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Published on: September 25, 2021
A comparative analysis of nested subset patterns of species composition.
David H Wright1, Bruce D Patterson2, Greg M Mikkelson3
1U.S. Fish and Wildlife Service, 3310 El Camino, Suite 130, Sacramento, CA 95821, USA, , , , , , US.
Nested subset structure is common in ecological communities, particularly in island archipelagos, suggesting extinction drives this pattern. Area size influences nestedness, while taxonomic and latitudinal factors show weaker effects.
Area of Science:
- Ecology
- Community Ecology
- Biogeography
Background:
- Nested subset structure describes non-random species composition where smaller communities are subsets of larger ones.
- Understanding nestedness is crucial for biodiversity conservation and ecosystem functioning.
- Previous studies have highlighted various factors influencing nestedness, but a broad comparative assessment is lacking.
Purpose of the Study:
- To conduct a broad comparative assessment of nestedness in ecological communities across diverse taxa, regions, and scales.
- To identify ecological patterns in the prevalence and strength of nested subset structure.
- To evaluate differences and biases among various nestedness metrics and methodologies.
Main Methods:
- Compiled 279 presence-absence matrices from diverse ecological studies.
- Applied a variety of metrics to measure nestedness and used null hypotheses for evaluation.
- Analyzed data from vertebrates, arthropods, mollusks, plants, and other taxa across different latitudes.
Main Results:
- Statistically significant nestedness was frequently observed, especially in landbridge archipelagos.
- Nestedness was positively correlated with the ratio of site areas, indicating area range is influential.
- Extinction was supported as a major driver of nested structure; taxonomic and latitudinal effects were weak.
Conclusions:
- Nested subset structure is a prevalent pattern in ecological communities, largely driven by extinction processes.
- Methodological choices, particularly matrix fill, can introduce biases in nestedness analyses.
- A multi-filter framework (sampling, distance, habitat, area) and community constraints explain nestedness patterns.
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