The evolutionary genomics of species' responses to climate change

De novo genome assembly of the Edwardsiid anthozoan Edwardsia elegans

Cnidarians (sea anemones, corals, hydroids, and jellyfish) are a key outgroup for comparisons with bilateral animals to trace the evolution of genomic complexity and diversity within the animal kingdom, as they separated from most other animals 100 s of million years ago. Cnidarians have extensive diversity, yet the paucity of genomic resources limits our ability to compare genomic variation between cnidarian clades and species. Here, we report the genome for Edwardsia elegans, a sea anemone in the most specious genus of the family Edwardsiidae, a phylogenetically important family of sea anemones that contains the model anemone Nematostella vectensis. The E. elegans genome is 396 Mb in length and is predicted to encode approximately 49,000 proteins. We annotated a large conservation of macrosynteny between E. elegans and other Edwardsiidae anemones as well as conservation of both microRNAs and ultra-conserved noncoding elements previously reported in other cnidarians species. We also highlight microsyntenic variation of clustered developmental genes and ancient gene clusters that vary between species of sea anemones, despite previous research showing conservation between cnidarians and bilaterians. Overall, our analysis of the E. elegans genome highlights the importance of using multiple species to represent a taxonomic group for genomic comparisons, where genomic variation can be missed for large and diverse clades.

Evolutionarily distinct lineages of a migratory bird of prey show divergent responses to climate change

Accurately predicting species' responses to anthropogenic climate change is hampered by limited knowledge of their spatiotemporal ecological and evolutionary dynamics. We combine landscape genomics, demographic reconstructions, and species distribution models to assess the eco-evolutionary responses to past climate fluctuations and to future climate of an Afro-Palaearctic migratory raptor, the lesser kestrel (Falco naumanni). We uncover two evolutionarily and ecologically distinct lineages (European and Asian), whose demographic history, evolutionary divergence, and historical distribution range were profoundly shaped by past climatic fluctuations. Using future climate projections, we find that the Asian lineage is at higher risk of range contraction, increased migration distance, climate maladaptation, and consequently greater extinction risk than the European lineage. Our results emphasise the importance of providing historical context as a baseline for understanding species' responses to contemporary climate change, and illustrate how incorporating intraspecific genetic variation improves the ecological realism of climate change vulnerability assessments.

Investigating the Distribution Dynamics of the Camellia Subgenus Camellia in China and Providing Insights into Camellia Resources Management Under Future Climate Change

Rapid climate change has significantly impacted species distribution patterns, necessitating a comprehensive understanding of dominant tree dynamics for effective forest resource management and utilization. The Camellia subgenus Camellia, a widely distributed taxon in subtropical China, represents an ecologically and economically important group of woody plants valued for both oil production and ornamental purposes. In this study, we employed the BIOMOD2 ensemble modeling framework to investigate the spatial distribution patterns and range dynamics of the subgenus Camellia under projected climate change scenarios. Our analysis incorporated 1455 georeferenced occurrence records from 15 species, following the filtering of duplicate points, along with seven bioclimatic variables selected after highly correlated factors were eliminated. The ensemble model, which integrates six single species distribution models, demonstrated robust predictive performance, with mean true skil l statistic (TSS) and area under curve (AUC) values exceeding 0.8. Our results identified precipitation of the coldest quarter (Bio19) and temperature seasonality (Bio4) as the primary determinants influencing species distribution patterns. The center of species richness for the subgenus Camellia was located in the Nanling Mountains and eastern Guangxi Zhuang Autonomous Region. The projections indicate an overall expansion of suitable habitats for the subgenus under future climate conditions, with notable scenario-dependent variations: distribution hotspots are predicted to increase by 8.86% under the SSP126 scenario but experience a 2.53% reduction under the SSP585 scenario. Furthermore, a westward shift in the distribution centroid is anticipated. To ensure long-term conservation of Camellia genetic resources, we recommend establishing a germplasm conservation center in the Nanling Mountains region, which represents a critical biodiversity hotspot for this taxon.

