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Biodiversity as a Means of Poverty Alleviation in Sub-­Saharan Africa 2012

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Biodiversity	
  as	
  a	
  Means	
  of	
  Poverty	
  Alleviation	
  in	
  Sub-­Saharan	
  Africa	
  	
  This	
  paper	
  investigates	
  the	
  relationship	
  between	
  high	
  levels	
  of	
  poverty	
  and	
  biodiversity	
  in	
  sub-­‐Saharan	
  Africa	
  (SSA).	
  Using	
  a	
  collection	
  of	
  secondary	
  research,	
  it	
  was	
  found	
  that	
  the	
  link	
  between	
  these	
  two	
  variables	
  is	
  more	
  than	
  geographic,	
  and	
  that	
  biodiversity	
  conservation	
  is	
  a	
  crucial	
  factor	
  in	
  the	
  alleviation	
  of	
  poverty	
  in	
  SSA.	
  A	
  variety	
  of	
  poverty	
  reducing	
  strategies	
  that	
  incorporate	
  biodiversity	
  conservation	
  have	
  been	
  implemented	
  and	
  succeeded	
  elsewhere,	
  implying	
  that	
  the	
  same	
  is	
  possible	
  for	
  this	
  region.	
  Overall,	
  the	
  paper	
  suggests	
  that	
  the	
  biodiversity	
  of	
  SSA	
  will	
  be	
  particularly	
  important	
  for	
  the	
  economic	
  wellbeing	
  of	
  the	
  poor	
  in	
  a	
  future	
  of	
  climate	
  change.	
  	
  	
   1.	
  Introduction	
  	
  	
  	
  	
  	
  Sub-­‐Saharan	
  Africa	
  (SSA)	
  is	
  defined	
  as	
  the	
  region	
  of	
  Africa	
  that	
  lies	
  below	
  the	
  Sahara	
  desert	
  (Figure	
  1).	
  It	
  includes	
  47	
  African	
  countries,	
  800	
  million	
  people,	
  and	
  covers	
  an	
  area	
  of	
  23.6	
  million	
  square	
  kilometers	
  (Africa,	
  2010;	
  Walker,	
  2009).	
  Poverty	
  in	
  this	
  region	
  is	
  pervasive,	
  with	
  close	
  to	
  half	
  of	
  the	
  SSA	
  population	
  living	
  in	
  absolute	
  poverty	
  on	
  less	
  than	
  $1	
  per	
  day,	
  as	
  defined	
  by	
  the	
  World	
  Bank	
  (Fisher	
  &	
  Christopher,	
  2007;	
  Lufumpa,	
  2005).	
  Despite	
  such	
  a	
  simple	
  definition	
  in	
  this	
  case,	
  poverty	
  is	
  a	
  complex,	
  multi-­‐dimensional	
  material	
  deprivation	
  that	
  involves	
  the	
  lack	
  of	
  access	
  to	
  basic	
  needs	
  such	
  as	
  education,	
  health	
  and	
  nutrition	
  (Roe,	
  2010).	
  The	
  poverty	
  in	
  SSA	
  will	
  only	
  be	
  amplified	
  by	
  the	
  region’s	
  expected	
  drastic	
  increase	
  in	
  population	
  to	
  1.7	
  billion	
  people	
  by	
  2050,	
  and	
  3	
  billion	
   	
  Figure	
  1:	
  Map	
  of	
  sub-­‐Sahara	
  nations.	
  From	
  Buggey	
  (2007).	
  	
   by	
  the	
  end	
  of	
  the	
  century	
  (Lufumpa,	
  2005;	
  Walker,	
  2009).	
  The	
  majority	
  of	
  this	
  growing	
  population	
  lives	
  in	
  rural	
  areas	
  and	
  depends,	
  as	
  pastoralists	
  and	
  cultivators,	
  on	
  the	
  high	
  levels	
  of	
  biodiversity	
  provided	
  by	
  the	
  broad	
  range	
  of	
  climatic,	
  geological,	
  soil	
  and	
  landscape	
  forms	
  in	
  the	
  region	
  (Darkoh,	
  2009;	
  Lufumpa,	
  2005).	
  This	
  biodiversity,	
  defined	
  as	
  species	
  variability,	
  encompasses	
  the	
  variety	
  that	
  occurs	
  within	
  living	
  things,	
  including	
  genetic	
  variation	
  and	
  variations	
  between	
  species	
  (Barrett,	
  Travis,	
  &	
  Dasgupta,	
  2011).	
  When	
  measured	
  in	
  terms	
  of	
  species	
  richness	
  and	
  endemism,	
  SSA	
  has	
  one	
  of	
  the	
  highest	
  levels	
  of	
  biodiversity	
  globally,	
  making	
  it	
  home	
  to	
  7.5%	
  of	
  the	
  world’s	
  vascular	
  plant	
  species,	
  5.8%	
  of	
  mammals,	
  8%	
  of	
  birds,	
  16%	
  of	
  marine	
  fish,	
  and	
  5.5%	
  of	
  insects	
  (Roe,	
  2010;	
  Roe,	
  Walpole,	
  &	
  Elliott,	
  2010).	
  	
   2.	
  Understanding	
  SSA	
   2.1.	
  Environmental	
  Issues	
  	
  	
  	
  	
  	
  SSA	
  is	
  a	
  region	
  particularly	
  vulnerable	
  to	
  environmental	
  degradation	
  due	
  to	
  the	
  heavy	
  reliance	
  of	
  its	
  rural	
  populations	
  on	
  the	
  land	
  for	
  their	
  livelihoods	
  (Darkoh,	
  2009).	
  These	
  environmental	
  concerns,	
  including	
  deforestation,	
  desertification,	
  population	
  growth,	
  pollution	
  and,	
  most	
  relevantly,	
  biodiversity	
  loss,	
  are	
  all	
  expected	
  to	
  be	
  amplified	
  by	
  future	
  changes	
  in	
  climate	
  (Darkoh,	
  2009).	
  The	
  past	
  decade	
  has	
  been	
  the	
  warmest	
  and	
  driest	
  of	
  the	
  century,	
  and	
  climate	
  change	
  is	
  expected	
  to	
  make	
  the	
  SSA	
  climate	
  more	
  variable,	
  bringing	
  more	
  frequent	
  and	
  severe	
  weather	
  events	
  such	
  as	
  droughts	
  and	
  floods	
  (Darkoh,	
  2009).	
  	
