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Improving inferences about functional connectivity from animal translocation experiments

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Abstract

Context

Functional connectivity reflects the ease with which an organism can access different locations within its environment. Because functional connectivity can significantly influence dispersal, habitat selection, and ultimately the viability of populations, it is central to understanding and predicting biological responses to anthropogenic disturbance. Currently, no consensus exists on how to measure functional connectivity.

Objectives and methods

Species-centered approaches such as translocation experiments have recently been advocated because they enable strong inferences about functional connectivity. The use of these types of experiments is increasing rapidly, but to date there has been no synthesis of the wide range of methods available to minimize possible study design problems. Here, we review the recent literature on translocation experiments and highlight potential confounds that may lead to inappropriate conclusions from translocation studies.

Results

We report several approaches that can limit the degree to which these confounds affect inferences. We briefly describe paired and repeated-measures designs that use mixed models to address lack of spatial and temporal independence as means for coping with confounds.

Conclusions

Such approaches to the design and analyses of translocation experiments should facilitate high-quality measurements of landscape functional connectivity. We encourage investigators to continue functional connectivity research that capitalizes on the advantages of translocations while applying rigorous study designs.

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Acknowledgments

This research was supported by funding from NSF-DEB-1457837 to MGB and ASH, and NSF-DEB-1050954 to MGB and WDR. KJG thanks Baylor University for financial support. We are grateful to M. Bélisle and three anonymous reviewers for advice about the manuscript.

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Authors and Affiliations

  1. Department of Forest Ecosystems and Society, Oregon State University, Corvallis, OR, 97331, USA

    Matthew G. Betts & Adam S. Hadley

  2. Department of Biology, Baylor University, Waco, TX, 76798, USA

    Kevin J. Gutzwiller

  3. Cape Breton Highlands National Park, Ingonish, NS, B0C 1L0, Canada

    Matthew J. Smith

  4. Department of Fisheries and Wildlife, Oregon State University, Corvallis, 97331, USA

    W. Douglas Robinson

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  1. Matthew G. Betts
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  2. Kevin J. Gutzwiller
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  3. Matthew J. Smith
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  4. W. Douglas Robinson
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  5. Adam S. Hadley
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Correspondence to Matthew G. Betts.

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Betts, M.G., Gutzwiller, K.J., Smith, M.J. et al. Improving inferences about functional connectivity from animal translocation experiments. Landscape Ecol 30, 585–593 (2015). https://doi.org/10.1007/s10980-015-0156-x

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