Genomic Signatures of Environmental Adaptation in Castanopsis hainanensis (Fagaceae)

As an endemic Castanopsis species on Hainan Island, Castanopsis hainanensis Merr. is uniquely adapted to tropical climatic conditions and occupies a relatively narrow habitat range. Given its long generation times, limited dispersal capacity, and ecological and economic importance, understanding the genomic processes shaping this dominant tree species is critical for conservation. Its adaptation to specialized habitats and distinct geographical distribution provide valuable insights into biodiversity challenges in island ecosystems. This study employs genome-wide single-nucleotide polymorphism (SNP) markers to investigate genetic structure, population dynamics, and adaptive variation. Analyses revealed weak genetic divergence among populations, suggesting high gene flow. Demographic reconstruction indicated a historical population bottleneck, consistent with MaxEnt modeling projections of future range contraction under climate change. Selective sweep and genotype-environment association (GEA) analyses identified SNPs strongly correlated with environmental variables, particularly moisture and temperature. Using these SNPs, we quantified the risk of non-adaptedness (RONA) across climate scenarios, pinpointing regions at heightened vulnerability. Gene Ontology (GO) enrichment highlighted the key genes involved in plant growth and stress adaptation. By integrating genomic and environmental data, this study establishes a framework for deciphering adaptive mechanisms of C. hainanensis and offers actionable insights for informed conservation strategies to mitigate climate-driven biodiversity loss.

Conservation genomics of a threatened subtropical Rhododendron species highlights the distinct conservation actions required in marginal and admixed populations

With the impact of climate change and anthropogenic activities, the underlying threats facing populations with different evolutionary histories and distributions, and the associated conservation strategies necessary to ensure their survival, may vary within a species. This is particularly true for marginal populations and/or those showing admixture. Here, we re-sequence genomes of 102 individuals from 21 locations for Rhododendron vialii, a threatened species distributed in the subtropical forests of southwestern China that has suffered from habitat fragmentation due to deforestation. Population structure results revealed that R. vialii can be divided into five genetic lineages using neutral single-nucleotide polymorphisms (SNPs), whereas selected SNPs divide the species into six lineages. This is due to the Guigu (GG) population, which is identified as admixed using neutral SNPs, but is assigned to a distinct genetic cluster using non-neutral loci. R. vialii has experienced multiple genetic bottlenecks, and different demographic histories have been suggested among populations. Ecological niche modeling combined with genomic offset analysis suggests that the marginal population (Northeast, NE) harboring the highest genetic diversity is likely to have the highest risk of maladaptation in the future. The marginal population therefore needs urgent ex situ conservation in areas where the influence of future climate change is predicted to be well buffered. Alternatively, the GG population may have the potential for local adaptation, and will need in situ conservation. The Puer population, which carries the heaviest genetic load, needs genetic rescue. Our findings highlight how population genomics, genomic offset analysis, and ecological niche modeling can be integrated to inform targeted conservation.

Assessment of Stress and Immune Gene Expression in Australasian Snapper (Chrysophrys auratus) Exposed to Chronic Temperature Change

Background: Snapper is a significant commercial, recreational, and cultural teleost species in New Zealand, with aquaculture potential. The impact of long-term (chronic) temperature changes on immune and stress responses have not been studied in snapper, yet they have a critical importance to the health status of the fish. Methods: We investigated a set of genes in 30 individual snapper including fin, head kidney, and liver tissue, fish (10 per group) were exposed to either warm (22 °C), cold (14 °C), or ambient temperatures (10.5-18.6 °C) for 3 months. Results: Analyses of experimental fish using NanoString technologies to assess stress- and immune-related genes in the three tissue types showed that 22 out of 25 genes changed significantly in the experiment, indicating the significant impacts of chronic temperature changes on stress and immune responses. Furthermore, using a combined dataset based on this study and a previous one testing the impact of acute temperature changes in snapper, we identified five genes in the non-lethal fin-clip samples that can predict internal organ health status. Conclusions: Taken together, our experiments demonstrate the potential of the NanoString gene expression assessment tool for the rapid monitoring of stress responses in snapper, which can aid in the selection of stress-resilient wild stocks, monitor species in aquaculture environments, and inform the selection of locations for aquaculture.

