Large mammals at forest clearings in the Odzala National Park, Congo

Nous avons exploré 36 clairières incluses dans les forêts du Parc National d'Odzala au Congo. Treize espèces de mammifères y ont été observées, dont les plus fréquentes étaient les éléphants, les buffles, les gorilles, les sitatungas, les bongos, les potamochères et les hylochères. Sur la clairière de Maya Nord, les taux de présence des buffles dans la journée était de 71 %, celle des éléphants de 37 % et celle des gorilles de 34 %. Plus de 100 éléphants ont été dénombrés simultanément, ainsi qu'un groupe de 25 buffles tandis que la présence simultanée de deux groupes de gorilles a été observée à plusieurs reprises et qu'un groupe de 17 sitatungas résidait en permanence sur la clairière. Les différences dans le taux de fréquentation des clairières résultent pro parte de l'influence du braconnage des éléphants qui touche plus fortement les clairières situées à proximité des rivières. Les clairières sont essentiellement visitées par les animaux pour la collecte des sels minéraux trouvés dans l'eau, le sol et les végétaux. Elles jouent sans doute un rôle fondamental dans le maintien des fortes densités de populations observées dans la région notamment pour les éléphants et les gorilles. Elles constituent en outre des sites d'observation remarquables. Elles sont cependant des sites idéaux pour le braconnage. Les clairières les plus riches se trouvant hors des limites du PNO, l'extension de ces limites semble une priorité

Quantitative estimates of glacial refugia for chimpanzees (Pan troglodytes) since the Last Interglacial (120,000 BP).

Paleoclimate reconstructions have enhanced our understanding of how past climates have shaped present-day biodiversity. We hypothesize that the geographic extent of Pleistocene forest refugia and suitable habitat fluctuated significantly in time during the late Quaternary for chimpanzees (Pan troglodytes). Using bioclimatic variables representing monthly temperature and precipitation estimates, past human population density data, and an extensive database of georeferenced presence points, we built a model of changing habitat suitability for chimpanzees at fine spatio-temporal scales dating back to the Last Interglacial (120,000 BP). Our models cover a spatial resolution of 0.0467° (approximately 5.19 km2 grid cells) and a temporal resolution of between 1000 and 4000 years. Using our model, we mapped habitat stability over time using three approaches, comparing our modeled stability estimates to existing knowledge of Afrotropical refugia, as well as contemporary patterns of major keystone tropical food resources used by chimpanzees, figs (Moraceae), and palms (Arecacae). Results show habitat stability congruent with known glacial refugia across Africa, suggesting their extents may have been underestimated for chimpanzees, with potentially up to approximately 60,000 km2 of previously unrecognized glacial refugia. The refugia we highlight coincide with higher species richness for figs and palms. Our results provide spatio-temporally explicit insights into the role of refugia across the chimpanzee range, forming the empirical foundation for developing and testing hypotheses about behavioral, ecological, and genetic diversity with additional data. This methodology can be applied to other species and geographic areas when sufficient data are available

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

Range-wide indicators of African great ape density distribution

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

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

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