From Loci to Landscapes: The Molecular Determinants of Plant Adaptation and Migration Under Climatic Stress

Abstract

The survival of plant species in an era of rapid climatic flux depends on two fundamental strategies: migration to favorable habitats or adaptation in situ. Recent advances in evolutionary genomics have begun to unravel the complex molecular machinery that enables these responses. Based on the 2025 review by Hancock et al. in the Annual Review of Ecology, Evolution, and Systematics, along with a corpus of supporting research, this report provides a comprehensive examination of the genetic and demographic mechanisms driving plant adaptation. We explore the critical roles of standing genetic variation versus de novo mutation, the concept of mutational target size, and the genomic consequences of range expansion, such as expansion load and allele surfing. Through detailed case studies—from the model systems of Arabidopsis and Capsella to long-lived conifers and domesticated maize—we demonstrate that while convergent evolution is a recurring theme, no single molecular pathway dominates the adaptive landscape. Instead, the evolutionary trajectory of a species is shaped by a dynamic interplay between the availability of genetic variation, the architecture of specific traits, and the stochastic forces acting at the colonization front.

1. Introduction: The Sessile Imperative

In the grand theater of evolution, plants face a unique constraint: they are sessile. Unlike animals, which can migrate behaviorally to regulate their temperature or escape adverse conditions, plants are rooted in place. When the environment changes—whether through shifting precipitation regimes, rising temperatures, or altered seasonality—a plant population has limited options. It must either tolerate the change through phenotypic plasticity, evolve genetic adaptations to the new conditions, or disperse its seeds to colonize new, more favorable ranges. This biological imperative has driven the evolution of sophisticated molecular mechanisms that allow plants to sense and respond to their environments.¹

The contemporary crisis of anthropogenic climate change has accelerated the need for these responses, compressing evolutionary timescales. What might have once occurred over millennia must now happen over decades. This urgency has catalyzed a new wave of research integrating population genetics, molecular biology, and ecology to understand the "footprints" of adaptation left in plant genomes.¹ The central question guiding this inquiry is: How do plants adapt to climatic factors, and what happens to their genomes when they move?

Recent synthesis in the field, particularly the work of Hancock et al. (2025), suggests that the evolutionary and ecological dynamics of species are not isolated phenomena. Rather, they are simultaneously shaped by interactions with abiotic resources (like temperature and water) and biotic interactions within the community.² However, the ability to adapt is not infinite. It is constrained by the genetic material available—the standing genetic variation—and the "mutational target size" of the traits under selection.² Furthermore, the very act of moving (range expansion) imposes its own genetic costs, often leading to the accumulation of deleterious mutations at the leading edge of a population.⁵

This report dissects these complex dynamics. We begin by establishing the theoretical frameworks of genetic adaptation, exploring where adaptive alleles come from and how they persist. We then examine the genomic consequences of range expansion, a critical process for species tracking shifting climates. Finally, we delve into specific molecular pathways—flowering time, dormancy, and morphology—to illustrate how these theories manifest in the physical reality of plant life.

2. Theoretical Frameworks of Genetic Adaptation in Plants

To understand how a sessile organism adapts to a changing world, one must first understand the nature of the genetic variation available to it. Evolution is, at its core, a change in allele frequencies over time. But where do these alleles come from, and what determines their success?

2.1 The Origins of Adaptive Alleles: Standing Variation vs. De Novo Mutation

A fundamental debate in evolutionary biology concerns the source of the genetic variation that fuels adaptation. Does a population wait for a lucky new mutation to arise (de novo mutation), or does it utilize genetic variants that are already present in the population at low frequencies (standing genetic variation, or SGV)?

2.1.1 The Primacy of Standing Genetic Variation

Current evidence strongly suggests that rapid adaptation, particularly to climate change, relies heavily on standing genetic variation.² The logic is probabilistic and temporal. Waiting for a specific nucleotide mutation to occur de novo is a slow process, limited by the mutation rate (which is generally low). In contrast, standing variation represents a "bank" of alleles that are already present.

• Immediate Response: Because the alleles are already circulating in the population, the lag time associated with waiting for a mutation is eliminated. When the environment shifts, selection can immediately begin to increase the frequency of these pre-existing beneficial alleles.