Incorporating genetic load contributes to predicting Arabidopsis thaliana's response to climate change

Understanding how species respond to climate change can facilitate species conservation and crop breeding. Current prediction frameworks about population vulnerability focused on predicting range shifts or local adaptation but ignored genetic load, which is also crucial for adaptation. By analyzing 1115 globally distributed Arabidopsis thaliana natural accessions, we find that effective population size (Ne) is the major contributor of genetic load variation, both along genome and among populations, and can explain 74-94% genetic load variation in natural populations. Intriguingly, Ne affects genetic load by changing both effectiveness of purifying selection and GC biased gene conversion strength. In particular, by incorporating genetic load, genetic offset and species distribution models (SDM), we predict that, the populations at species' range edge are generally at higher risk. The populations at the eastern range perform poorer in all aspects, southern range have higher genetic offset and lower SDM suitability, while northern range have higher genetic load. Among the diverse natural populations, the Yangtze River basin population is the most vulnerable population under future climate change. Overall, here we deciphered the driving forces of genetic load in A. thaliana, and incorporated SDM, local adaptation and genetic load to predict the fate of populations under future climate change.

Population genomics of Marchantia polymorpha subsp. ruderalis reveals evidence of climate adaptation

Sexual reproduction results in the development of haploid and diploid cell states during the life cycle. In bryophytes, the dominant multicellular haploid phase produces motile sperm that swim through water to the egg to effect fertilization from which a relatively small diploid phase develops. In angiosperms, the reduced multicellular haploid phase produces non-motile sperm that is delivered to the egg through a pollen tube to effect fertilization from which the dominant diploid phase develops. These different life cycle characteristics are likely to impact the distribution of genetic variation among populations. However, little is known about the distribution of genetic variation among wild populations of bryophytes. To investigate how genetic variation is distributed among populations of a bryophyte and to establish the foundation for population genetics research in bryophytes, we described the genetic diversity of collections of Marchantia polymorpha subsp. ruderalis, a cosmopolitan ruderal liverwort. We identified 78 genetically unique (non-clonal) from a total of 209 sequenced accessions collected from 37 sites in Europe and Japan. There was no detectable population structure among European populations but significant genetic differentiation between Japanese and European populations. By associating genetic variation across the genome with global climate data, we showed that temperature and precipitation influence the frequency of potentially adaptive alleles. This collection establishes the core of an experimental platform that exploits natural genetic variation to answer diverse questions in biology.

The ecology of plant extinctions

Extinctions occur when enough individual plants die without replacement to extirpate a population, and all populations are extirpated. While the ultimate drivers of plant extinctions are known, the proximate mechanisms at individual and population level are not. The fossil record supports climate change as the major driver until recently, with land-use change dominating in recent millennia. Climate change may regain its leading role later this century. Documented recent extinctions have been few and concentrated among narrow-range species, but population extirpations are frequent. Predictions for future extinctions often use flawed methods, but more than half of all plants could be threatened by the end of this century. We need targeted interventions tailored to the needs of each threatened species.

Fine-Scale Variation in Soil Properties Promotes Local Taxonomic Diversity of Hybridizing Oak Species (Quercus spp.)

Although many tree species frequently hybridize and backcross, management decisions in forestry and nature conservation are usually concentrated on pure species. Therefore, understanding which environmental factors drive the distribution and admixture of tree species on a local stand scale is of great interest to support decision-making in the establishment and management of resilient forests. Here, we extensively sampled a mixed stand of hybridizing white oaks (Quercus petraea and Q. pubescens) near Lake Neuchâtel (Switzerland), where limestone and glacier moraine geologies coexist in proximity, to test whether micro-environmental conditions can predict taxonomic distribution and genetic admixture. We collected DNA from bud tissue, individual soil samples, and extracted high-resolution topographic data for 385 oak trees. We used 50 species-discriminatory single nucleotide polymorphism (SNP) markers to determine the taxonomic composition and admixture levels of individual trees and tested their association with micro-environmental conditions. We show that the trees' taxonomic distribution can be explained mainly by geographic position, soil pH, and potential rooting depth, a proxy for soil water availability. We found that admixed individuals tend to grow in habitats that are characteristic of the more drought-tolerant species Q. pubescens rather than in intermediate habitats. Using in situ measurements, we are the first to show that fine-scale variation in soil properties related to pH and water availability potentially drives the distribution of hybridizing tree species in a mixed stand. Microenvironmental variation therefore promotes local taxonomic diversity, facilitates admixture and adaptive introgression, and contributes to the resilience of forests under environmental change. Consequently, species such as white oaks should be managed and protected as a species complex rather than as pure species.

