Wildlife-friendly farming recouples grazing regimes to stimulate recovery in semi-arid rangelands.

While rangeland ecosystems are globally important for livestock production, they also support diverse wildlife assemblages and are crucial for biodiversity conservation. As rangelands around the world have become increasingly degraded and fragmented, rethinking farming practice in these landscapes is vital for achieving conservation goals, rangeland recovery, and food security. An example is reinstating livestock shepherding, which aims to recouple grazing regimes to vegetation conditioned to semi-arid climates and improve productivity by reducing overgrazing and rewiring past ecological functions. Tracking the large-scale ecosystem responses to shifts in land management in such sparsely vegetated environments have so far proven elusive. Therefore, our goal was to develop a remote tracking method capable of detecting vegetation changes and environmental responses on rangeland farms engaging in contrasting farming practices in South Africa: wildlife friendly farming (WFF) implementing livestock shepherding with wildlife protection, or rotational grazing livestock farming with wildlife removal. To do so, we ground-truthed Sentinel-2 satellite imagery using drone imagery and machine learning methods to trace historical vegetation change on four farms over a four-year period. First, we successfully classified land cover maps cover using drone footage and modelled vegetation cover using satellite vegetation indices, achieving 93.4% accuracy (к = 0.901) and an r-squared of 0.862 (RMSE = 0.058) respectively. We then used this model to compare the WFF farm to three neighbouring rotational grazing farms, finding that satellite-derived vegetation productivity was greater and responded more strongly to rainfall events on the WFF farm. Furthermore, vegetation cover and grass cover, patch size, and aggregation were greater on the WFF farm when classified using drone data. Overall, we found that remotely assessing regional environmental benefits from contrasting farming practices in rangeland ecosystems could aid further adoption of wildlife-friendly practices and help to assess the generality of this case study.

Low microsatellites used to investigate leopard genetic structure severely restricts the results by Ropiquet et al. (2015) to infer population structure for managers.

Low microsatellites used to investigate leopard genetic structure severely restricts the results by Ropiquet et al. (2015) to infer population structure for managers.

Gene flow and population structure of a solitary top carnivore in a human-dominated landscape.

While African leopard populations are considered to be continuous as demonstrated by their high genetic variation, the southernmost leopard population exists in the Eastern and Western Cape, South Africa, where anthropogenic activities may be affecting this population's structure. Little is known about the elusive, last free-roaming top predator in the region and this study is the first to report on leopard population structuring using nuclear DNA. By analyzing 14 microsatellite markers from 40 leopard tissue samples, we aimed to understand the populations' structure, genetic distance, and gene flow (Nm). Our results, based on spatially explicit analysis with Bayesian methods, indicate that leopards in the region exist in a fragmented population structure with lower than expected genetic diversity. Three population groups were identified, between which low to moderate levels of gene flow were observed (Nm 0.5 to 3.6). One subpopulation exhibited low genetic differentiation, suggesting a continuous population structure, while the remaining two appear to be less connected, with low emigration and immigration between these populations. Therefore, genetic barriers are present between the subpopulations, and while leopards in the study region may function as a metapopulation, anthropogenic activities threaten to decrease habitat and movement further. Our results indicate that the leopard population may become isolated within a few generations and suggest that management actions should aim to increase habitat connectivity and reduce human-carnivore conflict. Understanding genetic diversity and connectivity of populations has important conservation implications that can highlight management of priority populations to reverse the effects of human-caused extinctions.