Consequences of ignoring dispersal variation in network models for landscape connectivity

Lauren L Sullivan, Matthew J. Michalska-Smith, Katie P. Sperry, David A. Moeller, Allison K. Shaw

Research output: Contribution to journalArticlepeer-review

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 languageEnglish (US)
Pages (from-to)944-954
Number of pages11
JournalConservation Biology
Volume35
Issue number3
DOIs
StatePublished - 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

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