Guns, germs, and trees determine density and distribution of gorillas and chimpanzees in Western Equatorial Africa

We present a range-wide assessment of sympatric western lowland gorillas Gorilla gorilla gorilla and central chimpanzees Pan troglodytes troglodytes using the largest survey data set ever assembled for these taxa: 59 sites in five countries surveyed between 2003 and 2013, totaling 61,000 person-days of fieldwork. We used spatial modeling to investigate major drivers of great ape distribution and population trends. We predicted density across each taxon’s geographic range, allowing us to estimate overall abundance: 361,900 gorillas and 128,700 chimpanzees in Western Equatorial Africa—substantially higher than previous estimates. These two subspecies represent close to 99% of all gorillas and one-third of all chimpanzees. Annual population decline of gorillas was estimated at 2.7%, maintaining them as Critically Endangered on the International Union for Conservation of Nature and Natural Resources (IUCN) Red List. We quantified the threats to each taxon, of which the three greatest were poaching, disease, and habitat degradation. Gorillas and chimpanzees are found at higher densities where forest is intact, wildlife laws are enforced, human influence is low, and disease impacts have been low. Strategic use of the results of these analyses could conserve the majority of gorillas and chimpanzees. With around 80% of both subspecies occurring outside protected areas, their conservation requires reinforcement of anti-poaching efforts both inside and outside protected areas (particularly where habitat quality is high and human impact is low), diligent disease control measures (including training, advocacy, and research into Ebola virus disease), and the preservation of high-quality habitat through integrated land-use planning and implementation of best practices by the extractive and agricultural industries.Additional co-authors: Nicolas Bout, Thomas Breuer, Genevieve Campbell, Pauwel De Wachter, Marc Ella Akou, Fidel Esono Mba, Anna T. C. Feistner, Bernard Fosso, Roger Fotso, David Greer, Clement Inkamba-Nkulu, Calixte F. Iyenguet, Max Kokangoye, Hjalmar S. Kühl, Stephanie Latour, Bola Madzoke, Calixte Makoumbou, Guy-Aimé F. Malanda, Richard Malonga, Victor Mbolo, David B. Morgan, Prosper Motsaba, Gabin Moukala, Brice S. Mowawa, Mizuki Murai, Christian Ndzai, Tomoaki Nishihara, Zacharie Nzooh, Lilian Pintea, Amy Pokempner, Hugo J. Rainey, Tim Rayden, Heidi Ruffler, Crickette M. Sanz, Angelique Todd, Hilde Vanleeuwe, Ashley Vosper, Ymke Warren, and David S. Wilki

Monitoring great ape and elephant abundance at large spatial scales: measuring effectiveness of a conservation landscape.

Protected areas are fundamental to biodiversity conservation, but there is growing recognition of the need to extend beyond protected areas to meet the ecological requirements of species at larger scales. Landscape-scale conservation requires an evaluation of management impact on biodiversity under different land-use strategies; this is challenging and there exist few empirical studies. In a conservation landscape in northern Republic of Congo we demonstrate the application of a large-scale monitoring program designed to evaluate the impact of conservation interventions on three globally threatened species: western gorillas, chimpanzees and forest elephants, under three land-use types: integral protection, commercial logging, and community-based natural resource management. We applied distance-sampling methods to examine species abundance across different land-use types under varying degrees of management and human disturbance. We found no clear trends in abundance between land-use types. However, units with interventions designed to reduce poaching and protect habitats--irrespective of land-use type--harboured all three species at consistently higher abundance than a neighbouring logging concession undergoing no wildlife management. We applied Generalized-Additive Models to evaluate a priori predictions of species response to different landscape processes. Our results indicate that, given adequate protection from poaching, elephants and gorillas can profit from herbaceous vegetation in recently logged forests and maintain access to ecologically important resources located outside of protected areas. However, proximity to the single integrally protected area in the landscape maintained an overriding positive influence on elephant abundance, and logging roads--even subject to anti-poaching controls--were exploited by elephant poachers and had a major negative influence on elephant distribution. Chimpanzees show a clear preference for unlogged or more mature forests and human disturbance had a negative influence on chimpanzee abundance, in spite of anti-poaching interventions. We caution against the pitfalls of missing and confounded co-variables in model-based estimation approaches and highlight the importance of spatial scale in the response of different species to landscape processes. We stress the importance of a stratified design-based approach to monitoring species status in response to conservation interventions and advocate a holistic framework for landscape-scale monitoring that includes smaller-scale targeted research and punctual assessment of threats

Devastating Decline of Forest Elephants in Central Africa.

