailed models, to be constructed in 1998. Pending these detailed models, the preliminary model presented here was assembled t o : 1) document the approach used in con-structing mass-balance models, and the type of data required; 2) introduce the Ecopath software for con-struction of such models; and 3) determine whether sufficient data are available for constructing a balanced model for the less investigated pre-spill period, and an improved model, covering the post-spill period. PWS consists of a central basin, with a maximum depth of 800 m, sur-rounded by islands, fjords, bays, and a large tidal estuary system (Fig. 1); the mean water depth is 300 m (Cooney 1993, Loughlin 1994). The semi-enclosed nature of PWS justi-fies the application of a modeling approach, such as Ecopath (Box 1), that assumes mass-balance among the various elements of the system, and limited (or at least well-quantified) exchanges with adjacent systems (see also contributions in Pauly and Christensen 1996). 1 "^ Mi Mil. in .v v. v .?". .v.v I'lI'MII II l IUP WI !? I PI B m S K I P M B ?SBfcMp HHBUK" m V,",, ,VV .vl'l^ i'V'lT'l'ry ;;.;..;.-.; y t : . j,'-?' "'? _?1-1 ? L-M Naked Ktf&f Island smm DaricJtsott Bay Mcdure Bay M S U f ^ i - i S|fi3??5|l ZrAjNff ^ P r x r i e e W i l l i a m S o u n d ^ ^ CsK^ia? ijariiT i-rcftes fesssssPSijiSa iriorfii i ^ p ^ tfinc A IM 6 reoJf 4 B F ?*irfl?cfl Gulf of Alaska D 10 20 Kilometers 147 W Figure 1. Map of Prince William Sound, Alaska, showing locations mentioned in the text (modified from Sturdevant et al.1996). 2 The Ecopath approach and soft-ware The Ecopath approach and software were initially developed by Polovina (1984, 1995), of the U.S. National Marine Fisheries Service (Honolulu Laboratory). V. Christensen and D. Pauly, then both at the International Center for Living Aquatic Resources Management (ICLARM), improved on this work (see Christensen and Pauly 1992a), and made it widely available in the form of a well-documented software for computer running MS-DOS (Christensen and Pauly 1992b), and later Windows (Christensen and Pauly 1995, 1996). Both versions allow rapid construction and verifi-cation of mass-balance models of ecosystems. The steps involved con-sist essentially of: (i) Identification of the area and period for which a model is to be constructed; (ii) Definition of the functional groups (i.e., 'boxes') to be in-cluded; (iii) Entry of a diet matrix, express-ing the fraction that each 'box' in the model represents in the diet of its consumers; (iv) Entry of food consumption rate, of production/biomass ratio or of biomass, and of fisheries catches, if any, for each box; (v) Balance the model, or modify entries (iii & iv) until input = output for each box; (vi) Compare model outputs (net-work characteristics, estimated trophic levels and other features of each box) with estimates for the same area during another period, or with outputs of the same model type from other, similar areas, etc. 3 Box 1. Basic equations, assumptions and parameters of the Ecopath approach The mass-balance modeling approach used in this workshop combines an approach by Polovina and Ow (1983) and Polovina (1984, 1985) for estimation of biomass and food consumption of the various elements (species or groups of species) of an aquatic ecosystem (the original 'ECOPATH') with an approach proposed by Ulanowicz (1986) for analysis of flows between the elements of ecosystems The result of this synthesis was initially implemented as a DOS soft-ware called 'ECOPATH II', documented in Christensen and Pauly (1992a, 1992b), and more re-cently in form of a Windows software, Ecopath 3.0 (Christensen and Pauly 1995, 1996). Unless noted otherwise the word 'Ecopath' refers to the latter, Windows version. The ecosystem is modeled using a set of simultaneous linear equations (one for each group i in the system), i.e. Production by (i) - all predation on (i) - nonpredation losses of (i) - export of (i) = 0, for all (i). This can also be put as P-M21 - P (1-EE) - EX = 0 ...1) where P. is the production of (i), M2. is the total predation mortality of (i), EE. is the ecotrophic efficiency of (i) or the proportion of the production that is either exported or predated upon, (1-EE) is the "other mortality", and EX. is the export of (i). Equation (1) can be re-expressed as B*P/B( - Z.B*Q/B.*DCu-P/B*Bi(l-EEi)-EXi =0 ... 1) B.*P/B.*EE. - ?B*Q/B.*DC. - EX. = 0 ...2) where B. is the biomass of (i), P/B. is the production/biomass ratio, Q/B. is the consump-tion/bioinass ratio and DC is the fraction of prey (i) in the average diet of predator (j). Based on (2), for a system with n groups, n linear equations can be given in explicit terms: B P/BjEE,- BiQ/BiDC1]-B2Q/B2DC21 - ... BnQ/B DCni - EX; = 0 B2P/B2EE2- B ^ D C ^ - B2Q/B2DC22 - ...-BnQ/BnDCn2- EX2 = 0 B P/B EE - B Q/B DC - B Q/B DC - ...-B Q/B DC - EX = 0 n n n In 2 ^ 2 2n n n nn n This system of simultaneous linear equations can be solved through matrix inversion. In Ecopath, this is done using the generalized inverse method described by MacKay (1981), which has features making it generally more versatile than standard inverse methods. Thus, if the set of equations is overdetermined (more equations than unknowns) and the equa-tions are not consistent with each other, the generalized inverse method provides least squares estimates which minimize the discrepancies. If, on the other hand, the system is undetermined (more unknowns than equations), an answer that is consistent with the data (although not unique) will still be output. Generally only one of the parameters B., P/B., Q/B, or EE. may be unknown for any group i. In special cases, however, Q/B. may be unknown in addition to one of the other parameters (Chris-tensen and Pauly 1992b). Exports (e.g., fisheries catches) and diet compositions are always re-quired for all groups. A box (or "state variable") in an Ecopath model may be a group of (ecologically) related species, i.e., a functional group, a single species, or a single size/age group of a given species. 4 These steps can be implemented easily if basic parameters can be estimated (see also Box 1), especially as numerous well-documented ex-amples exist of Ecopath applications to aquatic ecosystems (see Pauly and Christensen 1993, and contributions in Christensen and Pauly 1993). We refer here frequently to three eco-systems that have much in common with PWS (the Strait of Georgia, the coast of British Columbia, and the Alaska gyre), documented through the contributions in Pauly and Christensen (1996), and from which many parameter estimates were taken. In the following pages, details are provided, by functional group, on how items (ii) to (vi) were imple-mented, following definition of the period (1980-1989) and area to be modeled (Fig 1). This is then followed by two authored appendices, by Kline and Pauly (1997; Appendix 1) and Pauly and Dalsgaard (1997; Appendix 2), illustrating some of the possible follow ups to the preliminary model documented here. PRELIMINARY MODEL INPUTS Phytoplankton The phytoplankton community in PWS is usually dominated by dia-toms. However, Goering et al. (1973) found that in Valdez Arm (Fig. 1), t he f lagellate Phaeocystis pouchetii was numerically dominant during April; also, during the less produc-tive July conditions, the phytoplank-ton community was dominated by the dinoflagellate Ceratium lon-gipes. Detailed seasonal data on phyto-plankton growth exist for selected areas of PWS. Chi. a concentrations and carbon production were meas-ured bimonthly from May 1971 to April 1972 in Port Valdez and Val-dez Arm. A typical spring-bloom sequence was found in which both standing crop and primary produc-tion increased rapidly in April, de-pleting nitrate from the upper water layers. Production then de creased during the reminder of the Summer, then increased again - at least in several areas - in the Fall (Sambrotto and Lorenzen 1986). The mean yearly primary production of ~185 gC m 2 estimated by Sam-brotto and Lorenzen (1986), may be assumed to apply to the whole of PWS (Cooney 1986), as the range is 150-200 g C m2-year1 (T. Cooney, pers. comm.). Assuming 0.1 gC ? lg ww, an annual primary production of 185 gC ? m 2 equals 1850 t ww ? km2 ? year1. Olivieri et al. (1993) estimated the P/B ratios of large diatoms and small phytoplankton (cells < 5 nm; including cyanobacteria and flagel-lates) to range from 125 to 255 year1, with a mean of 190 year1. From this, the phytoplankton bio-mass can be estimated as (1850 t ww-km2 year1) / (190 year1) - 10 t ww ? km2. 