Data from: 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.

解析资源选择与量化生境连通性，是土地利用管理与物种管理两类保护规划的核心基础。然而，管理机构可用于资源选择与连通性分析的数据集往往极为有限且碎片化。由此，连通性测算面临诸多挑战，且常难以融入保护规划与野生动物管理工作中。更为棘手的是，依赖尺度的资源利用行为使得跨尺度推演存在局限，资源选择模型常构建于物种未实际分布的区域，且连通性测算通常采用源-汇（source-to-sink）方法，错误地假定动物拥有预设的迁徙终点。

本研究以大型食肉动物豹（Panthera pardus）为研究对象，对非洲南部一片广袤且生物多样性丰富的区域开展资源利用与景观连通性特征刻画。本研究依托多套数据集以弥补食肉动物管理中固有的数据缺陷，通过在三级选择尺度下应用占用模型（occupancy modelling）与资源选择函数，克服了方法学层面的局限；并借助电路理论（circuit theory）估算了景观尺度下的生境连通性，该估算不依赖先验的源-汇位点。本研究还评估了单独使用占用模型能否准确支撑生境连通性分析，并明确了应用管理所需的保护优先级。

研究发现，所有选择尺度下均存在显著不同的尺度依赖关系。本研究提出的多数据、多尺度方法可精准预测多尺度下的资源利用情况，并阐明了管理机构如何更合理地利用碎片化数据集。此外，本研究构建了无偏的景观尺度生境连通性刻画模型，并识别出需开展针对性管理的关键连通廊道。研究未发现支持单独使用占用模型作为景观尺度生境连通性替代指标的证据，并进一步提醒在管理场景中谨慎使用该方法。

综合与应用
维持生境连通性仍是野生动物管理与保护的核心组成部分，但支撑这些生物与生态过程的相关数据往往十分匮乏。本研究提出了一种稳健的方法，该方法整合了管理机构日常收集的多尺度碎片化数据集（如死亡记录、许可数据、目击数据），可为野生动物管理与土地利用规划提供支撑。我们建议管理机构采用本研究提出的多数据、多尺度连通性分析方法，以识别连通性偏低的风险管理单元。