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Journal Article

Range‐wide indicators of African great ape density distribution

Authors

Ordaz‐Németh,  Isabel
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Sop,  Tenekwetche
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Amarasekaran,  Bala
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Bachmann,  Mona
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Boesch,  Christophe
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Brncic,  Terry
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Caillaud,  Damien
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Campbell,  Geneviève
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Carvalho,  Joana
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Chancellor,  Rebecca
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Davenport,  Tim R. B.
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Dowd,  Dervla
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Eno‐Nku,  Manasseh
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Ganas‐Swaray,  Jessica
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Granier,  Nicholas
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Greengrass,  Elizabeth
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/persons/resource/Stefanie.Heinicke

Heinicke,  Stefanie
Potsdam Institute for Climate Impact Research;

Herbinger,  Ilka
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Inkamba‐Nkulu,  Clement
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Iyenguet,  Fortuné
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Junker,  Jessica
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Bobo,  Kadiri S.
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Lushimba,  Alain
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Maisels,  Fiona
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Malanda,  Guy Aimé Florent
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McCarthy,  Maureen S.
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Motsaba,  Prosper
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Moustgaard,  Jennifer
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Murai,  Mizuki
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Ndokoue,  Bezangoye
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Nixon,  Stuart
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Nseme,  Rostand Aba'a
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Nzooh,  Zacharie
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Pintea,  Lilian
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Plumptre,  Andrew J.
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Roy,  Justin
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Rundus,  Aaron
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Sanderson,  Jim
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Serckx,  Adeline
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Strindberg,  Samantha
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Tweh,  Clement
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Vanleeuwe,  Hilde
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Vosper,  Ashley
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Waltert,  Matthias
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Williamson,  Elizabeth A.
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Wilson,  Michael
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Mundry,  Roger
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Kühl,  Hjalmar S.
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External Ressource
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Fulltext (public)

26290oa.pdf
(Publisher version), 3MB

Supplementary Material (public)
There is no public supplementary material available
Citation

Ordaz‐Németh, I., Sop, T., Amarasekaran, B., Bachmann, M., Boesch, C., Brncic, T., Caillaud, D., Campbell, G., Carvalho, J., Chancellor, R., Davenport, T. R. B., Dowd, D., Eno‐Nku, M., Ganas‐Swaray, J., Granier, N., Greengrass, E., Heinicke, S., Herbinger, I., Inkamba‐Nkulu, C., Iyenguet, F., Junker, J., Bobo, K. S., Lushimba, A., Maisels, F., Malanda, G. A. F., McCarthy, M. S., Motsaba, P., Moustgaard, J., Murai, M., Ndokoue, B., Nixon, S., Nseme, R. A., Nzooh, Z., Pintea, L., Plumptre, A. J., Roy, J., Rundus, A., Sanderson, J., Serckx, A., Strindberg, S., Tweh, C., Vanleeuwe, H., Vosper, A., Waltert, M., Williamson, E. A., Wilson, M., Mundry, R., Kühl, H. S. (2021): Range‐wide indicators of African great ape density distribution. - American Journal of Primatology, 83, 12, e23338.
https://doi.org/10.1002/ajp.23338


Cite as: https://publications.pik-potsdam.de/pubman/item/item_26290
Abstract
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.