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8 results for “bushmeat”
Bushmeat yields, species extinction rates and ecosystem-level impacts of bushmeat harvesting as predicted by the Madingley General Ecosystem Model
<p>The datasets contain data generated using the Madingley General Ecosystem Model for experiments decribed in the paper: "T. Barychka, G.M.Mace and D.W.Purves (2021) The Madingley General Ecosystem Model predicts bushmeat yields, species extinction rates and ecosystem-level impacts of bushmeat harvesting. Oikos."</p> <p>The Madingley General Ecosystem Model was used to generate predictions of bushmeat yields, extinction rates and broader ecosystem impacts for a range of harvesting intensities of duiker-sized endothermic herbivores. Duiker antelope (such as <i>Cephalophus callipygus</i> and <i>Cephalophus dorsalis</i>) are the most heavily hunted species in sub-Saharan Africa, contributing 34%-95% of all bushmeat in the Congo Basin. In the Madingley, the harvested group was described as "Heterotroph – Herbivore – Terrestrial – Mobile – Iteroparous– Endotherm", with adult bodymasses of 13-21 kg and juvenile bodymasses of >100 g. Harvesting period was set at 30 years (<em>n </em>=30).</p> <p>In the first experiment, we used the Madingley model to predict bushmeat yields ("Harvested Biomasses") and extinction rates ("Density") from harvesting duiker-sized herbivores using proportional harvesting strategy, with harvest rates ranging from 0 to 0.90. These were compared to the estimates of bushmeat yields and survival probabilities for two duiker antelope species (<i>Cephalophus callipygus</i> and <i>Cephalophus dorsalis) </i>from conventional single-species Beverton-Holt model. </p> <p>In the second experiment, we used the Madingley model to generate data on the state ("State") of the harvested ecosystem. The datasets contain estimates of biomasses, abundances, adult and juvenile bodymasses, etc. of the harvested duiker-sized herbivores as well as unharvested herbivores, omnivores and carnivores present in the simulated ecosystem. In the paper we focused on abundances; however, other estimates e.g., adult bodymasses can be used to conduct further studies on the effects of harvesting in tropical ecosystems.</p> <p>Main results of the experiments are that: 1) the Madingley model gave estimates for optimal harvesting rate, and extinction rate, that were qualitatively and quantitatively similar to the estimates from conventional single-species Beverton-Holt model; 2) the Madingley model predicted a background local extinction probability for the target species of at least 10%; 3) at medium and high levels of harvesting of duiker-sized herbivores, the Madingley model predicted statistically significant, but moderate, reductions in the densities of the targeted functional group; increases in small-bodied herbivores; decreases in large-bodied carnivores; and minimal ecosystem-level impacts overall.</p>
Data from: Predicting bushmeat biomass from species composition captured by camera traps: implications for locally-based wildlife monitoring
<p>The 'StatAnalysis.zip' contains the data and model files. We used it for the four analyses below.</p> <p>First, we estimated population densities, the mean body mass and camera-trap capture rates of five main bushmeat targets in a rainforest of southeast Cameroon: Peters's duikers (<em>Cephalophus callipygus</em>), bay duikers (<em>C. dorsalis</em>), blue duikers (<em>Philantomba monticola</em>), brush-tailed porcupines (<em>Atherurus africanus</em>) and Emin's pouched rats (<em>Cricetomys emini</em>). Second, on the basis of the density and body mass estimates, we estimated bushmeat biomass—the total biomass of the five bushmeat species—and its spatial variation. Third, we calculated six bushmeat indicators based on the capture rate estimates. Lastly, we examined the correlation between bushmeat biomass and the indicators.</p> <p>The ZIP file consists of 16 R script files, three CSV files (in the 'data' subfolder) and 135 stan files (in the 'stan' subfolders). It also has two empty folders, 'figure' and 'res', where the figures and R objects of model results will be stored following the analyses. Please see the document 'README.txt' before performing the analysis. This text file gives the ZIP file structure and brief descriptions of the files.</p>
Bushmeat yields, species extinction rates and ecosystem-level impacts of bushmeat harvesting as predicted by the Madingley General Ecosystem Model
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Data from: Predicting bushmeat biomass from species composition captured by camera traps: implications for locally-based wildlife monitoring
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Data from: Drivers of bushmeat hunting and perceptions of zoonoses in Nigerian hunting communities
Bushmeat hunting threatens biodiversity and increases the risk of zoonotic pathogen transmission. Nevertheless, limited information exists on patterns of contact with wildlife in communities that practice bushmeat hunting, especially with respect to social drivers of hunting behavior. We used interview responses from hunters and non-hunters in rural hunting communities in Nigeria to: 1) quantify contact rates with wildlife, 2) identify specific hunting behaviors that increase frequency of contact, 3) identify socioeconomic factors that predispose individuals to hunt, and 4) measure perceptions of risk. Participants engaged in a variety of behaviors that increased contact with wild animals, including: butchering to sell (37%), being injured (14%), using body parts for traditional medicine (19%), collecting carcasses found in forests and/or farms (18%), and keeping as pets (16%). Hunters came into contact with wildlife significantly more than non-hunters, even through non-hunting exposure pathways. Participants reported hunting rodents (95%), ungulates (93%), carnivores (93%), primates (87%), and bats (42%), among other prey. Reported hunting frequencies within taxonomic groups of prey were different for different hunting behaviors. Young age, lower education level, larger household size, having a father who hunts, and cultural group were all associated with becoming a hunter. Fifty-five percent of respondents were aware that they could contract diseases from wild animals, but only 26% of these individuals reported taking protective measures. Overall, hunters in this setting frequently contact a diversity of prey in risky ways, and the decision to become a hunter stems from family tradition, modified by economic necessity. Conservation and public health interventions in such settings may be most efficient when they capitalize on local knowledge and target root socio-economic and cultural drivers that lead to hunting behavior. Importantly, interventions that target consumption alone will not be sufficient; other drivers and modes of interaction with wildlife must also be considered.
Data from: Drivers of bushmeat hunting and perceptions of zoonoses in Nigerian hunting communities
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Data from: Bushmeat genetics: setting up a reference framework for the DNA-typing of African forest bushmeat
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Data from: Bushmeat hunting changes regeneration of African rainforests
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