5 Macroalgae In PWS, dense macrolagal assem-blages are typical in the shallow subtidal zone, which extends from the intertidal zone to depths of about 20m (Dean et al. 1996). Dean et al. (1996) compared the density and biomass of subtidal macroalgae in oiled versus non-oiled (control) sites in PWS one year after the Exxon Valdez oil spill. While the relative species com-position of these assem-blages appeared to have changed, the authors' study revealed no differ-ences in total density, biomass, or percent cover. These results pro-vide some justification for using the biomass values of this study's con-trol locations for a pre-spill baseline reference Use of these values as-sumes that they are representative of the shallow subtidal zone of the entire PWS for the entire decade from 1980 to 1989, prior to the oil spill. Three type of habitats were identi-fied by Dean et al. (1996): 1. Agarum-Laminaria beds in bays(2-llm, ll-20m); 2. Agarum-Laminaria beds on points (2-1 lm, ll-20m); and 3. Nereocystis beds (2 -8m). It is assumed here that each of these habitats cover 1/3 of the shallow subtidal zone (0 - 20 m) of PWS. Furthermore, we assume that the shallow subtidal zone is 1/10 of the surface area of PWS. Since PWS has a surface area of approximately 8800 km2, the shallow subtidal zone is 880 km2 . These assumptions are being revised during the next itera-tion to account for areas with no kelp cover and by decreasing the areal proportion of shallow subtidal zone in PWS using GIS measure-ments. Dean et al. (1996) found Agarum cri-brosum a n d Lami-naria saccharina t o be the dominant subtidal macroal-gae in sheltered bays. Generally, these two species constituted more than 90% of total macroalgal bio-mass. Agarum cribrosum also dominated on exposed points (more than 60 % in terms of number of individuals). Less abundant algae were Laminaria saccharina a n d L. groenlandica. Nereocystes habitats are located on exposed sites, and the algal diversity was higher than in the other two habitats. The kelp forest structure at these locations consists of a canopy of Nereocystes luetkeana w i t h a n understory of L. groenlandica (61 % of t he b iomass ) , L. yezoensis, Pleu-rophycus gardneri, and A. cribro-sum. Based on the aforementioned as-sumptions, the biomass of macroal-gae was calculated to be 3,967 g m2 for 880 km2 of shallow subtidal area; re-expressed for the PWS as a whole, this corresponds to ~ 400 t ? km2. Table 1. Macroalgae bio-mass estimates for differ-ent PWS habitats3'. Biomass Habitats (g ww ? m2) Shallow Deeper Bays 1,766 529 Points 2,690 678 Nereocystis 6,240 -Means 3,565 402 a) Modified from Dean et al. (1996). 6 Estimates of the P/B ratio of PWS macroalgae were not found. The value of 4.4 year1 used here, per-taining to Laminaria beds in the North Atlantic, is from Brady-Campbell et al. (1984). Detritus Rough estimates of the standing stock of detritus in marine ecosys-tems may be obtained from: log,nD = -2.41 + 0.954 log,?PP + 0.8631og,JE where D is the standing stock of detritus, in gC-m2, PP the primary production in gC-m2 year1, and E is the euphotic depth in meters (Pauly et al. 1993). In the absence of a readily available estimates of mean euphotic depth for PWS, the detritus standing stock estimated by this equation for the Strait of Georgia, of 7 t km2 (Venier 1996), is used. The precise value of this estimate has no effect on the computation of detritus flows. T a b l e 2. Mean settled zooplankton volume, upper 20m of PWS (T. Cooney, pers. comm.)" Bacteria (incl. bacterioplank-ton) are not included in the model: it is assumed that bacteria consume only detri-tus, and that the fluxes asso-ciated with this consumption can be treated as if they oc-curred in another, adjacent ecosystem, i.e., that in which detritus accumulates when it leaves PWS. This omission of bacterial fluxes has no im-pact whatsoever on the other estimates of fluxes estimated by Ecopath. Zooplankton Year ml ? m ! 1981 1.45 1982 2.43 1983 2.65 1984 2.39 1985 4.48 1986 1.53 1987 1.42 1988 0.91 1989 5.2 Mean 1.75 a) Sampled using a 0.25 mm mesh size and 0.5 m diameter net. The data are average values for March 15 to June 15, and were taken 2-3 times weekly in the southern part of the Sound. In March-May, the upper layer of zooplankton in PWS is dominated by t he c o p e p o d s Neocalanus cristatus, N. plumchrus, Eucalanus bungii, which are oceanic species, by Cala-nus marshallae, Pseudocalanus s p p which are not, and by the arrow-worm Sagitta elegans. Towards June, this community is gradually re-placed by late stage copepodites of Calanus marshallae, t h e sma l l e r co-p e p o d s Acartia, Centropages, Torta-nus a n d Pseudocalanus, Metridia okhotensis, M. pacifica, a n d t h e cla-d o c e r a n s Podon a n d Evadne. In t he Fall and Winter, these are followed b y Sagitta elegans a n d M. pacifica. Other groups also occurring in zoo-plankton samples are amphipods, euphausiids (5 species), and coelen-terates, among others (Anon 1980; Cooney 1986; Cooney 1993; Ted Cooney, pers. comm.). Published estimates of zooplankton biomass could not be found for the period prior to the EVOS, and we therefore relied on the data in Table 2, made available by Dr T. Cooney (pers. comm.): Settled volumes in ml m 3 can be converted to g m 3 by assuming that 70% of settled volume in millili-ters is equivalent to wet weight in grams (Weibe et al. 1975). Applying this conversion factor, 1.75 ml ? m 3 correspond to 1.225 g ww-m3 . Given that PWS on average is 300m deep, and that zooplankton occur at the 7 same density throughout the water column, the biomass of zooplankton per surface area would be: 1.225 g m 3 -300m = 368 g m2. For the model, it is assumed that 25% of zooplankton biomass con-sists of macroplankton, based on Cooney (1993), who gave 25% as a conservative estimate of macro-plankton production to total zoo-plankton production. The remain-ing 75 % are assumed to consists overwhelmingly of mesoplankon (microzooplanton is not considered here). This leads to biomass esti-mates of 92 t km2 for macroplank-ton and 276 t k m 2 for mesoplank-ton. Another input required by Ecopath is Q/B, here assumed to have the same value, 10.5 year1, as herbivo-rous zooplankton in the Strait of Georgia (Harrison et al. 1983). Fi-nally, we assume mesozooplankton to have a diet consisting only of phytoplankton, while macrozoo-plankton is assumed to consume 75% mesozooplankton and 25% phy-toplankton. For both zooplankton groups, we set EE at 0.95, a default value for groups heavily preyed upon (Polovina 1984). Benthic invertebrates The values used herein for benthic invertebrates larger than 0.5 mm are very tentative. Estimates for these components need consider-able refinement. To account for substrate and other habitat differences, PWS was split into the following three areas with generally different habitat charac-teristics. For this initial exercise, one third of the surface area was allo-cated to each area. 1. Central Basin and Hinchinbrook Entrance; 2. Eastern fjords and bays; 3. Western fjords and bays. The substratum in the central basin (1) is composed of sand, silt and clay, reflecting a depositional envi-ronment. The fjords in the west of PWS (3) are impacted by glacial silt, and characterized by low infaunal abundance and biomass, at least when compared to the communities in the east and north of PWS. Here, muddy bottoms dominate, sup-porting a primarily deposit-feeding infauna (Feder and Jewett 1986). Table 3 and 4 shows the estimated biomass of benthic infauna and ben-thic epifauna respectively. Table 3a. Estimated biomass of benthic fauna, in PWS (from Feder and Jewett 1986) Area Biomass (tkm2) Functional groups (% weight) Central Basin 417 Deposit feeders (66.8), Suspension feeders (26.8 Scavengers & predators (( Eastern fjords & bays 246" Polychaetes, mollusks, echinoderms, crustaceans Western fjords & bays 10.5b Polychaetes (dep. feed.), Bivalves (dep. feed.), Suspension feeders Mean 225 ? a) Port Valdez and Valdez Arm; Derickson Bay (20 g m2); Blue Fjord (13 & 3 g m2) McClure Bay(6gm 2 ) . 8 Feder and Jewett (1986, Table 12-9) indicate that the infaunal biomass at Hinchinbrook Entrance, of 343 g m2, produces 4.6 gCm^year1, corre-sponding to 222 g ww ? m^year1. Table 3b. Estimated biomass of ben-thic epifauna, PWS (from Feder and Jewett 198 6). Area Biomass (tkm2) Species (group) (% weight) Central basin 2.4 Tanner crab (67), Pink shrimp (7), Mud star (5), Other groups (21) Eastern fjords & bays' 0.8 Sunflower star (62), Pink shrimp (28), Tanner crab (4), Mollusks (0.2), Others groups (5.8) Western fjords & bays 0.8b n.a. Mean 1.3 ? a) Near Port Etches; b) No estimate available; biomass assumed to be the same as for eastern fjords and bays. This leads to a P/B estimate of 0.6 year1, which we apply throughout PWS. The same table in Feder and Jewett (1986) gives a P/B ratio of 2.0 year1 for the epifaunal macrofauna, here also applied to the entire PWS. Trowbridge (1996) gives the follow-Table 4. Q/B estimates3 PWS zoobenthos. and diet matrix b (% weight) of Zoobenthos Q/B (year" Inf. Epif. Detrit. Zoopl. M. algae Infauna 23 10 10 60 20 -Epifauna 10 30 20 30 10 10 a) From Guenette (1996, based on several sources); Based on Table 3 a for infauna (mainly deposit feeders) and Table 3b for epifauna (mainly predators: tanner crab is a scavenger/predator; pink shrimp feed on small polychaetes and crustaceans; and sun-flower feed mainly on mollusks). ing