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  4. Revisiting Alwyn H. Gentry’s forest transect data: latitudinal beta diversity patterns are revealed using a statistical sampling-model-based approach
 
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Revisiting Alwyn H. Gentry’s forest transect data: latitudinal beta diversity patterns are revealed using a statistical sampling-model-based approach

Journal
Japanese Journal of Statistics and Data Science
Date Issued
2023-01-01
Author(s)
Anne Chao
CHUN-HUO CHIU  
Hu, Kai Hsiang
DAVID ZELENÝ  orcid-logo
DOI
10.1007/s42081-023-00214-1
URI
https://scholars.lib.ntu.edu.tw/handle/123456789/635427
URL
https://api.elsevier.com/content/abstract/scopus_id/85168611819
Abstract
Gentry’s forest transect data have been frequently used to assess global patterns of plant diversity and plant species compositional changes along environmental and geographical gradients. Based on the worldwide woody plant abundance records from Gentry’s 197 localities/plots (each consisting of ten 2 m × 50 m subplots/transects), we apply a recently developed sampling-model-based standardization method (iNEXT.beta3D standardization) to examine how beta diversity among subplots varies with latitude. Beta diversity quantifies the extent of among-subplot differentiation which represents the interacting effect of species abundance distribution and spatial aggregation. Here beta diversity is obtained by a multiplicative decomposition scheme based on the framework of Hill numbers of any order q ≥ 0. Under statistical sampling models, data in nearly all of the 197 localities were incomplete, i.e., there were species present in the assemblage but undetected in the data. For Gentry’s data collected along narrow transects, the dependence among sampled individuals due to spatial aggregation is generally weak. The observed beta diversity depends on the among-subplot differentiation and sampling effort/completeness, which in turn induce dependence of the observed beta diversity on alpha and gamma diversity. To control for sampling effort/completeness, the iNEXT.beta3D method standardizes both alpha and gamma diversity at the same level of sample coverage to formulate coverage-based beta diversity. The resulting standardized beta diversity provides a statistical solution to remove the dependence of beta diversity on both alpha and gamma diversities, and thus reflects the pure among-subplot differentiation. The coverage-based standardization reveals latitudinal beta diversity patterns/trends not only for richness-based, but also for abundance-sensitive beta diversity.
Subjects
Alpha diversity | Beta diversity | Extrapolation | Gamma diversity | Hill numbers | Rarefaction
Type
journal article

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