Biology subjects

Exposito-Alonso, M.

Publications and source records attributed to Exposito-Alonso, M..

At least 19 recordsLinked to original sources

bioRxiv2026

Catch me if you can: Arabidopsis thaliana lags in adaptation to contemporary climate change

Anthropogenic climate change fosters unprecedented temperature challenges, with each year breaking a temperature record. Through evolution by natural selection, species and their populations have adapted to their previously local environments. However, as the average global land temperature has increased by ~2 {degrees}C or more, natural selection on many species may not act fast enough with climate change, creating an adaptation lag. To understand potential adaptation lags to recent climate change, we conducted a meta-analysis on the largest set of single-species field transplantation experiments across climates with the broadly-distributed model plant, Arabidopsis thaliana, with a total of 1,600 germplasm and 42 field trials. We developed a Gaussian fitness model dependent on local environment and climate deviations to infer genotype-specific adaptation lag parameters. We estimate a mean thermal adaptation lag over 1.91 {degrees}C, suggesting that local populations, on average, are better adapted when transplanted to locations cooler than their home climates. While a less than 2 {degrees}C temperature mismatch appears small, its impact on fitness corresponds to a 14% cumulative burden over time, which compounds depending on the future climate emission scenario. Combining climate model projections under different scenarios, we found that by 2025, populations would have lost 30% demographic potential under a moderate emissions scenario. Our discovery of this adaptation lag shows that even this highly adaptable species has not kept pace with recent climate change.

evolutionary biology↗

bioRxiv2026

How many genes can CRISPR edit to engineer complex adaptations?

Polygenic traits require the coordinated effects of multiple genes. Such complex traits have been a long-term target of study for geneticists, but multiplex CRISPR--the editing of multiple loci in the genome via multiple guide RNAs--is in its infancy. Reviewing 106 plant studies using multiplex CRISPR, we find that the multiplexing capacity has doubled every 5.4 years. Furthermore, a systematic experiment with 8, 16, and 24 simultaneous targets in Arabidopsis thaliana reveals efficiency of up to 75% in 24-plex editing in transformed plants confirmed by sequencing. We surprisingly found that the level of multiplexing, or the number of the targets, causes lesser efficiency reductions than other uncontrolled factors such as gRNA design or natural variation across plants. In fact, mathematical modeling of the decay in editing efficiency as a function of the gRNA numbers, showed a logistic model with sustained efficiency fits the data better than decay due to Cas9 competition or random editing. We then project that editing close to 100 genes in a plant can be feasible with reasonably large plant screens. However, feasible and reliable polygenic genome engineering will need developments outside of the CRISPR editing machinery itself, including innovations in gRNA vector delivery for large cargos, and a broader conceptual shift toward population-level poly-gene editing leveraging large distributions of mutations for breeding, natural selection, or experimental evolution. Author ContributionsM.E.-A. conceived the project and secured funding. M.E.-A. and M.Es. designed the experimental strategy. M.Es. established the multiplex CRISPR and transformation pipelines in the laboratory, propagation through the T1 and T2 generations, and oversaw the first amplicon sequencing. Y.P. established the in-house iSeq amplicon sequencing protocol and contributed to cloning and genotyping pilots. M.Es supervised K.P. to construct cloning, bacterial transformations, plant growth, floral-dip transformations, and selection of T1 plants. E.K. contributed to early amplicon genotyping. J.K. propagated and sampled the T3 and J.K. and J.M. conducted the final amplicon sequencing panel. J.K. and M.E.-A. performed gene editing variant mapping, dataset quality control, and summarized results from published multiplex CRISPR studies. M.E.-A. modeled editing efficiency. J.K and M.E.-A. generated figures and wrote the first draft. All authors revised and improved the manuscript. J.K. and M.Es. contributed equally to this work and are designated as co-first authors.