• Tested Utility: Alleles from standing variation are often older. They may have been tested by selection in past environments or maintained in the population by balancing selection. This creates a higher probability that they are compatible with the organism's existing physiology compared to a random new mutation, which is more likely to be deleterious.⁸

• Soft Sweeps: Adaptation from SGV often results in "soft selective sweeps." Unlike a "hard sweep," where a single new mutation rises to fixation (wiping out diversity at linked sites), soft sweeps involve multiple adaptive alleles rising simultaneously. This preserves more genetic diversity in the region surrounding the selected gene, a pattern increasingly observed in plant genomic studies.⁹

A classic example of this is seen in maize domestication, where the gene Tb1 (Teosinte branched 1), which controls the plant's architecture, was selected from standing variation present in the wild ancestor, teosinte.⁷ The allele required for the single-stalked form of modern corn was already present at low frequency in the wild, waiting for the selective pressure of human cultivation to favor it.

2.1.2 The Role of De Novo Mutations

While SGV is critical for rapid response, de novo mutations are not irrelevant. They are the ultimate source of all variation. In scenarios of range expansion, where populations colonize entirely new territories with novel stressors, the role of new mutations can become surprisingly prominent.

This is particularly true in "mutational hotspots" or traits with large mutational target sizes (discussed below). Furthermore, demographic effects at the expansion front can allow new mutations—even those that might be lost to drift in a stable population—to establish and spread. This is sometimes referred to as "allele surfing" (see Section 3.2), where the wave of expansion carries a new mutation to high frequency regardless of its selective value.⁸

2.2 The Concept of Mutational Target Size

Why do some traits evolve quickly while others remain static? One of the most powerful explanatory concepts in modern evolutionary genomics is mutational target size.²

This concept defines the probability that a mutation will affect a specific trait based on the number of genomic loci (genes, regulatory elements, pathways) that underlie that trait.

• Large Mutational Target Size (Polygenic Traits): Consider a trait like drought tolerance or height. These are controlled by hundreds or thousands of genes working in concert. A mutation in any one of these hundreds of genes could potentially alter the phenotype. Therefore, the "target" for mutation is huge. This leads to a high "mutational variance," meaning the trait can evolve rapidly because there are many ways to break or tweak the system to get the desired result.¹³ In these cases, adaptation often proceeds via subtle shifts in allele frequencies across many loci (polygenic adaptation) rather than the fixation of a single major gene.¹²

• Small Mutational Target Size (Oligogenic/Mendelian Traits): Conversely, consider a trait like resistance to a specific herbicide or a specific change in enzyme specificity. This might require a precise amino acid substitution in a single protein. The mutational target is tiny—perhaps only a few nucleotides in the entire genome. Adaptation here is slower to initiate (waiting for the specific mutation) but often proceeds via "hard sweeps" of large effect once the mutation arises.¹⁶

Recent syntheses indicate that for climate adaptation, the mutational target size is a primary determinant of the evolutionary trajectory. The high mutational variance observed in life-history traits (like flowering time) is likely due to their large mutational target sizes. This structural reality explains why we see rapid evolution in these traits: the genome presents a massive surface area for selection to act upon.¹²

2.3 Polygenicity and the "Omnigenic" Reality

Modern Genome-Wide Association Studies (GWAS) have fundamentally shifted the view of adaptation from a "gene-for-trait" model to a "polygenic" or "omnigenic" model. Most traits relevant to climate adaptation—yield, biomass, stress tolerance—are highly polygenic.¹

In a polygenic framework, adaptation is not about a single hero gene saving the population. Instead, it involves the collective shift of allele frequencies across the entire genome. A study on climate adaptation might not find a single locus with a massive spike in FST (a measure of population differentiation). Instead, it might find thousands of loci shifting slightly in unison. This "transient" architecture makes detecting the genomic basis of adaptation computationally difficult, as no single locus contributes enough variance to be statistically significant on its own.¹⁵

This has profound implications for breeding and conservation. If adaptation is polygenic, transferring a single gene (via genetic engineering or backcrossing) may not be sufficient to confer climate resilience. Instead, breeders and conservationists must consider the "genetic background" or the "genomic matrix" that supports these complex traits.¹⁸

Adaptation Mode	Genetic Basis	Detection Method	Evolutionary Speed	Example
Oligogenic	Few genes of large effect	High FST outliers, QTL mapping	Rapid (if variation exists)	FRIGIDA (Flowering time)
Polygenic	Many genes of small effect	Polygenic scores, subtle frequency shifts	Continuous, incremental	Drought tolerance, Biomass
Convergent	Distinct lineages use same genes	Comparative genomics	Variable	Cold tolerance in Conifers

