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08:20
A Method for Quantifying Foliage-Dwelling Arthropods
Published on: October 20, 2019
Estimating species richness in hyper-diverse large tree communities.
Hans Ter Steege1,2,3, Daniel Sabatier4, Sylvia Mota de Oliveira1
1Naturalis Biodiversity Center, Leiden, The Netherlands.
Ecology
|April 19, 2017
Summary
Nonparametric estimators are unsuitable for estimating species richness in tropical forests due to low sampling intensity. A logseries approach is more effective for species richness estimation in these environments.
Area of Science:
- Ecology
- Biodiversity Science
- Statistical Ecology
Background:
- Species richness estimation is a fundamental ecological analysis.
- Nonparametric estimators are commonly used for this purpose.
- Tropical forests present unique challenges due to high species diversity and often low sampling intensity.
Purpose of the Study:
- To evaluate the suitability of nonparametric estimators for species richness estimation in tropical forests.
- To compare the performance of nonparametric estimators with a logseries approach.
- To assess the validity of estimator assumptions against typical tropical forest sampling strategies.
Main Methods:
- Testing nonparametric estimators and a logseries approach.
- Utilizing simulated tropical forest data.
- Analyzing five empirical field data sets.
Main Results:
- Nonparametric estimators failed to meet assumptions for tropical forest sampling.
- High species richness and low sampling intensity in tropical forests challenge these estimators.
- The logseries approach demonstrated greater effectiveness and better-matched assumptions.
Conclusions:
- Nonparametric estimators are not recommended for species richness estimation in tropical forests.
- The logseries approach offers a more reliable method for estimating species richness in these ecosystems.
- Matching estimator assumptions to sampling strategies is crucial for accurate ecological analysis.
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