Assessing Africa-wide pangolin exploitation by scaling local data

Overexploitation is one of the main pressures driving wildlife closer to extinction, yet broad-scale data to evaluate species’ declines are limited. Using African pangolins (Family: Pholidota) as a case study, we demonstrate that collating local-scale data can provide crucial information on regional trends in exploitation of threatened species to inform conservation actions and policy. We estimate that 0.4-2.7 million pangolins are hunted annually in Central African forests. The number of pangolins hunted has increased by ∼150% and the proportion of pangolins of all vertebrates hunted increased from 0.04% to 1.83% over the past four decades. However, there were no trends in pangolins observed at markets, suggesting use of alternative supply chains. The price of giant (Smutsia gigantea) and arboreal (Phataginus sp.) pangolins in urban markets has increased 5.8 and 2.3 times respectively, mirroring trends in Asian pangolins. Efforts and resources are needed to increase law enforcement and population monitoring, and investigate linkages between subsistence hunting and illegal wildlife trade

Global distribution maps of the leishmaniases

The leishmaniases are vector-borne diseases that have a broad global distribution throughout much of the Americas, Africa, and Asia. Despite representing a significant public health burden, our understanding of the global distribution of the leishmaniases remains vague, reliant upon expert opinion and limited to poor spatial resolution. A global assessment of the consensus of evidence for leishmaniasis was performed at a sub-national level by aggregating information from a variety of sources. A database of records of cutaneous and visceral leishmaniasis occurrence was compiled from published literature, online reports, strain archives, and GenBank accessions. These, with a suite of biologically relevant environmental covariates, were used in a boosted regression tree modelling framework to generate global environmental risk maps for the leishmaniases. These high-resolution evidence-based maps can help direct future surveillance activities, identify areas to target for disease control and inform future burden estimation efforts. DOI: http://dx.doi.org/10.7554/eLife.02851.00

The multiplicity of malaria transmission: a review of entomological inoculation rate measurements and methods across sub-Saharan Africa

Plasmodium falciparum malaria is a serious tropical disease that causes more than one million deaths each year, most of them in Africa. It is transmitted by a range of Anopheles mosquitoes and the risk of disease varies greatly across the continent. The "entomological inoculation rate" is the commonly-used measure of the intensity of malaria transmission, yet the methods used are currently not standardized, nor do they take the ecological, demographic, and socioeconomic differences across populations into account. To better understand the multiplicity of malaria transmission, this study examines the distribution of transmission intensity across sub-Saharan Africa, reviews the range of methods used, and explores ecological parameters in selected locations. It builds on an extensive geo-referenced database and uses geographical information systems to highlight transmission patterns, knowledge gaps, trends and changes in methodologies over time, and key differences between land use, population density, climate, and the main mosquito species. The aim is to improve the methods of measuring malaria transmission, to help develop the way forward so that we can better assess the impact of the large-scale intervention programmes, and rapid demographic and environmental change taking place across Africa

Mapping biomass with remote sensing: a comparison of methods for the case study of Uganda

<p>Abstract</p> <p>Background</p> <p>Assessing biomass is gaining increasing interest mainly for bioenergy, climate change research and mitigation activities, such as reducing emissions from deforestation and forest degradation and the role of conservation, sustainable management of forests and enhancement of forest carbon stocks in developing countries (REDD+). In response to these needs, a number of biomass/carbon maps have been recently produced using different approaches but the lack of comparable reference data limits their proper validation. The objectives of this study are to compare the available maps for Uganda and to understand the sources of variability in the estimation. Uganda was chosen as a case-study because it presents a reliable national biomass reference dataset.</p> <p>Results</p> <p>The comparison of the biomass/carbon maps show strong disagreement between the products, with estimates of total aboveground biomass of Uganda ranging from 343 to 2201 Tg and different spatial distribution patterns. Compared to the reference map based on country-specific field data and a national Land Cover (LC) dataset (estimating 468 Tg), maps based on biome-average biomass values, such as the Intergovernmental Panel on Climate Change (IPCC) default values, and global LC datasets tend to strongly overestimate biomass availability of Uganda (ranging from 578 to 2201 Tg), while maps based on satellite data and regression models provide conservative estimates (ranging from 343 to 443 Tg). The comparison of the maps predictions with field data, upscaled to map resolution using LC data, is in accordance with the above findings. This study also demonstrates that the biomass estimates are primarily driven by the biomass reference data while the type of spatial maps used for their stratification has a smaller, but not negligible, impact. The differences in format, resolution and biomass definition used by the maps, as well as the fact that some datasets are not independent from the reference data to which they are compared, are considered in the interpretation of the results.</p> <p>Conclusions</p> <p>The strong disagreement between existing products and the large impact of biomass reference data on the estimates indicate that the first, critical step to improve the accuracy of the biomass maps consists of the collection of accurate biomass field data for all relevant vegetation types. However, detailed and accurate spatial datasets are crucial to obtain accurate estimates at specific locations.</p

Environmental factors associated with the malaria vectors Anopheles gambiae and Anopheles funestus in Kenya

<p>Abstract</p> <p>Background</p> <p>The <it>Anopheles gambiae </it>and <it>Anopheles funestus </it>mosquito species complexes are the primary vectors of <it>Plasmodium falciparum </it>malaria in sub-Saharan Africa. To better understand the environmental factors influencing these species, the abundance, distribution and transmission data from a south-eastern Kenyan study were retrospectively analysed, and the climate, vegetation and elevation data in key locations compared.</p> <p>Methods</p> <p>Thirty villages in Malindi, Kilifi and Kwale Districts with data on <it>An. gambiae sensu strict</it>, <it>Anopheles arabiensis</it> and <it>An. funestus</it> entomological inoculation rates (EIRs), were used as focal points for spatial and environmental analyses. Transmission patterns were examined for spatial autocorrelation using the Moran's <it>I </it>statistic, and for the clustering of high or low EIR values using the Getis-Ord Gi* statistic. Environmental data were derived from remote-sensed satellite sources of precipitation, temperature, specific humidity, Normalized Difference Vegetation Index (NDVI), and elevation. The relationship between transmission and environmental measures was examined using bivariate correlations, and by comparing environmental means between locations of high and low clustering using the Mann-Whitney <it>U </it>test.</p> <p>Results</p> <p>Spatial analyses indicated positive autocorrelation of <it>An. arabiensis </it>and <it>An. funestus </it>transmission, but not of <it>An. gambiae s.s</it>., which was found to be widespread across the study region. The spatial clustering of high EIR values for <it>An. arabiensis </it>was confined to the lowland areas of Malindi, and for <it>An. funestus </it>to the southern districts of Kilifi and Kwale. Overall, <it>An. gambiae s.s</it>. and <it>An. arabiensis </it>had similar spatial and environmental trends, with higher transmission associated with higher precipitation, but lower temperature, humidity and NDVI measures than those locations with lower transmission by these species and/or in locations where transmission by <it>An. funestus </it>was high. Statistical comparisons indicated that precipitation and temperatures were significantly different between the <it>An. arabiensis </it>and <it>An. funestus </it>high and low transmission locations.</p> <p>Conclusion</p> <p>These finding suggest that the abundance, distribution and malaria transmission of different malaria vectors are driven by different environmental factors. A better understanding of the specific ecological parameters of each malaria mosquito species will help define their current distributions, and how they may currently and prospectively be affected by climate change, interventions and other factors.</p