plant biology↗

bioRxiv2025

Natural variation in regulatory code revealed through Bayesian analysis of plant pan-genomes and pan-transcriptomes

Understanding the genetic code of cis-regulatory elements (CREs) is essential for engineering gene expression and modulating agronomic traits in crops. In plants, CREs underlying rapid evolution of gene expression often overlap with structural variation in promoters, making them undetectable using single-reference genomes. Here, we develop K-PROB (K-mer-based in silico PROmoter Bashing), a computational tool that learns from intraspecies promoter sequence and gene expression variation in pan-genomes and pan-transcriptomes to identify CREs controlling gene expression. K-PROB deploys a k-mer-based Bayesian variable selection framework to prioritize causal variable identification. We demonstrate the effectiveness of our approach in maize and soybean, two staple crops species. Applying K-PROB to genes with the most highly variable promoter sequences and the most diverse patterns of expression, such as nucleotide-binding leucine-rich repeat receptors, we identified k-mers enriched for bona fide transcription factor binding sequences, and overlapping with open chromatin regions and DAP-seq binding sites. Notably, multiple significant k-mers are located within presence/absence structural variants, highlighting structural variation in promoters as key drivers of transcriptional diversity of highly variable genes. We further validated the regulatory effects of identified k-mers on gene expression using luciferase reporter assays. Our results showcase a high-throughput and pangenomic approach for probing natural intraspecies cis-regulatory diversity, discovering new causative cis-elements, and facilitating future expression engineering across plant species. Significance StatementUnderstanding which DNA sequences control gene expression is essential for crop improvement. Current methods for identifying regulatory elements rely on expensive, specialized biochemical datasets typically limited to a single genotype. We developed a computational tool that links natural sequence variation and gene expression variation to identify functional regulatory sequences. Our tool employs a statistical framework that prioritizes causality over correlation, in contrast to most genome-wide association studies. Applying it to maize and soybean, two staple crops, we uncovered known and novel regulatory elements and validated them with molecular assays. Our approach is scalable, cost-effective, and efficiently utilizes natural variation from existing pangenomic datasets, opening new avenues for future crop engineering and studying gene regulation in diverse plant species.

bioinformatics↗

bioRxiv2025

Simulated climate change magnifies genetic vulnerabilities from mutation load and maladaptation

As climate change intensifies, the genetic diversity and composition of natural populations will become critical for adaptation and survival. Standing genetic diversity within populations differs across a species range, due to past demographic and natural selection processes driving the accumulation of adaptive, neutral, and deleterious variation. While accumulating genomic knowledge could be used to evaluate population extinction risk from local mal-adaptive genetic makeups, testing such approaches in natural environments remains challenging. Leveraging the genomic resources of Arabidopsis thaliana, we created experimental synthetic populations of similar genetic diversity but differing genetic makeups by mixing 245 natural accessions with different levels of potentially-climate-adaptive alleles and/or genomic burden of deleterious mutations. We planted our populations in a climate change field experiment simulating a gradient of declining rainfall. By tracking survival and reproduction of 135 synthetic experimental populations over three years, we show substantial predictability of genetic makeup on survival and population growth rate. Further, the accumulation of deleterious mutations and locally (mal)adaptive alleles synergistically reduces fitness in increasingly stressful climates. Our findings underscore that for populations to have the greatest chance of surviving climate change, the optimal combination of genomic makeups is essential.

evolutionary biology↗

bioRxiv2025

marApp: An R package and web portal to calculate mutations- and genetic diversity-area relationship for conservation