3. The Genomic Consequences of Range Expansion

As the climate warms, isoterms (lines of equal temperature) move poleward and upward in elevation. To stay within their thermal niches, plant populations must move with them. This process of range expansion is not merely a geographic shift; it is a potent evolutionary force that reshapes the genome.¹

3.1 Expansion Load: The Cost of Colonization

A paradox of range expansion is that success can breed genetic failure. This phenomenon is known as expansion load.¹

Imagine the leading edge of a plant population expanding into new territory. This edge is often composed of a small number of individuals—the "pioneers." Because this leading edge population is small, the force of genetic drift (random chance) becomes much stronger than natural selection.

• The Mechanism: In a large, stable population, natural selection is efficient at weeding out harmful (deleterious) mutations. However, at the expansion front, drift dominates. If a pioneer individual happens to carry a deleterious mutation, that mutation can be passed on to all its descendants simply because there are no other competitors.

• The Result: As the expansion wave moves forward, these deleterious mutations can "surf" to high frequencies (see below), accumulating in the genome. The population expands, but its mean fitness decreases due to this genetic burden.⁵

Empirical studies on plants like Campanula americana (American bellflower) have confirmed this theoretical prediction. Researchers found that populations farther from the species' glacial refugium (i.e., those that had expanded the furthest) displayed elevated heterosis (hybrid vigor) when crossed with other populations. This "rebound" in fitness upon crossing indicates that the parental populations were suffering from inbreeding depression caused by the accumulation of recessive deleterious mutations during their expansion.6

Crucially, this load is often driven by alleles of moderate to large effect. In a stationary population, a large-effect deleterious mutation would be purged immediately. At the expansion front, drift is so powerful that it can overpower selection, allowing even significantly harmful alleles to persist and spread.5

3.2 Allele Surfing: Riding the Wave

Closely related to expansion load is the phenomenon of allele surfing. This occurs when a rare allele exists at the wave front of an expanding population. As the population expands into empty space, the offspring of these edge individuals are the exclusive colonizers of the new territory.

If a rare allele—whether it is beneficial, neutral, or even harmful—happens to be present in the leading edge individuals, it can be propagated into the new territory, effectively "surfing" the wave of population growth. This can lead to the allele becoming fixed over vast geographic areas purely by chance, creating spatial patterns that mimic local adaptation but are actually just artifacts of history.¹¹

• Implications for Adaptation: Surfing can cut both ways. It can help a beneficial mutation establish itself quickly, inflating its frequency faster than selection alone would permit. However, simulations suggest that the efficiency of selection is generally reduced at the front. The "noise" of surfing often drowns out the "signal" of selection, meaning that beneficial mutations are often lost to drift, while deleterious ones surf to fixation. This contributes to the accumulation of expansion load.²³

• Genomic Footprints: Distinguishing between a "surfed" allele and a "selected" allele is a major challenge in population genomics. Both result in an allele having high frequency in a specific geographic region. Disentangling these requires explicit demographic modeling to test whether the observed pattern could have arisen by chance alone during expansion.⁵

3.3 Reproductive Assurance: The Shift to Selfing

Range expansion also exerts profound selection on plant mating systems. This is encapsulated in Baker's Law (or Baker's Rule), which posits that colonization is easier for self-compatible organisms.

• The Logic: If a single seed lands in a new, uncolonized territory, it has no mates. If it is an obligate outcrosser (requiring pollen from another individual), it is evolutionarily dead. If it is self-compatible (capable of pollinating itself), it can establish a new population single-handedly.

• The Evidence: Recent studies confirm that range expansion selects for reproductive assurance mechanisms, primarily autonomous self-pollination. In marginal populations where mates or pollinators are scarce, the ability to self-fertilize is favored despite the long-term genetic costs of inbreeding (inbreeding depression).²

For example, in Campanula americana, the ability to self-fertilize was found to be strongly positively correlated with the distance from the glacial refugium. This suggests that as the species expanded post-Ice Age, selection favored individuals that could self-fertilize, ensuring reproduction at the lonely wave front.6

However, this transition creates an evolutionary trade-off. While selfing ensures survival in the short term (reproductive assurance), it can lead to an evolutionary "dead end" in the long term. Selfing lineages have reduced effective recombination rates and lower genetic diversity, which limits their ability to adapt to future environmental changes.24

4. Key Molecular Pathways in Climate Adaptation

While the theoretical frameworks of expansion load and polygenicity provide the rules of the game, specific genes and pathways act as the pieces on the board. The literature identifies several recurring molecular players that serve as the "knobs" evolution turns to adjust plant physiology to new climates.

