Decomposing biodiversity data using the Latent Dirichlet Allocation model, a probabilistic multivariate statistical method

D Valle; B Baiser; C W Woodall; Robin L Chazdon

doi:10.1111/ele.12380

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Decomposing biodiversity data using the Latent Dirichlet Allocation model, a probabilistic multivariate statistical method

Journal article

Open access

Peer reviewed

Decomposing biodiversity data using the Latent Dirichlet Allocation model, a probabilistic multivariate statistical method

D Valle, B Baiser, C W Woodall and Robin L Chazdon

Ecology Letters, Vol.17(12), pp.1591-1601

2014

DOI: https://doi.org/10.1111/ele.12380

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Abstract

biodiversity data

cluster analysis

community ecology

Latent Dirichlet Allocation

multivariate statistics

text-mining

We propose a novel multivariate method to analyse biodiversity data based on the Latent Dirichlet Allocation (LDA) model. LDA, a probabilistic model, reduces assemblages to sets of distinct component communities. It produces easily interpretable results, can represent abrupt and gradual changes in composition, accommodates missing data and allows for coherent estimates of uncertainty. We illustrate our method using tree data for the eastern United States and from a tropical successional chronosequence. The model is able to detect pervasive declines in the oak community in Minnesota and Indiana, potentially due to fire suppression, increased growing season precipitation and herbivory. The chronosequence analysis is able to delineate clear successional trends in species composition, while also revealing that site-specific factors significantly impact these successional trajectories. The proposed method provides a means to decompose and track the dynamics of species assemblages along temporal and spatial gradients, including effects of global change and forest disturbances. © 2014 John Wiley & Sons Ltd/CNRS.

Details

Title: Decomposing biodiversity data using the Latent Dirichlet Allocation model, a probabilistic multivariate statistical method
Authors: D Valle (Author) - University of Florida, United States
B Baiser (Author) - University of Florida, United States
C W Woodall (Author) - United States Forest Service, United States
Robin L Chazdon (Author) - University of Connecticut, United States
Publication details: Ecology Letters, Vol.17(12), pp.1591-1601
Publisher: Wiley-Blackwell Publishing Ltd.
Date published: 2014
DOI: 10.1111/ele.12380
ISSN: 1461-023X
Copyright note: Copyright © 2014 The Authors. Ecology Letters published by John Wiley & Sons Ltd and CNRS. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Organisation Unit: Tropical Forests and People Research Centre; University of the Sunshine Coast, Queensland; Forest Research Institute
Language: English
Record Identifier: 99450541202621
Output Type: Journal article

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