A pan-African spatial assessment of human conflicts with lions and elephants.

African lions (Panthera leo) and African savanna (Loxodonta africana) and forest (L. cyclotis) elephants pose threats to people, crops, and livestock, and are themselves threatened with extinction. Here, we map these human-wildlife conflicts across Africa. Eighty-two percent of sites containing lions and elephants are adjacent to areas with considerable human pressure. Areas at severe risk of conflict (defined as high densities of humans, crops, and cattle) comprise 9% of the perimeter of these species' ranges and are found in 18 countries hosting, respectively, ~ 74% and 41% of African lion and elephant populations. Although a variety of alternative conflict-mitigation strategies could be deployed, we focus on assessing the potential of high-quality mitigation fences. Our spatial and economic assessments suggest that investments in the construction and maintenance of strategically located mitigation fences would be a cost-effective strategy to support local communities, protect people from dangerous wildlife, and prevent further declines in lion and elephant populations.

Reconciling corruption with conservation triage: Should investments shift from the last best places?

Considerable outside funding will be required to overcome the financial shortfalls faced by most of Africa's protected areas. Given limited levels of external support, it will be essential to allocate these funds wisely. While most recent studies on conservation triage have recommended prioritizing reserves with the highest remaining conservation value (the "last best places"), such investments are complicated by the fact that these same reserves often attract the greatest revenues from ecotourism and thus the most attention from corrupt local governments. Alternatively, philanthropic organizations might achieve greater returns from investing in the management of neglected areas with lower current conservation value but with less financial leakage from corruption. We outline here how high levels of corruption could favor a strategy that shifts investments away from the last best places.

Linking social and spatial networks to viral community phylogenetics reveals subtype-specific transmission dynamics in African lions.

Heterogeneity within pathogen species can have important consequences for how pathogens transmit across landscapes; however, discerning different transmission routes is challenging. Here, we apply both phylodynamic and phylogenetic community ecology techniques to examine the consequences of pathogen heterogeneity on transmission by assessing subtype-specific transmission pathways in a social carnivore. We use comprehensive social and spatial network data to examine transmission pathways for three subtypes of feline immunodeficiency virus (FIVPle ) in African lions (Panthera leo) at multiple scales in the Serengeti National Park, Tanzania. We used FIVPle molecular data to examine the role of social organization and lion density in shaping transmission pathways and tested to what extent vertical (i.e., father- and/or mother-offspring relationships) or horizontal (between unrelated individuals) transmission underpinned these patterns for each subtype. Using the same data, we constructed subtype-specific FIVPle co-occurrence networks and assessed what combination of social networks, spatial networks or co-infection best structured the FIVPle network. While social organization (i.e., pride) was an important component of FIVPle transmission pathways at all scales, we find that FIVPle subtypes exhibited different transmission pathways at within- and between-pride scales. A combination of social and spatial networks, coupled with consideration of subtype co-infection, was likely to be important for FIVPle transmission for the two major subtypes, but the relative contribution of each factor was strongly subtype-specific. Our study provides evidence that pathogen heterogeneity is important in understanding pathogen transmission, which could have consequences for how endemic pathogens are managed. Furthermore, we demonstrate that community phylogenetic ecology coupled with phylodynamic techniques can reveal insights into the differential evolutionary pressures acting on virus subtypes, which can manifest into landscape-level effects.

Future threats to biodiversity and pathways to their prevention.

Tens of thousands of species are threatened with extinction as a result of human activities. Here we explore how the extinction risks of terrestrial mammals and birds might change in the next 50 years. Future population growth and economic development are forecasted to impose unprecedented levels of extinction risk on many more species worldwide, especially the large mammals of tropical Africa, Asia and South America. Yet these threats are not inevitable. Proactive international efforts to increase crop yields, minimize land clearing and habitat fragmentation, and protect natural lands could increase food security in developing nations and preserve much of Earth's remaining biodiversity.

A generalized approach for producing, quantifying, and validating citizen science data from wildlife images.

Citizen science has the potential to expand the scope and scale of research in ecology and conservation, but many professional researchers remain skeptical of data produced by nonexperts. We devised an approach for producing accurate, reliable data from untrained, nonexpert volunteers. On the citizen science website www.snapshotserengeti.org, more than 28,000 volunteers classified 1.51 million images taken in a large-scale camera-trap survey in Serengeti National Park, Tanzania. Each image was circulated to, on average, 27 volunteers, and their classifications were aggregated using a simple plurality algorithm. We validated the aggregated answers against a data set of 3829 images verified by experts and calculated 3 certainty metrics-level of agreement among classifications (evenness), fraction of classifications supporting the aggregated answer (fraction support), and fraction of classifiers who reported "nothing here" for an image that was ultimately classified as containing an animal (fraction blank)-to measure confidence that an aggregated answer was correct. Overall, aggregated volunteer answers agreed with the expert-verified data on 98% of images, but accuracy differed by species commonness such that rare species had higher rates of false positives and false negatives. Easily calculated analysis of variance and post-hoc Tukey tests indicated that the certainty metrics were significant indicators of whether each image was correctly classified or classifiable. Thus, the certainty metrics can be used to identify images for expert review. Bootstrapping analyses further indicated that 90% of images were correctly classified with just 5 volunteers per image. Species classifications based on the plurality vote of multiple citizen scientists can provide a reliable foundation for large-scale monitoring of African wildlife.