Large brains and behavioural innovation are positively correlated, species-specific traits, associated with the behavioural flexibility animals need for adapting to seasonal and unpredictable habitats. Similar ecological challenges would have been important drivers throughout human evolution. However, studies examining the influence of environmental variability on within-species behavioural diversity are lacking despite the critical assumption that population diversification precedes genetic divergence and speciation. Here, using a dataset of 144 wild chimpanzee (Pan troglodytes) communities, we show that chimpanzees exhibit greater behavioural diversity in environments with more variability — in both recent and historical timescales. Notably, distance from Pleistocene forest refugia is associated with the presence of a larger number of behavioural traits, including both tool and non-tool use behaviours. Since more than half of the behaviours investigated are also likely to be cultural, we suggest that environmental variability was a critical evolutionary force promoting the behavioural, as well as cultural diversification of great apes.

Strontium isotope (⁸⁷Sr/⁸⁶Sr) analysis with reference to strontium isotope landscapes (Sr isoscapes) allows reconstructing mobility and migration in archaeology, ecology, and forensics. However, despite the vast potential of research involving ⁸⁷Sr/⁸⁶Sr analysis particularly in Africa, Sr isoscapes remain unavailable for the largest parts of the continent. Here, we measure the ⁸⁷Sr/⁸⁶Sr ratios in 778 environmental samples from 24 African countries and combine this data with published data to model a bioavailable Sr isoscape for sub-Saharan Africa using random forest regression. We demonstrate the efficacy of this Sr isoscape, in combination with other lines of evidence, to trace the African roots of individuals from historic slavery contexts, particularly those with highly radiogenic ⁸⁷Sr/⁸⁶Sr ratios uncommon in the African Diaspora. Our study provides an extensive African ⁸⁷Sr/⁸⁶Sr dataset which includes scientifically marginalized regions of Africa, with significant implications for the archaeology of the transatlantic slave trade, wildlife ecology, conservation, and forensics.

Much like humans, chimpanzees occupy diverse habitats and exhibit extensive behavioural variability. However, chimpanzees are recognized as a discontinuous species, with four subspecies separated by historical geographic barriers. Nevertheless, their range-wide degree of genetic connectivity remains poorly resolved, mainly due to sampling limitations. By analyzing a geographically comprehensive sample set amplified at microsatellite markers that inform recent population history, we found that isolation by distance explains most of the range-wide genetic structure of chimpanzees. Furthermore, we did not identify spatial discontinuities corresponding with the recognized subspecies, suggesting that some of the subspecies-delineating geographic barriers were recently permeable to gene flow. Substantial range-wide genetic connectivity is consistent with the hypothesis that behavioural flexibility is a salient driver of chimpanzee responses to changing environmental conditions. Finally, our observation of strong local differentiation associated with recent anthropogenic pressures portends future loss of critical genetic diversity if habitat fragmentation and population isolation continue unabated.

Understanding the effects of land cover change on wildlife distribution is very important for resource management and conservation planning. This paper aimed at detecting the effects of land cover change on great apes distribution at the Lobéké National Park and its bounded forest management units (FMUs). Data on great ape nests were collected in the field for the years 2001 and 2014 through distance sampling with line transects. Landsat TM images of South-East Cameroon for the years 2001 and 2014 were acquired from earth explorer and corrected atmospherically for proper visualization. An area of interest comprising the Lobéké National Park and its FMUs was extracted for classification and change detection. A comparison in great apes nest distribution and change per land cover change category was done for both years through point pattern analysis, whereas a time series analysis of the detected land cover change impacts on great apes nest distribution for a period of 13 years was modeled using logistic growth and regression equations in Vensim 7.2. The results could illustrate that, as land cover changes from one cover type in 2001 to another in 2014, increases or decreases in great apes nests were observed within each changed area.

The Congo Basin tropical forests are home to many endemic and endangered species, and a global hotspot for forest fragmentation and loss. Yet, little has been done to document the region’s rapid deforestation, assess its effects and consequences, or project future forest cover loss to aid in effective planning. Here we applied the Random Forest (RF) supervised classification algorithm in Google Earth Engine (GEE) to map and quantify decadal changes in forest cover and land use (LCLU) in the Congo Basin between 1990 and 2020. We cross-validated our LCLU maps with existing global land cover products, and projected our validated results to 2050 under three climate change scenarios, using the Multiperceptron Artificial Neural Network and Markov chain algorithms of the Idrissi Land Change modeller from TerrSet. We found that, over 5.2% (215,938 km²), 1.2% (50,046 km²), and a 2.1% (86,658 km²) of dense forest cover were lost in the Congo Basin between 1990–2000, 2000–2010, and 2010–2020, totaling approximately 8.5% (352,642 km²) loss estimated between 1990–2020. For the period 2020–2050, we estimated a projected 3.7–4.0% (174,860–204,161 km²) loss in dense forest cover under all three climate change scenarios (i.e., 174,860 km² loss projected for SSP1-2.6, 199,608 km² for SSP2-4.5, and 204,161 km² for SSP5-8.5), suggesting that approximately 12.3–12.6% (527,502 km²–556,803 km²) of dense forest cover could be lost over a 60-year period (1990–2050). Our study represents a novel application of spatial modeling tools and Machine Learning algorithms for assessing long-term deforestation and forest degradation within the Congo Basin, under human population growth and IPCC climate change scenarios. We provide spatial and quantitative results required for supporting long-term deforestation and forest degradation monitoring within Congo Basin countries, especially under the United Nations Framework Convention on Climate Change (UNFCCC) REDD+ (Reduce Emissions from Deforestation and Forest Degradation) program.

As a result of extensive data collection efforts over the last 20–30 years, there is quite a good understanding of the large‐scale geographic distribution and range limits of African great apes. However, as human activities increasingly fragment great ape spatial distribution, a better understanding of what constitutes suitable great ape habitat is needed to inform conservation and resource extraction management. Chimpanzees (Pan troglodytes troglodytes) and gorillas (Gorilla gorilla gorilla) inhabit the Lobéké National Park and its surrounding forest management units (FMUs) in South‐East Cameroon. Both park and neighboring forestry concessions require reliable evidence on key factors driving great ape distribution for their management plans, yet this information is largely missing and incomplete. This study aimed at mapping great ape habitat suitability in the area and at identifying the most influential predictors among three predictor categories, including landscape predictors (dense forest, swampy forest, distance to water bodies, and topography), human disturbance predictors (hunting, deforestation, distance to roads, and population density), and bioclimatic predictor (annual precipitation). We found that about 63% of highly to moderately suitable chimpanzee habitat occurred within the Lobéké National Park, while only 8.4% of similar habitat conditions occurred within FMUs. For gorillas, highly and moderately suitable habitats occurred within the Lobéké National Park and its surrounding FMUs (82.6% and 65.5%, respectively). Key determinants of suitable chimpanzee habitat were hunting pressure and dense forest, with species occurrence probability optimal at relatively lower hunting rates and at relatively high‐dense forest areas. Key determinants of suitable gorilla habitat were hunting pressure, dense forests, swampy forests, and slope, with species occurrence probability optimal at relatively high‐dense and swampy forest areas and at areas with mild slopes. Our findings show differential response of the two ape species to forestry activities in the study area, thus aligning with previous studies.