RT Journal Article
SR Electronic
T1 Unravelling drivers of local adaptation through Evolutionary Functional-Structural Plant modelling
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2022.09.02.506361
DO 10.1101/2022.09.02.506361
A1 Jorad de Vries
A1 Simone Fior
A1 Aksel Pålsson
A1 Alex Widmer
A1 Jake M. Alexander
YR 2022
UL http://biorxiv.org/content/early/2022/09/04/2022.09.02.506361.abstract
AB 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.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.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.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 StatementThe authors have declared no competing interest.