Quantifying the Effects of Multiple Environmental Factors on Plant Demography: Prediction and Inference in a Multivariate World

All populations are affected simultaneously by multiple environmental factors, yet most plant demography studies examine single factors in isolation. Failing to account for multiple environmental factors can lead to inaccurate inferences and predictions. We identify four key complications associated with inference and prediction in multifactor studies: ( a ) correlations among factors, ( b ) nonadditive effects of factors on vital rates, ( c ) nonadditivity arising from the effects of factors on the sensitivity of population growth rate to vital rates, and ( d ) violations of space-for-time substitution. We review the plant population ecology literature to assess how frequently multiple environmental factors are considered and how rigorously multifactor studies address each complication. We find that most studies address only one factor, and multifactor studies address few of these challenges. We synthesize conceptual and empirical work addressing each complication and outline practical recommendations for improving inference and prediction in multivariate demographic studies.

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Publication Details

Journal
Annual Review of Ecology Evolution and Systematics
Published
2026-09-08
DOI
https://doi.org/10.1146/annurev-ecolsys-102924-052521
Primary Topic
Ecology and Vegetation Dynamics Studies
Type
article
Field-Weighted Citation Impact
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article

Quantifying the Effects of Multiple Environmental Factors on Plant Demography: Prediction and Inference in a Multivariate World

Allison M. Louthan, William F. Morris
Annual Review of Ecology Evolution and Systematics
Ecology and Vegetation Dynamics Studies
article

Quantifying the Effects of Multiple Environmental Factors on Plant Demography: Prediction and Inference in a Multivariate World

Allison M. Louthan, William F. Morris
article en

Abstract

All populations are affected simultaneously by multiple environmental factors, yet most plant demography studies examine single factors in isolation. Failing to account for multiple environmental factors can lead to inaccurate inferences and predictions. We identify four key complications associated with inference and prediction in multifactor studies: ( a ) correlations among factors, ( b ) nonadditive effects of factors on vital rates, ( c ) nonadditivity arising from the effects of factors on the sensitivity of population growth rate to vital rates, and ( d ) violations of space-for-time substitution. We review the plant population ecology literature to assess how frequently multiple environmental factors are considered and how rigorously multifactor studies address each complication. We find that most studies address only one factor, and multifactor studies address few of these challenges. We synthesize conceptual and empirical work addressing each complication and outline practical recommendations for improving inference and prediction in multivariate demographic studies.

Annual Review of Ecology Evolution and Systematics
Duke University (US), Kansas State University (US)
Openalex Percentile: Top 7%
Ecology and Vegetation Dynamics Studies
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