catchesof benthic invertebrat from PWS: 1) Epifauna (including pink ai other shrimps), king crab (re blue, brown), and tanner era 0.143 t -km2 year1; 2) Infauna (razor clam and other; 0.003 t -km2 year1. It is here assumed that simili catches were made in the 1980-198 period. Intertidal invertebrates Intertidal invertebrates, dominate by barnacles, gastropods, and b valves (especially Mytilus edult are, in PWS, an important source ( food for birds and sea otters, amor others predators. The only biomas estimate we have identified, 62 g m2, is from Stekoll et al. (1991 Table 2), and was obtained during study carried out from the Spring ( 1990 to the Summer 1991, to asses the impact on the intertidal zone ( the EVOS, and of the cleanup efforl which followed. Assuming the intertidal zone make up 1% of the surface area of PW: the total size of the zone is 88 km Averaged over the total area of PW! the invertebrate biomass is 6.2 t k m 2 . P/B and Q/B are assume equal to the values fc epifaunal benthos (se above). O'Clair and Zimme man (1986, Table 11-^  list the followin feeding groups of ii tertidal benthos ( rocky areas of the Gu of Alaska: herbivore (22%), suspensio 9 feeders (23%), carnivores (26%), de-posit feeders (16%), omnivores (6%), and scavengers (7%). Demersal fish Demersal fish, as defined here, in-cludes true bottom fish such as flat-fish and skates and semi-demersal fish such as pacific cod, walleye pollock and others. In PWS, the two dominant demersal fish species are arrowtooth flounder and walleye pollock. Table 5 shows the biomass estimates resulting from a trawl survey conducted in PWS in 1989. As reported by NMFS (1993), "arrowtooth flounder made up the greatest proportion of total biomass at every site except Central Basin and Port Wells. It accounted for 67% of total biomass in the area of Knight Island/Montague Strait and 65% of total biomass in the area outside PWS" (NMFS 1993). Based on this, arrowtooth flounder was set to contribute 60% of total demersal biomass in Table 5. Based on Table 5, the density of demersal fish in PWS was calculated as: 83,000 ton-nes / 8800 km2 = 9.4 t k m used here are simple averages for 1987. and 1988 (Table 6). These sug-Table 5. Estimated biomass of demers Species Biomass (tonnes) 95% confi-dence interval Arrowtooth flounder 50,000 6,000-90,000 Walleye pollock 9,500? 6,000-13,000 Flathead sole 8,000? -Sablefish 4,000? 1,000-8,000 Other speciesb ll ,500d -Total 83,000 -a) Adapted from IN fMFS (1993); Table 6. Mean demer-sal fish catch from PWS, 1987-1988 Pending detailed analyses of data from PWS, the P/B value of 1 year1, and the Q/B value of 4.24 year1, pertaining to the demersal fishes of the Strait of Geor-gia, were taken from Venier (1996, Table 36). No suitable data set being available for the period prior to 1987, the catches Species Catcht (tyear1) Rockfish 45.631 Sablefish 93.576 Pacific cod 174.780 Flatfish 9.663 Lingcod 0.439 Other 4.948 Total 329.037 Adapted (1995). b) Big skate, Bering skate, Alaska skate, Aleuti skate, Pacific halibut, rex sole, Pacific c< rougheye rockfish and others; c) Based on the 95% confidence interval (walle pollock and sablefish) and the fact that the walle pollock biomass was only slightly greater than tl of flathead sole (NMFS 1993);Based on arrowtoc flounder contributing 60% of total biomass gest, for PWS as a whole, a catch of demersal fishes of 0.037 t k m 2 ? year1. Adult halibut and cod are apex predators, and feed on a variety of medium to large fish such as pol-lock, flatfish, and sculpins. They also feed on invertebrates, such as crabs, shrimps and krill, and small pelagic fishes such as smelt. Walleye pollock and many rock-fish species feed pre-dominantly on small to medium-size nektonic prey such as large am-phipods, copepods, krill, smelt, and other small fish. Pollock is also known to be cannibalis-tic. Sablefish is an om-nivore and scavenger feeding on fish and in-from Bechtol 10 vertebrates. Flatfish and sculpins have overwhelmingly benthic diets. Soles consume small invertebrates (worms, snails, clams, brittlestars, etc.), while flathead sole feed on shrimp, krill, herring, and smelt (Alton 1981). Based on such feeding habits infor-mation, as well as diet information presented in various contributions in Pauly and Christesen (1996), the following diet composition was de-rived for the demersal fish of PWS (in % weight): benthic invertebrates (25); pelagic fish (25); macrozoo-plankton (15); mesozooplankton (15); herring (10); and demersal fish (10; cannibalism). from the above figures. Natural mor-tality (M) was estimated as 0.53 year \ as the means of age-specific esti-mates (age 3 to 8) for herring in the Gulf of Alaska (Wespestad and Fried 1983). Since P/B, under equilibrium, equals total mortality (Z; Allen 1971), and Z = F + M, the P/B ratio for herring can be estimated from 0.53+ 0.14 = 0.67 year1. The value of Q/B used here, of 18 year1, is the same as that used for small pelagics (mainly herring) in the Strait of Georgia (Venier 1996); the diet consists of zooplankton: euphausiids, copepods, mysids, and amphipods, among other (White-head 1985). Herring Herring spawns in PWS in Spring, from mid-April to early May (Mor-stad et al. 1996). This is also the season for seine and gill net fisher-ies, for sac roe, and for two spawn-on-kelp fisheries. Another fishery, for food and bait, occurs in the Fall. Table 7 presents mean catches for the period from 1980 to 1988. Based on Table 7, the catch of her-ring in PWS equals 1.136 tkm 2 ; The corresponding biomass, also for the 1980-1988 period, was esti-mated as 71,341 t or 8.107 t-km2 , based on an age-structured analysis (Morstad et al. 1996, Appendix H.ll) . Given that, under equilibrium, F = catch/biomass, a fishing mortality (F) of 0.14 year1 can be estimated Table 7. Average harvest of herring in PWS from 1980 to 1988.a Fishery Mean catch (t year ') Seine and gillnet 7586 Spawn-on-kelp, natural 819 Spawn-on-kelp, pounds 538 Food and bait 1053 Total 9996 From Morstad et al. (1996). Salmon f ry Both wild fry and hatchery-released salmon fry occur in PWS. The hatch-ery released fry is mostly pink salmon, which are believed to reside in the Sound from early April to July/early August (the hatchery stock is released in late April/early May). Table 8 summarizes key fea-ture of salmon fry in PWS. 11 Initially, salmon fry consume meso-plankton; calanoid copepods are a preferred prey, but diversity of the diet increases with size of the fish (Cooney et al. 1978). For the present model, it will be assumed that the Table 10 presents minimum esti-mates of the mean biomass of hatchery and wild pink and chum salmon in PWS from 1980 to 1989, based on wild stock escapement (minimum estimates), hatchery re-turns and catches. Table 8. Characteristics of wild salmon fry, Parameters Wild fry Hatchery fry Abundance (million) 500 300c Density (t km2)" 0.014 0.009 Survivors after 120 days (%) 22 37 Consumption (t) in 120 days 4979 4,513 Q/B (year1) 40 60 a) From Cooney (1993); both wild anc hatchery re-leased fry are about 25 g, and remain in PWS for 120 days when entering PWS; b) As sinning that fry are evenly distributed within PWS; Mean release of (mainly) pink salmon, 1980-1989 (Morstad et al. 1996). diet of young salmon consists of 75% mesoplankton and 25% macro-plankton; also EE was set as 0.78 for wild fry and 0.63 for hatchery re-leased fry (see section on 'Balancing the model'). Adult Salmon Adult salmon appear in PWS from June through September, while on their spawning runs. All parameters in the text below were therefore subsequently corrected to a yearly average as required for the model (multiplied by 4/12). Table 9 shows the average harvest of salmon in the Sound from 1980 to 1989. From Table 9, the average catch of salmon per area of PWS for the pe-riod 1980-1989 is calculated as 4.2 tkm 2 . Biomass estimates for the three other salmon species in PWS could not be found. However, pink salmon is the dominant species, contrib-uting about 83% of the catch (in weight), while chum con-tributes about 13%. Assuming the same percentages apply to the biomas, the mean total standing stock of salmon in PWS (wild and hatchery) from 1980 to 1989 was 42,000 tonnes, or about 5 t km2. Total mortality estimates for the oceanic phase of the various species of salmon caught in PWS are given in Table 11; their weighted mean is 2.37 year1, which serves as our estimate of P/B for salmon as a Table 9. Catches of salmon in PWS, base on data from 1980 to 1989 (commerci Species Catch Catch8 Mean wt (kg) (number) (kg)* Chinook 8,457 755 11.2 Sockeye 974,014 374,621 2.6 Coho 173,794 41,380 4.2 Pink 30,487,004 19,054,377 1.6 Chum 4,908,645 1,363,512 3.6 Total 36,551,913 20,834,645 1.8) a) Average catches in PWS from 1980 to 198 based on Morstad et al. (1996, Appendices E.2 & G.2); Weighted means, based on Morstad et al. (19? Appendix A.5). 