DOI: 10.5061/dryad.h4tn7
title: Data from: Cats, connectivity and conservation: incorporating datasets and integrating scales for wildlife management

description: 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.
description: First-order
 DataframeRaw occupancy data
 (first-order scale of selection) for leopards Panthera
 pardus.Dryad_Pitman_et.al_2016_First_Order_Dataframes.RdataSecond-order DataframeRaw logistic regression data (second-order scale of selection) for leopards Panthera pardus.Dryad_Pitman_et.al_2016_Second_Order_Dataframe.RdataThird-order DataframeRaw logistic regression data (third-order scale of selection) for leopards Panthera pardus.Dryad_Pitman_et.al_2016_Third_Order_Dataframe.Rdata