International conservation policies including the Kunming-Montreal Global Biodiversity Framework now consider genetic diversity of wild species in their targets. However, scalable, theory-driven tools to assess and predict genetic diversity loss are still emerging, limiting their use in conservation planning. Analogous to the species-area relationship, recent work has shown that genetic diversity scales with area, described by the mutations-area relationship (MAR) or genetic-diversity-area relationship (GDAR), can approximate the genetic diversity loss in a species from habitat reduction. To enable application of these insights for conservation practitioners and policy makers, we present the mar R package and marApp web portal, a fast and user-friendly tool for MAR/GDAR analysis. The mar package connects genetic diversity patterns in space to ecological theory, and automates steps from reading genetic and geographic data to simulating various habitat extinction scenarios using MAR/GDAR. The mar package estimates only short-term genetic diversity, providing a lower-limit for the far greater long-term genetic losses, underscoring the need to maximize present-day habitat conservation before it becomes irreversible. As a case example, we showcase predictions of coral (Acropora sp.) genetic diversity loss from reef coverage impacts. We demonstrate the usage of marApp without requirements for prior genetics or coding experiences, and provide downloadable reports for conservation.

ecology↗

bioRxiv2025

Signals of consistent genetic diversity decline are not yet measurable in global meta-analysis

Genetic diversity within species must be conserved as the basis for evolutionary adaptive capacity. To inform new global conservation policy, Shaw et al.1 conducted a meta-analysis of temporal genetic diversity data for over 600 wild species spanning a median of 7 years, reporting significant overall diversity loss of effect size g = -0.1. My re-analysis translating this effect to percentage change finds no robust statistical support for consistent decline, with overall changes near zero--from -1% to +1% diversity change depending on the averaging method. When testing each species individually, roughly half increased and half decreased in diversity. While genetic diversity is expected to decline following population losses, evolutionary theory predicts such declines substantially lag behind population reductions, and thus should not be measurable on average at the timescales in Shaws data, except in dramatically collapsing species. However, conservation policy should not wait for consistently measurable genetic diversity loss--to avoid future lagging losses, we must protect populations now.

ecology↗

bioRxiv2025

Polygenic and monogenic adaptation drive evolutionary rescue at different magnitudes of environmental change

Understanding the genetic basis of rapid adaptation is key to predicting species evolutionary responses to environmental change. However, it is still debatable whether many small-effect mutations or a few large-effect mutations underlie rapid adaptation, and how this knowledge can predict population survival or extinction. To address this question, we performed a series of ecologically grounded forward-in-time genetic simulations to study rapid adaptation and extinction with increasing magnitudes of environmental change. These simulations were seeded with genomic variation of the plant Arabidopsis thaliana to have a realistic genomic structure, with one (monogenic) to 1,000 (polygenic) variants with varying heritabilities contributing to an environmental adaptive trait. Our results revealed two distinct scenarios of rapid adaptation and population rescue. Under small to moderate environmental shifts, high polygenic traits increased evolutionary rescue probability. Under extreme environmental shifts, high polygenic traits lead predictably to extinction, yet monogenic traits sometimes produce one-off winning adaptive genotypes. We interpret our rapid evolutionary rescue findings in terms of the fundamental theorem of natural selection, where monogenic and polygenic traits differ in how they create stable versus skewed fitness variance (Vw) and how they respond to environmental shifts. These results highlight the insights genomics gives us into the (un)predictability of species evolutionary responses to global change, with management implications for assisted adaptation conservation.

evolutionary biology↗

bioRxiv2024

Genetic diversity loss in the Anthropocene will continue long after habitat destruction ends

