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Simulation-based insights into community uniqueness within fragmented landscapes

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Abstract

Context

Local contribution to beta-diversity (LCBD) assesses community composition uniqueness of sites within a region. While it is useful to identify sites with exceptional species composition and, thus, prioritize conservation actions, it is unclear what determines community uniqueness in patchy habitats.

Objectives

The goal of this study was to clarify the processes underlying community uniqueness in fragmented landscapes and understand how habitat characteristics and community characteristics affect this beta-based diversity indicator.

Methods

We simulated neutral metacommunities and used a variance-based method to assess the contribution of each habitat patch to total beta-diversity, both in terms of replacement and abundance difference. Then, we analyzed the effects of patch and metacommunity characteristics on LCBD.

Results

Community uniqueness in species replacement and richness/abundance differences responded differently to community and patch features. Patch quality was the habitat attribute with the strongest effects on all community uniqueness aspects, leading to singular assemblages with high species richness and abundance of rare species. While patch connectivity promoted singular assemblages with high richness, patch size increased community uniqueness in species replacement over time, favoring assemblages with high abundances of rare species.

Conclusions

Community uniqueness in species replacement and richness/abundance differences convey different information and should be considered separately to propose adequate conservation strategies. Habitat quality emerged as a critical factor in shaping beta-diversity, suggesting that it should be a primary focus of conservation efforts. Future studies are needed to evaluate the generality of our results in different spatial and ecological contexts.

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Data availability

All input files used to simulate communities and the output files produced for each landscape replicate and investigated time-step are already in the public domain. They are available at the figshare repository https://doi.org/10.6084/m9.figshare.22581868 (Lozada et al. 2023). All the other data used in this study are provided in the Supporting Information file.

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Acknowledgements

The authors thank two anonymous reviewers for their constructive feedback and insightful comments, which greatly contributed to the improvement of this manuscript. This work was financed by the Dirección de Investigación y Desarrollo de la Universidad de La Serena (DIDULS), DIDULS regular PR192126. A.L. received a scholarship Program/ DOCTORADO BECAS CHILE/2019-21190608 from the National Agency for Research and Development (ANID). E.L.L. was supported by United States National Institute of General Medical Sciences of the National Institutes of Health grant P20GM130418. Computational resources and support from the University of Montana’s Computational Ecology Lab and Griz Shared Computing Cluster contributed to this research (NSF award numbers 2018112 & 1925267).

Funding

This work was financed by the Dirección de Investigación y Desarrollo de la Universidad de La Serena (DIDULS), DIDULS regular PR192126. A.L. received a scholarship Program/DOCTORADO BECAS CHILE/2019-21190608 from the National Agency for Research and Development (ANID). E.L.L. was supported by United States National Institute of General Medical Sciences of the National Institutes of Health grant P20GM130418. Computational resources and support from the University of Montana’s Computational Ecology Lab and Griz Shared Computing Cluster contributed to this research (NSF award numbers 2018112 & 1925267).

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Authors and Affiliations

  1. Departamento de Biología, Facultad de Ciencias, Universidad de La Serena, Av. Raúl Bitrán 1305, La Serena, Chile

    Adriana Lozada & Angéline Bertin

  2. Computational Ecology Lab, School of Public and Community Health Sciences, University of Montana, Missoula, MT, 59812, USA

    Casey C. Day & Erin L. Landguth

  3. Center for Population Health Research, School of Public and Community Health Sciences, University of Montana, Missoula, MT, 59812, USA

    Erin L. Landguth

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  1. Adriana Lozada
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  2. Casey C. Day
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  4. Angéline Bertin
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Contributions

All the authors conceived this study and participated to the model implementation. AL performed simulation modeling. AB and AL led the statistical analyses and the writing. All authors provided intellectual input and drafted the final version of the manuscript.

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Correspondence to Angéline Bertin.

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Lozada, A., Day, C.C., Landguth, E.L. et al. Simulation-based insights into community uniqueness within fragmented landscapes. Landsc Ecol 38, 2533–2546 (2023). https://doi.org/10.1007/s10980-023-01735-6

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