The relative effect of top-down versus bottom-up forces in regulating and limiting wildlife populations is an important theme in ecology. Untangling these effects is critical for a basic understanding of trophic dynamics and effective management. We examined the drivers of moose (Alces alces) population growth by integrating two independent sources of observations within a hierarchical Bayesian population model. This analysis used one of the largest existing spatiotemporal datasets on ungulate population dynamics globally. We documented a 20% population decline over the period examined. Moose population growth was negatively density-dependent. Although the mechanisms producing density-dependent suppression of population growth could not be determined, the relatively low densities at which moose populations were documented suggests it could be due primarily to density-dependent predation. Predation primarily limited population growth, except at low density, where it was regulating. Harvest appeared to be largely additive and contributed to population declines. Our results, highlight how population dynamics are context dependent and vary strongly across gradients in climate, forest type, and predator abundance. These results help clarify long-standing questions in population ecology and highlight the complex relationships between natural and human-caused mortality in driving ungulate population dynamics.

See the manuscript for details on how the dataset was collected and processed.

Data is found here on Dryad (moose_data_dryad.RData), but the R scripts (run_jags_model.R and gompertz_jags.R) are found on Zenodo (https://doi.org/10.5281/zenodo.6030027). See the README.txt for a description of all 3 files.