Genetic diversity within species is the basis for evolutionary adaptive capacity and has recently been included as a target for protection in the United Nations Global Biodiversity Framework (GBF). However, we lack large-scale mathematical frameworks to quantify how much genetic diversity has already been lost, let alone to predict future losses under 21st century conservation scenarios. To fill this gap, we developed an area-based spatio-temporal predictive framework of genetic diversity calibrated with population-scale genomic data of 29 plant and animal species. To estimate present genetic diversity loss with our framework, we used species habitat area and population sizes losses reported in the Living Planet Index, the Red List, and new GBF indicators across 13,808 species for the last 5 decades. Applying our evolutionary framework across these species, we estimate genetic diversity loss lags behind population and habitat area declines, with an estimated current 13-22% {pi} genetic diversity loss. However, we forecast future genetic diversity losses will reach 41-76% even if populations are not further contracted. These results highlight that safeguarding existing habitats is insufficient to maintain the genetic health of species and relying solely on continuous genetic monitoring underestimates lagging long term impacts. Significance statementGenetic diversity is crucial for both species adaptation and survival. Recently, it has been included as a target for protection in the United Nations Global Biodiversity Framework. However, we lack large-scale predictive methods to quantify current and future losses of genetic diversity across species. Here, we develop an area-based spatio-temporal predictive framework trained with high-quality genome-wide data from 29 plant and animal species to enable quantitative predictions of genetic biodiversity at global scales. We infer global genetic diversity losses are beyond the preliminary UN targets to protect 90% of genetic diversity of species, evolutionary models dramatic genetic losses will occur in the future even with habitat protection if populations across species are not recovered.

genomics↗

bioRxiv2024

Evolutionary adaptation under climate change: Aedes sp. demonstrates potential to adapt to warming

Climate warming is expected to shift the distributions of mosquitoes and mosquito-borne diseases, facilitating expansions at cool range edges and contractions at warm range edges. However, whether mosquito populations could maintain their warm edges through evolutionary adaptation remains unknown. Here, we investigate the potential for thermal adaptation in Aedes sierrensis, a congener of the major disease vector species that experiences large thermal gradients in its native range, by assaying tolerance to prolonged and acute heat exposure, and its genetic basis in a diverse, field-derived population. We found pervasive evidence of heritable genetic variation in acute heat tolerance, which phenotypically trades off with tolerance to prolonged heat exposure. A simple evolutionary model based on our data shows that the estimated maximum rate of evolutionary adaptation in mosquito heat tolerance typically exceeds that of projected climate warming under idealized conditions. Our findings indicate that natural mosquito populations may have the potential to track projected warming via genetic adaptation. Prior climate-based projections may thus underestimate the range of mosquito and mosquito-borne disease distributions under future climate conditions. Significance StatementGlobal change may have profound impacts on the distribution of mosquito-borne diseases, which collectively cause nearly one million deaths each year. Accurately predicting these impacts is critical for disease control preparedness, and will depend, in part, on whether mosquitoes can adapt to warming--a key open question. Using experimental and genomic data from a relative of major vector species that already experiences a wide thermal gradient, we find that natural mosquito populations have high levels of genetically-based variation in heat tolerance that could enable adaptation on pace with warming. Incorporating the potential for adaptive responses may therefore be necessary for accurate predictions of mosquito-borne disease distributions under warming, which is critical for preparing mosquito control interventions.

evolutionary biology↗

bioRxiv2024

Global coral genomic vulnerability explains recent reef losses

The dramatic decline of reef-building corals calls for a better understanding of coral adaptation to ocean warming. Here, we characterized genetic diversity of the widespread genus Acropora by building a genomic database of 595 coral samples from different oceanic regions--from the Great Barrier Reef to the Persian Gulf. Through genome-environment associations, we found that different Acropora species showed parallel evolutionary signals of heat-adaptation in the same genomic regions, pointing to genes associated with molecular heat shock responses and symbiosis. We then projected the present and the predicted future distribution of heat-adapted genotypes across reefs worldwide. Reefs projected with low frequency of heat-adapted genotypes display higher rates of Acropora decline, indicating a potential genomic vulnerability to heat exposure. Our projections also suggest a transition where heat-adapted genotypes will spread at least until 2040. However, this transition will likely involve mass mortality of entire non-adapted populations and a consequent erosion of Acropora genetic diversity. This genetic diversity loss could hinder the capacity of Acropora to adapt to the more extreme heatwaves projected beyond 2040. Genomic vulnerability and genetic diversity loss estimates can be used to reassess which coral reefs are at risk and their conservation.