  	
  	
  	
  	
  	
  The	
  numerous	
  environmental	
  issues	
  that	
  exist	
  in	
  SSA	
  are	
  interlinked,	
  all	
  contributing	
  in	
  one	
  way	
  or	
  another	
  to	
  a	
  loss	
  of	
  biodiversity	
  in	
  the	
  region.	
  Deforestation	
  and	
  desertification	
  cause	
  a	
  loss	
  of	
  5.3	
  million	
  hectares	
  of	
  SSA	
  forests	
   and	
  woodlands	
  annually	
  (Darkoh,	
  2009).	
  These	
  losses	
  are	
  due	
  to	
  unsustainable	
  land	
  use	
  practices	
  such	
  as	
  overgrazing	
  and	
  excessive	
  fertilization,	
  as	
  well	
  as	
  the	
  use	
  of	
  wood	
  for	
  cooking,	
  heating,	
  and	
  lighting	
  	
  (since	
  only	
  approximately	
  24%	
  of	
  the	
  SSA	
  population	
  have	
  access	
  to	
  electricity)	
  (Darkoh,	
  2009;	
  Lufumpa,	
  2005).	
  This	
  high	
  level	
  of	
  land	
  degradation	
  poses	
  serious	
  threats	
  to	
  the	
  region’s	
  biodiversity	
  by	
  destroying	
  ecosystems,	
  natural	
  habitats,	
  and	
  threatening	
  the	
  survival	
  of	
  many	
  plant	
  and	
  animal	
  species	
  (Lufumpa,	
  2005).	
  Population	
  growth	
  in	
  this	
  region	
  is	
  extreme,	
  putting	
  a	
  strain	
  on	
  environmental	
  resources	
  through	
  a	
  required	
  increase	
  in	
  production	
  and	
  consumption	
  (Darkoh,	
  2009).	
  As	
  standards	
  of	
  living	
  in	
  the	
  region	
  improve,	
  the	
  currently	
  low	
  levels	
  of	
  air	
  and	
  water	
  pollution	
  will	
  likely	
  be	
  increased	
  due	
  to	
  demands	
  for	
  industrialization	
  (Darkoh,	
  2009).	
  This	
  increased	
  stress	
  on	
  natural	
  resources	
  will	
  lead	
  to	
  further	
  biodiversity	
  degradation	
  (Darkoh,	
  2009).	
  Even	
  civil	
  conflicts	
  pose	
  a	
  threat	
  to	
  the	
  region’s	
  diversity,	
  as	
  displaced	
  populations	
  are	
  forced	
  to	
  pay	
  little	
  attention	
  to	
  environmental	
  concerns	
  (Darkoh,	
  2009;	
  Lufumpa,	
  2005).	
  These	
  threats	
  to	
  biodiversity	
  are	
  a	
  major	
  concern	
  for	
  a	
  region	
  with	
  such	
  initially	
  high	
  levels	
  of	
  diversity	
  and	
  such	
  high	
  economic	
  dependence	
  on	
  the	
  land	
  (Darkoh,	
  2009).	
  The	
  extinction	
  rate	
  in	
  SSA	
  is	
  already	
  high	
  by	
  global	
  standards,	
  and	
  the	
  region’s	
  plant	
  and	
  animal	
  species	
  continue	
  to	
  be	
  threatened	
  daily	
  (Darkoh,	
  2009;	
  Lufumpa,	
  2005).	
  	
   2.2.	
  Poverty	
   	
  	
  	
  	
  Poverty	
  in	
  SSA	
  is	
  widespread,	
  particularly	
  in	
  rural	
  regions,	
  with	
  at	
  least	
  313	
  million	
  of	
  the	
  region’s	
  population	
  living	
  on	
  less	
  than	
  $1	
  a	
  day	
  (Munthali,	
  2007).	
  Although	
  not	
  the	
  poorest	
  region	
  of	
  the	
  world,	
  SSA	
  is	
  the	
  only	
  region	
  in	
  which	
  poverty	
  is	
  anticipated	
  to	
  increase	
  significantly	
  (by	
  19%	
  by	
  2015),	
  contrary	
  to	
  the	
  United	
  Nations	
  Millennium	
  development	
  goal	
  to	
  cut	
  the	
  number	
  living	
  in	
  poverty	
  in	
  half	
  by	
  2015	
  (Lufumpa,	
  2005;	
  Munthali,	
  2007).	
  SSA	
  currently	
  accounts	
  for	
  30%	
  of	
  the	
  developing	
  world’s	
  population	
  living	
  in	
  poverty	
  (Figure	
  2),	
  compared	
  to	
  16%	
  in	
  the	
  1980’s	
  (Lufumpa,	
  2005).	
  This	
  pervasive	
  poverty	
  is	
  closely	
  related	
  to	
  the	
  deterioration	
  of	
  biodiversity	
  in	
  the	
  region,	
  as	
  large	
  rural	
  communities	
  are	
  forced	
  to	
  degrade	
  the	
  environment	
  for	
  survival	
  (Lufumpa,	
  2005).	
  This	
  interrelation	
  is	
  a	
  major	
  concern	
  for	
  SSA,	
  as	
  these	
  impoverished	
  rural	
  residents	
  have	
  a	
  strong	
  dependence	
  on	
  this	
  degraded	
  land	
  as	
  their	
  main	
  source	
  of	
  livelihood,	
  thereby	
  creating	
  a	
  vicious	
  cycle	
  (Lufumpa,	
  2005).	
  	
   3.	
  Link	
  Between	
  Biodiversity	
  and	
  Poverty	
   3.1.	
  Geographical	
  Link	
  	
  	
  	
  	
  	
  There	
  is	
  a	
  high	
  magnitude	
  of	
  overlap	
  between	
  globally	
  important	
  regions	
  of	
  biodiversity	
  and	
  regions	
  of	
  poverty,	
  and	
  mounting	
  evidence	
  suggests	
  that	
  these	
  two	
  variables	
  do	
  coincide	
  spatially	
  (Figure	
  3)	
  (Barrett,	
  Travis,	
  &	
  Dasgupta,	
  2011;	
  Fisher,	
   	
  Figure	
  2:	
  Population	
  living	
  in	
  poverty	
  (percentage	
  below	
  $1	
  a	
  day	
  of	
  income).	
  From	
  Lufumpa	
  (2005).	
  	