4.1 Flowering Time: The Master Switch

In seasonal environments, timing is everything. A plant must flower early enough to set seed before winter (or the dry season) arrives, but late enough to maximize vegetative growth and resource accumulation. Consequently, genes regulating phenology (flowering time) show some of the strongest signatures of adaptation to climate.²

4.1.1 FRIGIDA and Latitudinal Clines in Arabidopsis

In the model plant Arabidopsis thaliana, the gene FRIGIDA (FRI) acts as a major brake on flowering. Functional FRI alleles impose a vernalization requirement—the plant essentially "waits" for the prolonged cold of winter to pass before it transitions to flowering. This prevents the fatal mistake of flowering in autumn.

Research has documented a distinct latitudinal cline in FRI function. In northern Europe, functional FRI alleles are common, enforcing a winter-annual life cycle. As one moves south, loss-of-function mutations in FRI become more common, allowing plants to flower rapidly without vernalization (a summer-annual strategy).

However, the story is more complex than a simple "North = Late, South = Early" dichotomy. Recent studies have found that in southern latitudes, putatively functional FRI alleles are sometimes associated with accelerated flowering relative to nonfunctional alleles under specific winter conditions.²⁶ This counter-intuitive finding suggests that FRI interacts with other environmental cues (like photoperiod) in a non-linear way. The maintenance of both functional and non-functional FRI alleles within populations allows the species to bet-hedge, maintaining diverse life-history strategies to cope with unpredictable seasonal lengths.²⁶

4.1.2 Parallel Evolution in Capsella rubella

The predictability of evolution is highlighted by comparing Arabidopsis with its close relative, Capsella rubella. In C. rubella, variation in flowering time is also controlled by the FLC locus (the gene regulated by FRI).

Researchers identified two overlapping deletions in the 5' untranslated region (UTR) of the C. rubella FLC gene. These cis-regulatory mutations reduce FLC expression, releasing the brake on flowering and promoting an early-flowering phenotype.28

Crucially, these variants arose independently and spread to intermediate frequencies in natural populations. This is a classic example of parallel evolution. Even though Arabidopsis and Capsella separated millions of years ago, they both target the same genetic pathway (FRI/FLC)—and often the same specific regulatory regions—to adapt to climatic pressures. This suggests that while adaptation can be polygenic, certain "genetic hotspots" with large phenotypic effects are repeatedly targeted by selection because they offer the most direct route to the desired phenotype.28

4.2 Seed Dormancy and Temperature Sensing: DOG1

If flowering is the exit strategy from the vegetative state, germination is the entry strategy. Germinating at the wrong time (e.g., during a mid-winter warm spell) is fatal. The gene DELAY OF GERMINATION 1 (DOG1) has emerged as the central regulator of this decision.

• The Mechanism: DOG1 acts as a thermal history sensor. The level of DOG1 protein accumulated in the seed is determined by the temperatures experienced by the mother plant during seed maturation. Low maturation temperatures (indicating a coming winter) induce high DOG1 levels, which impose deep dormancy. High temperatures induce lower levels, allowing easier germination.³¹

• The Pathway: Molecularly, DOG1 influences the Gibberellin (GA) hormone pathway. It alters the expression of genes required for the biomechanical weakening of the seed coat (the endosperm cap). High DOG1 levels prevent this weakening, keeping the seed sealed and dormant. This mechanism effectively sets a "thermal window" for germination, ensuring seeds only wake up when the probability of seedling survival is high.³¹

• Geographic Adaptation: Surveys of Arabidopsis accessions reveal that DOG1 haplotypes (variant forms) diverge according to the ancestral climate regimes of the populations. This geographic signature confirms that DOG1 is a key locus for local adaptation to thermal environments.³³ Furthermore, DOG1 has been implicated in drought tolerance in mature plants, suggesting it has pleiotropic effects (one gene affecting multiple traits). This pleiotropy creates a "genetic correlation" where selection for drought tolerance might inadvertently alter germination timing, further constraining evolutionary trajectories.³⁴

4.3 Morphological Adaptation: The SPL9 Pathway

While phenology is a temporal adaptation, plants also adapt morphologically—changing their shape to suit the environment. In Cardamine hirsuta (hairy bittercress), colonization of the Azores islands led to the evolution of a distinct "Azorean morphotype" adapted to the local climate.

