Suchergebnisse

This study was funded by a grant from the Arcus Foundation No. G-PGM-1508-1368 to TH; PA was supported by the MINECO and the Universidad de Castilla-La Mancha (UCLM) through a 'Ramón y Cajal' contract (RYC-2012-11970), and Tacugama Chimpanzee Sanctuary provided logistical support. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. We are grateful to the Ministry of Agriculture, Forestry and Food Security of the Sierra Leone Government for granting us permission to conduct this research. This work would not have been possible without the collaboration of the people in the study communities. We also thank the outreach and management teams at the Tacugama Chimpanzee Sanctuary, in particular David Momoh, Joseph Marah, Konkofa Marah, Yirah Koroma, Bockarie Kanneh and Natalia Casado, for their assistance in the field. We are also extremely grateful to Dr. Raj Amin, Institute of Zoology in London, for providing the camera trap analysis software and to Jasper Gilardi for his help with processing camera trap images. Finally, we would also like to thank the two anonymous reviewers who provided useful suggestions for improving the quality of this manuscript. ; Human population growth and anthropogenic activities are exacerbating pressures on biodiversity globally. Land conversion is aggravating habitat fragmentation and non-human primates are increasingly compelled to live in forest-agricultural mosaics. In Sierra Leone, more than half of the wild chimpanzee population (Pan troglodytes verus) occurs outside protected areas and competes for resources with farmers. Our study area, in the Moyamba district in south-western Sierra Leone, is practically devoid of forest and is dominated by cultivated and fallow fields, swamps and mangroves. In this region, traditional slash-and-burn agriculture modifies annually the landscape, sparing swamps and mangroves and semi-domesticated oil palms (Elaeis guineensis). This study aimed to explore ecological and anthropogenic factors influencing chimpanzee relative abundance across this highly degraded and human-impacted landscape. Between 2015 and 2016, we deployed 24 camera traps systematically across 27 1.25x1.25 km grid cells. Cameras were operational over a period of 8 months. We used binomial iCAR models to examine to what extent anthropogenic (roads, settlements, abandoned settlements and human presence) and habitat variables (swamps, farmland and mangroves) shape chimpanzee relative abundance. The best model explained 43.16% of the variation with distance to roads and swamps emerging as the best predictors of chimpanzee relative abundance. Our results suggest that chimpanzees avoid roads and prefer to maintain proximity to swamps. There was no significant effect of settlements, abandoned settlements, mangroves or human presence. It appears that chimpanzees do not avoid areas frequented by people; although, our findings suggest temporal avoidance between the two species. We highlight the importance of studying chimpanzee populations living in anthropogenic habitats like agricultural-swamp matrixes to better understand factors influencing their distribution and inform conservation planning outside protected areas.

Even though information on global biodiversity trends becomes increasingly available, large taxonomic and spatial data gaps persist at the scale relevant to planning conservation interventions. This is because data collectors are hesitant to share data with global repositories due to workload, lack of incentives, and perceived risk of losing intellectual property rights. In contrast, due to greater conceptual and methodological proximity, taxon-specific database initiatives can provide more direct benefits to data collectors through research collaborations and shared authorship. The IUCN SSC Ape Populations, Environments and Surveys (A.P.E.S.) database was created in 2005 as a repository for data on great apes and other primate taxa. It aims to acquire field survey data and make different types of data accessible, and provide up-to-date species status information. To support the current update of the conservation action plan for western chimpanzees (Pan troglodytes verus) we compiled field surveys for this taxon from IUCN SSC A.P.E.S., 75% of which were unpublished. We used spatial modeling to infer total population size, range-wide density distribution, population connectivity and landscape-scale metrics. We estimated a total abundance of 52 800 (95% CI 17 577-96 564) western chimpanzees, of which only 17% occurred in national parks. We also found that 10% of chimpanzees live within 25 km of four multi-national 'development corridors' currently planned for West Africa. These large infrastructure projects aim to promote economic integration and agriculture expansion, but are likely to cause further habitat loss and reduce population connectivity. We close by demonstrating the wealth of conservation-relevant information derivable from a taxon-specific database like IUCN SSC A.P.E.S. and propose that a network of many more such databases could be created to provide the essential information to conservation that can neither be supplied by one-off projects nor by global repositories, and thus are highly complementary to existing initiatives. © 2019 The Author(s). Published by IOP Publishing Ltd. ; Peer reviewed

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.