We quantify the impacts of poaching, Ebola, and habitat degradation on western lowland gorillas and central chimpanzees.

Integrated conservation and development projects (ICDPs) have had limited success in addressing the often conflicting objectives of conservation and development. We developed a model with local participants to explore the trade-offs between conservation and development in southeastern Cameroon, where illegal hunting is regarded as the greatest challenge to conservation. We simulated the effects of different ICDP strategies by varying the degree of focus on antipoaching activities, anticorruption measures and direct development investments, and by varying the overall budget for such activities. Our outcome variables were numbers of selected wildlife species and household incomes. The model outcomes from the different scenarios were used to stimulate debate among stakeholders. Contributing to poverty alleviation while maintaining current animal population sizes will be extremely difficult and will require long-term external financial support. Devoting greater attention to improving local environmental governance emerged as the highest priority for this investment. We used the model outputs to inform some of the major policy makers in the region. Participatory modeling is a valuable means of capturing the complexities of achieving conservation at landscape scales and of stimulating innovative solutions to entrenched problems.

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An integrated framework for assessing conservation and development changes at the scale of a large forest landscape in the Congo Basin is described. The framework allows stakeholders to assess progress in achieving the often conflicting objectives of alleviating poverty and conserving global environmental values. The study shows that there was little change in either livelihood or conservation indicators over the period 2006 to 2008, and that the activities of conservation organizations had only modest impacts on either. The global economic down-turn in 2008 had immediate negative consequences for both local livelihoods and for biodiversity as people lost their employment in the cash economy and reverted to illegal harvesting of forest products. Weakness of institutions, and corruption were the major obstacles to achieving either conservation or development objectives. External economic changes had more impact on this forest landscape than either the negative or positive interventions of local actors.

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.