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

Clinal variations in seedling traits and responses to water availability correspond to seed-source environmental gradients in a foundational dryland tree species

BACKGROUND AND AIMS

In dryland ecosystems, conifer species are threatened by more frequent and severe droughts, which can push species beyond their physiological limits. Adequate seedling establishment will be critical for future resilience to global change. We used a common garden glasshouse experiment to determine how seedling functional trait expression and plasticity varied among seed sources in response to a gradient of water availability, focusing on a foundational dryland tree species of the western USA, Pinus monophylla. We hypothesized that the expression of growth-related seedling traits would show patterns consistent with local adaptation, given clinal variation among seed source environments.

METHODS

We collected P. monophylla seeds from 23 sites distributed across rangewide gradients of aridity and seasonal moisture availability. A total of 3320 seedlings were propagated with four watering treatments representing progressively decreasing water availability. Above- and below-ground growth-related traits of first-year seedlings were measured. Trait values and trait plasticity, here representing the degree of variation among watering treatments, were modelled as a function of watering treatment and environmental conditions at the seed source locations (i.e. water availability, precipitation seasonality).

KEY RESULTS

We found that, under all treatments, seedlings from more arid climates had larger above- and below-ground biomass compared to seedlings from sites experiencing lower growing-season water limitation, even after accounting for differences in seed size. Additionally, trait plasticity in response to watering treatments was greatest for seedlings from summer-wet sites that experience periodic monsoonal rain events.

CONCLUSIONS

Our results show that P. monophylla seedlings respond to drought through plasticity in multiple traits, but variation in trait responses suggests that different populations are likely to respond uniquely to changes in local climate. Such trait diversity will probably influence the potential for future seedling recruitment in woodlands that are projected to experience extensive drought-related tree mortality.

Importance of interindividual interactions in eco-evolutionary population dynamics: The rise of demo-genetic agent-based models

The study of eco-evolutionary dynamics, that is of the intertwinning between ecological and evolutionary processes when they occur at comparable time scales, is of growing interest in the current context of global change. However, many eco-evolutionary studies overlook the role of interindividual interactions, which are hard to predict and yet central to selective values. Here, we aimed at putting forward models that simulate interindividual interactions in an eco-evolutionary framework: the demo-genetic agent-based models (DG-ABMs). Being demo-genetic, DG-ABMs consider the feedback loop between ecological and evolutionary processes. Being agent-based, DG-ABMs follow populations of interacting individuals with sets of traits that vary among the individuals. We argue that the ability of DG-ABMs to take into account the genetic heterogeneity-that affects individual decisions/traits related to local and instantaneous conditions-differentiates them from analytical models, another type of model largely used by evolutionary biologists to investigate eco-evolutionary feedback loops. Based on the review of studies employing DG-ABMs and explicitly or implicitly accounting for competitive, cooperative or reproductive interactions, we illustrate that DG-ABMs are particularly relevant for the exploration of fundamental, yet pressing, questions in evolutionary ecology across various levels of organization. By jointly modelling the effects of management practices and other eco-evolutionary processes on interindividual interactions and population dynamics, DG-ABMs are also effective prospective and decision support tools to evaluate the short- and long-term evolutionary costs and benefits of management strategies and to assess potential trade-offs. Finally, we provide a list of the recent practical advances of the ABM community that should facilitate the development of DG-ABMs.

Evolution of flowering time in a selfing annual plant: Roles of adaptation and genetic drift

Resurrection studies are a useful tool to measure how phenotypic traits have changed in populations through time. If these trait modifications correlate with the environmental changes that occurred during the time period, it suggests that the phenotypic changes could be a response to selection. Selfing, through its reduction of effective size, could challenge the ability of a population to adapt to environmental changes. Here, we used a resurrection study to test for adaptation in a selfing population of Medicago truncatula, by comparing the genetic composition and flowering times across 22 generations. We found evidence for evolution toward earlier flowering times by about two days and a peculiar genetic structure, typical of highly selfing populations, where some multilocus genotypes (MLGs) are persistent through time. We used the change in frequency of the MLGs through time as a multilocus fitness measure and built a selection gradient that suggests evolution toward earlier flowering times. Yet, a simulation model revealed that the observed change in flowering time could be explained by drift alone, provided the effective size of the population is small enough (<150). These analyses suffer from the difficulty to estimate the effective size in a highly selfing population, where effective recombination is severely reduced.

