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Where is the optimum? Predicting the variation of selection along climatic gradients and the adaptive value of plasticity. A case study on tree phenology.

ABSTRACT: Many theoretical models predict when genetic evolution and phenotypic plasticity allow adaptation to changing environmental conditions. These models generally assume stabilizing selection around some optimal phenotype. We however often ignore how optimal phenotypes change with the environment, which limit our understanding of the adaptive value of phenotypic plasticity. Here, we propose an approach based on our knowledge of the causal relationships between climate, adaptive traits, and fitness to further these questions. This approach relies on a sensitivity analysis of the process-based model phenofit, which mathematically formalizes these causal relationships, to predict fitness landscapes and optimal budburst dates along elevation gradients in three major European tree species. Variation in the overall shape of the fitness landscape and resulting directional selection gradients were found to be mainly driven by temperature variation. The optimal budburst date was delayed with elevation, while the range of dates allowing high fitness narrowed and the maximal fitness at the optimum decreased. We also found that the plasticity of the budburst date should allow tracking the spatial variation in the optimal date, but with variable mismatch depending on the species, ranging from negligible mismatch in fir, moderate in beech, to large in oak. Phenotypic plasticity would therefore be more adaptive in fir and beech than in oak. In all species, we predicted stronger directional selection for earlier budburst date at higher elevation. The weak selection on budburst date in fir should result in the evolution of negligible genetic divergence, while beech and oak would evolve counter-gradient variation, where genetic and environmental effects are in opposite directions. Our study suggests that theoretical models should consider how whole fitness landscapes change with the environment. The approach introduced here has the potential to be developed for other traits and species to explore how populations will adapt to climate change.

SUBMITTER: Gauzere J

PROVIDER: S-EPMC7156102 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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Where is the optimum? Predicting the variation of selection along climatic gradients and the adaptive value of plasticity. A case study on tree phenology.

Gauzere Julie J Teuf Bertrand B Davi Hendrik H Chevin Luis-Miguel LM Caignard Thomas T Leys Bérangère B Delzon Sylvain S Ronce Ophélie O Chuine Isabelle I

Evolution letters 20200310 2

Many theoretical models predict when genetic evolution and phenotypic plasticity allow adaptation to changing environmental conditions. These models generally assume stabilizing selection around some optimal phenotype. We however often ignore how optimal phenotypes change with the environment, which limit our understanding of the adaptive value of phenotypic plasticity. Here, we propose an approach based on our knowledge of the causal relationships between climate, adaptive traits, and fitness t ...[more]

PMID: 32313687

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Project description:Natural ecosystems are under pressure from increasing abiotic and biotic stressors, including climate change and novel pathogens, which are putting species at risk of local extinction, and altering community structure, composition and function. Here, we aim to assess adaptive variation in growth and fungal disease resistance within a foundation tree, Corymbia calophylla to determine local adaptation, trait heritability and genetic constraints in adapting to future environments. Two experimental planting sites were established in regions of contrasting rainfall with seed families from 18 populations capturing a wide range of climate origins (~4,000 individuals at each site). Every individual was measured in 2015 and 2016 for growth (height, basal diameter) and disease resistance to a recently introduced leaf blight pathogen (Quambalaria pitereka). Narrow-sense heritability was estimated along with trait covariation. Trait variation was regressed against climate-of-origin, and multivariate models were used to develop predictive maps of growth and disease resistance. Growth and blight resistance traits differed significantly among populations, and these differences were consistent between experimental sites and sampling years. Growth and blight resistance were heritable, and comparisons between trait differentiation (Q ST) and genetic differentiation (F ST) revealed that population differences in height and blight resistance traits are due to divergent natural selection. Traits were significantly correlated with climate-of-origin, with cool and wet populations showing the highest levels of growth and blight resistance. These results provide evidence that plants have adaptive growth strategies and pathogen defence strategies. Indeed, the presence of standing genetic variation and trait heritability of growth and blight resistance provide capacity to respond to novel, external pressures. The integration of genetic variation into adaptive management strategies, such as assisted gene migration and seed sourcing, may be used to provide greater resilience for natural ecosystems to both biotic and abiotic stressors.

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Dataset Information

Where is the optimum? Predicting the variation of selection along climatic gradients and the adaptive value of plasticity. A case study on tree phenology.

Publications

Where is the optimum? Predicting the variation of selection along climatic gradients and the adaptive value of plasticity. A case study on tree phenology.

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