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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 have 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 analyzing 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 modeling workflow can be rerun periodically when new data become available for our study population. As the workflow is also designed to be easily adapted for other harvested species, it contributes to the development of cost-effective population analyses that help inform management strategies and mitigate biodiversity loss.