Past Connectivity but Recent Inbreeding in Cross River Gorillas Determined Using Whole Genomes from Single Hairs.

The critically endangered western gorillas (Gorilla gorilla) are divided into two subspecies: the western lowland (G. g. gorilla) and the Cross River (G. g. diehli) gorilla. Given the difficulty in sampling wild great ape populations and the small estimated size of the Cross River gorilla population, only one whole genome of a Cross River gorilla has been sequenced to date, hindering the study of this subspecies at the population level. In this study, we expand the number of whole genomes available for wild western gorillas, generating 41 new genomes (25 belonging to Cross River gorillas) using single shed hairs collected from gorilla nests. By combining these genomes with publicly available wild gorilla genomes, we confirm that Cross River gorillas form three population clusters. We also found little variation in genome-wide heterozygosity among them. Our analyses reveal long runs of homozygosity (>10 Mb), indicating recent inbreeding in Cross River gorillas. This is similar to that seen in mountain gorillas but with a much more recent bottleneck. We also detect past gene flow between two Cross River sites, Afi Mountain Wildlife Sanctuary and the Mbe Mountains. Furthermore, we observe past allele sharing between Cross River gorillas and the northern western lowland gorilla sites, as well as with the eastern gorilla species. This is the first study using single shed hairs from a wild species for whole genome sequencing to date. Taken together, our results highlight the importance of implementing conservation measures to increase connectivity among Cross River gorilla sites.

Long-Term Urban Market Dynamics Reveal Increased Bushmeat Carcass Volume despite Economic Growth and Proactive Environmental Legislation on Bioko Island, Equatorial Guinea.

Bushmeat hunting is extensive in west and central Africa as both a means for subsistence and for commercial gain. Commercial hunting represents one of the primary threats to wildlife in the region, and confounding factors have made it challenging to examine how external factors influence the commercial bushmeat trade. Bioko Island, Equatorial Guinea is a small island with large tracts of intact forest that support sizeable populations of commercially valuable vertebrates, especially endemic primates. The island also has a low human population and has experienced dramatic economic growth and rapid development since the mid-1990's. From October 1997 - September 2010, we monitored the largest bushmeat market on Bioko in Malabo, recording over 197,000 carcasses for sale. We used these data to analyze the dynamics of the market in relation to political events, environmental legislation, and rapid economic growth. Our findings suggest that bushmeat hunting and availability increased in parallel with the growth of Equatorial Guinea's GDP and disposable income of its citizens. During this 13-year study, the predominant mode of capture shifted from trapping to shotguns. Consequently, carcass volume and rates of taxa typically captured with shotguns increased significantly, most notably including intensified hunting of Bioko's unique and endangered monkey fauna. Attempts to limit bushmeat sales, including a 2007 ban on primate hunting and trade, were only transiently effective. The hunting ban was not enforced, and was quickly followed by a marked increase in bushmeat hunting compared to hunting rates prior to the ban. Our results emphasize the negative impact that rapid development and unenforced legislation have had on Bioko's wildlife, and demonstrate the need for strong governmental support if conservation strategies are to be successful at preventing extinctions of tropical wildlife.

Model selection, zero-inflated models, and predictors of primate abundance in Korup National Park, Cameroon.

Determining the ecological and anthropogenic factors that shape the abundance and distribution of wild primates is a critical component of primate conservation research. Such research is complicated, however, whenever the species under study are encountered infrequently, a characteristic of many taxa that are threatened with extinction. Typically, the resulting data sets based on surveys of such species will have a high frequency of zero counts which makes it difficult to determine the predictor variables that are associated with species abundance. In this study, we test various statistical models using survey data that was gathered on seven species of primate in Korup National Park, Cameroon. Predictor variables include hunting signs and aspects of habitat structure and floristic composition. Our statistical models include zero-inflated models that are tailored to deal with a high frequency of zero counts. First, using exploratory data analysis we found the most informative set of models as ranked by Δ-AIC (Akaike's information criterion). On the basis of this analysis, we used five predictor variables to construct several regression models including Poisson, zero-inflated Poisson, negative binomial, and zero-inflated negative binomial. Total basal area of all trees, density of secondary tree species, hunting signs, and mean basal area of all trees were significant predictors of abundance in the zero-inflated models. We discuss the statistical logic behind zero-inflated models and provide an interpretation of parameter estimates. We recommend that researchers explore a variety of models when determining the factors that correlate with primate abundance.