Adaptive responses to temperature and precipitation variation at the early-life stages of Pinus sylvestris

Early-stage fitness variation has been seldom evaluated at broad scales in forest tree species, despite the long tradition of studying climate-driven intraspecific genetic variation. In this study, we evaluated the role of climate in driving patterns of population differentiation at early-life stages in Pinus sylvestris and explored the fitness and growth consequences of seed transfer within the species range. We monitored seedling emergence, survival and growth over a 2-yr period in a multi-site common garden experiment which included 18 European populations and spanned 25° in latitude and 1700 m in elevation. Climate-fitness functions showed that populations exhibited higher seedling survival and growth at temperatures similar to their home environment, which is consistent with local adaptation. Northern populations experienced lower survival and growth at warmer sites, contrary to previous studies on later life stages. Seed mass was higher in populations from warmer areas and was positively associated with survival and growth at more southern sites. Finally, we did not detect a survival-growth trade-off; on the contrary, bigger seedlings exhibited higher survival probabilities under most climatic conditions. In conclusion, our results reveal that contrasting temperature regimes have played an important role in driving the divergent evolution of P. sylvestris populations at early-life stages.

Tree Mortality Risks Under Climate Change in Europe: Assessment of Silviculture Practices and Genetic Conservation Networks

General Context: Climate change can positively or negatively affect abiotic and biotic drivers of tree mortality. Process-based models integrating these climatic effects are only seldom used at species distribution scale.

Objective: The main objective of this study was to investigate the multi-causal mortality risk of five major European forest tree species across their distribution range from an ecophysiological perspective, to quantify the impact of forest management practices on this risk and to identify threats on the genetic conservation network.

Methods: We used the process-based ecophysiological model CASTANEA to simulate the mortality risk of Fagus sylvatica, Quercus petraea, Pinus sylvestris, Pinus pinaster, and Picea abies under current and future climate conditions, while considering local silviculture practices. The mortality risk was assessed by a composite risk index (CRIM) integrating the risks of carbon starvation, hydraulic failure and frost damage. We took into account extreme climatic events with the CRIMmax, computed as the maximum annual value of the CRIM.

Results: The physiological processes' contributions to CRIM differed among species: it was mainly driven by hydraulic failure for P. sylvestris and Q. petraea, by frost damage for P. abies, by carbon starvation for P. pinaster, and by a combination of hydraulic failure and frost damage for F. sylvatica. Under future climate, projections showed an increase of CRIM for P. pinaster but a decrease for P. abies, Q. petraea, and F. sylvatica, and little variation for P. sylvestris. Under the harshest future climatic scenario, forest management decreased the mean CRIM of P. sylvestris, increased it for P. abies and P. pinaster and had no major impact for the two broadleaved species. By the year 2100, 38–90% of the European network of gene conservation units are at extinction risk (CRIMmax=1), depending on the species.

Conclusions: Using a process-based ecophysiological model allowed us to disentangle the multiple drivers of tree mortality under current and future climates. Taking into account the positive effect of increased CO2 on fertilization and water use efficiency, average mortality risk may increase or decrease in the future depending on species and sites. However, under extreme climatic events, our process-based projections are as pessimistic as those obtained using bioclimatic niche models.

The within-population variability of leaf spring and autumn phenology is influenced by temperature in temperate deciduous trees

