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.

Coordination of spring vascular and organ phenology in deciduous angiosperms growing in seasonally cold climates

“…At the ecosystem level, it impacts agroecosystem processes such as productivity, water and energy exchanges (Cleland et al ., 2007) and thus feedbacks of the biosphere to the atmosphere (Richardson et al ., 2013). At the species level, phenology impacts species performance and distributions (Chuine, 2010; Gaüzère et al ., 2020) along with interspecific interactions and food webs (Renner & Zohner, 2018). At the population and individual levels, phenology mediates the impact of biotic and abiotic conditions on a plant's growth, survival and reproduction (Forrest & Miller‐Rushing, 2010).…”

Does Phenological Plasticity Help or Hinder Range Shifts Under Climate Change?

“…Several studies have used species' phenological traits to develop models of their geographic distribution, suggesting an important role for phenology in determining range limits (e.g., Chuine and Beaubien, 2001;Morin et al, 2008;Chapman et al, 2014;Duputié et al, 2015), and some of these have included variation in phenology across populations or geographic gradients (Chapman et al, 2017;Gauzere et al, 2020). Such models provide a fruitful avenue to explore the potential consequences of variation in phenological plasticity and/or genetic variation in phenology across geographic gradients.…”

Chronic selection for early reproductive phenology in an annual plant across a steep, elevational gradient of growing season length

“…Our results support two emerging trends. First, phenotypic selection analyses typically yield quadratic selection gradients that are small and not significant (Kingsolver et al 2001) even though adaptive trait differentiation among populations, which appears common in nature (Hereford 2009), is thought to occur through stabilizing selection favoring different trait optima in different habitats (Hansen 1997;Gauzere et al 2020). Second, phenotypic selection usually favors early flowering in natural plant populations whether selection is quantified along environmental gradients or not (Munguía-Rosas et al 2011;Austen et al 2017).…”

“…Apparent selection for early flowering might also arise from an asymmetry in the function relating flowering time to fitness (Weis et al 2014;Austen et al 2017), although this has almost never been tested (but see Gauzere et al 2020 for a simulation example). For instance, the penalty for flowering too late may be death or failed seed maturation, whereas the penalty for flowering too early could be a milder reduction in fitness.…”