Genetic mapping identified a Quantitative Trait Locus (QTL) responsible for this change, centered on the SPL9 transcription factor. SPL9 is part of a family of genes that regulate "heterochrony"—the timing of developmental events.35

The SPL9 allele associated with the Azorean morphotype modulates shoot development, likely allowing the plant to thrive in the specific year-round growing conditions of the islands, which are punctuated by dry summer spells. This locus shows strong statistical evidence of a "selective sweep," indicating that it was positively selected during the colonization of the islands.36 This case study illustrates that transcription factors, which sit at the top of gene regulatory networks, are prime targets for morphological adaptation because a single change in their sequence can cascade down to alter complex developmental programs.

5. Convergent Evolution: From Weeds to Trees

Convergent evolution—the independent evolution of similar traits in different lineages—provides some of the strongest evidence for the power of natural selection. If two distantly related species face the same problem and solve it with the same gene, it suggests that there are limited genetic solutions to that specific problem.

5.1 Convergent Adaptation in Conifers

Conifers such as White Spruce (Picea glauca) and Lodgepole Pine (Pinus contorta) are separated by millions of years of evolution, yet they inhabit similar boreal environments and face similar challenges: extreme cold and short growing seasons.

Comparative genomic studies have identified a suite of approximately 47 genes that show associations with temperature variables in both species.³⁷ These genes are not random; they cluster in functional categories related to freezing tolerance and abiotic stress response. This "reuse" of genetic modules suggests that for complex physiological traits like cold hardiness, the "genetic toolkit" is conserved. Evolution does not reinvent the wheel; it recruits the same set of highly conserved stress-response genes to build cold tolerance in pine trees and spruce trees alike.³⁷

5.2 Maize and Teosinte: Domestication as Climate Adaptation

Domestication is effectively a rapid, human-mediated range expansion and adaptation event. The history of maize (Zea mays) and its wild ancestor teosinte offers a high-resolution view of how demography shapes selection.

Maize underwent a severe population bottleneck during domestication, reducing its effective population size to approximately 5% of that of teosinte.³⁹ This demographic crash had profound genomic consequences.

• Linked Selection: The bottleneck altered the landscape of "linked selection." In maize, the efficiency of purifying selection dropped, leading to the accumulation of deleterious alleles (similar to expansion load).

• Adaptive Introgression: However, maize didn't just lose diversity; it also gained it back. Studies show evidence of adaptive introgression from wild teosinte populations. Maize growing in highland regions (which are colder than the tropical lowlands of its origin) "borrowed" genes from highland teosinte populations to adapt to the cold.⁴⁰

• Convergent Highland Adaptation: Interestingly, adaptation to highland climates in maize and teosinte often involves independent mutations in the same pathways, another example of convergence. However, the Tb1 gene—the master regulator that turned the bushy teosinte into the single-stalked maize—is a classic example of adaptation from standing genetic variation. The allele was present in the wild, but rare; human selection pulled it to fixation.⁷

6. Challenges in Analyzing Adaptation

The comprehensive analysis by Hancock et al. (2025) and related works identifies several challenges that complicate our understanding of climate adaptation.

6.1 The "Missing Heritability" of Adaptation

Because many climate-adaptive traits are polygenic and involve transient allele frequency changes, standard tests for selection often fail. Methods designed to detect "hard sweeps" (where one allele is fixed) will miss the subtle, coordinated shifts of "soft sweeps" or polygenic adaptation. This leads to a situation where we know a trait is adaptive and heritable, but we cannot pinpoint the specific loci responsible using standard genomic scans.¹⁵

6.2 The Confounding Role of History

As discussed regarding expansion load and allele surfing, not all genomic differentiation is adaptive. A high FST at a locus might indicate local adaptation, or it might simply be an allele that "surfed" to high frequency during a past range expansion.