   handful of African countries are likely to attain the Millennium Development Goal (MDG) of halving poverty levels by 2015. Close to half of Africa’s population of over 800 million lives in absolute poverty (see Figure 1). While Africa is in absolute terms not the world’s poorest region, it is the only region where the number of poor people is increasing significantly. Though the number of poor people has decreased recently in developing countries, Africa saw a significant increase in the number of its poor. Hence, Africa accounts today for some 30 per cent of the poor in developing countries, compared with about 16 per cent in the mid-1980s. Poverty indicators for Africa show that the majority of the poor live in rural areas, with subsistence agriculture, fishing and hunting as the main sources of livelihood. In both urban and rural areas, women comprise, relative to men, a disproportionately large number of people living in absolute poverty. With regard to the main social indicators, Africa lags behind other developing regions. The crude death rate is about 15.2 per 1,000 people compared with 6.6 in South America and 7.7 for Asia. Though infant mortality in the region has fallen substantially since the 1970s to 80.6 children per 1,000 live births, it still compares unfavourably with the average of 60.9 for all low-income countries (see Figure 2). Further, though most African countries can sustain several harvests a year, malnutrition is still widespread. It is estimated that about 26 per cent of all African children under 5 years of age suffer from severe malnutrition or stunting, while only 62 per ce t f the African popula- tion have access to health services, compared to 80 per cent for develop- ing countries as a whole. Using its human development index (HDI), a measure incorporating aspects such as life expectancy, education and in ome levels to estimate the quality of life, the United Nations Development Program (2005) has Figure 1: Population living in poverty (percentage below $1 a day, 2000) 46.7% 23% 20% 0 10 20 30 40 50 Africa Developing Countries Developed Countries Source: African Development Bank, Statistics Division. 368 C. L. Lufumpa #African Development Bank 2005 &	
  Christopher	
  2007;	
  Roe,	
  2010).	
  SSA	
  is	
  a	
  particularly	
  interesting	
  case	
  of	
  this	
  overlap	
  between	
  biodiversity	
  and	
  poverty,	
  as	
  it	
  displays	
  increasing	
  poverty	
  levels	
  along	
  with	
  decreases	
  in	
  biodiversity	
  (Roe,	
  2010;	
  Roe,	
  Walpole,	
  &	
  Elliott,	
  2010).	
  This	
  geographical	
  link	
  is	
  important	
  as	
  it	
  is	
  often	
  presented	
  as	
  rationale	
  for	
  pursuing	
  biodiversity	
  conservation	
  and	
  poverty	
  reduction	
  together	
  (Roe,	
  Walpole,	
  &	
  Elliott,	
  2010).	
  	
   3.2.	
  Misleading	
  Implication	
  	
  	
  	
  	
  	
  On	
  the	
  surface,	
  this	
  strong	
  overlap	
  between	
  high	
  levels	
  of	
  biodiversity	
  and	
  high	
  levels	
  of	
  poverty	
  may	
  suggest	
  that	
  a	
  healthy	
  economy	
  and	
  diverse	
  environment	
  are	
  mutually	
  exclusive	
  occurrences	
  (Adams	
  et	
  al.,	
  2004).	
  This	
  strong	
  spatial	
  link	
  can	
  lead	
  to	
  dangerous	
  conclusions,	
  as	
  it	
  may	
  suggest	
  a	
  cause-­‐and-­‐effect	
  relationship	
  in	
  which	
  poverty	
  is	
  a	
  constraint	
  on	
  conservation,	
  or	
  conservation	
  is	
  harmful	
  to	
  those	
  in	
  poverty	
  (Adams	
  et	
  al.,	
  2004;	
  Fisher,	
  &	
  Christopher,	
  2007).	
  The	
  more	
  dangerous	
  of	
  these	
  conclusions	
  is	
  that	
  conservation	
  efforts	
  may	
  be	
  harmful	
  to,	
  and	
  should	
  not	
   	
  Figure	
  3:	
  Global	
  biodiversity	
  and	
  poverty	
  overlap	
  (Darker	
  shades	
  show	
  the	
  most	
  impoverished	
  of	
  the	
  world’s	
  34	
  biodiversity	
  hot	
  spots).	
  From	
  Fisher	
  &	
  Christopher	
  (2007).	
   By re-aggregating the countries back to the biodiversity hotspots we can get a sense of the hottest areas as based on ecoregion (Table 2). Through this lens we see that 14 hotspots appeared in Table 1 at least three times. Of these only three hotspots made the top 25 five times. They are Eastern Afromontane, Guinean Forests of West Africa, and the Himalaya. Six hotspots appeared in the top 25 four times. They are the Coastal Forests of Eastern Africa, East Melane- sian Islands, Horn of Africa, Indo-Burma, Madagascar and the India Ocean Islands, and Mountains of Central Asia. Of special note are the Coastal Forests of Eastern Africa, Indo- Burma and Madagascar and the India Ocean Islands. These three also appeared in the hottest hotspots list based solely on ecological indicators in the original Myers et al. Nature article. When re-ranked by area affected, we get a different ordering, with the Horn of Africa well above the rest. Again the Indo-Burma, Madagascar and the India Ocean Islands, and the Eastern Afromontane hotspots rank highly. But with this ranking ey are joined by the Tropical Andes and Cerrado hotspots (Table 3). 7. Limitations Our examination of the socio-economic landscape in the countries where CI's hotspots lie has a number of limitations: 1) The biodiversity hotspots are aggregated based on similar ecological characteristics, ignoring political bou daries, while most socio-economic data, including all used in this analysis, are available only for national boundaries. As global datasets improve and become more closely linked with geographical information systems, this analysis could focus dir ctly on hotspots rather than through nati s. At the same time much important initiative funding is channeled and tied to political boundaries i.e. countries (Balmford et al., 2000). 2) With analysis on 125 countries multiple data sources were used. While all attempts were made to standardize the data, deficiencies may still exist. One example is that each country determines its own poverty line, and therefore there are inherent methodological and precision errors. 3) Population density and growth figures are only proxies for human impact on ecological systems (Cincotta et al., 2000). For example, low density slash and burn populations can have large ecological effects. Also, proximity to urban areas may also provide a link to the impact of poverty on ecosystems. 4) The indicators used were picked from available global datasets. Sufficient datasets for additional appropriate socio-economic indicators do not exist. For example, primary fuel source data would be an appropriate indicator for population pressure on local forest resources. Extensive data on the nutritional sources of a country would also be an important indicator to flesh out the human dependence on local resources. On the economic side some figure on national wealth as adjusted by a distribution index (such as the Gini Index) would also be of great value for this analysis. 5) Due to its recent political history there is no data on the state of Western Sahara. This country, which contains part of the West African Forests hotspot, is likely to have poor socio-economic statistics and heref re although it is not included in the analysis both the country and hotspot should be given careful consideration. 6) Myers et al.'s analysis created ecoregion sized biodiversity hotspots, where only 3–30% of their extent would truly be considered a ‘hotspot’. In thi analysis we utilized the entire defined hotspot (ecoregion) for analysis. Fig. 1 –Darker shades show themore imperiled of CI's 34 biodiversity hotspots according to this multifactor assessment, based on aggregate area of hotspot affected by conditions of socio-economic poverty. 98 E C O L O G I C A L E C O N O M I C S 6 2 ( 2 0 0 7 ) 9 3 – 1 0 1 compromise,	
  poverty	
  reduction	
  (Adams	
  et	
  al.,	
  2004;	
  Fisher,	
  &	
  Christopher,	
  2007).	
  This	
  implies	
  that	
  poverty	
  should	
  not	
  be	
  increased	
  due	
  to	
  conservational	
  efforts,	
  and	
  that	
  the	
  livelihood	
  of	
  the	
  poor	
  should	
  not	
  be	
  undermined	
  in	
  order	
  to	
  conserve	
  biodiversity	
  in	
  the	
  region	
  (Adams	
  et	
  al.,	
  2004).	
  This	
  is	
  a	
  troubling	
  implication,	
  as	
  it	
  suggests	
  that	
  a	
  choice	
  needs	
  to	
  be	
  made	
  between	
  the	
  environmental	
  and	
  social	
  wellbeing	
  of	
  this	
  region.	
  	
