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Unravelling drivers of local adaptation through Evolutionary Functional-Structural Plant modelling

View ORCID ProfileJorad de Vries, View ORCID ProfileSimone Fior, Aksel Pålsson, View ORCID ProfileAlex Widmer, View ORCID ProfileJake M. Alexander
doi: https://doi.org/10.1101/2022.09.02.506361
Jorad de Vries
1ETH Zürich, Institute for Integrative Biology, Zürich, Switzerland
2Wageningen University, Department Environmental Sciences, Wageningen, The Netherlands
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  • For correspondence: jorad.devries@wur.nl
Simone Fior
1ETH Zürich, Institute for Integrative Biology, Zürich, Switzerland
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Aksel Pålsson
1ETH Zürich, Institute for Integrative Biology, Zürich, Switzerland
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Alex Widmer
1ETH Zürich, Institute for Integrative Biology, Zürich, Switzerland
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Jake M. Alexander
1ETH Zürich, Institute for Integrative Biology, Zürich, Switzerland
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Summary

  1. Local adaptation to contrasting environmental conditions along environmental gradients is a widespread phenomenon in plant populations, yet we lack a mechanistic understanding of how individual agents of selection contribute to local adaptation.

  2. Here, we developed a novel evolutionary functional-structural plant (E-FSP) model that simulates local adaptation of virtual plants along an environmental gradient. First, we validate the model by testing if it can recreate two elevational ecotypes of Dianthus carthusianorum occurring in the Swiss Alps. Second, we use the E-FSP model to disentangle the relative contribution of abiotic (temperature) and biotic (competition and pollination) selection pressures to elevational adaptation in D. carthusianorum.

  3. The model reproduced the qualitative differences between the elevational ecotypes in two phenological (germination and flowering time) and one morphological trait (stalk height), as well as qualitative differences in four performance variables that emerge from GxE interactions (flowering time, number of stalks, rosette area and seed production). Our results suggest that elevational adaptation in D. carthusianorum is predominantly driven by the abiotic environment.

  4. Our approach shows how E-FSP models incorporating physiological, ecological and evolutionary mechanisms can be used in combination with experiments to examine hypotheses about patterns of adaptation observed in the field.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Posted September 04, 2022.
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Unravelling drivers of local adaptation through Evolutionary Functional-Structural Plant modelling
Jorad de Vries, Simone Fior, Aksel Pålsson, Alex Widmer, Jake M. Alexander
bioRxiv 2022.09.02.506361; doi: https://doi.org/10.1101/2022.09.02.506361
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Unravelling drivers of local adaptation through Evolutionary Functional-Structural Plant modelling
Jorad de Vries, Simone Fior, Aksel Pålsson, Alex Widmer, Jake M. Alexander
bioRxiv 2022.09.02.506361; doi: https://doi.org/10.1101/2022.09.02.506361

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