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

ABSTRACT: 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.

SUBMITTER: Buckley HL

PROVIDER: S-EPMC8038644 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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

Buckley Hannah L HL Day Nicola J NJ Case Bradley S BS Lear Gavin G

PeerJ 20210408

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 chang ...[more]

PMID: 33889442

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Project description:The diversity in organismal responses to environmental changes (i.e., response diversity) plays a crucial role in shaping community and ecosystem stability. However, existing measures of response diversity only consider a single environmental variable, whereas natural communities are commonly exposed to changes in multiple environmental variables simultaneously. Thus far, no approach exists to integrate multifarious environmental change and the measurement of response diversity. Here, we show how to consider and quantify response diversity in the context of multifarious environmental change, and in doing so introduce a distinction between response diversity to a defined or anticipated environmental change, and the response capacity to any possible set of (defined or undefined) future environmental changes. First, we describe and illustrate the concepts with empirical data. We reveal the role of the trajectory of environmental change in shaping response diversity when multiple environmental variables fluctuate over time. We show that, when the trajectory of the environmental change is undefined (i.e., there is no information or a priori expectation about how an environmental condition will change in future), we can quantify the response capacity of a community to any possible environmental change scenario. That is, we can estimate the capacity of a system to respond under a range of realistic or extreme environmental changes, with utility for predicting future responses to even multifarious environmental change. Finally, we investigate determinants of response diversity within a multifarious environmental change context. We identify factors such as the diversity of species responses to each environmental variable, the relative influence of different environmental variables and temporal means of environmental variable values as important determinants of response diversity. In doing so, we take an important step towards measuring and understanding the insurance capacity of ecological communities exposed to multifarious environmental change.

Dataset Information

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

Publications

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

Similar Datasets

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