Genomic predictions of invasiveness and adaptability of the cotton bollworm in response to climate change

Agricultural pests cause enormous losses in annual agricultural production. Understanding the evolutionary responses and adaptive capacity of agricultural pests under climate change is crucial for establishing sustainable and environmentally friendly agricultural pest management. In this study, we integrate climate modeling and landscape genomics to investigate the distributional dynamics of the cotton bollworm (Helicoverpa armigera) in the adaptation to local environments and resilience to future climate change. Notably, the predicted inhabitable areas with higher suitability for the cotton bollworm could be eight times larger in the coming decades. Climate change is one of the factors driving the dynamics of distribution and population differentiation of the cotton bollworm. Approximately 19,000 years ago, the cotton bollworm expanded from its ancestral African population, followed by gradual occupations of the European, Asian, Oceanian, and American continents. Furthermore, we identify seven subpopulations with high dispersal and adaptability which may have an increased risk of invasion potential. Additionally, a large number of candidate genes and SNPs linked to climatic adaptation were mapped. These findings could inform sustainable pest management strategies in the face of climate change, aiding future pest forecasting and management planning.

Relationship between secondary metabolites and ecological suitability zones for Eucommia ulmoides

The quality of Chinese medicinal materials is closely related to the types and contents of their secondary metabolites, while ecological adaptability influences the production of secondary metabolites. Therefore, identifying the relationship between ecological adaptability and secondary metabolites is important for enhancing the quality of Chinese medicinal materials. In this study, we collected 10-year-old Cortex Eucommiae (Eucommia ulmoides, EU) samples from 21 plots in eight provinces which are the primary production areas of EU in central China. We used the MaxEnt model to determine the ecological suitability zones for EU at the 21 sampling sites and classified them accordingly. The contents of six pharmacologically active secondary metabolites, including chlorogenic acid, aucubin, geniposidic acid, geniposide, pinoresinol monoglucoside, and pinoresinol diglucoside were measured in the EU bark. The results demonstrated significant variations in the content of the six secondary metabolites in EU bark among different sampling sites. Correlation analysis indicated a close relationship between the content of chlorogenic acid and aucubin in EU bark and the ecological suitability of their respective production areas. The total content of the six secondary metabolites also showed good consistency with the ecological suitability of the production areas. Exploratory factor analysis further revealed a strong consistency between the factor analysis comprehensive scores based on the content of major secondary metabolites and the types of suitability zones at the sample locations. The cluster analysis results demonstrated good consistency between clustering groups and ecological suitability zone groups, with higher consistency as the suitability level of the ecological zone increased. This indicated a significant impact of suitable ecological environments on the content of EU secondary metabolites.

Temperature-dependent variations in under-canopy herbaceous foliar diseases following shrub encroachment in grasslands

Shrub encroachment into grasslands poses a global concern, impacting species biodiversity and ecosystem functioning. Yet, the effect of shrub encroachment on herbaceous diseases and the dependence of that effect on climatic factors remain ambiguous. This study spans over 4,000 km, examining significant variability in temperature and precipitation. Our findings reveal that herbaceous plant species richness diminishes the pathogen load of foliar fungal diseases of herbaceous plants in both shrub and grassland patches. Temperature emerges as the primary driver of variations in herbaceous biomass and pathogen load within herbaceous plant communities. Disparities in herbaceous biomass between shrub and grassland patches elucidate changes in pathogen load. In colder regions, shrub encroachment diminishes herbaceous biomass and pathogen load. Conversely, in warmer regions, shrubs either do not reduce or even amplify pathogen load. These discoveries underscore the necessity for adaptive management strategies tailored to specific shrub encroachment scenarios.

Global distribution pattern and conservation of the cosmopolitan cold-water coral species Desmophyllum dianthus under climate change