evolutionary biology↗

bioRxiv2023

Conflicts in natural selection constrain adaptation to climate change in Arabidopsis thaliana

Climate change has already caused noticeable changes in species-wide traits, such as the well-documented acceleration of spring flowering. Because the evolutionary past has favored certain combinations of traits, some strategies like fast growth with early flowering that are adaptive today are at odds with other plant resilience strategies such as elevated water use efficiency. We know that the evolution of trait combinations is shaped by genomic constraints, but it is unclear whether and how this is affected by natural selection from climate change. Growing hundreds of Arabidopsis thaliana natural populations under different rainfall regimes revealed opposing natural selection on flowering time and water use efficiency, with strong antagonistic genetic correlations and contrasting causal alleles identified by Genome-Wide Association analyses. Inactivation of the central flowering regulator FLC in multiple, diverse accessions relaxed trait correlations in a genetic background-dependent manner and allowed for the emergence of a novel adaptive trait combination--early flowering and intermediate water use efficiency. Future climates are predicted to escalate conflicts in natural selection among adaptive traits, but our work shows that surprisingly simple genetic changes can help solve these conflicts.

evolutionary biology↗

bioRxiv2022

Ecological and genetic trade-offs drive Arabidopsis thaliana range expansion in Europe

How trade-offs between traits constrain adaptation to contrasted environments is critical to understand the distribution range of a given species. In Arabidopsis thaliana, genetic analyses recently revealed that a group of genotypes successfully recolonized Europe from its center after the last glaciation, outcompeting older lineages and leaving them only at the distribution margins, where environmental conditions are more stressing. However, whether trade-offs between traits related to dispersal, competition, and stress tolerance explain the success and persistence of different lineages across the species geographic range remains an open question. Here, we compared the genetic and phenotypic differentiation between 72 ecotypes originating from three geographical groups in Europe (North, South and Center). We measured key traits related to fecundity, dispersal ability, competition tolerance, and stress tolerance, and used genomic data to infer the effect of selection on these traits. We showed that a trade-off between plant fecundity and seed mass constrains the diversification of A. thaliana in Europe. In particular, the success of the cosmopolitan genotypes that recolonized Europe can be explained by their higher dispersal ability at the expense of their competitive ability and stress tolerance. Inversely, peripheral ecotypes exhibited the opposite trait syndrome: high competition and stress tolerance but low dispersal ability. Moreover, peripheral genotypes tend to differentiate from central ones at genes involved in dispersal and competitive traits such as seed mass. Combining ecological and genomic approaches, our study demonstrated the role of key ecological trade-offs as evolutionary drivers of the distribution of plant populations along a geographic gradient. SignificanceAcross geographic gradients, differential adaptive phenotypes among populations can reduce the risk of local extinctions and favor niche dynamics. However, a phenotypic advantage often comes at a cost. For instance, the competition-colonization trade-off is proposed as an important driver of plant interspecific diversity, but its role for local adaptation at the intraspecific level is still unclear. Using the broadly-distributed species Arabidopsis thaliana, we evaluate how ecological trade-offs have shaped the demography and evolution of central and peripheral populations in its native geographic gradient. Our study demonstrates that the competition-colonization trade-off is responsible of the spatially-structured phenotypic variation of A. thaliana across its geographical range. Our study highlights seed mass as a key trait for plant adaptation across environmental conditions.

ecology↗

bioRxiv2022

Century-long timelines of herbarium genomes predict plant stomatal response to climate change

