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A framework for linking dispersal biology to connectivity across landscapes

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Abstract

Context

Dispersal typically consists of three components—departure, transience and settlement—each of which can be influenced by the landscape. A fundamental aspect of dispersal is the dispersal kernel, which describes how the likelihood of settlement varies as a function of the distance from the departure location. Dispersal concepts are often closely connected to the interpretation of landscape connectivity, yet models of landscape connectivity often do not generate dispersal kernels nor explicitly capture the three components of dispersal.

Objectives

We apply Markov chain theory for the generation of random-walk dispersal kernels that are based on the three components of dispersal to better link dispersal processes to landscape connectivity.

Methods

We extend the spatial absorbing Markov chain (SAMC) framework, which is aimed at addressing a broad range of problems in landscape connectivity, to explicitly model dispersal kernels that acknowledge each component of the dispersal process and how the landscape can alter each of these components. We provide an example with the Florida black bear (Ursus americanus floridanus), a species of conservation and management concern, where we contrast expected connectivity between key subpopulations when models do and do not consider random-walk dispersal kernels.

Results

Our extensions show how the SAMC can generate different types of random-walk kernels that include information on how the landscape alters departure, transience and settlement processes. Importantly, this framework can also readily incorporate mortality into predictions and be applied to make time-explicit predictions across landscapes. Connectivity for the Florida black bear is predicted to be much lower when acknowledging dispersal kernels and suggests that the settlement process may be more influential to connectivity predictions than landscape resistance.

Conclusion

These results provide a foundation for applying the SAMC to dispersal kernels. Not only do these extensions provide a formal linkage of connectivity to concepts in dispersal biology, but also help to bring together concepts from common connectivity models (e.g., circuit theory and least-cost resistant kernels) to facilitate predicting connectivity across landscapes.

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Data availability

Data for bear example are provided at Figshare (https://figshare.com/; DOI: https://doi.org/10.6084/m9.figshare.22776218).

Code availability

We provide the R code used to generate examples in Figures 2-3 using the samc package in the Supporting Information. Code for the black bear example is deposited at Figshare (https://figshare.com/:DOI: https://doi.org/10.6084/m9.figshare.22776218).

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Acknowledgements

This work was supported by the National Science Foundation (DEB-1655555) to RJF and the University of Florida’s Biodiversity Institute. We thank B. Peterman and two anonymous reviewers for their suggestions.

Funding

Funding was provided by National Science Foundation (Grant No. DEB-1655555).

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Authors and Affiliations

  1. Department of Wildlife Ecology and Conservation, University of Florida, 110 Newins-Ziegler Hall, PO Box 110430, Gainesville, FL, 32611-0430, USA

    Robert J. Fletcher Jr., Maria E. Iezzi & Andrew J. Marx

  2. Florida Museum of Natural History, University of Florida, Gainesville, FL, 32611-0430, USA

    Robert Guralnick

  3. Department of Geography and Emerging Pathogens Institute, University of Florida, Gainesville, FL, 32611-0430, USA

    Sadie J. Ryan

  4. School of Forest, Fisheries and Geomatics Sciences, University of Florida, Gainesville, FL, 32611-0430, USA

    Denis Valle

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  1. Robert J. Fletcher Jr.
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  4. Andrew J. Marx
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Contributions

RJF conceived the ideas and designed methodology. RJF and MI formatted and analyzed data. RJF led writing of the manuscript. All authors contributed critically to the drafts and gave final approval for publication.

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Correspondence to Robert J. Fletcher Jr..

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Fletcher, R.J., Iezzi, M.E., Guralnick, R. et al. A framework for linking dispersal biology to connectivity across landscapes. Landsc Ecol 38, 2487–2500 (2023). https://doi.org/10.1007/s10980-023-01741-8

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