Leaf phenology is a major driver of ecosystem functioning in temperate forests and a robust indicator of climate change. Both the inter-annual and inter-population variability of leaf phenology have received much attention in the literature; in contrast, the within-population variability of leaf phenology has been far less studied. Beyond its impact on individual tree physiological processes, the within-population variability of leaf phenology can affect the estimation of the average budburst or leaf senescence dates at the population scale. Here, we monitored the progress of spring and autumn leaf phenology over 14 tree populations (9 tree species) in six European forests over the period of 2011 to 2018 (yielding 16 site-years of data for spring, 14 for autumn). We monitored 27 to 512 (with a median of 62) individuals per population. We quantified the within-population variability of leaf phenology as the standard deviation of the distribution of individual dates of budburst or leaf senescence (SD_BBi and SD_LSi, respectively). Given the natural variability of phenological dates occurring in our tree populations, we estimated from the data that a minimum sample size of 28 (resp. 23) individuals, are required to estimate SD_BBi (resp. SD_LSi) with a precision of 3 (resp. 7) days. The within-population of leaf senescence (average SD_LSi = 8.5 days) was on average two times larger than for budburst (average SD_BBi = 4.0 days). We evidenced that warmer temperature during the budburst period and a late average budburst date were associated with a lower SD_BBi, as a result of a quicker spread of budburst in tree populations, with a strong species effect. Regarding autumn phenology, we observed that later senescence and warm temperatures during the senescence period were linked with a high SD_LSi, with a strong species effect. The shares of variance explained by our models were modest suggesting that other factors likely influence the within-population variation in leaf phenology. For instance, a detailed analysis revealed that summer temperatures were negatively correlated with a lower SD_LSi.

The legacy of climate variability over the last century on populations' phenotypic variation in tree height

Phenotypic plasticity and local adaptation are the two main processes underlying trait variability. Under rapid environmental change, phenotypic plasticity, if adaptive, could increase the odds for organisms to persist. However, little is known on how environmental variation has shaped plasticity across species ranges over time. Here, we assess whether the portion of phenotypic variation of tree populations linked to the environment is related to the inter-annual climate variability of the last century and how it varies among populations across species ranges and age. To this aim, we used 372,647 individual tree height measurements of three pine species found in low elevation forests in Europe: Pinus nigra Arnold, P. pinaster Aiton and P. pinea L. Measurements were taken in a network of 38 common gardens established in Europe and North Africa with 315 populations covering the distribution range of the species. We fitted linear mixed-effect models of tree height as a function of age, population, climate and competition effects. Models allowed us to estimate tree height response curves at the population level and indexes of populations' phenotypic variation, as a proxy of phenotypic plasticity, at 4, 8 and 16 years old, and relate these indexes to the inter-annual climate variability of the last century. We found that phenotypic variation in tree height was higher in young trees than in older ones. We also found that P. pinea showed the highest phenotypic variation in tree height compared with P. pinaster and P. nigra. Finally, phenotypic variation in tree height may be partly adaptive, and differently across species, as climate variability during the last century at the origin of the populations explained between 51 and 69% of the current phenotypic variation of P. nigra and P. pinea, almost twice of the levels of P. pinaster. MAIN CONCLUSIONS: Populations' phenotypic variation in tree height is largely explained by the climate variability that the populations experienced during the last century, which we attribute to the genetic diversity among populations.

"Green pointillism": detecting the within-population variability of budburst in temperate deciduous trees with phenological cameras

Phenological cameras have been used over a decade for identifying plant phenological markers (budburst, leaf senescence) and more generally the greenness dynamics of forest canopies. The analysis is usually carried out over the full camera field of view, with no particular analysis of the variability of phenological markers among trees. Here we show that images produced by phenological cameras can be used to quantify the within-population variability of budburst (WPVbb) in temperate deciduous forests. Using seven site-years of image analyses, we report a strong correlation (r² = 0.97) between the WPVbb determined with a phenological camera and its quantification through ground observation. We show that WPVbb varies strongly (by a factor of 4) from year to year in a given population and that those variations are linked with temperature conditions during the budburst period, with colder springs associated to a higher differentiation of budburst (higher WPVbb) among trees. Deploying our approach at the continental scale, i.e., throughout phenological cameras networks, would improve the understanding of the spatial (across populations) and temporal (across years) variations of WPVbb, which have strong implications on forest functioning, tree fitness and phenological modelling.