12 Table 10. Estimated standing stock of hatchery and wild pink and chum salmon in PWS, 1980-198S Stock Population" (N) Mean wtb (kg) Biomass (kg) Pink 21,269,184 1.6 34,030.694 Chum 1,632,316 3.6 5,876.338 Total 22,901,500 (1.8) 39,907,032 Based on Morstad et al. (1996, Appendices E.5 & E.9);Weighted mean, based Morstad et al. (1996, Appendix A. 5). functional group. Adult salmon only feed a short time within PWS; in the model, their low trophic impact Table 11. Instantane-ous oceanic mortality rates (Z) for five spe-cies of salmon occur-ring in PWSa Total Species mortality (Z;yr>) Chinook 0.42 0.92 I - - 1.32 1 - - 2.45 1 -- 1.64 i . . 2.37 can be captured by giving them a low value of Q/B, here 1 year1, corre-sponding to 1/12 of the annual value for pink salmon in the Alaska gyre (L. a) From Huato (1996), based on Ricker (1975) and Bradford (1995); b) Weighted by the catches in Table 9. Huato, comm.; tensen Table pers. Chris-1996, 10). A diet composi-tion (by weight) of pink salmon of 85% small pelagics and 15% macrozooplankton came from Huato (1996). Miscellaneous small pelagic fishes This group includes capelin, eu-lachon, smelt, and other small fishes. While not fished, small pelagics are important in PWS, as they are the major preys of pin-nipeds, cetaceans, birds and of many larger fishes. As no standing stock estimates is available for the small pelagics of PWS, their biomass is left as an un-known to be estimated by the model; given the important role they play in the diet of larger vertebrates, this estimation of biomass will be based on an assumed value of EE = 0.95; the other parameters for this group are set as for the small pelagics of the Strait of Georgia, i.e., P/B = 2 year1 and Q/B = 18 year1 (Venier 1996). The diet of the small pelagic group (in % weight) is also adapted from that in Venier (1996), with modifica-tions as required to balance the model: mesozoolankton (80); large zooplankton (10); and small macro-benthos (10). Birds Of the 219 species of birds recorded in the Northern coast of the Gulf of Alaska and in PWS, 111 are primarily associated with water bodies. A large number of birds concentrate in the PWS area during the Spring mi-gration and smaller numbers during the Fall migration. Shorebirds and waterfowls are especially numerous. During Summer, many nesting spe-cies utilizes the PWS area. The most common of these are alcids, black-legged kittiwakes, cormorants, glau-cous-winged gulls, and arctic terns. In Winter, waterfowls such as "mal-lards, greater scaup, common and barrow's goldeneye, buffleheads, oldsquaws, harlequin duck, white-winged -surf -and common scoters, and common and red-breasted mer-gansers and alcids" use the inshore 13 areas together with many gulls (Is-leib and Kessel 1973). The model of PWS presented here docs not consider shorebirds, con-cern rating instead on seabirds and waterfowls (in that order). Of the latter, only ducks arc included, i.e., swans, etc., are not consid-ered. As mentioned above, many species of ducks overwinter in PWS, while in Summer, sco-ters are most abun-dant. Table 12 shows the species composi-tion of ducks winter-ing in PWS, and Table 13 presenls estimates of the abundance of ducks in PWS during summer and winter. Table 14 summarizes the information on diet composition of ducks in PWS. The following seabirds are known to breed in PWS, including Monta-gue, Hinchinbrook, and Hawkins Is-lands {DeGange and Sanger 1986): ? storm petrel (fork-tailed, Leach's); ? cormorants (double-crested, pelagic, red-faced); ? gulls (mew, her-ring, glaucous-winged, biack-tegged, kittiwake); ? terns (arctic, Aleutian); ? common murres; ? pigeon guillemot; ? small alcids (kittlitz'a murrelei, parakeet auklet); and Table 12. Population statistics of ducks overwintering in PWS'. Species Body weight (kg) Pop. (N) Biomass (kg) Food cons." (kg year ') Green-winged leal 0.3 4" rare . Mallard 1.16 -1,600 5.336 389,528 Northern pintail 1.01 50 50.5 3,687 American widgeon 0.76h rare - -Scaup (greater) 1,05 1.400 1,470 107310 Harlequin duck 0,61 4.900 2.989 218,197 Oldsquaw 0,89 1,-100 1,246 90.958 Hlack scoter 1.15 4.850 5,577.5 407,158 Surf scoter 1,10' 4,950 5,445 397.485 White-winged scoter 1,35J 1,950 2,632.5 192,173 Unidentified scoter 1.15 7,850 9,027.5 659,008 Goldeneyes 0.90 11,600 10,440 762,120 Bufflehead 0.45 1,700 765 83,768 Uniden. merganser l,12h 4,750 5320 388,360 Total - 50,000' 50,299 3.699,752 a) Modified from DeGange and Sanger (1986); h) From Dunning (1993); c) From Vermeer (1981, p. 114); d) From Palmer (1976, p. 115); e) Consumption was calculated assuming thai birds weighing 200-000 g consume 30% of their body weight each day, and birds greater than (iOO % consume of their body weight each day (see also Nilsson and Nilsson 1976; Muck and Pauly 1987; and Wada 1996). Table 1 J. Estimation of cluck biomass in 1JWS, by season. Season Species Pop. (N) Body weight (kg)" Density ( ikm -) Cons," it year ' ) Q/B (year') Summer Scoters 1 1,000 1.15 0.001 923 73 Other ducks I ! ,000 0.90 0.001 723 73 Total 22,000 - 0,002 1,646 73 Winter' Ducks 50,000 - 0.006 3.700 74 Mean 36,000 - 0.004 2673 74 a) Degunge and Sanger (1986, Table 16-4): b) Assuming lhai ihe birds eat the equivalent of 20% of their body weight day1 (see Table 12, note e for sources); a) See Table 12. 14 Table 14. Diet matrix for some selected ducks in Prince William Sound. Prey \ pred. Barrow goldeneyes* Harlequin duckb Old-squaw* Scoter" Mean % in diet Bivalves 0.712 - 0.G 0.50 0.453 Gastropods 0.09G - 0.2 0.25 0.137 Other molluscs - 0.434 - . 0.109 Crustaceans 0.182 0.355 - 0.25 0.197 Insects - 0.044 - - 0.011 F.chinoderms - 0.120 - - 0.030 Sandlanee - 0.2 - 0.050 Turbellaria - 0.005 - - 0.001 Algae 0.010 0.042 - - 0.013 a) Modified from Koehl et al. (1982); b) Modified From Dzinbal and Jarvis (1982); c) Based on Degange and Sanger (1986); d) Based on Vermeer and Bourne (1982). ? puffins (tufted, horned). Other seabirds occurring in PWS are marbled murrelets, red-faced cor-morant, pelagic cormorant, double-crested cormorant, common loon, and others (Paine et al. 199G). Table 16. Diet matrix for the seabirds of PWS1 Table 15. Seabird densities in PWS. (Modified from DeGange and Season N'km'3 Spring 29.0 Summer 56.7 Fan 35.6 Winter 18.2 Mean 34.9 Of these breeding-birds, black-legged kittiwake is the most abundant in PWS, with 20,000 pairs nesting al 27 colo-nies. They occur in the Sound from Feb-ruary/March to August/September, and feed near the surface, preying chiefly on young her-ring, Pacific sand lance, capelin and young walleye pollock (Irons 1996). ? 5= E9 U W J4 w ZJ rt . cj J= Irt C Predator \ prey o a. _o a S i ??j i -a I ri C-3 LJ VI 1 ST ?j u a s 1 a CJ "3 c. "a u u a a TS s es ift y ? V > E ?5 O a. O in V. C-E ?c e C3 tA U ? Fork-tailed storm parol 0.675 0.223 0.03 0.017 0.042 0.013 Mew gull 0.067 0.074 0,017 0.035 0.026 Glatieous-winfccd gun0 0.002 0.004 0.003 0.026 0.016 0.925 0.0! 6 Black-lcaged kiitiwake 0.001 0.1X16 0.104 0,002 0,667 0,012 0.086 0.1 0.022 Annie lent 0.001 0.968 0.001 0.014 0.013 0.002 0,001 AlcntUin tern 0.022 0,765 0.032 0.12 0.046 0.015 Pelagic cormorant 0,002 0.004 0.018 0.006 0.85S 0.101 0.002 0.009 Pigeon guillemot 0.0B 0.327 0.13 0.399 0,013 0.004 0.051 o.ots Marbled niunelei 0.014 0.05 J 0.479 0.001 0.213 0.14 0.002 O.OD1 D.003 Kitllilz's nurrclet 0.243 0.018 0.036 0.686 0.017 Parakeet tutklci 0.465 0.121 0.414 Common murre 0.001 0.032 0.01 0.453 0.117 0.239 0.146 0.002 Homed puffin 0.012 0.002 0.005 0.619 0.001 0.162 0.198 0.001 lulled puffin 0.078 0.112 0,741 0.006 0.054 0.007 0.002 a) Modified from Degange and Sanger (198G). The original die! fractions for the various birds did not all add up to 1. This was corrected for by modifying (he fraction contrib-uted by the most important prey groups. Additional entries not in the table are: mew gulls: 78.1% gammarid amphipods; glaucous-winged gulls: 0.2% hexagrammids, and 0.6% other birds; pigeon guillemot: 1.5% prickle-backs; marbled murrelet: 9.4% mysids. Pigeon guillemot is another abun-dant seabird breeding in PWS. it feeds in inshore waters, primarily on benthic fishes and inverte-brates. During a survey of the guillemot population in PWS, con-ducted in 1984 and 1985, 4660 guillemots were counted, compared to 15,000 in 1972-1973 (Oakley and Kuletz 1996). Table 15 shows rough seabird density estimates for PWS, by season. Based on Table 8 in Kelson et al. (1996), the average weight of seabirds is set at 0.5 kg, resulting in an overall density of 0.017 t k m 2 over PWS. Assuming, with DeGange and Sanger (1986), that sea-birds between 200 and 600g consume about 30% of their body weight per day, leads to an estimated total food consumption of 2.157 ton-nes annually, corresponding to a Q/B estimate of 110 year1. The diet matrix, indicating the food items thus consumed, is given as Table 16. The summary statistics used for the combination of waterfowls and sea-birds are: biomass = 0.021 t km2 (see Tables 13 and 15); P/B = 0.1 year1 (from Muck and Pauly 1987); and Q/B = 103 (weighted mean, given 88 % seabirds and 12 % ducks). The mean (weighted) diet composi-tion