  	
  	
  	
  	
  	
  Further	
  research	
  has	
  shown	
  that	
  this	
  implied	
  causal	
  link	
  may	
  be	
  too	
  simplistic	
  to	
  describe	
  the	
  complex	
  interconnection	
  between	
  these	
  variables	
  (Adams	
  et	
  al.,	
  2004;	
  Fisher,	
  &	
  Christopher,	
  2007;	
  Roe,	
  2010).	
  Although	
  the	
  geographical	
  overlap	
  should	
  not	
  be	
  ignored,	
  a	
  more	
  in	
  depth	
  understanding	
  of	
  the	
  link	
  between	
  poverty	
  and	
  biodiversity	
  may	
  suggest	
  a	
  more	
  accurate	
  approach	
  to	
  this	
  complex	
  relationship	
  (Adams	
  et	
  al.,	
  2004;	
  Fisher,	
  &	
  Christopher,	
  2007;	
  Roe,	
  2010).	
  	
   4.	
  Importance	
  of	
  Biodiversity	
  in	
  Alleviating	
  Poverty	
   4.1.	
  Dependence	
  on	
  Biodiversity	
  	
  	
  	
  	
  	
  	
  The	
  majority	
  of	
  the	
  poor	
  in	
  SSA	
  live	
  in	
  rural	
  areas	
  with	
  a	
  livelihood	
  critically	
  dependent	
  upon	
  the	
  exploitation	
  of	
  natural	
  resources	
  such	
  as	
  water,	
  arable	
  land,	
  and	
  forest	
  resources	
  (Lufumpa,	
  2005).	
  This	
  makes	
  the	
  poor	
  in	
  this	
  region	
  disproportionately	
  and	
  directly	
  dependent	
  upon	
  its	
  biodiversity	
  (Reid,	
  &	
  Swiderska,	
  2008;	
  Roe,	
  Walpole,	
  &	
  Elliott,	
  2010).	
  The	
  history	
  of	
  civilization	
  in	
  SSA	
  shows	
  a	
  remarkable	
  link	
  with	
  biodiversity,	
  as	
  pre-­‐colonial	
  population	
  centers	
  were	
  built	
  in	
  areas	
  with	
  an	
  average	
  of	
  444.4	
  species,	
  as	
  opposed	
  to	
  the	
  359.6	
  species	
  average	
  in	
  the	
  rest	
  of	
  the	
  region	
  (Fjeldsa,	
  &	
  Burgwss,	
  2011).	
  Current	
  population	
  centers	
  and	
  species	
  richness	
  also	
  appear	
  to	
  be	
  strongly	
  correlated	
  (Figure	
  4),	
  suggesting	
  that	
  the	
   	
  Figure	
  4:	
  Scatter	
  plot	
  showing	
  species	
  richness	
  and	
  endemism	
  against	
  human	
  population	
  density	
  in	
  SSA.	
  From	
  Fjeldsa	
  &	
  Burgwss	
  (2008).	
   Discussion Environmental conditions of Africa’s population centres Our assessment confirms the idea of a general large-scale correlation between biodiversity and human population in Africa, suggested by Fjeldså & Lovett (1997) and Balmford et al. (2001). From this, we may infer that the traditional land use in Africa did not erase the natural large-scale biodiversity pattern. Table 1 shows a stronger positive correlation in the past than under the present diachronic regime, where effects of political change and globalization are overlain on the ancient population pattern, and where external demands lead to economic growth and infra- structure development in new areas. The simplest explanations would be that the spatial pattern of population growth in Africa has been gov- erned by environmental factors which also explain the large-scale variation in biological diversity, such as climate (Jetz & Rahbek, 2002). Balmford et al. (2001) demon- strated that the contemporary human population density exhibits a similar (though weaker) hump-shaped rela- tionship with productivity (Net Primary Productivity – NPP), as is seen with species richness. Human population density is particularly high in the transition zone between tropical savannah and rainforest and in tropical highlands and their adjacent foothills. The lowland rainforest, which represents the highest biological production, has never supported many people and also has a moderate species richness (Fig. 2c,d). The main discrepancy is the high biodiversity and moderate population density in southern Cameroon and Gabon. The denser human populations in the northern savannah zones compared with the southern woodland savannahs, especially Zambia, imply that the relation- ship is not simple. The Sahel zone had much higher precipitation in the past, with enormous wetlands in the early Holocene, and generally good rainfall during the early precolonial high cultures (e.g. Street & Grove, 1979). The people of this region took advantage of the Fig 4 Scatter plots of species richness and endemism (range-size rarity score) against human population density across 1805 one-degree grid cells in sub-Saharan Africa. (a) Log vertebrate species richness against log human population density, (b) log range-size rarity against log human population density, (c) log vertebrate species richness against log human infrastructure and (d) log range-size rarity against log human infrastructure 38 J. Fjeldså and N. D. Burgess ! 2008 The Authors. Journal compilation ! 2008 Blackwell Publishing Ltd, Afr. J. Ecol., 46 (Suppl. 1), 33–42 spatial	
  patterns	
  of	
  population	
  growth	
  have	
  been	
  governed	
  by	
  environmental	
  factors	
  such	
  as	
  biodiversity	
  (Fjeldsa,	
  &	
  Burgwss,	
  2011;	
  Roe,	
  Walpole,	
  &	
  Elliott,	
  2010).	
  This	
  implies	
  that	
  biodiversity	
  is	
  intrinsic	
  to	
  the	
  indigenous	
  agro-­‐pastoral	
  systems	
  of	
  the	
  region,	
  emphasizing	
  their	
  dependence	
  upon	
  it	
  (Fjeldsa,	
  &	
  Burgwss,	
  2011;	
  Roe,	
  Walpole,	
  &	
  Elliott,	
  2010).	
  	
