Reliable estimates of population status are a pre-requisite for informed wildlife management and conservation. However, abundance estimates can be challenging to obtain, especially for species that are highly mobile, rare and elusive. Investigators often resort to minimum counts and proxies, or piece together estimates from local studies to make extrapolations that are questionable at best. For nearly two decades, management agencies in Norway and Sweden have been monitoring populations of three large carnivores, brown bear (Ursus ursus), wolf (Canis lupus) and wolverine (Gulo gulo) using non-invasive genetic sampling (NGS) across the entire Scandinavian range of these transboundary species (nearly 600 000 square kilometers). The goal of our study was to develop statistical methods that allow a comprehensive assessment of population status and dynamics using NGS data and other sources of information at very large spatial scales that have thus far eluded spatial capture-recapture studies due to logistic and computational constraints. We developed a Bayesian open-population spatial capture-recapture (OPSCR) model that, using a combination of NGS and recoveries of dead carnivores, jointly estimates 1) the spatial variability in the probability of genetic detection, 2) the spatial distribution and interannual movements of individuals and 3) population size and dynamics. We fitted this model to the extensive individual-based monitoring data for which had been compiled by the national monitoring programs in Sweden and Norway between 2012 and 2018.
Results/Conclusions
The unique Scandinavian data set combined with a novel OPSCR model allowed us to quantify the population status of three sympatric large carnivores at an unprecedented spatial scale. The OPSCR model yielded annual density maps and both total and jurisdiction-specific population sizes estimates. For example, in 2018, the estimated large carnivore abundance in Scandinavia was 2 757 (95% credible interval, CrI: 2 636 - 2 877) bears, 375 (CrI: 352 - 402) wolves and 1 035 (CrI: 985 - 1 088) wolverines. Annual cause-specific mortality and recruitment were also estimated, which are both useful metrics of the population status and trajectory. The findings present a comprehensive and spatially-explicit picture of the status and dynamics of bears, wolverines, and wolves in Scandinavia, quantify anthropogenic effects on their populations, and offer a tool for identifying focal areas for conservation intervention and conflict mitigation. Our study illustrates how advances in non-invasive monitoring methods, spatial capture-recapture modelling, and computation enable scale-transcending assessments in wildlife population ecology.