derived from Tables 14 and 16 for this combined group, is: pelagic fish, including cephalopods (45.9 %); invertebrates (21.5%); demersal fish (13.6%); euphausiids (18.7%) algae (0.2%); and insects (0.1%). Sea otters Two estimates of the population size of sea otters in PWS exist for the period considered here: 4000-6000 in 1985, and 5000-10,000 in 1989 (Burn 1994). The mean of the midranges, multiplied with the mean weight of adults (females 21, males 28 kg; Calkins 1986) and as-suming a female male ratio of 1:1, leads to a density of 0.017 t km2 for PWS as a whole. Further, given daily rations of 5.3 kg for the females and 7.0 kg for the males (Calkins 1986), Q/B is esti-mated as 92 year1. The major prey organisms of sea otters in PWS are mollusks, crusta-ceans, and echinoderms (Garshelis et al. 1986, Calkins 1978); Table 17 summarizes the results of an analy-sis of the diet composition of sea otters in Montague Strait. Other marine mammals The marine mammals of PWS, be-sides sea otters, can be split into three groups: resident, transient, and pinnipeds. The first group com-prises killer whales, Dall's porpoise, and harbor porpoise. The second group comprises fin whales, hump-back whales, minke whales, beluga whales, and killer whales, occurring only seasonally in PWS. The third group is comprised of harbor seals and Steller sea lions. Table 18 sum-marizes key population statistics of the different species. Note that in this table, the Q/B values are based on sex ratios of 1:1, except for Steller sea lion, where there are 1.2 females per male (Calkins 1986). Table 17. Diet composi-tion of sea otters in Monta-gue Strait, PWS (adapted from Calkins 1976 and Garshelis et al. 1986). Food item Contrib. (% wt.) Molluscs clams 81.0 mussels 0.3 octopus 0.6 Crustaceans -crabs 7.0 Echinoderms -seastar 0.9 sea cucumber 0.3 Others inverts 9.9 Table 18. Population statistics ol marine mamma s in PWS (excl. sea otter) Species Mean Body weight(kg) Females Males Pop. (N) Biomass ( t k m 2 ) Days in PWS Rat (kg? Males ion Jay') Females Q/B (year1) Transients Fin whale 59819" 51361' 50< 0.078 90" 2055.0' 2393.0' 3.6 Humpbacks 32493* 28323" 96" 0.191 210" 365.0' 407.0' 2.7 Minke 7011* 6121" 10' 0.004 180" 107.0" 119.0' 3.1 Belugas 590" 860" 200" 0.003 60" 47.3" 32.5" 3.3 Trans. Orca 2761' 3068* 45' 0.005" 12' 61.6' 56.6" 2.4 Residents Res. Orca 1974" 2587' 176' 0.040" 365 53.7' 43.3' 7.8 Dall's porpoise til- 63' 7,328' 0.052 365h 2.8' 2.7' 16.2 Harbor porpoise 30" 33' 768" 0.003 365" 1.6" 1.5' 18.0 Pinnipeds Harbor seal IT 85" l,300r 0.012 365" 6.4" 5.8" 27.5 Steller sea lion 263h 566" 6537h 0.285 365" 45.3b 21.0" 29.2 a) Tritcs and Heisc (1996, Appendix Table A, B); b) Calkins (1986); c) Anon. (1980); d) Estimated populations of 590 porpoises in Winter and 946 in summer (1979)" Rive an annual mean of 768 porpoises; e) Leathenvood et al. (1990); f) Derived from Leathenvood et al. (1990, Table 2), assuming thai immature/other killer whales weigh the same as a female, and the calves weigh on average 180 kg (Calkins 1986); g) Calkins and Pitcher (1982); h) Rased on record of 37 minke whales in the Gulf of Alaska (including PWS) during a survey con-ducted in 1980 (Rice and Wolman 1981); i) Indirect estimate, obtained by first assuming a higher residence time, and evaluating its impact on the preys. Table 19. Basic statistics for transient marine mammals in PWS. Species Biomass (tkm2) P/B* (year1) Q/B (year1) Fin whale 0.078 0.005 3.6 Humpback whale 0.191 0.012 2.7 Minke whale 0.004 0.001 3.1 Beluga whale 0.003 0.003 3.3 Killer whale, trans. 0.001 0.007 2.4 Total (weighted average) 0.281 0.020 3.0 a) Trites and Heise (1996). Table 20. Basic statistics for resident marine mammals in PWS Species Biomass (tkm3) P/B' (year1) Q/B (year1) Killer whale, resid. 0.040 0.02 7.8 Dall's porpoise 0.052 0.02 16.2 Harbor porpoise 0.003 0.02 18.0 Total (weighted average) 0.095 0.02 12.7 Trites and Heise (1996). Table 19-21 summarize the sta-tistics of each of the three groups. For transient mammals, all values have been adjusted using the number of days that the species arc thought to occur in the Sound in proportion to the number of days in a year. Table 22, finally, presents the diet matrix for the three groups covered here. BALANCING THE MODEL There are two ways that Ecopath models can be balanced, given a set of inputs such as presented here: (1) by modifying those inputs subjectively felt to be most questionable until mass-n Table 21. Basic statist ics for pinnipeds in PWS. Species Biomass (tkm2) P/Ba (year1) Q/B (year1) Harbor seal 0.012 0.06 27.5 Steller sea lion 0.285 0.06 29.2 Total (weighted average) 0.297 0.06 29.1 Trites and Heise (1996). balance is achieved, or (2), more rig-orously, by entering uniform, trian-gular or normal distributions about each of the inputs (B, P/B, Q/B, EE, DC), and using the 'Ecoranger' rou-tine of Ecopath to identify, through a Monte-Carlo approach, a set of models fulfilling realistic mass-balance and other thermodynamic Bayesian context, as 'pos-terior distributions', pro-viding added knowledge on likely values for the biomass, mortalities, etc., of key elements of the ecosystem under study (Walters 1996). We have used here the less rigorous approach in (1), pending availability of the parameter estimates with confidence intervals, or other meas-ures of uncertainty that will be used for updating the model presented here. Table 22. Diet matrix for the marine mammals of PWS Predator \ prey Euphausiids Copepods Small pelagics Herring Salmon Pinnipeds Porpoise Whales (transient) Demersal fish Birds Invertebrates Marine mammals (transient) Fin whale" 0.4 0.4 0.2 Humpback whalea 0.5 0.3 0.1 0.1 Minke whale" 0.5 0.1 0.1 0.1 0.2 Beluga whale" 0.6 0.2 0.2 Killer whale, trans 0.56 0.21 0.21 0.02 Marine mammals (resident) Killer whale" 0.5 0.5 Dall's porpoise" 0.8 0.2 Harbor porpoise" 0.5 0.25 0.25 t* ? A ? Pinnipeds 0.2 0.05 0.05 0.65 0.05 a) Based on Calkins (1986); b) Modified from Wada (1996, Table M), and pertaining to the Strait of Georgia; c) Based on Hobson et al. (1997). constraints. This allows not only selection, from among this set, of a 'best model' in the least-square sense, but also the output of the distributions of input values associ-ated with the accepted models. These can then be interpreted in a Few parameters, besides the diet matrix (see below) had to be modi-fied to get the model to balance: ? The P/B ratios for resident and transient marine mammals, and for pinnipeds, were found to be incom-patible with a sustained presence of 18 Table 23. Basic estimates and trophic levels of the various groups in the balanced model of PWS (1980-1989). Values in bold characters were calculated by the program. Group Biomass (t vvwkm"2) P/B (year1) Q/B (year1) EE Annual catch (t-kmz) Trophic level 1 Phytoplankton 41.513 190.00 0.00 0.90 0.000 1.0 2 Macroalgae 400.000 4.40 0.00 -0.00 0.000 1.0 3 Mesozooplankton 276.000 9.30 30.99 0.95 0.000 2.0 4 Inf. zoobenthos 225.000 0.60 23.00 0.59 0.003 2.3 5 Intertidal inv. 6.240 2.00 10.00 0.79 0.000 2.5 6 Macrozooplankton 92.000 1.35 10.50 0.95 0.000 2.8 7 Epi. zoobenthos 1.300 2.00 10.00 0.92 0.143 2.9 8 Wild salmon fry 0.014 18.25 40.00 0.78 0.000 3.2 9 Hatch, salmon fiy 0.009 35.15 60.00 0.63 0.000 3.2 10 Herring 8.107 0.67 18.00 0.95 1.136 3.3 11 Small pelagics 8.909 2.00 18.00 0.95 0.000 3.3 12 Sea otters 0.017 0.71 92.00 0.10 0.000 3.5 13 Demersal fish 9.400 1.00 4.24 0.96 0.037 3.9 14 Birds 0.021 0.10 103.00 0.00 0.000 4.1 15 Salmon 2.125 0.80 1.00 0.95 1.400 4.1 16 Trans, mammals 0.280 0.02 3.00 0.00 0.000 4.2 17 Res. mammals 0.095 0.02 12.70 0.44 0.000 4.4 18 Pinnipeds 0.300 0.06 29.10 0.19 0.000 4.5 19 Detritus 7.000 - - 0.50 0.000 1.0 transient killer whales in PWS. In-deed, this presence had to be re-duced, from high initial guesses, to less that two weeks per year for other marine mammals to be able to accommodate the predation pres-sure of killer whales. The implica-tions of this constraint will have to be followed up in future models; ? The ill-founded initial standing stock estimate of 10 t km2 for phy-toplankton was abandoned and the EE value fixed at 0.9 instead. The biomass was then estimated by Eco-path, based on the estimated pri-mary production in PWS; ? The initial Q/B value of 10.5 year1 for mesoplankton, which generated an excessively high gross conver-sion efficiency (GE = (P/B) / (Q/B)), had to be abandoned, and GE fixed at 0.3. Normally, GE values can only exceed 0.5 for groups such as fast-growing fish larvae, nauplii, or bac-teria. For most groups, GE values range between 0.1-0.3. (Christensen and Pauly 1992b). ? The original density estimate of 1.17 t k m 2 for salmon was aban-doned and the EE fixed at 0.95 in-stead, leaving the density as a free parameter to be estimated by Eco-path. The resulting estimate was higher than the initial value, which is appropriate, since the initial value was known to be an underes-timate (see above). 