  	
  	
  	
  	
  	
  Biodiversity	
  is	
  important	
  in	
  this	
  region	
  as	
  a	
  means	
  of	
  direct	
  income,	
  as	
  well	
  as	
  insurance,	
  since	
  the	
  prevalent	
  biodiversity	
  acts	
  as	
  a	
  buffer	
  against	
  risks	
  and	
  shocks	
  that	
  the	
  region	
  may	
  face	
  (Roe,	
  2010).	
  The	
  direct	
  economic	
  benefit	
  of	
  biodiversity	
  comes	
  from	
  the	
  biodiversity-­‐based	
  resources	
  used	
  for	
  household	
  income,	
  production,	
  and	
  consumption	
  (Roe,	
  2010).	
  Wild	
  animals	
  and	
  plants	
  play	
  an	
  enormous	
  role	
  as	
  resources	
  for	
  the	
  poor	
  in	
  this	
  region,	
  and	
  the	
  genetic	
  diversity	
  in	
  these	
  plant	
  and	
  animal	
  resources	
  is	
  therefore	
  vital	
  for	
  the	
  livelihood	
  of	
  these	
  communities	
  (Roe,	
  2010).	
  Table	
  1	
  shows	
  the	
  dependence	
  of	
  different	
  areas	
  of	
  SSA	
  on	
  certain	
  biodiversity	
  resources,	
  and	
  Table	
  2	
  shows	
  how	
  this	
  dependence	
  decreases	
  for	
  those	
  relieved	
  of	
  poverty	
  (The	
  variability	
  in	
  biodiversity	
  resources	
  used	
  as	
  a	
  source	
  of	
  livelihood	
  in	
  these	
  tables	
  reflects	
  the	
  availability	
  and	
  access	
  to	
  the	
  resource	
  each	
  area)	
  (Roe,	
  2010).	
  The	
  biodiversity	
  in	
  SSA	
  is	
  also	
  indirectly	
  relied	
   upon,	
  as	
  it	
  improves	
  the	
  resilience	
  of	
  the	
  regions	
  ecosystems	
  and	
  agricultural	
  land	
  (Roe,	
  2010).	
  Resilience	
  in	
  this	
  case	
  refers	
  to	
  the	
  ability	
  of	
  the	
  system	
  to	
  absorb	
  shocks	
  or	
  disturbances,	
  and	
  return	
  to	
  a	
  reference	
  state	
  after	
  perturbation	
  (Roe,	
  2010).	
  Strong	
  and	
  consistent	
  findings	
  show	
  that	
  by	
  improving	
  the	
  resilience	
  of	
  a	
  system,	
  biodiversity	
  has	
  a	
  positive	
  effect	
  on	
  mean	
  crop	
  yields	
  and	
  a	
  negative	
  effect	
  on	
  the	
  variability	
  of	
  crop	
  yields	
  (Roe,	
  2010).	
  This	
  provides	
  strong	
  insurance	
  against	
  food	
  security	
  risks	
  (Roe,	
  2010).	
  High	
  levels	
  of	
  biodiversity	
  in	
  SSA	
  farms	
  not	
  only	
  decrease	
  the	
  risk	
  of	
  crop	
  failure,	
  but	
  also	
  increase	
  soil	
  fertility,	
  improve	
  water	
  supplies,	
  and	
  provide	
  natural	
  pest	
  control	
  that	
  allows	
  for	
  an	
  increase	
  in	
  productivity	
  and	
  a	
  direct	
  economic	
  benefit	
  (Roe,	
  2010;	
  Roe,	
  Walpole,	
  &	
  Elliott,	
  2010).	
  	
  Table	
  1:	
  Collected	
  evidence	
  on	
  the	
  dependence	
  of	
  different	
  regions	
  of	
  SSA	
  on	
  biodiversity	
  for	
  income.	
  From	
  Roe	
  (2010).	
  	
   Source	
   Region	
   Evidence	
   Resource	
  type	
  Bene	
  et	
  al.	
  2009	
   West	
  Africa	
  	
   Varies	
  from	
  90%(poorest)-­‐29.7%(richest)	
   Fish	
  Cavendish	
  2000	
   Southern	
  Africa	
   35.4%	
  of	
  household	
  income	
  in	
  1993-­‐94;	
  36.9%	
  in	
  1996-­‐97	
   Wild	
  foods,	
  wood,	
  grasses	
  and	
  other	
  environmental	
  resources	
  de	
  Merode	
  et	
   al.	
  2004	
   West	
  Africa	
   24%	
  of	
  cash	
  sales	
   Wild	
  foods	
  Fisher	
  2004	
   Southern	
  Africa	
  	
   30%	
  of	
  household	
  income	
   Forests	
  Kamanga	
  et	
  al.	
  2009	
   Southern	
  Africa	
  	
   15%	
  of	
  total	
  household	
  income	
   Forests	
  Mamo	
  et	
  al.	
  2007	
   East	
  Africa	
  	
   39%	
  of	
  total	
  household	
  income	
  	
   Forests	
  	
  	
  	
  	
   Table	
  2:	
  Collected	
  evidence	
  on	
  the	
  relative	
  dependence	
  of	
  the	
  poor	
  in	
  different	
  regions	
  of	
  SSA	
  on	
  biodiversity	
  resources	
  (NTFP	
  means	
  non-­‐timber	
  forest	
  products).	
  From	
  Roe	
  (2010).	
  	
