Density and distribution of western chimpanzees around a bauxite deposit in the Boé Sector, Guinea-Bissau

Spatio-temporal changes in chimpanzee density and abundance in the Greater Mahale Ecosystem, Tanzania

Species conservation and management require reliable information about animal distribution and population size. Better management actions within a species' range can be achieved by identifying the location and timing of population changes. In the Greater Mahale Ecosystem (GME), western Tanzania, deforestation due to the expansion of human settlements and agriculture, annual burning, and logging are known threats to wildlife. For one of the most charismatic species, the endangered eastern chimpanzee (Pan troglodytes schweinfurthii), approximately 75% of the individuals are distributed outside national park boundaries, requiring monitoring and protection efforts over a vast landscape of various protection statuses. These efforts are especially challenging when we lack data on trends in density and population size. To predict spatio-temporal chimpanzee density and abundance across the GME, we used density surface modeling, fitting a generalized additive model to a 10-year time-series data set of nest counts based on line-transect surveys. The chimpanzee population declined at an annual rate of 2.41%, including declines of 1.72% in riparian forests (from this point forward, forests), 2.05% in miombo woodlands (from this point forward, woodlands) and 3.45% in nonforests. These population declines were accompanied by ecosystem-wide declines in vegetation types of 1.36% and 0.32% per year for forests and woodlands, respectively; we estimated an annual increase of 1.35% for nonforests. Our model predicted the highest chimpanzee density in forests (0.86 chimpanzees/km² , 95% confidence intervals (CIs) 0.60-1.23; as of 2020), followed by woodlands (0.19, 95% CI 0.12-0.30) and nonforests (0.18, 95% CI 0.10-1.33). Although forests represent only 6% of the landscape, they support nearly one-quarter of the chimpanzee population (769 chimpanzees, 95% CI 536-1103). Woodlands dominate the landscape (71%) and therefore support more than a half of the chimpanzee population (2294; 95% CI 1420-3707). The remaining quarter of the landscape is represented by nonforests and supports another quarter of the chimpanzee population (750; 95% CI 408-1381). Given the pressures on the remaining suitable habitat in Tanzania, and the need of chimpanzees to access both forest and woodland vegetation to survive, we urge future management actions to increase resources and expand the efforts to protect critical forest and woodland habitat and promote strategies and policies that more effectively prevent irreversible losses. We suggest that regular monitoring programs implement a systematic random design to effectively inform and allocate conservation actions and facilitate interannual comparisons for trend monitoring, measuring conservation success, and guiding adaptive management.

New observations on chimpanzee accumulative stone throwing in Boé, Guinea Bissau

Chimpanzee accumulative stone throwing at trees has been described by Kühl, H.S., Kalan, A.K., Arandjelovic, M., Aubert, F., D'Auvergne, L., Goedmakers, A., Jones, S., Kehoe, L., Regnaut, S., Tickle, A., et al. (2016). Chimpanzee accumulative stone throwing. Sci. Rep. 6: 1–8, but we lack important details about the social and ecological context for this rare behavior. Further observations may enhance future research, as the described observations have not yet been shared in the literature. We analyzed camera trap records from 2010 to 2020 of various research projects conducted in the Boé sector of Gabu Province in south-east Guinea Bissau, West-Africa, to identify ecological and social factors that might potentially influence chimpanzee accumulative stone throwing behavior (on a total of 298 records). From September 2019 until November 2019, we filmed five trees over 48 days to conduct a further exploratory study of this behavior. We discuss the importance of study design when investigating a little-described phenomenon, and the threat posed to chimpanzee populations in West-Africa by the expected expansion of mining activities. More knowledge on chimpanzee accumulative stone throwing is needed as the chimpanzee population is under stress because of increased mining activities in the area. With habitat rapidly being disturbed and destroyed, this population and its rare behavior are increasingly at risk of extermination.

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.

No time to rest: How the effects of climate change on nest decay threaten the conservation of apes in the wild

Since 1994, IUCN Red List assessments apply globally acknowledged standards to assess species distribution, abundance and trends. The extinction risk of a species has a major impact on conservation science and international funding mechanisms. Great ape species are listed as Endangered or Critically Endangered. Their populations are often assessed using their unique habit of constructing sleeping platforms, called nests. As nests rather than apes are counted, it is necessary to know the time it takes for nests to disappear to convert nest counts into ape numbers. However, nest decomposition is highly variable across sites and time and the factors involved are poorly understood. Here, we used 1,511 bonobo (Pan paniscus) nests and 15 years of climatic data (2003-2018) from the research site LuiKotale, Democratic Republic of the Congo, to investigate the effects of climate change and behavioural factors on nest decay time, using a Bayesian gamma survival model. We also tested the logistic regression method, a recommended time-efficient option for estimating nest decay time. Our climatic data showed a decreasing trend in precipitation across the 15 years of study. We found bonobo nests to have longer decay times in recent years. While the number of storms was the main factor driving nest decay time, nest construction type and tree species used were also important. We also found evidence for bonobo nesting behaviour being adapted to climatic conditions, namely strengthening the nest structure in response to unpredictable, harsh precipitation. By highlighting methodological caveats, we show that logistic regression is effective in estimating nest decay time under certain conditions. Our study reveals the impact of climate change on nest decay time in a tropical remote area. Failure to account for these changes would invalidate biomonitoring estimates of global significance, and subsequently jeopardize the conservation of great apes in the wild.