• Differentiation vs. Adaptation: If a population expands from South to North, allele frequencies will drift along that gradient. If the temperature also changes from South to North, the allele frequency will correlate with temperature. Is the allele adapted to temperature, or is it just drifting? Distinguishing between these two scenarios requires explicit demographic modeling, which is computationally demanding and requires robust historical data.⁵

6.3 Interactions Between Stressors

Plants rarely face a single stressor. Climate change brings heat, drought, and altered biotic interactions (pathogens, herbivores) simultaneously. The genetic architecture of adaptation to these combined stressors is likely complex.

For instance, we know DOG1 affects both germination and drought tolerance.34 If the climate shifts to be both hotter (selecting for one DOG1 allele) and drier (selecting for perhaps a different function), the gene may experience conflicting selection pressures. These "genetic correlations" can constrain the speed of adaptation, as the plant cannot optimize one trait without compromising another.42

7. Conclusions and Future Directions

The molecular basis of adaptation to climatic factors is a multi-faceted process that defies simple categorization. The 2025 review by Hancock et al., supported by a wealth of satellite studies, establishes that there is no single "climate adaptation gene." Instead, adaptation is an emergent property of the genome interacting with population history.

Key Takeaways for the Field:

1. Demography is Destiny: One cannot understand the genetics of adaptation without understanding the history of the population. Range expansions create genomic patterns (load, surfing) that can mimic or mask true signatures of selection. Future studies must integrate demographic modeling as a standard practice.

2. Architecture Varies by Trait: There is no "one size fits all" for genetic architecture. Discrete traits with small mutational target sizes (like the vernalization requirement via FRI) may evolve via large-effect mutations and parallel evolution. Complex quantitative traits (like drought tolerance or biomass) likely evolve via polygenic shifts and soft sweeps.

3. Standing Variation is the Primary Fuel: Rapid response to climate change depends heavily on the genetic variation already present in the "bank." This highlights the critical conservation value of maintaining genetically diverse populations, even if they are not currently "elite" or dominant. The loss of wild relatives (like teosinte for maize) represents a permanent loss of adaptive potential.

4. Reproductive Systems are Fluid: The stress of colonization drives shifts in mating systems (e.g., toward selfing), which in turn alters the evolutionary potential of the lineage. Understanding these shifts is crucial for predicting the long-term viability of range-expanding species.

Future Outlook:

Research must move beyond simple "gene hunting." The field requires a synthesis of ecological validation—proving that a specific allele actually confers a fitness advantage in the field, not just in a greenhouse—and functional genomics to understand the molecular mechanisms in detail.

We need to understand not just which genes change, but how they interact within the "omnigenic" networks to produce a phenotype. Furthermore, as climate change accelerates, understanding the "ecological drivers that shape diversification at local scales" remains a priority.1 The race is on to determine which species possess the genomic architecture to adapt, and which are burdened by expansion load or lack of variation. In this race, the molecular details—the target sizes, the standing variation, and the regulatory pathways—will determine the winners and losers of the Anthropocene.

Summary of Key Genetic Drivers Discussed

Gene/Locus	Species	Function	Adaptive Significance	Mechanism
FRIGIDA (FRI)	Arabidopsis	Flowering Repressor	Adaptation to latitude/season length	Loss-of-function variants remove vernalization requirement.
FLC	Arabidopsis / Capsella	Flowering Repressor	Parallel evolution of early flowering	cis-regulatory deletions reduce expression.
DOG1	Arabidopsis	Dormancy / Germination	Temperature sensing / Germination timing	Alters GA metabolism; haplotypes correlate with climate.
SPL9	Cardamine	Developmental Timing	Morphological adaptation (Azorean form)	Positive selection on a QTL affecting shoot shape.
Tb1	Zea mays (Maize)	Branching Architecture	Domestication / Stand density	Selection on standing variation from Teosinte.
Various	Conifers (Picea/Pinus)	Cold Hardiness	Convergent local adaptation	Recruitment of shared stress-response gene families.

References referenced in this report are identified by snippet IDs:.¹

Works cited

1. The Molecular Basis of Adaptation to Climatic Factors and Range Change in Plants, accessed January 12, 2026, https://www.annualreviews.org/content/journals/10.1146/annurev-ecolsys-102723-053810

2. Annual Review of Ecology, Evolution, and Systematics, accessed January 12, 2026, https://www.annualreviews.org/content/journals/ecolsys/browse?pageSize=50&page=1

3. The Molecular Basis of Adaptation to Climatic Factors and Range Change in Plants | Request PDF - ResearchGate, accessed January 12, 2026, https://www.researchgate.net/publication/395316205_The_Molecular_Basis_of_Adaptation_to_Climatic_Factors_and_Range_Change_in_Plants

4. accessed January 12, 2026, https://www.researchgate.net/publication/395316205_The_Molecular_Basis_of_Adaptation_to_Climatic_Factors_and_Range_Change_in_Plants#:~:text=The%20crucial%20factors%20that%20determine,processes%20that%20promote%20adaptive%20changes.

