The importance of accounting for spatial heterogeneity in studies of plant competition and coexistence

Abstract Spatial environmental heterogeneity maintains species diversity in ecological communities, but it is difficult to model and its effects on individuals are often ignored in empirical studies of species coexistence. This is problematic because many studies estimate plant competition at the neighbourhood level, and modelling individual demographic responses without neighbourhood‐level environmental data could lead to biased results. We aimed to understand how and when ignoring spatial heterogeneity produces biased estimates of the strength of intraspecific and interspecific competition and, therefore, incorrect predictions about species coexistence. First, we used a spatially explicit individual‐based model (IBM), with neighbourhood competition depending on neighbour size and distance, to simulate two plant populations that coexist via differing responses to spatial heterogeneity. Next, we mimicked the action of ecologists collecting data in observational studies or short‐term experimental studies and sampled from the simulated populations. Then, we fitted demographic models for each species including parameters for the intensity of intra‐ and interspecific competition without information about spatial heterogeneity. Finally, we simulated invasions of species at low density using the IBM and estimated parameters to compute invasion growth rates (IGR). Demographic modelling with data from simulated observational studies resulted in underestimates of intraspecific competition and overestimates of interspecific competition. When we simulated invasions with the IBM and those estimated competition coefficients, the IGRs were negative or around zero and incorrectly predicted competitive exclusion. In simulated experimental studies, the estimates of competition were more accurate, but the model still incorrectly predicted competitive exclusion. Synthesis : Our study demonstrates how biases can arise in neighbourhood competition studies and highlights the importance of explicitly incorporating spatial heterogeneity into empirical coexistence studies. Failure to account for environmental heterogeneity at the level of individual plants may lead to mistaken conclusions about coexistence outcomes.

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Publication Details

Journal
Journal of Ecology
Published
2025-12-22
DOI
https://doi.org/10.1111/1365-2745.70221
Primary Topic
Ecology and Vegetation Dynamics Studies
Type
article
Field-Weighted Citation Impact
0.00

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article

The importance of accounting for spatial heterogeneity in studies of plant competition and coexistence

Robin E. Snyder, Stephen P. Ellner, Christina M. Hernandez, Giles Hooker et al.
Journal of Ecology
Ecology and Vegetation Dynamics Studies
article

The importance of accounting for spatial heterogeneity in studies of plant competition and coexistence

Robin E. Snyder, Stephen P. Ellner, Christina M. Hernandez, Giles Hooker, Annie Schiffer, Peter B. Adler
article en

Abstract

Abstract Spatial environmental heterogeneity maintains species diversity in ecological communities, but it is difficult to model and its effects on individuals are often ignored in empirical studies of species coexistence. This is problematic because many studies estimate plant competition at the neighbourhood level, and modelling individual demographic responses without neighbourhood‐level environmental data could lead to biased results. We aimed to understand how and when ignoring spatial heterogeneity produces biased estimates of the strength of intraspecific and interspecific competition and, therefore, incorrect predictions about species coexistence. First, we used a spatially explicit individual‐based model (IBM), with neighbourhood competition depending on neighbour size and distance, to simulate two plant populations that coexist via differing responses to spatial heterogeneity. Next, we mimicked the action of ecologists collecting data in observational studies or short‐term experimental studies and sampled from the simulated populations. Then, we fitted demographic models for each species including parameters for the intensity of intra‐ and interspecific competition without information about spatial heterogeneity. Finally, we simulated invasions of species at low density using the IBM and estimated parameters to compute invasion growth rates (IGR). Demographic modelling with data from simulated observational studies resulted in underestimates of intraspecific competition and overestimates of interspecific competition. When we simulated invasions with the IBM and those estimated competition coefficients, the IGRs were negative or around zero and incorrectly predicted competitive exclusion. In simulated experimental studies, the estimates of competition were more accurate, but the model still incorrectly predicted competitive exclusion. Synthesis : Our study demonstrates how biases can arise in neighbourhood competition studies and highlights the importance of explicitly incorporating spatial heterogeneity into empirical coexistence studies. Failure to account for environmental heterogeneity at the level of individual plants may lead to mistaken conclusions about coexistence outcomes.

Journal of EcologyVol. 114(1)
Utah State University (US), Cornell University (US), University of Oxford (GB), Case Western Reserve University (US), University of Pennsylvania (US)
Division of Environmental Biology
Reduced inequalities
Openalex Percentile: Top 27%
Ecology and Vegetation Dynamics Studies
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