Dissecting plant responses to the environment is key to understanding if and how plants adapt to anthropogenic climate change. Stomata, plants pores for gas exchange, are expected to decrease in density following increased CO2 concentrations, a trend already observed in multiple plant species. However, it is unclear if such responses are based on genetic changes and evolutionary adaptation. Here we make use of extensive knowledge of 43 genes in the stomatal development pathway and newly generated genome information of 191 A. thaliana historical herbarium specimens collected over the last 193 years to directly link genetic variation with climate change. While we find that the essential transcription factors SPCH, MUTE and FAMA, central to stomatal development, are under strong evolutionary constraints, several regulators of stomatal development show signs of local adaptation in contemporary samples from different geographic regions. We then develop a polygenic score based on known effects of gene knock-out on stomatal development that recovers a classic pattern of stomatal density decrease over the last centuries without requiring direct phenotype observation of historical samples. This approach combining historical genomics with functional experimental knowledge could allow further investigations of how different, even in historical samples unmeasurable, cellular plant phenotypes have already responded to climate change through adaptive evolution. One sentence summaryUsing a molecular-knowledge based genetic phenotype proxy, historical whole-genome A. thaliana timelines compared with contemporary data indicate a shift of stomatal density following climate-associated predictions.

plant biology↗

bioRxiv2022

An image is worth a thousand species: combining neural networks, citizen science, and remote sensing to map biodiversity

Anthropogenic habitat destruction and climate change are altering the composition of plant communities worldwide1,2. However, traditional species distribution models cannot detect rapid, local plant species changes due to their low spatial and temporal resolution3,4, and remote sensing models can only identify changes in coarse vegetation categories5,6. Here we combine open-access remote sensing imagery, citizen science observations, and deep learning to create a multi-species prediction model at high spatial and temporal resolution. We train a novel deep convolutional neural network using [~]half a million observations within California to simultaneously predict the presence of over 2,000 plant species at meter-level resolution. This model--deepbiosphere--accurately performs many key biodiversity monitoring tasks, from fine-mapping geographic distributions of individual species and communities, to detecting rapid plant community changes in space and time. Deepbiosphere shifts the paradigm for species distribution modeling, providing a roadmap for inexpensive, automatic, and scalable detection of anthropogenic impacts on species worldwide.

ecology↗

bioRxiv2022

Monitoring rapid evolution of plant populations at scale with Pool-Sequencing

The change in allele frequencies within a population over time represents a fundamental process of evolution. By monitoring allele frequencies, we can analyze the effects of natural selection and genetic drift on populations. To efficiently track time-resolved genetic change, large experimental or wild populations can be sequenced as pools of individuals sampled over time using high-throughput genome sequencing (called the Evolve & Resequence approach, E&R). Here, we present a set of experiments using hundreds of natural genotypes of the model plant Arabidopsis thaliana to showcase the power of this approach to study rapid evolution at large scale. First, we validate that sequencing DNA directly extracted from pools of flowers from multiple plants -- organs that are relatively consistent in size and easy to sample -- produces comparable results to other, more expensive state-of-the-art approaches such as sampling and sequencing of individual leaves. Sequencing pools of flowers from 25-50 individuals at [~]40X coverage recovers genome-wide frequencies in diverse populations with accuracy r > 0.95. Secondly, to enable analyses of evolutionary adaptation using E&R approaches of plants in highly replicated environments, we provide open source tools that streamline sequencing data curation and calculate various population genetic statistics two orders of magnitude faster than current software. To directly demonstrate the usefulness of our method, we conducted a two-year outdoor evolution experiment with A. thaliana to show signals of rapid evolution in multiple genomic regions. We demonstrate how these laboratory and computational Pool-seq-based methods can be scaled to study hundreds of populations across many climates.

evolutionary biology↗

bioRxiv2021

Uncovering natural variation in root system architecture and growth dynamics using a robotics-assisted phenomics platform