Global climate change impacts marine ecosystems differently across oceanic regions and depths. Thus, understanding how widespread key species adapt globally and locally to multidimensional climate change is crucial for targeted conservation. This study focuses on the cosmopolitan cold-water coral (CWC) Desmophyllum dianthus using ecological niche models (ENMs) to explore climate adaptation and conservation strategies. The findings indicated that D. dianthus occupied a broad ecological niche but had low ecological niche overlap across populations, suggesting local adaptations and supporting population-level ENMs. The models predicted that over 80% of D. dianthus suitable habitats would persist under SSP1-2.6 and SSP5-8.5 climate scenarios by the 2100s, potentially increasing to 95% as new habitats emerge, demonstrating its robust adaptability. However, localized environmental shifts could precipitate habitat losses in areas like the Reykjanes Ridge, Rockall Plateau, Mediterranean Sea, and Patagonian Shelf. We also applied Linkage Mapper to identify potential ecological corridors that intertwined nearshore macrohabitat patches with deep-sea stepping-stone habitats such as escarpments, seamounts, and ridges, maintaining population connectivity. Despite this, the habitats and ecological corridors of D. dianthus remained largely unprotected, with vulnerable portions lying outside of marine protected areas (MPAs), thus underscoring the urgent need for more MPA. These spatial-temporal predictions provide essential insights for the conservation and management of cosmopolitan CWC D. dianthus and serve as a benchmark for the adaptive survival of similar taxa.

Response strategies to acute and chronic environmental stress in the arctic breeding Lapland longspur (Calcarius lapponicus)

The potentially devastating effects of climate change have raised awareness of the need to understand how the biology of wild animals is influenced by extreme-weather events. We investigate how a wild arctic-breeding bird, the Lapland longspur (Calcarius lapponicus), responds to different environmental perturbations and its coping strategies. We explore the transcriptomic response to environmental adversity during the transition from arrival at the breeding grounds to incubation on the Arctic tundra. The effects of an extremely cold spring on arrival and a severe storm during incubation are examined through RNA-seq analysis of pertinent tissues sampled across the breeding cycle. The stress response, circadian rhythms, reproduction, and metabolism are all affected. A key gene of the Hypothalamic-Pituitary-Adrenal axis, FKBP5, was significantly up-regulated in hypothalamus. The genome assembly and gene expression profiles provide comprehensive resources for future studies. Our findings on different coping strategies to chronic and acute stressors will contribute to understanding the interplay between changing environments and genomic regulation.

Geographic Distribution Pattern Determines Soil Microbial Community Assembly Process in Acanthopanax senticosus Rhizosphere Soil

The geographic distribution patterns of soil microbial communities associated with cultivated Acanthopanax senticosus plants in Northeast China were investigated. High-throughput sequencing revealed that the diversity and community assembly of bacterial and fungal communities in the inter-root soil varied significantly with geographic location. The study found that bacterial communities were predominantly assembled through stochastic processes at most sites, while fungal communities showed greater variation, with both stochastic and deterministic processes involved. The complexity of bacterial-fungal co-occurrence networks also varied with longitude and latitude, demonstrating both positive and negative interactions. PICRUSt 2.0 and FUNGuild were used to predict the potential functions of soil bacterial and fungal microbiota, respectively, during different land use patterns. The average taxonomic distinctness (AVD) index indicated varying degrees of community stability across sites. Key microbial taxa contributing to community variability were identified through Random Forest modeling, with Bacteriap25 and Sutterellaceae standing out among bacteria, and Archaeorhizomyces and Clavaria among fungi. Soil chemical properties, including pH, TN, TP, EC, and SOC, significantly correlated with microbial diversity, composition, and co-occurrence networks. Structural equation modeling revealed that geographic distribution patterns directly and indirectly influenced soil chemical properties and microbial communities. Overall, the study provides insights into the geographic distribution patterns of soil microbial communities associated with A. senticosus and highlights the need for further research into the underlying mechanisms shaping these patterns.

Multi-Omics Inform Invasion Risks Under Global Climate Change

Global climate change is exacerbating biological invasions; however, the roles of genomic and epigenomic variations and their interactions in future climate adaptation remain underexplored. Using the model invasive ascidian Botryllus schlosseri across the Northern Hemisphere, we investigated genomic and epigenomic responses to future climates and developed a framework to assess future invasion risks. We employed generalized dissimilarity modeling and gradient forest analyses to assess genomic and epigenomic offsets under climate change. Our results showed that populations with genomic maladaptation did not geographically overlap with those experiencing epigenomic maladaptation, suggesting that genomic and epigenomic variations play complementary roles in adaptation to future climate conditions. By integrating genomic and epigenomic offsets into the genome-epigenomic index, we predicted that populations with lower index values were less maladapted, indicating a higher risk of future invasions. Native populations exhibited lower offsets than invasive populations, suggesting greater adaptive potentials and higher invasion risks under future climate change scenarios. These results highlight the importance of incorporating multi-omics data into predictive models to study future climate (mal)adaptation and assess invasion risks under global climate change.

