Unravelling drivers of local adaptation through evolutionary functional-structural plant modelling

Area of Science:

• Plant evolutionary biology
• Ecological modeling
• Functional-structural plant modeling

Background:

• Local adaptation to environmental gradients is common in plants.
• Mechanistic understanding of selection pressures driving adaptation is limited.

Purpose of the Study:

• Develop and validate a novel evolutionary functional-structural plant (E-FSP) model.
• Investigate the drivers of elevational adaptation in Dianthus carthusianorum.
• Quantify the relative importance of abiotic and biotic factors in adaptation.

Main Methods:

• Developed an E-FSP model to simulate plant adaptation.
• Validated the model using two elevational ecotypes of Dianthus carthusianorum.
• Disentangled abiotic (temperature) and biotic (competition, pollination) selection pressures.

Main Results:

• The E-FSP model successfully reproduced elevational ecotypes.
• Elevational adaptation in D. carthusianorum is predominantly driven by abiotic factors.
• Model captured phenological and morphological trait differences and performance variations due to gene-by-environment interactions.

Conclusions:

• E-FSP models are valuable tools for studying adaptation.
• Abiotic factors play a primary role in the elevational adaptation of D. carthusianorum.
• Combining modeling with experiments can test field-observed adaptation patterns.