Simulating local adaptation to climate of forest trees with a Physio‐Demo‐Genetics model

Sylvie Oddou‐Muratorio,Hendrik Davi

doi:10.1111/eva.12143

Sylvie Oddou‐Muratorio, Hendrik Davi

Open Access

https://doi.org/10.1111/eva.12143

Copy DOI

Abstract

One challenge of evolutionary ecology is to predict the rate and mechanisms of population adaptation to environmental variations. The variations in most life history traits are shaped both by individual genotypic and by environmental variation. Forest trees exhibit high levels of genetic diversity, large population sizes, and gene flow, and they also show a high level of plasticity for life history traits. We developed a new Physio-Demo-Genetics model (denoted PDG) coupling (i) a physiological module simulating individual tree responses to the environment; (ii) a demographic module simulating tree survival, reproduction, and pollen and seed dispersal; and (iii) a quantitative genetics module controlling the heritability of key life history traits. We used this model to investigate the plastic and genetic components of the variations in the timing of budburst (TBB) along an elevational gradient of Fagus sylvatica (the European beech). We used a repeated 5 years climatic sequence to show that five generations of natural selection were sufficient to develop nonmonotonic genetic differentiation in the TBB along the local climatic gradient but also that plastic variation among different elevations and years was higher than genetic variation. PDG complements theoretical models and provides testable predictions to understand the adaptive potential of tree populations.

Highlights

The ongoing and predicted rapid changes in temperature, precipitation and CO2 atmospheric concentration and the resulting increase in the frequency and intensity of extreme events such as droughts will have a wide range of long-term implications for natural population dynamics and ecosystem sustainability
We propose a new Physio-Demo-Genetics model (PDG) coupling the following: (1) a functional module derived from CASTANEA (Dufrêne et al, 2005) to simulate carbohydrate and water fluxes at the tree level using daily climate observations; (2) a population dynamics module to convert carbohydrate reserves into demographic rates for adult trees and to simulate ecological processes across the life cycle; and (3) a quantitative genetics module relating genotype of the quantitative trait loci (QTL) to the phenotype of one or more functional traits
Among the various traits contributing to fitness, we focused on the timing of budburst (TBB), a phenological trait that determines the length of the growing season in F

Summary

Introduction

The ongoing and predicted rapid changes in temperature, precipitation and CO2 atmospheric concentration and the resulting increase in the frequency and intensity of extreme events such as droughts will have a wide range of long-term implications for natural population dynamics and ecosystem sustainability. Within a population, these changes impose strong selective pressures, which affect demographic rates and can cause genetic evolution across generations (Hansen et al, 2012). The interplay between genetic evolution and phenotypic plasticity determines a population's ability to adjust (without migrating) to novel environmental conditions imposed by CC Investigating these mechanisms is essential for predicting eco-evolutionary dynamics and ecosystem services and for guiding conservation efforts. Another pervasive interaction involves plasticity and genetic adaptation; plasticity can be adaptive if plastic trait variation increases individual fitness (Nicotra et al., 2010), or it can be maladaptive if plasticity decreases fitness (Ghalambor et al, 2007)

Methods

Results

Discussion

Conclusion