Evolutionary genomics can improve prediction of species' responses to climate change

Global climate change (GCC) increasingly threatens biodiversity through the loss of species, and the transformation of entire ecosystems. Many species are challenged by the pace of GCC because they might not be able to respond fast enough to changing biotic and abiotic conditions. Species can respond either by shifting their range, or by persisting in their local habitat. If populations persist, they can tolerate climatic changes through phenotypic plasticity, or genetically adapt to changing conditions depending on their genetic variability and census population size to allow for de novo mutations. Otherwise, populations will experience demographic collapses and species may go extinct. Current approaches to predicting species responses to GCC begin to combine ecological and evolutionary information for species distribution modelling. Including an evolutionary dimension will substantially improve species distribution projections which have not accounted for key processes such as dispersal, adaptive genetic change, demography, or species interactions. However, eco‐evolutionary models require new data and methods for the estimation of a species' adaptive potential, which have so far only been available for a small number of model species. To represent global biodiversity, we need to devise large‐scale data collection strategies to define the ecology and evolutionary potential of a broad range of species, especially of keystone species of ecosystems. We also need standardized and replicable modelling approaches that integrate these new data to account for eco‐evolutionary processes when predicting the impact of GCC on species' survival. Here, we discuss different genomic approaches that can be used to investigate and predict species responses to GCC. This can serve as guidance for researchers looking for the appropriate experimental setup for their particular system. We furthermore highlight future directions for moving forward in the field and allocating available resources more effectively, to implement mitigation measures before species go extinct and ecosystems lose important functions.

Towards a New Generation of Trait-Flexible Vegetation Models

Plant trait variability, emerging from eco-evolutionary dynamics that range from alleles to macroecological scales, is one of the most elusive, but possibly most consequential, aspects of biodiversity. Plasticity, epigenetics, and genetic diversity are major determinants of how plants will respond to climate change, yet these processes are rarely represented in current vegetation models. Here, we provide an overview of the challenges associated with understanding the causes and consequences of plant trait variability, and review current developments to include plasticity and evolutionary mechanisms in vegetation models. We also present a roadmap of research priorities to develop a next generation of vegetation models with flexible traits. Including trait variability in vegetation models is necessary to better represent biosphere responses to global change.

Genotypic variation in phenological plasticity: Reciprocal common gardens reveal adaptive responses to warmer springs but not to fall frost

Species faced with rapidly shifting environments must be able to move, adapt, or acclimate in order to survive. One mechanism to meet this challenge is phenotypic plasticity: altering phenotype in response to environmental change. Here, we investigated the magnitude, direction, and consequences of changes in two key phenology traits (fall bud set and spring bud flush) in a widespread riparian tree species, Populus fremontii. Using replicated genotypes from 16 populations from throughout the species' thermal range, and reciprocal common gardens at hot, warm, and cool sites, we identified four major findings: (a) There are significant genetic (G), environmental (E), and GxE components of variation for both traits across three common gardens; (b) The magnitude of phenotypic plasticity is correlated with provenance climate, where trees from hotter, southern populations exhibited up to four times greater plasticity compared to the northern, frost-adapted populations; (c) Phenological mismatches are correlated with higher mortality as the transfer distances between provenance and garden increase; and (d) The relationship between plasticity and survival depends not only on the magnitude and direction of environmental transfer, but also on the type of environmental stress (i.e., heat or freezing), and how particular traits have evolved in response to that stress. Trees transferred to warmer climates generally showed small to moderate shifts in an adaptive direction, a hopeful result for climate change. Trees experiencing cooler climates exhibited large, non-adaptive changes, suggesting smaller transfer distances for assisted migration. This study is especially important as it deconstructs trait responses to environmental cues that are rapidly changing (e.g., temperature and spring onset) and those that are fixed (photoperiod), and that vary across the species' range. Understanding the magnitude and adaptive nature of phenotypic plasticity of multiple traits responding to multiple environmental cues is key to guiding restoration management decisions as climate continues to change.