   Reference	
  	
   Region	
   Resource	
  	
   Relative	
   Dependence	
  Babulo	
  et	
  al.	
  2008	
   East	
  Africa	
  	
   Forests	
  	
   Decreases	
  with	
  wealth	
  Bene	
  et	
  al.	
  2009	
   West	
  Africa	
  	
   Fish	
   Decreases	
  with	
  wealth	
  Cavendish	
  2000	
   Southern	
  Africa	
  	
   Multiple	
  	
   Decreases	
  with	
  wealth	
  de	
  Merode	
  et	
  al.	
  2004	
   West	
  Africa	
  	
   Wild	
  plants	
  	
   Consumption/sale	
  decreases	
  with	
  wealth	
  	
  Fisher	
  2004	
   Southern	
  Africa	
  	
   Low	
  return	
  forest	
  activities	
  	
   Decreases	
  with	
  wealth	
  Kamanga	
  et	
  al.	
  2007	
   Southern	
  Africa	
  	
   Forests	
   Decreases	
  with	
  wealth	
  Mamo	
  et	
  al.	
  2007	
   East	
  Africa	
  	
   Forests	
   Decreases	
  with	
  wealth	
  Paumgarten	
  and	
  Shackleton	
  2009	
   Southern	
  Africa	
  	
   NTFP	
   Sale	
  decreases	
  with	
  wealth	
  Shackleton	
  and	
  Shackleton	
  2006	
   Southern	
  Africa	
  	
   NTFP	
   Sale	
  decreases	
  with	
  wealth	
  	
  Shackleton	
  and	
  Shackleton	
  2006	
   Southern	
  Africa	
  	
   Fuelwood	
   Consumption	
  decreases	
  with	
  wealth	
  	
  Shackleton	
  and	
  Shackleton	
  2006	
   Southern	
  Africa	
  	
   Edible	
  herbs	
  	
   Consumption	
  decreases	
  with	
  wealth	
   	
   4.2.	
  Biodiversity	
  Conservation	
  as	
  a	
  Means	
  of	
  Poverty	
  Reduction	
  	
  	
  	
  	
  	
  The	
  conservation	
  of	
  biodiversity	
  is	
  a	
  unique	
  way	
  to	
  provide	
  direct	
  and	
  indirect	
  services	
  that	
  sustain	
  the	
  economy	
  in	
  SSA	
  (Turner	
  et	
  al.,	
  2012).	
  The	
  labour	
  of	
  the	
  poor	
  results	
  in	
  economic	
  returns	
  that	
  are	
  directly	
  dependent	
  upon	
  the	
  quality	
  and	
  quantity	
  of	
  the	
  natural	
  resources	
  available,	
  and	
  these	
  resources	
  are,	
  in	
  turn,	
  dependent	
  upon	
  the	
  biodiversity	
  of	
  the	
  region	
  (Barrett,	
  Travis,	
  &	
  Dasgupta,	
  2011).	
  The	
  high	
  dependency	
  of	
  the	
  SSA	
  economy	
  on	
  its	
  biodiversity	
  suggests	
  that,	
  at	
  a	
   minimum,	
  this	
  biodiversity	
  acts	
  as	
  a	
  safety	
  net	
  to	
  maintain	
  the	
  region’s	
  current	
  economy	
  (Turner	
  et	
  al.,	
  2012;	
  Roe,	
  Walpole,	
  &	
  Elliott,	
  2010).	
  It	
  also	
  suggests	
  that	
  biodiversity	
  is	
  a	
  crucial	
  factor	
  in	
  any	
  hope	
  for	
  poverty	
  alleviation	
  in	
  the	
  region	
  (Turner	
  et	
  al.,	
  2012;	
  Roe,	
  Walpole,	
  &	
  Elliott,	
  2010).	
  Although	
  ecosystem	
  services	
  (sometimes	
  looked	
  at	
  as	
  natural	
  capital),	
  defined	
  as	
  the	
  value	
  of	
  services	
  generated	
  by	
  a	
  habitat,	
  are	
  often	
  taken	
  for	
  granted,	
  underpriced,	
  and	
  overexploited,	
  these	
  services	
  are	
  extremely	
  valuable	
  and	
  essential	
  in	
  the	
  SSA	
  economy	
  (Turner	
  et	
  al.,	
  2012;	
  Roe,	
  2010).	
  If	
  current	
  payments	
  for	
  these	
  ecosystem	
  services	
  made	
  it	
  directly	
  to	
  the	
  poor,	
  there	
  would	
  be	
  an	
  increase	
  in	
  economic	
  value	
  of	
  49.7%,	
  suggesting	
  that	
  management	
  of	
  this	
  natural	
  capital	
  could	
  result	
  in	
  poverty	
  alleviation	
  in	
  the	
  region	
  (Turner	
  et	
  al.,	
  2012).	
  An	
  example	
  of	
  the	
  ability	
  of	
  biodiversity	
  conservation	
  to	
  alleviate	
  poverty	
  comes	
  from	
  the	
  comparison	
  of	
  two	
  similar	
  districts	
  in	
  both	
  Costa	
  Rica	
  and	
  Thailand,	
  one	
  with	
  biodiversity	
  conservation	
  and	
  one	
  without	
  (Turner	
  et	
  al.,	
  2012).	
  The	
  protected	
  areas	
  experienced	
  10%	
  less	
  poverty	
  in	
  Costa	
  Rica,	
  and	
  30%	
  less	
  poverty	
  in	
  Thailand,	
  providing	
  discrete	
  examples	
  of	
  how	
  this	
  relationship	
  could	
  provide	
  possible	
  benefits	
  to	
  the	
  SSA	
  economy	
  as	
  well	
  (Turner	
  et	
  al.,	
  2012).	
  A	
  variety	
  of	
  similar	
  success	
  stories	
  are	
  available,	
  emphasizing	
  the	
  promising	
  capability	
  of	
  biodiversity	
  conservation	
  as	
  a	
  means	
  of	
  poverty	
  reduction	
  (Fisher,	
  &	
  Christopher,	
  2007;	
  Munthali,	
  2007;	
  Roe,	
  2010).	
  	
