TY - JOUR
T1 - Range-wide indicators of African great ape density distribution
AU - Ordaz-Németh, Isabel
AU - Sop, Tenekwetche
AU - Amarasekaran, Bala
AU - Bachmann, Mona
AU - Boesch, Christophe
AU - Brncic, Terry
AU - Caillaud, Damien
AU - Campbell, Geneviève
AU - Carvalho, Joana
AU - Chancellor, Rebecca
AU - Davenport, Tim R.B.
AU - Dowd, Dervla
AU - Eno-Nku, Manasseh
AU - Ganas-Swaray, Jessica
AU - Granier, Nicholas
AU - Greengrass, Elizabeth
AU - Heinicke, Stefanie
AU - Herbinger, Ilka
AU - Inkamba-Nkulu, Clement
AU - Iyenguet, Fortuné
AU - Junker, Jessica
AU - Bobo, Kadiri S.
AU - Lushimba, Alain
AU - Maisels, Fiona
AU - Malanda, Guy Aimé Florent
AU - McCarthy, Maureen S.
AU - Motsaba, Prosper
AU - Moustgaard, Jennifer
AU - Murai, Mizuki
AU - Ndokoue, Bezangoye
AU - Nixon, Stuart
AU - Nseme, Rostand Aba a.
AU - Nzooh, Zacharie
AU - Pintea, Lilian
AU - Plumptre, Andrew J.
AU - Roy, Justin
AU - Rundus, Aaron
AU - Sanderson, Jim
AU - Serckx, Adeline
AU - Strindberg, Samantha
AU - Tweh, Clement
AU - Vanleeuwe, Hilde
AU - Vosper, Ashley
AU - Waltert, Matthias
AU - Williamson, Elizabeth A.
AU - Wilson, Michael
AU - Mundry, Roger
AU - Kühl, Hjalmar S.
N1 - Publisher Copyright:
© 2021 The Authors. American Journal of Primatology published by Wiley Periodicals LLC
PY - 2021/12
Y1 - 2021/12
N2 - Species distributions are influenced by processes occurring at multiple spatial scales. It is therefore insufficient to model species distribution at a single geographic scale, as this does not provide the necessary understanding of determining factors. Instead, multiple approaches are needed, each differing in spatial extent, grain, and research objective. Here, we present the first attempt to model continent-wide great ape density distribution. We used site-level estimates of African great ape abundance to (1) identify socioeconomic and environmental factors that drive densities at the continental scale, and (2) predict range-wide great ape density. We collated great ape abundance estimates from 156 sites and defined 134 pseudo-absence sites to represent additional absence locations. The latter were based on locations of unsuitable environmental conditions for great apes, and on existing literature. We compiled seven socioeconomic and environmental covariate layers and fitted a generalized linear model to investigate their influence on great ape abundance. We used an Akaike-weighted average of full and subset models to predict the range-wide density distribution of African great apes for the year 2015. Great ape densities were lowest where there were high Human Footprint and Gross Domestic Product values; the highest predicted densities were in Central Africa, and the lowest in West Africa. Only 10.7% of the total predicted population was found in the International Union for Conservation of Nature Category I and II protected areas. For 16 out of 20 countries, our estimated abundances were largely in line with those from previous studies. For four countries, Central African Republic, Democratic Republic of the Congo, Liberia, and South Sudan, the estimated populations were excessively high. We propose further improvements to the model to overcome survey and predictor data limitations, which would enable a temporally dynamic approach for monitoring great apes across their range based on key indicators.
AB - Species distributions are influenced by processes occurring at multiple spatial scales. It is therefore insufficient to model species distribution at a single geographic scale, as this does not provide the necessary understanding of determining factors. Instead, multiple approaches are needed, each differing in spatial extent, grain, and research objective. Here, we present the first attempt to model continent-wide great ape density distribution. We used site-level estimates of African great ape abundance to (1) identify socioeconomic and environmental factors that drive densities at the continental scale, and (2) predict range-wide great ape density. We collated great ape abundance estimates from 156 sites and defined 134 pseudo-absence sites to represent additional absence locations. The latter were based on locations of unsuitable environmental conditions for great apes, and on existing literature. We compiled seven socioeconomic and environmental covariate layers and fitted a generalized linear model to investigate their influence on great ape abundance. We used an Akaike-weighted average of full and subset models to predict the range-wide density distribution of African great apes for the year 2015. Great ape densities were lowest where there were high Human Footprint and Gross Domestic Product values; the highest predicted densities were in Central Africa, and the lowest in West Africa. Only 10.7% of the total predicted population was found in the International Union for Conservation of Nature Category I and II protected areas. For 16 out of 20 countries, our estimated abundances were largely in line with those from previous studies. For four countries, Central African Republic, Democratic Republic of the Congo, Liberia, and South Sudan, the estimated populations were excessively high. We propose further improvements to the model to overcome survey and predictor data limitations, which would enable a temporally dynamic approach for monitoring great apes across their range based on key indicators.
KW - Bonobo
KW - IUCN SSC A.P.E.S. database
KW - chimpanzee
KW - gorilla
KW - range-wide assessment
UR - http://www.scopus.com/inward/record.url?scp=85117256483&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85117256483&partnerID=8YFLogxK
U2 - 10.1002/ajp.23338
DO - 10.1002/ajp.23338
M3 - Article
C2 - 34662462
AN - SCOPUS:85117256483
SN - 0275-2565
VL - 83
JO - American journal of primatology
JF - American journal of primatology
IS - 12
M1 - e23338
ER -