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 effects of local human population density and distance to markets on the condition of coral reef fisheries

Coral reef fisheries support the livelihoods of millions of people but have been severely and negatively affected by anthropogenic activities. We conducted a systematic review of published data on the biomass of coral reef fishes to explore how the condition of reef fisheries is related to the density of local human populations, proximity of the reef to markets, and key environmental variables (including broad geomorphologic reef type, reef area, and net productivity). When only population density and environmental covariates were considered, high variability in fisheries conditions at low human population densities resulted in relatively weak explanatory models. The presence or absence of human settlements, habitat type, and distance to fish markets provided a much stronger explanatory model for the condition of reef fisheries. Fish biomass remained relatively low within 14 km of markets, then biomass increased exponentially as distance from reefs to markets increased. Our results suggest the need for an increased science and policy focus on markets as both a key driver of the condition of reef fisheries and a potential source of solutions

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

Low emission development strategies in agriculture. An agriculture, forestry, and other land uses (AFOLU) perspective

As countries experience economic growth and choose among available development pathways, they are in a favorable position to adopt natural resource use technologies and production practices that favor efficient use of inputs, healthy soils, and ecosystems. Current emphasis on increasing resilience to climate change and reducing agricultural greenhouse gasses (GHG) emissions strengthens the support for sustainable agricultural production. In fact, reducing losses in soil fertility, reclaiming degraded lands, and promoting synergistic interaction between crop production and forests are generally seen as good climate change policies. In order for decision-makers to develop long-term policies that address these issues, they must have tools at their disposal that evaluate trade-offs, opportunities, and repercussions of the options considered. In this paper, the authors combine and reconcile the output of three models widely accessible to the public to analyze the impacts of policies that target emission reduction in the agricultural sector. We present an application to Colombia which reveals the importance of considering the full scope of interactions among the various land uses. Results indicate that investments in increasing the efficiency and productivity of the livestock sector and reducing land allocated to pasture are preferable to policies that target deforestation alone or target a reduction of emissions in crop production. Investments in livestock productivity and land-carrying capacity would reduce deforestation and provide sufficient gains in carbon stock to offset greater emissions from increased crop production while generating higher revenues