   4.3.	
  Implementation	
  of	
  Findings	
  	
  	
  	
  	
  	
  	
  The	
  complex	
  relationship	
  between	
  poverty	
  and	
  biodiversity	
  in	
  SSA	
  provides	
  compelling	
  reasons	
  for	
  its	
  communities	
  to	
  engage	
  in	
  conservation,	
  as	
  it	
  can	
  be	
  economically,	
  environmentally,	
  politically,	
  socially,	
  and	
  culturally	
  beneficial	
  (Roe,	
   Walpole,	
  &	
  Elliott,	
  2010).	
  Community	
  appropriate	
  strategies	
  and	
  policies	
  for	
  incorporating	
  biodiversity	
  conservation	
  and	
  poverty	
  reduction	
  must	
  be	
  designed	
  in	
  order	
  to	
  take	
  advantage	
  of	
  these	
  compelling	
  benefits	
  (Roe,	
  Walpole,	
  &	
  Elliott,	
  2010).	
  	
  	
  	
  	
  	
  	
  There	
  are	
  a	
  variety	
  of	
  possibilities	
  and	
  previously	
  implemented	
  strategies	
  that	
  take	
  advantage	
  of	
  the	
  relationship	
  between	
  these	
  two	
  variables,	
  providing	
  “win-­‐win”	
  solutions	
  (Munthali,	
  2007;	
  Roe,	
  2010).	
  Community	
  based	
  natural	
  resource	
  management	
  programs	
  are	
  key,	
  as	
  they	
  recognize	
  the	
  importance	
  of	
  the	
  participation	
  of	
  those	
  who	
  live	
  near	
  and	
  are	
  interconnected	
  with	
  the	
  resources	
  at	
  hand	
  (Munthali,	
  2007).	
  A	
  complex	
  example	
  of	
  such	
  an	
  ecosystem	
  management	
  initiative	
  is	
  Transfrontier	
  Conservation	
  Areas	
  (TFCAs),	
  which	
  recognize	
  that	
  political	
  borders	
  between	
  countries	
  are	
  not	
  necessarily	
  ecological	
  borders	
  (Munthali,	
  2007).	
  This	
  strategy	
  aims	
  to	
  ensure	
  that	
  key	
  ecological	
  processes	
  continue	
  to	
  function	
  where	
  borders	
  have	
  divided	
  an	
  ecosystem,	
  while	
  also	
  encouraging	
  cooperation	
  between	
  different	
  governments	
  and	
  communities	
  in	
  the	
  region	
  (Munthali,	
  2007).	
  	
  	
  	
  	
  	
  	
  A	
  variety	
  of	
  other	
  conservation	
  mechanisms	
  provide	
  strong	
  evidence	
  of	
  contributions	
  to	
  reductions	
  in	
  poverty	
  by	
  conserving	
  biodiversity	
  (Roe,	
  2010).	
  Examples	
  include	
  non-­‐timber	
  forest	
  products	
  (NTFPs)	
  in	
  which	
  products	
  such	
  as	
  honey,	
  bamboo	
  and	
  mushrooms	
  can	
  be	
  cultivated	
  and	
  generate	
  profit	
  for	
  the	
  region,	
  as	
  well	
  as	
  timber	
  itself,	
  when	
  forests	
  are	
  owned	
  by	
  communities	
  and	
  harvested	
  sustainably	
  by	
  small-­‐scale	
  wood	
  processing	
  to	
  provide	
  the	
  community	
  with	
  wealth	
  that	
  has	
  historically	
  gone	
  to	
  national	
  elites	
  (Roe,	
  2010).	
  The	
  use	
  of	
  these	
  strategies	
   in	
  example	
  cases	
  such	
  as	
  Mexico,	
  Bolivia,	
  and	
  Vietnam	
  has	
  been	
  successful	
  in	
  reducing	
  poverty	
  (Roe,	
  2010).	
  	
  	
  	
  	
  	
  	
  	
  An	
  initiative	
  called	
  payments	
  for	
  environmental	
  services	
  (PES),	
  which	
  involves	
  the	
  selling	
  of	
  well-­‐defined	
  environmental	
  services	
  (such	
  as	
  watershed	
  protection	
  or	
  carbon	
  sequestration)	
  so	
  that	
  landowners	
  are	
  compensated	
  for	
  providing	
  environmentally	
  sustainable	
  ecosystem	
  services,	
  has	
  been	
  successfully	
  implemented	
  in	
  Costa	
  Rica	
  for	
  forest	
  protection,	
  and	
  in	
  Ecuador	
  for	
  watershed	
  protection	
  (Fisher,	
  &	
  Christopher,	
  2007;	
  Roe,	
  2010).	
  These	
  cases	
  of	
  PES	
  provide	
  considerable	
  evidence	
  of	
  the	
  ability	
  of	
  this	
  strategy	
  to	
  reduce	
  poverty,	
  as	
  it	
  now	
  supplies	
  more	
  than	
  30%	
  of	
  the	
  household	
  income	
  for	
  the	
  poor	
  in	
  both	
  of	
  these	
  regions	
  (Fisher,	
  &	
  Christopher,	
  2007;	
  Roe,	
  2010).	
  	
  	
  	
  	
  	
  	
  Nature-­‐based	
  tourism	
  is	
  another	
  possible	
  option	
  for	
  SSA,	
  as	
  international	
  attractions	
  such	
  as	
  eco-­‐lodges	
  and	
  safari	
  operations	
  provide	
  direct	
  and	
  indirect	
  benefits	
  to	
  the	
  region	
  in	
  which	
  they	
  are	
  implemented	
  (Roe,	
  2010).	
  Direct	
  benefits	
  include	
  the	
  creation	
  of	
  jobs	
  in	
  the	
  tourism	
  sector	
  (Roe,	
  2010).	
  Indirect	
  benefits	
  are	
  the	
  infrastructure	
  and	
  development	
  that	
  come	
  along	
  with	
  tourism,	
  as	
  research	
  has	
  shown	
  that	
  each	
  dollar	
  spent	
  by	
  a	
  tourist	
  leads	
  to	
  a	
  $2-­‐3	
  national	
  economic	
  benefit	
  (Roe,	
  2010).	
  	
