Modelling the distribution of plant‐associated microbes with species distribution models

Abstract Plants interact with diverse microorganisms that play a crucial role in plant growth and development. The diversity and distribution of plant microbiota are altered by anthropogenic environmental change, leading to subsequent impacts on ecosystems. Modeling the distribution of plant‐associated microbes is critical for predicting and managing future changes in microbial function, but challenges and open questions when developing these models still remain. We present a conceptual framework for process‐oriented predictive modeling of the distribution of plant‐associated microbiota. We first describe different approaches to incorporate host plants into modeling microbial distributions, namely by including them as static variables, nesting them within microbial distribution models or incorporating them simultaneously via joint species distribution models. Additionally, we discuss issues associated with collecting and analyzing sequencing‐based microbial data, emphasizing the importance of data normalization and careful interpretation of species distribution models. We further discuss how to incorporate evolutionary history into microbial distribution modeling. Finally, we present a case study demonstrating how incorporating host information can improve the prediction of microbial distributions. Synthesis: This study provides insights for predicting future distributions of plant‐associated microbes under climate change and plant species redistribution scenarios, which can be generalized to other host‐associated microbial systems.

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Publication Details

Journal
Journal of Ecology
Published
2025-04-08
DOI
https://doi.org/10.1111/1365-2745.70035
Citations
1
Primary Topic
Plant Pathogens and Fungal Diseases
Type
article
Field-Weighted Citation Impact
1.15

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article

Modelling the distribution of plant‐associated microbes with species distribution models

Steven W. Kembel, Sarah Piché‐Choquette, Sarah Ishak, Zihui Wang et al.
1 citations
Journal of Ecology
Plant Pathogens and Fungal Diseases
1.15
article

Modelling the distribution of plant‐associated microbes with species distribution models

Steven W. Kembel, Sarah Piché‐Choquette, Sarah Ishak, Zihui Wang, Jocelyn Lauzon
article en
1 citations

Abstract

Abstract Plants interact with diverse microorganisms that play a crucial role in plant growth and development. The diversity and distribution of plant microbiota are altered by anthropogenic environmental change, leading to subsequent impacts on ecosystems. Modeling the distribution of plant‐associated microbes is critical for predicting and managing future changes in microbial function, but challenges and open questions when developing these models still remain. We present a conceptual framework for process‐oriented predictive modeling of the distribution of plant‐associated microbiota. We first describe different approaches to incorporate host plants into modeling microbial distributions, namely by including them as static variables, nesting them within microbial distribution models or incorporating them simultaneously via joint species distribution models. Additionally, we discuss issues associated with collecting and analyzing sequencing‐based microbial data, emphasizing the importance of data normalization and careful interpretation of species distribution models. We further discuss how to incorporate evolutionary history into microbial distribution modeling. Finally, we present a case study demonstrating how incorporating host information can improve the prediction of microbial distributions. Synthesis: This study provides insights for predicting future distributions of plant‐associated microbes under climate change and plant species redistribution scenarios, which can be generalized to other host‐associated microbial systems.

Journal of EcologyVol. 113(6)
University of British Columbia (CA), Université du Québec à Montréal (CA)
Natural Sciences and Engineering Research Council of Canada
Openalex Percentile: Top 26%
Plant Pathogens and Fungal Diseases
1.15
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