Can phenological models predict tree phenology accurately in the future? The unrevealed hurdle of endodormancy break

The onset of the growing season of trees has been earlier by 2.3 days per decade during the last 40 years in temperate Europe because of global warming. The effect of temperature on plant phenology is, however, not linear because temperature has a dual effect on bud development. On one hand, low temperatures are necessary to break bud endodormancy, and, on the other hand, higher temperatures are necessary to promote bud cell growth afterward. Different process-based models have been developed in the last decades to predict the date of budbreak of woody species. They predict that global warming should delay or compromise endodormancy break at the species equatorward range limits leading to a delay or even impossibility to flower or set new leaves. These models are classically parameterized with flowering or budbreak dates only, with no information on the endodormancy break date because this information is very scarce. Here, we evaluated the efficiency of a set of phenological models to accurately predict the endodormancy break dates of three fruit trees. Our results show that models calibrated solely with budbreak dates usually do not accurately predict the endodormancy break date. Providing endodormancy break date for the model parameterization results in much more accurate prediction of this latter, with, however, a higher error than that on budbreak dates. Most importantly, we show that models not calibrated with endodormancy break dates can generate large discrepancies in forecasted budbreak dates when using climate scenarios as compared to models calibrated with endodormancy break dates. This discrepancy increases with mean annual temperature and is therefore the strongest after 2050 in the southernmost regions. Our results claim for the urgent need of massive measurements of endodormancy break dates in forest and fruit trees to yield more robust projections of phenological changes in a near future.

In situ marker-based assessment of leaf trait evolutionary potential in a marginal European beech population

Evolutionary processes are expected to be crucial for the adaptation of natural populations to environmental changes. In particular, the capacity of rear edge populations to evolve in response to the species limiting conditions remains a major issue that requires to address their evolutionary potential. In situ quantitative genetic studies based on molecular markers offer the possibility to estimate evolutionary potentials manipulating neither the environment nor the individuals on which phenotypes are measured. The goal of this study was to estimate heritability and genetic correlations of a suite of leaf functional traits involved in climate adaptation for a natural population of the tree Fagus sylvatica, growing at the rear edge of the species range. Using two marker-based quantitative genetics approaches, we obtained consistent and significant estimates of heritability for leaf phenological (phenology of leaf flush), morphological (mass, area, ratio mass/area) and physiological (δ(13)C, nitrogen content) traits. Moreover, we found only one significant positive genetic correlation between leaf area and leaf mass, which likely reflected mechanical constraints. We conclude first that the studied population has considerable genetic diversity for important ecophysiological traits regarding drought adaptation and, second, that genetic correlations are not likely to impose strong genetic constraints to future population evolution. Our results bring important insights into the question of the capacity of rear edge populations to evolve.

The agony of choice: different empirical mortality models lead to sharply different future forest dynamics

Dynamic models are pivotal for projecting forest dynamics in a changing climate, from the local to the global scale. They encapsulate the processes of tree population dynamics with varying resolution. Yet, almost invariably, tree mortality is modeled based on simple, theoretical assumptions that lack a physiological and/or empirical basis. Although this has been widely criticized and a growing number of empirically derived alternatives are available, they have not been tested systematically in models of forest dynamics. We implemented an inventory-based and a tree-ring-based mortality routine in the forest gap model ForClim v3.0. We combined these routines with a stochastic and a deterministic approach for the determination of tree status (alive vs. dead). We tested the four new model versions for two Norway spruce forests in the Swiss Alps, one of which was managed (inventory time series spanning 72 years) and the other was unmanaged (41 years). Furthermore, we ran long-term simulations (-400 years) into the future under three climate scenarios to test model behavior under changing environmental conditions. The tests against inventory data showed an excellent match of simulated basal area and stem numbers at the managed site and a fair agreement at the unmanaged site for three of the four empirical mortality models, thus rendering the choice of one particular model difficult. However, long-term simulations under current climate revealed very different behavior of the mortality models in terms of simulated changes of basal area and stem numbers, both in timing and magnitude, thus indicating high sensitivity of simulated forest dynamics to assumptions on tree mortality. Our results underpin the potential of using empirical mortality routines in forest gap models. However, further tests are needed that span other climatic conditions and mixed forests. Short-term simulations to benchmark model behavior against empirical data are insufficient; long-term tests are needed that include both nonequilibrium and equilibrium conditions. Thus, there is the potential to greatly improve the robustness of future projections of forest dynamics via more reliable tree mortality submodels.