  	
  	
  	
  	
  	
  Fish	
  spillover	
  is	
  another	
  strategy	
  that	
  has	
  been	
  proven	
  to	
  reduce	
  poverty	
  in	
  the	
  locations	
  it	
  is	
  implemented	
  (Roe,	
  2010).	
  The	
  protection	
  of	
  a	
  key	
  area	
  of	
  marine	
  habitat	
  allows	
  for	
  the	
  fish	
  stocks	
  to	
  replenish	
  and	
  overspill	
  into	
  adjacent	
  areas	
  where	
  they	
  can	
  be	
  caught	
  and	
  benefitted	
  from	
  by	
  the	
  poor	
  (Roe,	
  2010).	
  The	
  protected	
  areas	
  provide	
  marine	
  biodiversity	
  conservation,	
  while	
  the	
  spillover	
  areas	
   generate	
  income	
  to	
  reduce	
  poverty	
  in	
  the	
  region	
  (Roe,	
  2010).	
  This	
  strategy	
  has	
  lead	
  to	
  a	
  doubling	
  of	
  local	
  incomes	
  within	
  five	
  years	
  of	
  its	
  establishment	
  in	
  two	
  different	
  Fijian	
  communities	
  (Roe,	
  2010).	
  	
  	
  	
  	
  	
  	
  It	
  is	
  a	
  combination	
  of	
  these	
  various	
  strategies	
  and	
  policies	
  that	
  will	
  be	
  necessary	
  to	
  establish	
  any	
  significant	
  poverty	
  alleviation	
  in	
  a	
  region	
  as	
  large	
  and	
  diverse	
  as	
  SSA.	
  Research	
  and	
  experience	
  have	
  shown	
  that	
  these	
  strategies	
  can	
  contribute	
  measurably	
  to	
  both	
  the	
  conservation	
  of	
  biodiversity	
  and	
  alleviation	
  of	
  poverty	
  if	
  executed	
  properly	
  (Munthali,	
  2007;	
  Roe,	
  2010).	
  It	
  is	
  important	
  that	
  the	
  strategies	
  implemented	
  incorporate	
  sufficient	
  understanding	
  of	
  the	
  complex	
  relationship	
  between	
  poverty	
  and	
  the	
  environment	
  in	
  SSA,	
  in	
  order	
  to	
  ensure	
  an	
  overall	
  sustainable	
  outcome	
  (Lufumpa,	
  2005).	
  Challenges	
  faced	
  by	
  such	
  policy	
  implementation	
  include	
  political	
  instability	
  in	
  the	
  region,	
  poor	
  government	
  implementation	
  and	
  a	
  disconnection	
  between	
  government	
  policy	
  and	
  the	
  scholarly	
  research	
  behind	
  the	
  issues	
  (Munthali,	
  2007).	
  A	
  main	
  challenge	
  for	
  the	
  region	
  is	
  ensuring	
  that	
  it	
  is	
  the	
  poor	
  who	
  benefit	
  from	
  these	
  policy	
  implementations,	
  as	
  opposed	
  to	
  the	
  elite	
  capturing	
  the	
  benefits	
  (Roe,	
  2010).	
  	
   5.	
  Conclusions	
  	
  	
  	
  	
  	
  Biodiversity	
  loss	
  and	
  poverty	
  reduction	
  are	
  global	
  challenges,	
  agreed	
  to	
  be	
  of	
  first	
  order	
  importance	
  in	
  the	
  Convention	
  on	
  Biological	
  Diversity	
  and	
  in	
  the	
  Millennium	
  Development	
  Goals	
  (Barrett,	
  Travis,	
  &	
  Dasgupta,	
  2011).	
  The	
  connection	
  between	
  these	
  two	
  variables	
  therefore	
  holds	
  profound	
  possibilities	
  for	
  SSA	
  and,	
  if	
  understood	
  fully,	
  could	
  provide	
  promising	
  mechanisms	
  to	
  combat	
  poverty	
  and	
  the	
  loss	
  of	
  biodiversity	
  together	
  (Lufumpa,	
  2005;	
  Roe,	
  2010).	
  The	
  close	
  interrelation	
  between	
   these	
  two	
  variables	
  suggests	
  that	
  if	
  not	
  arrested,	
  biodiversity	
  degradation	
  will	
  affect	
  the	
  regions	
  economic	
  growth,	
  further	
  worsening	
  the	
  situation	
  of	
  those	
  in	
  poverty	
  (Lufumpa,	
  2005).	
  The	
  importance	
  of	
  this	
  complex	
  relationship	
  must	
  be	
  taken	
  into	
  account,	
  and	
  biodiversity	
  conservation	
  should	
  be	
  a	
  priority	
  in	
  international	
  efforts	
  to	
  address	
  poverty	
  reduction	
  in	
  SSA	
  (Adams	
  et	
  al.,	
  2004;	
  Roe,	
  2010).	
  The	
  services	
  provided	
  by	
  diverse	
  ecosystems	
  and	
  the	
  habitats	
  providing	
  them	
  are	
  vanishing	
  at	
  alarming	
  rates,	
  and	
  are	
  undervalued	
  in	
  markets,	
  businesses,	
  and	
  government	
  decisions	
  (Turner	
  et	
  al.,	
  2012).	
  This	
  is	
  particularly	
  true	
  when	
  looking	
  into	
  a	
  future	
  of	
  climate	
  change,	
  where	
  this	
  biodiversity	
  will	
  be	
  especially	
  crucial	
  (Turner	
  et	
  al.,	
  2012;	
  Roe,	
  2010).	
  Although	
  SSA	
  emits	
  one	
  of	
  the	
  lowest	
  levels	
  of	
  green	
  house	
  gases	
  globally,	
  research	
  has	
  shown	
  that	
  this	
  drought-­‐prone	
  region	
  is	
  most	
  at	
  risk	
  of	
  climate	
  change	
  hazards	
  (Reid,	
  &	
  Swiderska,	
  2008).	
  Biodiversity	
  in	
  SSA	
  can	
  act	
  as	
  a	
  buffer,	
  ensuring	
  protection	
  and	
  resilience	
  against	
  the	
  adverse	
  weather	
  associated	
  with	
  climate	
  change	
  (Roe,	
  2010).	
  Those	
  in	
  poverty	
  have	
  the	
  lowest	
  capacity	
  to	
  deal	
  with	
  climate	
  change-­‐related	
  shocks,	
  and	
  the	
  resilience	
  provided	
  by	
  conserving	
  the	
  region’s	
  biodiversity	
  will	
  be	
  increasingly	
  important	
  for	
  the	
  economic	
  wellbeing	
  of	
  SSA	
  communities	
  in	
  a	
  future	
  of	
  climate	
  change	
  (Reid,	
  &	
  Swiderska,	
  2008;	
  Roe,	
  2010).	
  	
  	
  	
  	
  	
  	
   References	
  Adams,	
  W.	
  M.,	
  Aveling,	
  R.,	
  Brockington,	
  D.,	
  Dickson,	
  B.,	
  Elliot,	
  J.,	
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