5. Local Adaptation Interacts with Expansion Load during Range Expansion: Maladaptation Reduces Expansion Load | The American Naturalist: Vol 189, No 4, accessed January 12, 2026, https://www.journals.uchicago.edu/doi/full/10.1086/690673

6. Selfing ability and drift load evolve with range expansion - PMC - PubMed Central, accessed January 12, 2026, https://pmc.ncbi.nlm.nih.gov/articles/PMC6791181/

7. Standing variation and new mutations both contribute to a fast response to selection for flowering time in maize inbreds - PMC - PubMed Central, accessed January 12, 2026, https://pmc.ncbi.nlm.nih.gov/articles/PMC2837650/

8. Revisiting the Role of Genetic Variation in Adaptation* | The American Naturalist, accessed January 12, 2026, https://www.journals.uchicago.edu/doi/full/10.1086%2F726012

9. Elevated temperature increases genome-wide selection on de novo mutations | Proceedings B | The Royal Society, accessed January 12, 2026, https://royalsocietypublishing.org/rspb/article/288/1944/20203094/86007/Elevated-temperature-increases-genome-wide

10. Genetics of adaptation - PNAS, accessed January 12, 2026, https://www.pnas.org/doi/10.1073/pnas.2122152119

11. Allele Surfing Promotes Microbial Adaptation from Standing Variation - PMC - NIH, accessed January 12, 2026, https://pmc.ncbi.nlm.nih.gov/articles/PMC4942372/

12. Longitudinal sequencing reveals polygenic and epistatic nature of genomic response to selection | PNAS, accessed January 12, 2026, https://www.pnas.org/doi/10.1073/pnas.2410452122

13. A broad mutational target explains a fast rate of phenotypic evolution | eLife, accessed January 12, 2026, https://elifesciences.org/articles/54928

14. A broad mutational target explains a fast rate of phenotypic evolution - PubMed Central, accessed January 12, 2026, https://pmc.ncbi.nlm.nih.gov/articles/PMC7556874/

15. Mutation potentiates migration swamping in polygenic local adaptation - Oxford Academic, accessed January 12, 2026, https://academic.oup.com/genetics/article/228/4/iyae165/7819852

16. Factors influencing the effect size distribution of adaptive substitutions - PMC, accessed January 12, 2026, https://pmc.ncbi.nlm.nih.gov/articles/PMC4843649/

17. Mutation bias and the predictability of evolution - Royal Society Publishing, accessed January 12, 2026, https://royalsocietypublishing.org/rstb/article/378/1877/20220055/109146/Mutation-bias-and-the-predictability-of

18. Environmental genomic selection to leverage polygenic local adaptation in barley landraces - PMC - PubMed Central, accessed January 12, 2026, https://pmc.ncbi.nlm.nih.gov/articles/PMC12003830/

19. Local Adaptation by Alleles of Small Effect* | The American Naturalist: Vol 186, No S1, accessed January 12, 2026, https://www.journals.uchicago.edu/doi/10.1086/682405

20. Modern Strategies to Assess and Breed Forest Tree Adaptation to Changing Climate - Frontiers, accessed January 12, 2026, https://www.frontiersin.org/journals/plant-science/articles/10.3389/fpls.2020.583323/full

21. Genomic signatures of adaptation along an expansion route in the colonizing plant Leontodon longirostris (Asteraceae) | Journal of Evolutionary Biology | Oxford Academic, accessed January 12, 2026, https://academic.oup.com/jeb/advance-article/doi/10.1093/jeb/voaf133/8320539?searchresult=1

22. Allele Surfing Promotes Microbial Adaptation from Standing Variation - bioRxiv, accessed January 12, 2026, https://www.biorxiv.org/content/10.1101/049353v1.full.pdf

23. Allele surfing causes maladaptation in a Pacific salmon of conservation concern | PLOS Genetics - Research journals, accessed January 12, 2026, https://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1010918

