Species distribution models often aim to inform conservation and management decisions. Such decisions, however, typically require information beyond the likely presence of a species at a coarse resolution, as predicted by occurrence-based distribution models. Process-based distribution models build species distributions based on environmental relationships with biological processes, providing more detailed predictions and representing a key opportunity for data-driven management. We illustrate the use of a simulation-based model to compare four strategies for managing glossy buckthorn (Frangula alnus), an invasive shrub in the northeastern United States. On a gridded landscape in southern New Hampshire and Maine, this population-level model includes geographically varying rates of survival, fruiting, germination, and establishment, along with mechanistic seed dispersal and seed bank dynamics, with land cover as the dominant environmental driver. We parameterize the model with field and lab studies, supplementing with published data, expert knowledge, and pattern-oriented parameterization using historical records. To evaluate the sensitivity of model outputs to each parameter, we perform a global sensitivity analysis, where all parameters are varied simultaneously within data-based ranges to incorporate potential interactions, and boosted regression trees are used to calculate the relative influence of each parameter. To illustrate a direct application of the model, we compare the success of four management strategies across twelve properties managed by the University of New Hampshire. Specifically, we compare the abundance of glossy buckthorn under no management, stated management plans, realized management actions, and uniformly aggressive management.
Results/Conclusions
In the sensitivity analysis, we find the strongest influence of stochastic long distance dispersal on the distribution of glossy buckthorn, consistent with its introduction history as an ornamental, as well as the age of first reproduction. In the management simulations, immigration prevents total eradication within any property, though management effects are detectable in the abundances and seed bank, both on each property and in un-managed adjacent cells. This flexible model structure, combining realistic local and regional biological processes, allows the incorporation of specific management actions targeting particular processes and life stages into the regional context of a mechanistic species distribution model, providing a more robust method for evaluating potential management strategies.