Common drivers shaping niche distribution and climate change responses of one hundred tree species

Climate change is increasingly contributing to climatic mismatches, in which habitat suitability changes outpace the dispersal abilities of species. Climate niche models (CNM) have been widely used to assess such impacts on tree species. However, most studies have focused on either a single or a limited number of species, or have employed a fixed set of climate variables for multiple species. These limitations are largely due to the constraints of data availability, the complexity of the modeling algorithms, and integration approaches for the projections of diverse species. Therefore, whether specific climatic drivers determine the climatic niches of multiple tree species remains unclear. In this study, CNMs were developed for 100 economically and ecologically important tree species in China and were used to project their future distribution individually and collectively. Continentality was the predominant climate variable, affecting 71 species, followed by seasonal precipitation, which also significantly influenced over 50 species. Of the 100 tree species, the climate niche extent was projected to expand for 29 ("winners"), contract for 36 ("losers"), be stable for 27, and fluctuate for the remaining eight species. Principal component analysis showed that winners and losers were differentiated by geographic variables and the top five climatic variables, however, not by species type (deciduous vs. evergreen or conifer vs. broadleaf). The regions with the highest species richness were mainly distributed in the Hengduan Mountains, a global biodiversity hotspot, and were predicted to increase from 5.2% to 7.5% of the total area. Areas with low species richness were projected to increase from 33.0% to 42.4%. Significant shifts in species composition were anticipated in these biodiversity-rich areas, suggesting potential disruption owing to species reshuffling. This study highlights the urgent need for proactive forest management and conservation strategies to address the impacts of climate change on tree species and preserve ecological functions by mitigating climatic mismatches. In addition, this study establishes a framework to identify the common environmental drivers affecting niche distribution and evaluates the collective patterns of multiple tree species, thereby providing a scientific reference for enhanced forestry management and climate change mitigation.

Evolution and Plasticity of Gene Expression Under Progressive Warming in Drosophila subobscura

Understanding the molecular mechanisms of thermal adaptation is crucial to predict the impacts of global warming. However, there is still a lack of research on the effects of rising temperatures over time and of studies involving different populations from the same species. The present study focuses on these two aspects, which are of great importance in understanding how organisms cope and adapt to ongoing changes in their environment. This study investigates the impact of global warming on the gene expression patterns of Drosophila subobscura populations from two different latitudinal locations after 23 generations of evolution. Our results indicate that evolutionary changes depend on the genetic background of the populations, with different starting points for thermal evolution, and that high-latitude populations show more pronounced evolutionary changes, with some evidence of convergence towards low-latitude populations. We found an interplay between plasticity and selection, with the high-latitude population showing fewer initial plastic genes and lower levels of adaptive plasticity, but a greater magnitude of change in both plastic and selective responses during evolution under warming conditions compared with its low-latitude counterpart. A substantial proportion of the transcriptome was observed to be evolving, despite the lack of observable response at higher-order phenotypic traits. The interplay between plasticity and selection may prove to be an essential component in shaping species' evolutionary responses to climate change. Furthermore, the value of conducting studies on multiple populations of the same species is emphasised, given the identification of differences between populations with different backgrounds in several contexts.

Lineage Differentiation and Genomic Vulnerability in a Relict Tree From Subtropical Forests

The subtropical forests of East Asia are renowned for their high plant diversity, particularly the abundance of ancient relict species. However, both the evolutionary history of these relict species and their capacity for resilience in the face of impending climatic changes remain unclear. Using whole-genome resequencing data, we investigated the lineage differentiation and demographic history of the relict and endangered tree, Bretschneidera sinensis (Akaniaceae). We employed a combination of population genomic and landscape genomic approaches to evaluate variation in mutation load and genomic offset, aiming to predict how different populations may respond to climate change. Our analysis revealed a profound genomic divergence between the East and West lineages, likely as the result of recurrent bottlenecks due to climatic fluctuations during the glacial period. Furthermore, we identified several genes potentially linked to growth characteristics and hypoxia response that had been subjected to positive selection during the lineage differentiation. Our assessment of genomic vulnerability uncovered a significantly higher mutation load and genomic offset in the edge populations of B. sinensis compared to their core counterparts. This implies that the edge populations are likely to experience the most significant impact from the predicted climate conditions. Overall, our research sheds light on the historical lineage differentiation and contemporary genomic vulnerability of B. sinensis. Broadening our understanding of the speciation history and future resilience of relict and endangered species such as B. sinensis, is crucial in developing effective conservation strategies in anticipation of future climatic changes.