24. Evolutionary consequences of self-fertilization in plants | Proceedings B - The Royal Society, accessed January 12, 2026, https://royalsocietypublishing.org/rspb/article/280/1760/20130133/74630/Evolutionary-consequences-of-self-fertilization-in

25. Range expansions of sexual versus asexual organisms: Effects of reproductive assurance and migration load | Journal of Evolutionary Biology | Oxford Academic, accessed January 12, 2026, https://academic.oup.com/jeb/article/36/4/698/7326124

26. A latitudinal cline in flowering time in Arabidopsis thaliana modulated by the flowering time gene FRIGIDA | PNAS, accessed January 12, 2026, https://www.pnas.org/doi/10.1073/pnas.0306401101

27. A latitudinal cline in flowering time in Arabidopsis thaliana modulated by the flowering time gene FRIGIDA - PubMed, accessed January 12, 2026, https://pubmed.ncbi.nlm.nih.gov/15070783/

28. Parallel evolution of common allelic variants confers flowering diversity in Capsella rubella, accessed January 12, 2026, https://research.monash.edu/en/publications/parallel-evolution-of-common-allelic-variants-confers-flowering-d

29. Parallel Evolution of Common Allelic Variants Confers Flowering Diversity in Capsella rubella | The Plant Cell | Oxford Academic, accessed January 12, 2026, https://academic.oup.com/plcell/article/30/6/1322/6099237

30. Parallel Evolution of Common Allelic Variants Confers Flowering Diversity in Capsella rubella - PubMed, accessed January 12, 2026, https://pubmed.ncbi.nlm.nih.gov/29764984/

31. DELAY OF GERMINATION 1 mediates a conserved coat-dormancy mechanism for the temperature- and gibberellin-dependent control of seed germination | PNAS, accessed January 12, 2026, https://www.pnas.org/doi/10.1073/pnas.1403851111

32. Delay of Germination-1 (DOG1): A Key to Understanding Seed Dormancy - PMC - NIH, accessed January 12, 2026, https://pmc.ncbi.nlm.nih.gov/articles/PMC7238029/

33. Functional variants of DOG1 control seed chilling responses and variation in seasonal life-history strategies in Arabidopsis thaliana - PubMed Central, accessed January 12, 2026, https://pmc.ncbi.nlm.nih.gov/articles/PMC7007534/

34. Regulation of Seed Dormancy and Germination Mechanisms in a Changing Environment, accessed January 12, 2026, https://www.mdpi.com/1422-0067/22/3/1357

35. Pan-European study of genotypes and phenotypes in the Arabidopsis relative Cardamine hirsuta reveals how adaptation, demography, and development shape diversity patterns | PLOS Biology, accessed January 12, 2026, https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.3002191

36. Pan-European study of genotypes and phenotypes in the Arabidopsis relative Cardamine hirsuta reveals how adaptation, demography, and development shape diversity patterns - PubMed Central, accessed January 12, 2026, https://pmc.ncbi.nlm.nih.gov/articles/PMC10353826/

37. Convergent local adaptation to climate in distantly related conifers - ResearchGate, accessed January 12, 2026, https://www.researchgate.net/publication/308577022_Convergent_local_adaptation_to_climate_in_distantly_related_conifers

38. Modularity of genes involved in local adaptation to climate despite physical linkage - NIH, accessed January 12, 2026, https://pmc.ncbi.nlm.nih.gov/articles/PMC6173883/

39. Recent demography drives changes in linked selection across the maize genome | bioRxiv, accessed January 12, 2026, https://www.biorxiv.org/content/10.1101/031666v2.full-text

40. The interplay of demography and selection during maize domestication and expansion - PMC - PubMed Central, accessed January 12, 2026, https://pmc.ncbi.nlm.nih.gov/articles/PMC5683586/

41. Not so local: the population genetics of convergent adaptation in maize and teosinte - eLife, accessed January 12, 2026, https://elifesciences.org/reviewed-preprints/92405

42. Genome-wide shifts in climate-related variation underpin responses to selective breeding in a widespread conifer | PNAS, accessed January 12, 2026, https://www.pnas.org/doi/10.1073/pnas.2016900118

43. Pan-European study of genotypes and phenotypes in the Arabidopsis relative Cardamine hirsuta reveals how adaptation, demography, and development shape diversity patterns - PubMed, accessed January 12, 2026, https://pubmed.ncbi.nlm.nih.gov/37463141/