Nsombou Abalghe-Dzal Project (Community Wildlife Project Gabon)

Hunting for bushmeat represents a complex social–ecological system ill-suited to top-down management. Community participatory management is an alternative approach with increasing support for both ethical and pragmatic reasons. Key to a community approach is long-term monitoring: this can both catalyse local ownership of and cohesion around management and is necessary to assess the effects of interventions and make changes as needed through adaptive management. Yet community-driven methods to monitor hunting remain underdeveloped: they often fail to account for sampling bias and do not incorporate space in a thorough way, and data are not communally analysed to simulate effects of potential management decisions. We created a novel community bushmeat monitoring programme to address these gaps across 20 villages in north-eastern Gabon. Paraecologists conducted standardised monitoring of bushmeat, and hundreds of hunters conducted GPS self-follows mapping village hunting catchments. We integrated these data to estimate the proportion of bushmeat sampled and make robust extrapolations of total offtake across space and time, estimating an annual offtake of ~30,000 animals of >56 species across all villages. Here, we present our approach and data—and apply them through a case study of six sympatric duiker species—to inform new directions for social–ecological bushmeat research and management.

Hunting for wild meat in the tropics provides subsistence and income for millions of people. Methods have remained relatively unchanged since the introduction of shotguns and battery‐powered incandescent flashlights, but the short battery life of such flashlights has limited nocturnal hunting. However, hunters in many countries throughout the tropics have recently begun to switch to brighter and more efficient light‐emitting diode (LED) flashlights. Such brighter spotlights stimulate the freeze response of many species, and improved battery life allows hunters to pursue game more often and for longer periods of time. Interviews with hunters in African and South American tropical forests revealed that LEDs increase the frequency and efficiency of nocturnal hunting, and subsequently the number of kills made. In Brazil, these findings were supported by harvest data. The marked change in efficiency brought about by LEDs, well known to hunters around the world, poses a major threat to wildlife. Here we consider the implications of the increasing use of LED lights in hunting for communities, governments, wildlife managers, and conservationists.

Accurate estimations of animal populations are necessary for management, conservation, and policy decisions. However, methods for surveying animal communities disproportionately represent specific groups or guilds. For example, transect surveys can provide robust data for large arboreal species but underestimate cryptic or small‐bodied terrestrial species, whereas camera traps have the inverse tendency. The integration of information from multiple methodologies would provide the most complete inference on population size or responses to putative covariates, yet a simple, robust framework that allows integration and comparison of multiple data sources has been lacking. We use 27,813 counts of 35 species or species groups derived from concurrent visual transects, dung transects, and camera trap surveys in tropical forests and compare them within a generalized joint attribute modeling framework (GJAM) that both compares and integrates field‐collected dung, visual, and camera trap data to quantify the species‐ and trait‐specific differences in detection for each method. The effectiveness of survey method was strongly dependent on species, as well as animal traits. These differences in effectiveness contributed to meaningful differences in the reported strength of a known important covariate for animal communities (distance to nearest village). Data fusion through GJAM allows clear and unambiguous comparisons of the counts provided from each different methodology, the incorporation of trait information, and fusion of all three data streams to generate a more complete estimate of the effects of an anthropogenic disturbance covariate. Research and conservation resources are extremely limited, which often means that field campaigns attempt to maximize the amount of information gathered especially in remote, hard‐to‐access areas. Advances in these understudied areas will be accelerated by analytical methods that can fully leverage the total body of diverse biodiversity field data, even when they are collected using different methods. We demonstrate that survey methods vary in their effectiveness for counting species based on biological traits, but more importantly that generative models like GJAM can integrate data from multiple sources in one cohesive statistical framework to make improved inference in understudied environments.

Tropical areas are facing a bushmeat crisis involving the systematic over-exploitation of large-bodied mammals for both subsistence and commercial purposes. We hypothesize that because hunting generally originates from villages, it will create "halos of defaunation" where abundances of large mammals increase with distance away from villages. Whilst such patterns have been well characterized at the landscape scale, examining how de-faunation halos vary between different villages has received considerably less attention. Forests immediately surrounding villages are of considerable importance to the people residing within them and the factors hypothesized to influence local defaunation halos (e.g. village size, hunting practices and access to local markets) may affect local livelihoods and the ecological integrity of nearby forests. To address this, we adopted a par-ticipatory approach to establish and monitor sixty transects across ten village-distance gradients (1-8 km) in Gabon. Trained paraecologists, recruited from local villages, walked each transect twice monthly to determine the encounter rates of medium and large mammals across the village distance gradient and monitored village-level bushmeat availability. We found that overall rates of mammal observation and estimated species richness were constant across the village-distance gradient, however the total number of individuals encountered and bushmeat biomass were lower close to villages-consistent with local depletion of wildlife. These general trends were underpinned by depleted mammal species diversity with increasing proximity to villages and a marked shift in mammal community composition: small, non-hunted species were encountered most frequently near villages, whereas large, hunted species were encountered most frequently away from villages. We found some evidence for inter-village variation in the strength and depth of defaunation halos, which may be driven in part by the village-level hunting intensity. Several of the key parameters identified in landscape-scale bushmeat studies did not detectably influence village-level defaunation (e.g. road or market distance). Despite the prevalence of bushmeat hunting in the region, the conservation value of forests immediately surrounding villages was demonstrated through the detection of large-bodied species of conservation concern (e.g. chimpanzee and gorilla) at a high proportion of survey locations. The compositional shifts in mammal communities detailed here will ultimately lead to the altered composition and diversity of forests around villages, with potential implications for human livelihoods, health and transmission of zoonotic disease. This research also demonstrates the effectiveness of engaging paraecologists to answer focused ecological questions-the first step in facilitating effective natural resource management by local communities.