The plant kingdom contains a stunning array of complex morphologies easily observed above ground, but largely unexplored below-ground. Understanding the magnitude of diversity in root distribution within the soil, termed root system architecture (RSA), is fundamental to determining how this trait contributes to species adaptation in local environments. Roots are the interface between the soil environment and the shoot system and therefore play a key role in anchorage, resource uptake, and stress resilience. Previously, we presented the GLO-Roots (Growth and Luminescence Observatory for Roots) system to study the RSA of soil-grown Arabidopsis thaliana plants from germination to maturity (Rellan-Alvarez et al. 2015). In this study, we present the automation of GLO-Roots using robotics and the development of image analysis pipelines in order to examine the natural variation of RSA in Arabidopsis over time. This dataset describes the developmental dynamics of 93 accessions and reveals highly complex and polygenic RSA traits that show significant correlation with climate variables.

plant biology↗

bioRxiv2021

Haldane's cost of selection imposes a mild constraint on adaptation, with a high proportion of deaths in A. thaliana being selective

Haldanes Dilemma refers to the concern that the need for many "selective deaths" to complete a substitution (i.e. selective sweep) creates a speed limit to adaptation. However, discussion of this concern has been marked by confusion, especially with respect to the term "substitution load". Here we distinguish different historical lines of reasoning, and identify one, focused on finite reproductive excess and the proportion of deaths that are "selective" (i.e. causally contribute to adaptive allele frequency changes), that has not yet been fully addressed. We develop this into a more general theoretical model that can apply to populations with any life history, even those for which a generation or even an individual are not well defined. The actual speed of adaptive evolution is coupled to the proportion of deaths that are selective. The degree to which reproductive excess enables a high proportion of selective deaths depends on the details of when selection takes place relative to density regulation, and there is therefore no general expression for a speed limit. To make these concepts concrete, we estimate both reproductive excess, and the proportion of deaths that are selective, from a dataset measuring survival of 517 different genotypes of Arabidopsis thaliana grown in eight different environmental conditions. In this dataset, a much higher proportion of deaths contribute to adaptation, in all environmental conditions, than the 10% cap that was anticipated as substantially restricting adaptation during historical discussions of speed limits. LAY SUMMARYThe influential neutral theory of molecular evolution was predicated on theoretical arguments that adaptation is subject to a speed limit. We resolve confusions regarding historical speed limit arguments, which depend on differences in fitness, not variance (differences in fitness squared). We generalize the underlying concepts of selective deaths and reproductive excess to populations with any life cycle, even those for which an "individual" and hence generation and fitness, are poorly defined. We apply the revised theory to Arabidopsis data, demonstrating the potential for future related experiments.

evolutionary biology↗

bioRxiv2021

Into the range: a latitudinal gradient or a center-margins differentiation of ecological strategies in Arabidopsis thaliana?

Background and AimsDetermining within-species large-scale variation in phenotypic traits is central to elucidate the drivers of species ranges. Intraspecific comparisons offer the opportunity to understand how trade-offs and biogeographical history constrain adaptation to contrasted environmental conditions. Here we test whether functional traits, ecological strategies and phenotypic plasticity in response to abiotic stress vary along a latitudinal or a center-margins gradient within the native range of Arabidopsis thaliana. MethodsThe phenotypic outcomes of plant adaptation at the center and margins of its geographic range were experimentally examined in 30 accessions from southern, central and northern Europe. The variation of traits related to stress tolerance, resource use, colonization ability as well as survival and fecundity was determined in response to high temperature (34{degrees}C) or frost (- 6{degrees}C), in combination with response to water deficit. Key ResultsBoth evidence for a latitudinal and a center-margins differentiation was found. Traits related to the acquisitive/conservative strategy trade-off varied along a latitudinal gradient. Northern accessions presented a greater survival to stress than central and southern accessions. Traits related to a colonization-competition trade-off followed a center-margin differentiation. Central accessions presented a higher phenotypic plasticity and trait values associated with a higher colonization ability than northern and southern accessions which instead had a higher competition ability. ConclusionsIntraspecific phenotypic variation helps us understand how the distribution range has evolved in Arabidopsis thaliana, which is shaped both by climate and the population migratory history. We advocate to consider intraspecific trait variation in species range studies instead of species means only as classically done in macroecology.

ecology↗