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.
| Original language | English |
|---|---|
| Pages (from-to) | 2533-2546 |
| Number of pages | 14 |
| Journal | Landscape Ecology |
| Volume | 38 |
| Issue number | 10 |
| DOIs | |
| State | Published - Oct 2023 |
Funding
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). 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). 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) .
| Funders | Funder number |
|---|---|
| PR192126 | |
| CHILE/2019-21190608 | |
| P20GM130418 | |
| 2018112, 1925267 | |
| Agencia Nacional de Investigación y Desarrollo |
Keywords
- Beta diversity
- CDMetaPOP
- Community uniqueness
- Fragmented landscapes
- Habitat patch characteristics
- Simulation modeling