African forest elephants– taxonomically and functionally unique–are being poached at accelerating rates, but we lack range-wide information on the repercussions. Analysis of the largest survey dataset ever assembled for forest elephants (80 foot-surveys; covering 13,000 km; 91,600 person-days of fieldwork) revealed that population size declined by ca. 62% between 2002–2011, and the taxon lost 30% of its geographical range. The population is now less than 10% of its potential size, occupying less than 25% of its potential range. High human population density, hunting intensity, absence of law enforcement, poor governance, and proximity to expanding infrastructure are the strongest predictors of decline. To save the remaining African forest elephants, illegal poaching for ivory and encroachment into core elephant habitat must be stopped. In addition, the international demand for ivory, which fuels illegal trade, must be dramatically reduced

Estimated change in elephant dung density (/km²) distribution during 2002–2011 across the Central African forests.

<p>Results are shown as a percentage of the total area of potential elephant habitat overall (A & B) and by country (C & D) for the predictive model with variables: (A & C) survey year, Human Influence Index, corruption and the presence/absence of guards, and (B & D) survey year, proximity to road, human population density, corruption and the presence/absence of guards. The dung density (per km²) intervals are unequal and correspond to the following elephant population categories: extremely low density (0–100), very low (100–250), low (250–500), medium (500–1,000), high (1,000–3,000) and very high (3,000–7,500). With the loss of very high elephant populations in 2011, there is a significant shift into the lower density intervals over the nine years.</p

Elephant dung density and range reduction across the Central African forests.

<p>Predictions are shown for (A) 2002 and (B) 2011 for the model with variables: survey year∧, Human Influence Index***, corruption*** and the presence/absence of guards***, and (C) 2002 and (D) 2011 for the model with variables: survey year∧, proximity to road∧, human population density***, corruption*** and the presence/absence of guards*** (P-values are: ‘***’ <0.001 and ‘∧’ <0.1). Increasingly darker shades of green correspond to higher densities, grey represents extremely low elephant density range (the first interval: 0–100 elephant dung piles/km²) and white is non-habitat (80 survey sites outlined in red). Cutpoints are: 0; 100; 250; 500; 1,000; 1,500; 3,000; 5,000; and 7,500 dung piles/km². Countries 1–5 are: Cameroon; Central African Republic; Republic of Congo; DRC; Gabon.</p

Encounter rate of elephant dung per kilometre.

<p>Results are shown for the 80 survey sites in Central Africa included in this study. Grey shading represents forest cover.</p

Estimated conditional dependence of elephant dung density for top-ranked multi-variable models including hunter sign.

<p>Results are shown for the top-ranked model with variables: (A) hunter sign*, (B) survey year*, (C) proximity to roads∧, (D) human population density***, (E) corruption*** (higher values = less corrupt) and presence/absence of guards***. Also shown is (F) the Human Influence Index (HII) for the model with proximity to road and human population density variables replaced by the HII, i.e. one of the top-ranking models with variables: hunter sign**, survey year*, HII*, corruption***, and presence/absence of guards***. P-value significance codes are: ‘***’<0.001, ‘**’<0.01, ‘*’<0.05, and ‘∧’<0.1. Plot components are: Estimates on the scale of the linear predictor (solid lines) with the y-axis scale for each variable selected to optimally display the results, confidence intervals (dashed lines), and explanatory variable values of observations with a focus on the core 95% of values for hunter sign, proximity to road and human population density (rug plot - short vertical bars along each x-axis showing the x value for each site).</p

Boxplots of indices of elephant abundance and hunting intensity.

<p>Summaries shown are the natural logarithm of: (A) elephant dung encounter rate per 100 km grouped by the presence/absence of wildlife guards, (B) elephant dung encounter rate per 100 km grouped by the level of hunting intensity (group cutpoints are 0.6 and 1.75 hunter sign/km), and (C) hunter-sign frequency per 100 km grouped by the presence/absence of wildlife guards. Box-widths are proportional to the number of observations in each group.</p