28 Table 24. Diet matrix, expressing the trophic interactions of the various groups of the balanced model of PWS (1980-1989). Values in bold characters were changed from initial estimates, i.e., modified as required to achieve mass-balance. Prey \ pred. Mammals (res.) Herring Sm. pel. Sea otters Dem. fish Intertid. inv. Macrob. -epi. Macrob. -inf. Zoopl. -macro. Zoopl, -meso. Birds Mammals (trans.) Salmon Pinnipeds Wild salm. fry Hatch, salm. fry Mammals (res.) 0.001 Herring 0.296 0.080 0.067 0.051 Small pelagics 0.487 0.260 0.459 0.138 0.850 0.362 Sea otters 0.001 Demersal fish 0.150 0.100 0.136 0.193 0.500 Intertid. inv. 1.000 0.025 0.100 0.216 0.070 Epi. zoobenthos 0.030 0.080 0.000 Inf. zoobenthos 0.101 0.130 0.500 0.010 Macrozooplankton 0.010 0.400 0.299 0.265 0.187 0.459 0.150 0.250 0.250 Mesozooplankton 0.600 0.600 0.100 0.360 0.100 0.290 0.750 0.137 0.750 0.750 Phytopl. 0.230 0.250 0.800 Macroalgae 0.199 0.002 Birds Mammals (trans.) 0.000 Salmon 0.056 0.001 0.017 Pinnipeds 0.004 Wild salm. fry 0.005 Hatch, salm. fry 0.005 Detritus 0.310 0.121 0.700 0.200 20 RESULTS AND DISCUSSION Table 23 shows the basic parame-ters and estimated trophic levels, by functional group of the balanced model of PWS; Table 24 shows the corresponding diet matrix. A graphic version of the model is presented in Fig 2. It must be stressed that this model is tentative and intended as an exer-cise to identify knowledge gaps. Many estimates have been adopted from other models and/or other locations, or periods other than the 1980s. Moreover, some groups, such as nearshore fishes, herring fry and other fish larvae are not considered, while other groups, e.g., such as demersal, and pelagic fishes, are very over-aggregated. Also, seasonal changes were not explicitly consid-ered, though rigorous procedures exist for doing so (Walters 1996). However, useful inferences can be drawn even from a simple model, and this is illustrated in Fig. 3 and 4. Figure 3 represent a trophic impact matrix, expressing the effects the various groups of the systems have on each other. This type of matrix, often reflecting the cascade-like ef-fects of changes in the biomass of top predators on the lower trophic levels of ecosystems, was trans-ferred from economics (Leontief 1951) into ecology by Hannon (1979). However, their interpretation in the PWS context will be discussed when more detailed models become available. 21 CD > 0) O _c Q. O h-Fig. l . Simplified flowchart of Ecopath model of PWS. Box sizes are proportional to log(density) of the group represented; flows exiting from a box do so from its upper half; flows exiting from a box cannot divide, but can merge with flows from other boxes. The adult salmon box and the backflows to the detritus are omitted for clarity. IMPACTED GROUP O CL I 8 f ^ p ? 1 ^ ? ra ? a 5 S ~ < l > < ? E E J - ra TJ t C I g ' ^ g S g S S ^ ^ ^ g E ? ? S S 3 ? i ' E l S E f b b g - g - i d ^ E E c s o g ? = ^ RA <D ? 5 x y ) w Q J ? 5 S N N a , S o Q 5 ( 0 " > I Q iH Mammals (Res.) Herring Small pelagics Q. 3 Sea otters Demersal fish 0 Intertid. inv. O z Macrobent.-epi. a ? t - Macroben.-inf. ? ? i^am o < Zoopl.-macro Zoopl.-meso Phytoplankton Macroalgae Birds Mammals (trans) Salmon Pinnipeds Wild salmon fry Hatc.salmon fry Detritus -am rarmmr Fishery Fig. 2. Mixed trophic impacts of groups in the PWS ecosystem model, representing the impact an infinitesimal increase in any of the (horizontal) groups would have on all the other groups in the system. The impacts (black positive, shaded negative) are relative but comparable within rows. Phytoplankton Herring Small Pelagics F Herring Time (years) Fig. 4. Results of an Ecosim run of the PWS file generated by Ecopath, showing the system impact of increasing fishing pressure (or generally: mortality) for ten years on an important groups in the system (here: herring). Note the in-crease of their preys and competitors, and the long time it takes for the sys-tem to return to its initial state (model was run with all boxes in the system, but the graph was simplified to show changes for selected groups only). 24 Given the definitions of its various terms, the system of linear equa-tions in Box (1) can be written 0 = [B /(P/B),EEJ-[(/;? B; + Z B / - ( Q / B ) / D C J - 1 ) which is another way of stating that production and consumption are balanced within a system. However, we can reinterpret this as a system of ordinary differential equations, viz. dB/dt.= [B.-(P/B).-EE.l - [(F.-B.) + ?B - (Q/B)- DC,J ...2) where all terms are defined as in Box 1. We refer to Walters et al. (1997) for details on how the system of equations in (2) is implemented within Ecosim; Fig. 4 illustrates a run of Ecosim with the Ecopath file whose creation was documented here. Other applications of the Ecopath model whose construction was documented here are presented in Appendix 1 and 2. We hope that this model - if only by eliciting con-structive criticism - will be found a useful basis for the more detailed models that will explicitly account for input uncertainty during their construction in 1998. Acknowledgements We thank the Exxon Valdez Oil Spill Trustee Council for its support, Ted Cooney for extremely useful infor-mation on PWS zooplankton, Marcello Vasconcellos for generating Fig. 4, and Tom Okey for adapting Fig. 1, and for his assistance in fi-nalizing this report. 25 REFERENCES Allen, K.R. 1971. Relation between production and biomass. J. Fish. Res. Board Can. 28: 1573-1581. Alton, M.S. 1981. Gulf of Alaska Bot-tomfish and Shellfish Resources. NOAA Technical Memorandum NMFS F/NWC-10. U.S. Department of Commerce. National Technical Information Service. Springfield. U.S. Anon. 1980. Environmental Assess-ment of the Alaskan Continental Shelf. U.S. Department of Com-merce. Office of Marine Pollution Assessment. Science Applications Inc. Colorado. 313 p. Bechtol, W.R. 1995. Commercial Groundfish Fisheries in the Cen-tral Region. 1994. Regional In-formation Report No. 2A95-32. Alaska Department of Fish and Game. Anchorage, Alaska. Bradford, M.J. 1995. Comparative review of Pacific salmon survival rates. Can. J. Fish. Aquat. Sci. 52:1327-1338. Brady-Campbell, M.M., D.B. Campbell and M.M. Harlin. 1984. Productiv-ity of kelp (Laminaria spp.) near their southern limit in the north-western Atlantic Ocean. Mar. Ecol. Progr. Ser. 18:79-88. Burn, D.M. 1994. Boat-Based Popula-tion Surveys of Sea Otters in Prince William Sound, p. 61-80. In T.R. Loughlin (ed.). 1994. Marine Mammals and the Exxon Valdez. Academic Press, San Diego. Calkins, D.G. 1978. Feeding behavior and major prey species of the sea otter, Enhydra lutiis, in Montague Strait, Prince William Sound, Alaska. Fishery Bulletin 76(1):125-131. Calkins, D.G. 1986. Marine Mammals, p. 527-561. ioD.W. Hood and S.T. Zimmerman (eds.) The Gulf of Alaska: physical environment and biological resources. U.S. Depart-ment of Commerce, NOAA. U.S. Government Printing Office, Washington, D.C. Calkins, D.G. and K.W. Pitcher. 1982. Population assessment, ecology, and trophic relationships of Steller sea lions in the Gulf of Alaska. Research Unit 234. Envi-ronmental Assessment of the Alaskan Continental Shelf, Final Reports of Principal Investigators 19:445-546. Cooney, R.T. 1986. Zooplankton, p. 285-303. In D.W. Hood and S.T. Zimmerman (eds.) The Gulf of Alaska: Physical Environment and Biological Resources. U.S. De-partment of Commerce, NOAA. U.S. Government Printing Office, Washington, D.C. Cooney, R.T. 1993. A theoretical evaluation of the carrying capac-ity of Prince William Sound, Alaska, for juvenile Pacific salmon. Fisheries Research 18:77-87. Cooney, R.T., D. Urquhart, R. Neve, J. Heslinger, R. Clasby and D. Bar-nard. 1978. Some aspects of the carrying capacity of Prince Wil-liam Sound, Alaska for hatchery released pink and chum salmon fry. University of Marine Science. University of Alaska, Fairbanks, Alaska. 97 p. 26 Christensen, V. 1996. Balancing the Alaska gyre model, p. 32-36. In D. Pauly and V. Christensen (eds.) Mass-Balance Models of North-eastern Pacific Ecosystems. Fish-eries Centre Research Report 4 (1). Christensen, V. and D. Pauly. 1992a. ECOPATH II: a system for bal-ancing steady-state ecosystem models and calculating network characteristics. Ecol. Modelling. 61:169-185 Christensen, V. and D. Pauly. 1992b. A guide to the Ecopath II software system (version 2.1). ICLARM Software 6. 72 p. Christensen, V. and D. Pauly., editors. 1993. Trophic models of aquatic ecosystems. ICLARM Conf. Proc., 26. 390 p. Christensen, V. and D. Pauly. 1995. Fish Production, catches and the carrying capacity of the world ocean. Naga, the ICLARM Quar-terly 18(3):34-40. Christensen, V. and D. Pauly 1996. Ecological modeling for all. Naga, the ICLARM Quarterly 19(2):27-28. Dean, T.A., M.S. Stekoll and R.O. Smith. 1996. Kelps and Oil: Effects of the Exxon Valdez Oil Spill On Sub-tidal Algae, p. 412-423. In S.D. Rice, R.B. Spies, D.A. Wolfe and B.A. Wright (eds.) Proceedings of the Exxon Valdez Oil Spill Sympo-sium. American Fisheries Society Symposium 18, Bethesda. DeGange, A.R. and G.A. Sanger. 