Abstract
Habitat loss and fragmentation can negatively influence population persistence and biodiversity, but the effects can be mitigated if species successfully disperse between isolated habitat patches. Network models are the primary tool for quantifying landscape connectivity, yet in practice, an overly simplistic view of species dispersal is applied. These models often ignore individual variation in dispersal ability under the assumption that all individuals move the same fixed distance with equal probability. We developed a modeling approach to address this problem. We incorporated dispersal kernels into network models to determine how individual variation in dispersal alters understanding of landscape-level connectivity and implemented our approach on a fragmented grassland landscape in Minnesota. Ignoring dispersal variation consistently overestimated a population's robustness to local extinctions and underestimated its robustness to local habitat loss. Furthermore, a simplified view of dispersal underestimated the amount of habitat substructure for small populations but overestimated habitat substructure for large populations. Our results demonstrate that considering biologically realistic dispersal alters understanding of landscape connectivity in ecological theory and conservation practice.
Original language | English (US) |
---|---|
Pages (from-to) | 944-954 |
Number of pages | 11 |
Journal | Conservation Biology |
Volume | 35 |
Issue number | 3 |
DOIs | |
State | Published - Jun 2021 |
Bibliographical note
Funding Information:This work was supported by the Legislative‐Citizen Commission on Minnesota Resources (LCCMR) Environmental and Natural Resources Trust Fund (ENRTF) grant (M.L. 2016, Chp. 186, Sec. 2, Subd. 08b). We thank R. Johnson for help with GIS data layers; UMN Theory Group for topical discussions; L. Dee, D. Leach, N. Narayanan Venkatanarayanan, Z. Radford, R. Shaw, J. Sherman, T. Weiss‐Lehman, and 4 anonymous reviewers for helpful comments on the manuscript. The Minnesota Supercomputing Institute ( http://msi.umn.edu ) at University of Minnesota provided resources that contributed to the research results reported in this article.
Funding Information:
This work was supported by the Legislative-Citizen Commission on Minnesota Resources (LCCMR) Environmental and Natural Resources Trust Fund (ENRTF) grant (M.L. 2016, Chp. 186, Sec. 2, Subd. 08b). We thank R. Johnson for help with GIS data layers; UMN Theory Group for topical discussions; L. Dee, D. Leach, N. Narayanan Venkatanarayanan, Z. Radford, R. Shaw, J. Sherman, T. Weiss-Lehman, and 4 anonymous reviewers for helpful comments on the manuscript. The Minnesota Supercomputing Institute (http://msi.umn.edu) at University of Minnesota provided resources that contributed to the research results reported in this article.
Publisher Copyright:
© 2020 Society for Conservation Biology
Keywords
- fragmentación
- fragmentation
- graph theory
- grasslands
- modelos de redes
- network models
- pastizales
- population size
- redes ponderadas
- tamaño poblacional
- teoría de gráficos
- weighted networks
PubMed: MeSH publication types
- Journal Article
- Research Support, Non-U.S. Gov't