National Park Service
ORCID IDs
https://orcid.org/0000-0002-8439-1859
https://orcid.org/0000-0002-0594-0136
Date of this Version
9-10-2019
Citation
Environmetrics. 2020;31:e2604.
https://doi.org/10.1002/env.2604
Abstract
Partial differential equations (PDEs) are a useful tool for modeling spatiotemporal dynamics of ecological processes. However, as an ecological process evolves, we need statistical models that can adapt to changing dynamics as new data are collected. We developed a model that combines an ecological diffusion equation and logistic growth to characterize colonization processes of a population that establishes long-term equilibrium over a heterogeneous environment. We also developed a homogenization strategy to statistically upscale the PDE for faster computation and adopted a hierarchical framework to accommodate multiple data sources collected at different spatial scales. We highlighted the advantages of using a logistic reaction component instead of a Malthusian component when population growth demonstrates asymptotic behavior. As a case study, we demonstrated that our model improves spatiotemporal abundance forecasts of sea otters in Glacier Bay, Alaska. Furthermore, we predicted spatially varying local equilibrium abundances as a result of environmentally driven diffusion and density-regulated growth. Integrating equilibrium abundances over the study area in our application enabled us to infer the overall carrying capacity of sea otters in Glacier Bay, Alaska.
Included in
Environmental Education Commons, Environmental Policy Commons, Environmental Studies Commons, Fire Science and Firefighting Commons, Leisure Studies Commons, Natural Resource Economics Commons, Natural Resources Management and Policy Commons, Nature and Society Relations Commons, Other Environmental Sciences Commons, Physical and Environmental Geography Commons, Public Administration Commons, Recreation, Parks and Tourism Administration Commons
Comments
U.S. Government Works are not subject to copyright.