1986. Marine Birds, p. 479-524. In D.W. Hood and S.T. Zimmerman (eds.) The Gulf of Alaska: physical envi-ronment and biological resources. U.S. Department of Commerce, NOAA. U.S. Government Printing Office, Washington, D.C. Dunning, J.B. Jr., editor. 1993. CRC Handbook of Avian Body Masses. CRC Press. Boca Raton, Florida. 371 p. Dzinbal, K.A. and R.L. Jarvis. 1982. Coastal feeding ecology of Harle-quin Ducks in Prince William Sound, Alaska, during summer, p.6-10. In D.N. Nettleship, G.A. Sanger and P.F. Springer (eds.) Marine birds: their feeding ecol-ogy and commercial fisheries re-lationships. Proceedings of the Pacific Seabird Group Sympo-sium, Seattle, Washington. Feder, H.M., and S.C. Jewett 1986. The Subtidal Benthos, p. 347-396. In D.W. Hood and S.T. Zimmerman (eds.) The Gulf of Alaska: physical environment and biological re-sources. U.S. Department of Commerce, NOAA, Washington, D.C. Garshelis, D.L., J.A. Garshelis and A.T. Kimker. 1986. Sea otter time budgets and prey relationships in Alaska. J. Wildl. Manage. 50(4):637-647. Goering, J.J., W.E. Shiels and C.J. Pat-ton. 1973. Primary production, p. 253-279. In D.W. Hood, W.E. Shiels and E.J. Kelley. Environ-mental Studies of Port Valdez. In-stitute of Marine Science. Occa-sional Publication No. 3. Guenette, S. 1996. Macrobenthos, p. 65-67. In D. Pauly and V. Chris-tensen (eds.) Mass-Balance Mod-els of North-eastern Pacific Eco-27 systems. Fisheries Centre Re-search Report 4 (1). Hannon, B. 1979. Total energy costs in ecosystems. J. theor. Bio. 80: 271-293. Hobson, K.A., J.L. Sease, R.L. Merrick, and J.F. Piatt. 1997. Investigating trophic relationships of pinnipeds in Alaska and Washington using stable isotope ratios of nitrogen and carbon. Marine Mammal Sci-ence 13(1):114-132. Huato, L. 1996. Salmon in the Ocean, p. 21-23. . In D. Pauly and V. Christensen (eds.) Mass-Balance Models of North-eastern Pacific Ecosystems. Fisheries Centre Re-search Report 4(1). Irons, D.B. 1996. Size and Productivity of Black-legged Kittiwake Colo-nies in Prince William Sound be-fore and after the Exxon Valdez Oil Spill, p. 738-747. In S.D. Rice, R.B. Spies, D.A. Wolfe and B.A. Wright (eds.) 1996. Proceedings of the Exxon Valdez Oil Spill Sympo-sium. American Fisheries Society Symposium 18, Bethesda. Isleib, M.E. and B. Kessel. 1973. Birds of the North Gulf Coast-Prince William Sound Region, Alaska. Biological Papers of the University of Alaska, Anchorage, Alaska. Koehl, P.S., T.C. Rothe and D.V. Derk-sen 1982. Winter food habits of Barrow's goldeneyes in southeast Alaska, p. 1-5. In D.N. Nettleship, G.A. Sanger and P.F. Springer (eds.). Marine birds: their feeding ecology and commercial fisheries relationships. Proceedings of the Pacific Seabird Group Sympo-sium, Seattle, Washington. Leatherwood, S., C.O. Matkin, J.D. Hall and G.M. Ellis. 1990. Killer Whales, Orcinus orca, Photo-identified in Prince William Sound, Alaska, 1976 through 1987. The Canadian Field-Naturalist 104:362-371. Leontief, W.W. 1951. The structure of the American economy. 2nd Edi-tion. Oxford University Press, New York. 264 p. Loughlin, T.R., editor. 1994. Marine Mammals and the Exxon Valdez. Academic Press, Inc. California. 395 p. Kelson, J. Y. Wada and S. Speckman. 1996. Seabirds in the Alaskan Gyre, p. 31-32. In D. Pauly and V. Christensen (eds.) Mass-Balance Models of North-eastern Pacific Ecosystems. Fisheries Centre Re-search Report 4 (1). Kline, T. and D. Pauly. 1997. Cross-validation of trophic level esti-mates from a mass-balance mod-els of, and 15N/14N data from Prince William Sound. Presented at the 14th Lowell Wakefield Sym-posium, "Fishery Stock Assess-ment Models for the 21st Cen-tury", October 8-11, 1997, An-chorage, Alaska [see Appendix 1, this volume] Morstad, S., D. Sharp, J. Wilcock and J. Johnson. 1996. Prince William Sound Management Area 1995 Annual Finfish Management Re-port. Alaska Department of Fish and Game. Commercial Fisheries Management and Development Division, Central Region, Anchor-age, Alaska. 28 Muck, P. and D. Pauly. 1987. Monthly anchoveta consumption of guano birds, 1953 to 1982, p. 219-233. In D. Pauly and I. Tsukayama (eds.) the Peruvian anchoveta and its upwelling ecosystem: three decades of change. ICLARM Studies and Reviews 15. Nilsson, S.G. and I.N. Nilsson. 1976. Number, food and consumption, and fish predation by birds in Lake Mockeln, Southern Sweden. Ornis Scand. 7:61-71. NMFS. 1993. Final Report. State/Federal Natural Resource Damage Assessment. Prince Wil-liam Sound Trawl Assessment. Fish/Shellfish Study No 18. Na-tional Marine Fisheries Services, Alaska Fisheries Science Center. O'Clair, C.E. and S.T. Zimmerman. 1986. Biogeography and Ecology of Intertidal and Shallow Subtidal Communities, p. 305-344. In D.W. Hood and S.T. Zimmerman (eds.). The Gulf of Alaska: physical envi-ronment and biological resources. NOAA, U.S. Department of Com-merce, Washington, D.C. Oakley, K.L. and K.J. Kuletz. 1996. Population, Reproduction, and Foraging of Pigeon Guillemots at Naked Island, Alaska, before and after the Exxon Valdez Oil Spill, p. 759-769. In S.D. Rice, R.B. Spies, D.A. Wolfe and B.A. Wright (eds.) Proceedings of the Exxon Valdez Oil Spill Symposium. American Fisheries Society Symposium 18, Bethesda. Olivieri, R.A., A. Cohen and F.P. Chavez. 1993. An Ecosystem Model of Monterey Bay, Califor-nia, p. 315-322. In V. Christensen and D. Pauly (eds.) Trophic mod-els of aquatic ecosystems. ICLARM Conf. Proc. 26. Palmer, R.S., editor. 1976. Handbook of North Ameriacn birds. Vol. 2, Yale University Press, New Haven and London. Paine, R.T., J.L. Ruesink, A. Sun, E.L. Soulanille, M.J. Wonham, C.D.G. Harley, D.R. Brumbaugh and D.L. Secord. 1996. Touble on oiled wa-ters: lessons from the Exxon Val-dez oil spill. Ann. Rev. Ecol Syst. 27:197-235. Pauly, D. and V. Christensen. 1993. Stratified models of large marine ecosystem: a general approach and an application to the South China Sea, p. 148-174. In K. Sherman, L.M. Alexander and B.D. Gold (eds.) Large marine ecosys-tems: stress, mitigation and sustainability. AAAS Symposium. AAAS Press, Washington, D.C. Pauly, D. and V. Christensen, editors. 1996. Mass-Balance Models of North-eastern Pacific Ecosystems: Proceedings of a Workshop held at the Fisheries Centre, University of British Columbia, Vancouver, B.C., Canada. Fisheries Centre Re-search Reports 4(1). 131 p. Pauly, D., J. Dalsgaard and R. Powell. 1997. Mass-balance food web ecosystem models as an alterna-tive approach for combining mul-tiple information sources in fish-eries. Presented at the 14th Lowell Wakefield Symposium, "Fishery Stock Assessment Models for the 21st Century", October 8-11, 1997, 29 Anchorage, Alaska [see Appendix 2, this volume] Pauly, D., M. Soriano-Bartz and M.L.D. Palomares. 1993. Improved con-struction, parametrization and in-terpretation of steady-state eco-system models, p. 14-19. In V. Christensen and D. Pauly (eds.) Trophic models of aquatic eco-systems. ICLARM Conf. Proc. 26. Polovina, J.J. 1984. Models of a coral reef ecosystem I: the ECOPATH Model and its application to French Frigate Schoal. Coral Reefs 3(12):1-11. Polovina, J.J. 1985. An approach to estimating an ecosystem box model. U.S. Fish. Bull. 83(3):457-560. Polovina, J.J. and M.D. Ow. 1983. ECOPATH: a user's manual and program listings. NMFS/NOAA, Honolulu Admin. Rep. H-83-23. 46 p. Rice, D.W. and A.A. Wolman. 1981. Summer Distribution and Num-bers of Fin, Humpback, and Gray Whales in the Gulf of Alaska. En-vironmental Assessment of the Alaskan Continental Shelf, Final Reports of Principal Investigators 20:1-45. Rice, S.T., R.B. Spies, D.A. Wolfe and B.A. Wright, editors. 1996. Pro-ceedings of t he Exxon Valdez Oil Spill Symposium. American Fish-eries Society Symposium 18. Be-thesda. 931 p. Ricker, W.E. 1976. Review of the rate of growth and mortality of Pacific salmon in salt water, and non-catch mortality caused by fishing. J. Fish. Res. Board Can. 33(7):1483-1524. Sambrotto, R.N. and C.J. Lorenzen 1986. Phytoplankton and primay production, p. 249-282. In D.W. Hood and S.T. Zimmerman (eds.) The Gulf of Alaska: physical, envi-ronmental and biological re-sources. U.S. Department of Commerce, NOAA, Washington, D.C. Stekoll, M.S., L. Deysher, R.C. Highs-mith, S.M. Saupe, Z. Guo, W.P. Erickson, L. McDonals and D. Strickland. 1996. Coastal Habitat Injury Assessment: Intertidal Communities and the Exxon Val-dez Oil Spill, p. 177-192. In S.T. Rice, R.B. Spies, D.A. Wolfe and B.A. Wright (eds.) Proceedings of the Exxon Valdez Oil Spill Sympo-sium. American Fisheries Society Symposium 18. Bethesda. Sturdevant, M.V., A.C. Wertheimer, and J.L. Lum. 1996. Diets of Juvenile Pink and Chum Salmon in Oiled and Non-Oiled Nearshore Habi-tats in Prince William Sound, 1989 and 1990. P. 578-592 In S.T. Rice, R.B. Spies, D.A. Wolfe and B.A. Wright (eds.) Proceedings of the Exxon Valdez Oil Spill Sympo-sium. American Fisheries Society Symposium 18. Bethesda. Trites, A. and K. Heise. 