Network analysis of a stakeholder community combatting illegal wildlife trade

The illegal wildlife trade has emerged as a growing and urgent environmental issue. Stakeholders involved in the efforts to curb wildlife trafficking include nongovernmental organizations (NGOs), academia, and state government and enforcement bodies. The extent to which these stakeholders work and communicate among each other is fundamental to effectively combatting illicit trade. Using the United Kingdom as a case study, we used a social network analysis and semistructured interviews of stakeholders to assess communication relationships in the counter wildlife trafficking community. The NGOs consistently occupied 4 of the 5 most central positions in the generated networks, whereas academic institutions routinely occupied 4 of the 5 most peripheral positions. However, NGOs were the least diverse in their communication practices compared with the other stakeholder groups. Stakeholders identified personal relationships as the most important aspect of functioning communication. Participant insights also showed that stakeholder-specific variables (e.g., ethical and confidentiality concerns), competition, and fundraising can have a confounding effect on intercommunication. Evaluating communication networks and intrastakeholder communication trends is essential to creating cohesive, productive, and efficient responses to the challenges of combatting illegal wildlife trade. Article impact statement: Communication among those combatting illegal wildlife trade is confounded by stakeholder variables (ethics, confidentiality), competition, and fundraising.     

Use of linkage mapping and centrality analysis across habitat gradients to conserve connectivity of gray wolf populations in western North America

Centrality metrics evaluate paths between all possible pairwise combinations of sites on a landscape to rank the contribution of each site to facilitating ecological flows across the network of sites. Computational advances now allow application of centrality metrics to landscapes represented as continuous gradients of habitat quality. This avoids the binary classification of landscapes into patch and matrix required by patch-based graph analyses of connectivity. It also avoids the focus on delineating paths between individual pairs of core areas characteristic of most corridor- or linkage-mapping methods of connectivity analysis. Conservation of regional habitat connectivity has the potential to facilitate recovery of the gray wolf (Canis lupus), a species currently recolonizing portions of its historic range in the western United States. We applied 3 contrasting linkage-mapping methods (shortest path, current flow, and minimum-cost-maximum-flow) to spatial data representing wolf habitat to analyze connectivity between wolf populations in central Idaho and Yellowstone National Park (Wyoming). We then applied 3 analogous betweenness centrality metrics to analyze connectivity of wolf habitat throughout the northwestern United States and southwestern Canada to determine where it might be possible to facilitate range expansion and interpopulation dispersal. We developed software to facilitate application of centrality metrics. Shortest-path betweenness centrality identified a minimal network of linkages analogous to those identified by least-cost-path corridor mapping. Current flow and minimum-cost-maximum-flow betweenness centrality identified diffuse networks that included alternative linkages, which will allow greater flexibility in planning. Minimum-cost-maximum-flow betweenness centrality, by integrating both land cost and habitat capacity, allows connectivity to be considered within planning processes that seek to maximize species protection at minimum cost. Centrality analysis is relevant to conservation and landscape genetics at a range of spatial extents, but it may be most broadly applicable within single- and multispecies planning efforts to conserve regional habitat connectivity.     

Empirical selection between least-cost and current-flow designs for establishing wildlife corridors in Gabon

Corridors are intended to increase species survival by abating landscape fragmentation resulting from the conversion of natural habitats into human-dominated matrices. Conservation scientists often rely on 1 type of corridor model, typically the least-cost model or current-flow model, to construct a linkage design, and their choice is not usually based on theory or empirical evidence. We developed a method to empirically confirm whether corridors produced by these 2 models are used by target species under current landscape conditions. We applied this method in the Gamba landscape between 2 national parks in southwestern Gabon. We collected signs of presence of African forest elephant (Loxodonta cyclotis), forest buffalo (Syncerus caffer nanus), and 2 apes, western lowland gorilla (Gorilla gorilla gorilla) and central chimpanzee (Pan troglodytes troglodytes), on transects. We used patch-occupancy models to identify least-cost and current-flow corridors for these 4 species. On average, 28.7% of current-flow corridors overlapped with least-cost corridors, confirming that the choice of corridor model can affect the location of the resulting linkage design. We validated these corridors by monitoring signs and examining camera detections on new transects within and outside modeled corridors. Current-flow corridors performed better than least-cost corridors for elephants, whereas the opposite was found for buffalo and apes. Locations of the highest priority corridors for the 3 taxa did not overlap, and only 18.3% of their combined surface was common among 2 species. We used centrality metrics to calculate the average contribution of corridor pixels to landscape connectivity and derived an index that can be used to prioritize corridors. As a result, we recommend protecting at least 17.4% of the land surface area around Gamba town to preserve the preferred travel routes of the target species.