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Comparing species assemblages via species accumulation curves
1Department of Statistics, University of California, Riverside, Riverside, California 92521, USA. cmao@stat.ucr.edu
Biometrics
|February 13, 2009
Summary
Comparing species assemblages using incidence data is challenging. New eigenvalue-adjusted chi-squared (Eva-chi(2)) and Eva-bootstrap tests offer robust statistical methods for ecological comparisons.
Area of Science:
- Ecology
- Ecological Statistics
Background:
- Comparing species assemblages with incidence data is crucial in ecology.
- Current methods rely on visual inspection or ad hoc confidence bands of species accumulation curves, which can be unreliable.
Purpose of the Study:
- To develop and evaluate robust statistical tests for comparing species assemblages based on incidence data.
- To address the challenges associated with traditional comparison methods.
Main Methods:
- A chi-squared (chi(2)) test was developed for comparing species assemblages.
- Eigenvalue decomposition was used to adjust the chi(2) test, overcoming computational issues.
- The bootstrap method was employed to approximate the distribution of the test statistic, leading to the Eva-bootstrap test.
Main Results:
- The eigenvalue adjusted (Eva) chi(2) test and the Eva-bootstrap test were assessed through simulation studies.
- Both proposed tests demonstrated effectiveness in comparing species assemblages.
Conclusions:
- The Eva-chi(2) and Eva-bootstrap tests provide statistically sound and computationally feasible approaches for comparing species assemblages.
- These methods were successfully applied to a case study involving two woody seedling species assemblages.
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