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 OPEN ACCESS RECEIVED 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chimpanzees (Pan troglodytes verus) we compiled field surveys for this taxon from IUCN SSC A.P.E.S., 75% of which were unpublished.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.
Heinicke et al. Positive Deviants in Chimpanzee Populations social-ecological configurations: first, rainforest habitats with a low degree of human impact, second, steep areas, and third, areas with high prevalence of hunting taboos and low degree of human impact. The largest chimpanzee populations are nowadays found under the third social-ecological configuration, even though most of these areas are not officially protected. Most commonly chimpanzee conservation has been based on exclusion of threats by creation of protected areas and law enforcement. Our findings suggest, however, that this approach should be complemented by an additional focus on threat reduction, i.e., interventions that directly target individual human behavior that is most threatening to chimpanzees, which is hunting. Although changing human behavior is difficult, stakeholder co-designed behavioral change approaches developed in the social sciences have been used successfully to promote pro-environmental behavior. With only a fraction of chimpanzees and primates living inside protected areas, such new approaches might be a way forward to improve primate conservation.
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
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.
Rural communities in third world countries are concerned over land use changes resulting from resource exploitation. This is the case for the Bumbuna watershed in Sierra Leone following impoundment of the Bumbuna reservoir in 2009. Farmers have increased activities along the riparian zones in protest against inundation of their farmlands. The dam operators warn this practice would threaten sustainable power supply; the farmers contend the reservoir is increasing and taking over their farms. However, it is difficult to resolve this issue without a means of quantifying the change and developing early warning systems for land cover in the watershed. This research presents a case for the use of remotely sensed Landsat data for quantification of land cover change and the development of predictive models to inform preparedness for imminent problems that may arise from land use practices. In situ water loggers, in combination with manual readings, recorded water levels in 30-minute intervals since 2009. These datasets combined with spectral values of Landsat 7 and Landsat 8 for the development of regression algorithms for predictive purposes. Digital photographs and satellite imagery illustrated the changes in land cover over time (a 33% water rise and 44% NDVI change from 2009 to 2015). These visual and spectral pictures confirm the usefulness of remotely sensed data for early warning systems in the watershed. Results of the regression analysis show Band 1 (Blue) and Band 4 (NIR) as statistically significant predictors for water level in the reservoir. The tests accounted for 84% (R 2) of the data with p-values less than α at the 0.05 confidence level. However, future trials of the model will consider reducing the 4.6 error margin to minimize deviations from the observed data.
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