1996. Marine Mammals [of the Alaska Gyre], p. 25-30. In D. Pauly and V. Chris-tensen (eds.) Mass-Balance Mod-els of North-eastern Pacific Eco-systems. Fisheries Centre Re-search Report 4(1). Trowbridge, C. 1996. Prince William Sound Management Area 1995 30 Shellfish annual Management Re-port. Regional Informational Re-port No. 2A96-29. Alaska De-partment of Fish and Game, Divi-sion of Commercial Fisheries Management. Anchorage, Alaska. Venier, J. 1996. Balancing the Strait of Georgia model, p. 74-80. In D. Pauly and V. Christensen (eds.) Mass-Balance Models of North-eastern Pacific Ecosystems. Fish-eries Centre Research Report 4 (1). Vermeer, K. 1981. Food and popula-tions of surf scoters in British Columbia. Wildfowl. 32:107-116. Vermeer, K. and N. Bourne. 1982. The White-winged Scoter diet in Brit-ish Columbia waters: resource partitioning with other scoters, p. 30-38. In D.N. Nettleship, G.A. Sanger and P.F. Springer (eds.) Marine birds: their feeding ecol-ogy and commercial fisheries re-lationships. Proceedings of the Pacific Seabird Group Sympo-sium, Seattle, Washington. Wada, Y. 1996. Marine mammals and birds [of the Strait of Georgia], p. 25-30. In D. Pauly and V. Chris-tensen (eds.) Mass-Balance Mod-els of North-eastern Pacific Eco-systems. Fisheries Centre Re-search Report 4.(1). Walters, C. 1996. Suggested improve-ments for Ecopath modeling, p. 82-86. In D. Pauly and V. Chris-tensen (eds.) Mass-Balance Models of North-eastern Pacific Ecosys-tems. Fisheries Centre Research Report 4 (1). Walters, C., V. Christensen and D. Pauly. 1997. Structuring dynamic models of exploited ecosystems from trophic mass-balance as-sessments. Rev. Fish Biol. Fish. 7:139-172. Wespestad, V.G. and S.M. Fried. 1983. Review of the Biology and Abun-dance Trends of Pacific Herring (Clupea harengus pallasii), p. 17-29. In W.S. Wooster (ed.). From Year to Year: Interannual Vari-ability of the Environment and Fisheries of the Gulf of Alaska and the Eastern Bering Sea. Washington Sea Grant Publica-tion. University of Washington, Seattle. Wiebe, P.H., S. Boyd and J.L. Cox. 1975. Relationships between zooplank-ton displacement volume, wet weight, dry weight, and carbon. U.S. Fishery Bulletin 73(4):777-786. Whitehead, P.J.P. 1985. Clupeoid fishes of the world. An annotated and illustrated catalogue of the her-rings, sardines, pilchards, sprats, shads, anchovies and wolf-herrings. Part 1 - Chirocentridaie, Clupeidae and Pristigastridae. FAO Species Catalogue Vol. 7, Part 1. 303 p. 31 Appendix 1 Cross-validation of trophic level estimates f rom a mass-balance models of, and 15N/14N data from Prince William Sound3 by Thomas C. Kline Jr.1 and Daniel Pauly4 Abstract Trophic mass-balance models of ecosystems constructed using the Ecopath approach and software include the diet composition of the various groups as one of the inputs; trophic level estimates for these groups is one of the outputs. Trophic level can also be determined using On the other hand, the well-documented 0.34% enrichment of 15N/14N that occurs at each feeding step in food webs. This contribution is the first to examine the relationship between trophic levels estimated by these two independent methods. This was achieved using an Ecopath model of Prince William Sound (PWS) constructed by J. Dalsgaard and D. Pauly, who also identified the species groups included as 'boxes' in the model, then estimating 15N/14N ratios as a mean for each of these groups. Re-expression of theses ratios as absolute estimate of trophic levels (TL) was done following calibration using the herbivorous copepod Neocalanus crista tus, for which TL = 2. The correlation between both sets of TL values (n= 7) was extremely high (r = 0.915), with the points evenly distributed about the 1:1 line. Moreover the variance of the TL estimates based on 15N/14N data also correlated (r = 0.495) with the variance of the Ecopath estimates, i.e., with the 'omnivory index' (01) output by Ecopath. Applying 15N/14N data from PWS to an Ecopath model of the Alaska gyre resulted in reduced correlations, suggesting that TL and 01 estimates can be transferred between ecosystems, though at the cost of reduced precision. These encouraging results warrant further exploration. a Adapted from a poster presented at the 14th Lowell Wakefield Symposium, "Fishery Stock Assessment Models for the 21st Century", October 8-11,1997, Anchorage, Alaska. b Prince William Sound Science Center, P.O. Box 705, Cordova, AK 99574, Cordova, USA (pwssc.gen.ak.us) c Fisheries Centre, 2204 Main Mall, University of British Columbia, Vancouver, B.C., Canada. V6T 1Z4 (pauly@fisheries.com). 32 Appendix 1 Mass-balance food web ecosystem models as an alternative approach for combining multiple information sources in fisheries3 by Daniel Paulyb Johanne Dalsgaard2 and Robert Powellc Abstract: Highly parameterized analytical single-species models offer a tempting framework for integrating data from different sources, e.g., survey biomass estimates, fishery catches and catch composition data. We argue, however, that forcing data that usually cover a number of species into single-species models, however sophisticated, does not optimally use such data. Rather, emphasis should be given to models that explicitly account for multi-species interactions, especially trophic models. While mathematically not complex, trophic models can be made 'complete', i.e., they can be made to in-clude all groups in a system, and thus consider direct and indirect trophic im-pact on target species. Such completeness also, in itself provides set limits on difficult to-estimate stock sizes, production and mortality rates, i.e., on proc-esses directly relevant to fisheries resource management. In addition, these models the resp As trophic end themselves to answering questions about ecosystem dynamics and onses of ecosystems to anthropogenic changes. an example, we discuss the properties and behavior of a mass-balance model representing the Prince William Sound ecosystem from 1980 to 1989, i.q., prior to the Exxon Valdez Oil Spill. a Presented 21st Centi b Fisheries V6T 1Z4 c Departme 37996, US at the 14th Lowell Wakefield Symposium, "Fishery Stock Assessment Models for the ry", October 8-11, 1997, Anchorage, Alaska. Centre, 2204 Main Mall, University of British Columbia, Vancouver, B.C. Canada, (pauly @ fisheries.com). nt of Ecology and Evolutionary Biology, The University of Tennessee, Knoxville, TN A. 33 FISHERIES CENTRE RESEARCH REPORT SERIES Commercial Whaling - the Issues Reconsidered Fisheries Centre Research Reports 1993, Volume 1, Number 1, 36pp Decision Making by Commercial Fisherman: a missing component in fisheries management? Fisheries Centre Research Reports 1993, Volume 1, Number 2, 75pp Bycatch in Fisheries and their Impact on the Ecosystem Fisheries Centre Research Reports 1994, Volume 2, Number 1, 86pp Graduate Student Symposium on Fish Population Dynamics and Management Fisheries Centre Research Reports 1995, Volume 3, Number 1, 33pp Harvesting Krill: Ecological impact, assessment, products and markets Fisheries Centre Research Reports 1995, Volume 3, Number 3, 82pp Mass-Balance Models of North-eastern Pacific Ecosystems Fisheries Centre Research Reports 1996, Volume 4, Number i,13 lpp Reinventing Fisheries Management Fisheries Centre Research Reports 1996, Volume 4, Number 2, 84pp The Design & Monitoring of Marine Reserves Fisheries Centre Research Reports 1997, Volume 5, Number 1, 47pp Preliminary Mass-Balance Model of Prince William Sound, Alaska, for the Pre-Spill Period, 1980-1989 I Fisheries Centre Research Reports 1997, Volume 5, Number 2, 33pp Copies of any of these research reports may be obtained at a cost of Can$20.00, which includes surface mail. Payment may be made by Credit Card, cheque or money order. Please contact: Events Officer Fisheries Centre University of British Columbia 2204 Main Mall, Hut B-8 Vancouver, V6T 1Z4 Canada phone: 604 822-0618 fax: 604 822-8934 E-mail: events@fisheries.com Web Site: http://fisheries.com 

Cite

Citation Scheme:

        

Citations by CSL (citeproc-js)

Usage Statistics

Share

Embed

Customize your widget with the following options, then copy and paste the code below into the HTML of your page to embed this item in your website.
                        
                            <div id="ubcOpenCollectionsWidgetDisplay">
                            <script id="ubcOpenCollectionsWidget"
                            src="{[{embed.src}]}"
                            data-item="{[{embed.item}]}"
                            data-collection="{[{embed.collection}]}"
                            data-metadata="{[{embed.showMetadata}]}"
                            data-width="{[{embed.width}]}"
                            async >
                            </script>
                            </div>
                        
                    
IIIF logo Our image viewer uses the IIIF 2.0 standard. To load this item in other compatible viewers, use this url:
http://iiif.library.ubc.ca/presentation/dsp.52383.1-0074775/manifest

Comment

Related Items