Cats, connectivity and conservation: incorporating datasets and integrating scales for wildlife management

Understanding resource selection and quantifying habitat connectivity are fundamental to conservation planning for both land-use and species management plans. However, datasets available to management authorities for resource selection and connectivity analyses are often highly limited and fragmentary. As a result, measuring connectivity is challenging, and often poorly integrated within conservation planning and wildlife management. To exacerbate the challenge, scale-dependent resource use makes inference across scales problematic, resource use is often modelled in areas where the species is not present, and connectivity is typically measured using a source-to-sink approach, erroneously assuming animals possess predefined destinations. Here, we used a large carnivore, the leopard Panthera pardus, to characterise resource use and landscape connectivity across a vast, biodiverse region of southern Africa. Using a range of datasets to counter data deficiencies inherent in carnivore management, we overcame methodological limitations by employing occupancy modelling and resource selection functions across three orders of selection, and estimated landscape-scale habitat connectivity – independent of a priori source and sink locations – using circuit theory. We evaluated whether occupancy modelling on its own was capable of accurately informing habitat connectivity, and identified conservation priorities necessary for applied management. We detected markedly different scale-dependent relationships across all selection orders. Our multi-data, multi-scale approach accurately predicted resource use across multiple scales and demonstrates how management authorities can more suitably utilise fragmentary datasets. We further developed an unbiased landscape-scale depiction of habitat connectivity, and identified key linkages in need of targeted management. We did not find support for the use of occupancy modelling as a proxy for landscape-scale habitat connectivity and further caution its use within a management context. Synthesis and applications. Maintaining habitat connectivity remains a fundamental component of wildlife management and conservation, yet data to inform these biological and ecological processes are often scarce. We present a robust approach that incorporates multi-scale fragmentary datasets (e.g. mortality data, permit data, sightings data), routinely collected by management authorities, to inform wildlife management and land-use planning. We recommend that management authorities employ a multi-data, multi-scale connectivity approach—as we present here—to identify management units at risk of low connectivity

Multi-scale, multivariate community models improve designation of biodiversity hotspots in the Sunda Islands

Species occur in sympatric assemblages, bound together by ecological relationships and interspecific interactions. Borneo and Sumatra host some of the richest assemblages of biota worldwide. The region, however, faces the highest global deforestation rates, which seriously threaten its unique biodiversity. We used a large camera trap dataset that recorded data for 70 terrestrial species of mammals and birds, to explore the drivers of regional species richness patterns. Using a multi-scale, multivariate modelling framework which quantified the main environmental factors associated with patterns of biodiversity, while simultaneously assessing individual relationships of each species, we determined the ecological drivers of sampled biodiversity, and their contributions to community assemblages. We then mapped predicted species richness, evaluated the effectiveness of protected areas in securing biodiversity hotspots, performed gap analysis to highlight biodiverse areas lacking protection and compared our predictions with species richness maps produced by using IUCN range layers. Finally, we investigated the performance of each species as an indicator of sampled biodiversity. We demonstrate that biodiversity in Borneo and Sumatra is primarily affected by gradients of ecological and anthropogenic factors, and only marginally by topographic and spatial factors. In both islands, species are primarily associated with elevational gradients in vegetation and climate, leading to altitudinal zonation in niche separation as a major factor characterizing the islands' biodiversity. Species richness was highest in north-eastern Borneo and in western Sumatra. We found that most predicted biodiversity hotspots are not formally protected in either island; only 9.2 and 18.2% of the modelled species richness occurred within protected areas in Borneo and Sumatra, respectively. We highlighted that our prediction for Borneo performed better than, and differed drastically from, the IUCN species richness layer, while for Sumatra our modelled species richness layer and the IUCN one were similar, and both showed low predictive power. Our analysis suggests that common and generalist carnivores are the most effective indicators of sampled biodiversity and have high potential as focal, umbrella or indicator species to assist multi-species vertebrate conservation planning. Understanding existing drivers and patterns of biodiversity is critical to support the development of effective community conservation strategies in this rapidly changing region

The conservation costs of game ranching

The devolution of user rights of wildlife in southern Africa has led to a widespread land-use shift from livestock farming to game ranching. The economic advantages of game ranching over livestock farming are significant, but so too are the risks associated with breeding financially valuable game where free-ranging wildlife pose a credible threat. Here, we assessed whether the conservation potential of game ranching, and a decentralized approach to conservation more generally, may be undermined by an increase in human–wildlife conflict. We demonstrate that game rancher tolerance towards free-ranging wildlife has significantly decreased as the game ranching industry has evolved. Our findings reveal a conflict of interest between wealth and wildlife conservation resulting from local decision making in the absence of adequate centralized governance and evidence-based best practice. As a fundamental pillar of devolution-based natural resource management, game ranching proves an important mechanism for economic growth, albeit at a significant cost to conservation