Measuring change in biological communities: multivariate analysis approaches for temporal datasets with low sample size

PeerJ

Gavin Lear¹  Nicola J. Day²  Bradley S. Case³  Hannah L. Buckley³ 

[1] School of Biological Sciences, University of Auckland, Auckland, New Zealand;School of Biological Sciences, Victoria University of Wellington, Wellington, New Zealand;School of Science, Auckland University of Technology, Auckland, New Zealand;

关键词: Beta diversity;    Community variation;    Biodiversity;    Compositional change;    Multivariate analysis;    Species turnover;   

DOI  :  10.7717/peerj.11096

来源: DOAJ

【 摘 要 】

Effective and robust ways to describe, quantify, analyse, and test for change in the structure of biological communities over time are essential if ecological research is to contribute substantively towards understanding and managing responses to ongoing environmental changes. Structural changes reflect population dynamics, changes in biomass and relative abundances of taxa, and colonisation and extinction events observed in samples collected through time. Most previous studies of temporal changes in the multivariate datasets that characterise biological communities are based on short time series that are not amenable to data-hungry methods such as multivariate generalised linear models. Here, we present a roadmap for the analysis of temporal change in short-time-series, multivariate, ecological datasets. We discuss appropriate methods and important considerations for using them such as sample size, assumptions, and statistical power. We illustrate these methods with four case-studies analysed using the R data analysis environment.

【 授权许可】

Unknown