An integrated population modelling workflow for supporting mesopredator management

This is a Preprint and has not been peer reviewed. This is version 2 of this Preprint. You must log in to post a comment. There are no comments or no comments have been made public for this article. This is a Preprint and has not been peer reviewed. This is version 2 of this Preprint. Add a Comment You must log in to post a comment. Comments There are no comments or no comments have been made public for this article. - Code repository - Code archive (Zenodo) - OSF storage - Appendix S1 - Appendix S2 - Appendix S3 - Appendix S4 - Appendix S5 - Appendix S6 - Hunting data (COAT) - Carcass data (COAT) - Rodent data (COAT) Expanding populations of mesopredators threaten biodiversity and human health in many ecosystems across the world. Lethal control through harvest is commonly implemented as a mitigation measure, yet its effects on mesopredator population dynamics in interaction with compensatory mechanisms and environmental conditions has rarely been assessed quantitatively due to data constraints. Recent advances involving integrated population models (IPMs) have enabled promising new avenues for overcoming these constraints by jointly analysing multiple datasets while simultaneously accounting for bias and uncertainty. Here we developed a versatile IPM workflow for studying mesopredator population dynamics under different management regimes and applied it to an expanding population of red foxes in Arctic Norway. Our model combined routinely collected data on age, reproductive status, and genetic similarity from >4000 harvested red foxes with opportunistic field observations and information published on red foxes elsewhere. This allowed us to quantify population dynamics over a period of 20 years and identify the drivers of changes in population growth rates using retrospective (transient Life Table Response Experiments, tLTREs) and prospective (population viability analyses, PVAs) perturbation analyses. We found dramatic year-to-year fluctuations in red fox population size due to natural mortality and immigration responding to changes in rodent prey availability and population density. Forward projections indicated that current harvest levels were likely sufficient to prevent population increase over longer time periods. However, even substantial increases in harvest levels were unable to evoke population decline due to strong buffering effects of density-dependence, especially through immigration. Our study highlights the potential of IPMs for studying population dynamics even when no structured surveys of living animals are available and illustrates the value of extracting and curating information from harvested animals. Our semi-automated and reproducible modelling workflow is ready to be re-run periodically when new data becomes available for our study population and can easily be transferred and adapted to other harvested species, contributing to the development of cost-effective population analyses that are of high relevance for informing management strategies and mitigating biodiversity loss in practice. https://doi.org/10.32942/X2Z33G Applied Statistics, Biodiversity, Biostatistics, Ecology and Evolutionary Biology, Longitudinal Data Analysis and Time Series, Natural Resources and Conservation, Population Biology, Statistical Methodology, Statistical Models, Survival Analysis, Terrestrial and Aquatic Ecology, Zoology culling, Demography, harvest, hunting, Immigration, IPM, Mortality, population dynamics, reproducibility, Tundra, Vulpes vulpes Published: 2024-08-01 12:24 Last Updated: 2025-05-31 15:15 CC BY Attribution 4.0 International Data and Code Availability Statement: Raw data on harvested foxes and small rodent abundance are archived on the COAT Data Portal (https://data.coat.no/). Both datasets are currently under embargo; access can be requested through Dr. Dorothée Ehrich ([email protected]). The genetic data, opportunistic den survey data, complete model input data, posterior summaries from the model, and supplementary files are archived on OSF: https://osf.io/756re/. All code, including the “targets” pipeline and all necessary documentation for reproducing and adapting the workflow can be found on GitHub: https://github.com/ChloeRN/VredfoxIPM. The results presented in this paper were created using version 1.0 of the code. Language: English Views: 1565 Downloads: 829