Integrating evolutionary genomics of forest trees to inform future tree breeding amid rapid climate change

Global climate change is leading to rapid and drastic shifts in environmental conditions, posing threats to biodiversity and nearly all life forms worldwide. Forest trees serve as foundational components of terrestrial ecosystems and play a crucial and leading role in combating and mitigating the adverse effects of extreme climate events, despite their own vulnerability to these threats. Therefore, understanding and monitoring how natural forests respond to rapid climate change is a key priority for biodiversity conservation. Recent progress in evolutionary genomics, driven primarily by cutting-edge multi-omics technologies, offers powerful new tools to address several key issues. These include precise delineation of species and evolutionary units, inference of past evolutionary histories and demographic fluctuations, identification of environmentally adaptive variants, and measurement of genetic load levels. As the urgency to deal with more extreme environmental stresses grows, understanding the genomics of evolutionary history, local adaptation, future responses to climate change, and conservation and restoration of natural forest trees will be critical for research at the nexus of global change, population genomics, and conservation biology. In this review, we explore the application of evolutionary genomics to assess the effects of global climate change using multi-omics approaches and discuss the outlook for breeding of climate-adapted trees.

Signatures of local adaptation and maladaptation to future climate in wild Zizania latifolia

Global climate change poses challenges to agricultural production and food security. Assessing the adaptive capacity of crop wild relatives to future climate is important for protecting key germplasm resources and breeding new crops. We performed population genomics, genotype-environment association analyses, and genomic offset assessment of Chinese wild rice, Zizania latifolia, a crop wild relative and potential new grain crop, based on 168 individuals from 42 populations. We found two genetic lineages in Z. latifolia, corresponding to the south and north of its range, that diverged during the Late Pleistocene. We also identified lineage-specific positively selected genes associated with flower development and flowering, seed shattering, pathogen defense response and cold tolerance. We further found that populations from southeastern China are the most maladapted to future climate and should be prioritized for conservation. Our findings provide important clues for leveraging existing genetic diversity to identify important germplasm resources and create climate-resilient crops.

Genomic variation of European beech reveals signals of local adaptation despite high levels of phenotypic plasticity

Local adaptation is key for ecotypic differentiation and species evolution. Understanding underlying genomic patterns can allow the prediction of future maladaptation and ecosystem stability. Here, we report the whole-genome resequencing of 874 individuals from 100 range-wide populations of European beech (Fagus sylvatica L.), an important forest tree species in Europe. We show that genetic variation closely mirrors geography with a clear pattern of isolation-by-distance. Genome-wide analyses for genotype-environment associations (GEAs) identify relatively few potentially adaptive variants after correcting for an overwhelming signal of statistically significant but non-causal GEAs. We characterize the single high confidence genomic region and pinpoint a candidate gene possibly involved in winter temperature adaptation via modulation of spring phenology. Surprisingly, allelic variation at this locus does not result in any apparent fitness differences in a common garden. More generally, reciprocal transplant experiments across large climate distances suggest extensive phenotypic plasticity. Nevertheless, we find indications of polygenic adaptation which may be essential in natural ecosystems. This polygenic signal exhibits broad- and fine-scale variation across the landscape, highlighting the relevance of spatial resolution. In summary, our results emphasize the importance, but also exemplify the complexity, of employing natural genetic variation for forest conservation under climate change.

The influence of temperature and genomic variation on intracranial EEG measures in people with epilepsy

Heatwaves have serious impacts on human health and constitute a key health concern from anthropogenic climate change. People have different individual tolerance for heatwaves or unaccustomed temperatures. Those with epilepsy may be particularly affected by temperature as the electroclinical hallmarks of brain excitability in epilepsy (inter-ictal epileptiform discharges and seizures) are influenced by a range of physiological and non-physiological conditions. Heatwaves are becoming more common and may affect brain excitability. Leveraging spontaneous heatwaves during periods of intracranial EEG recording in participants with epilepsy in a non-air-conditioned telemetry unit at the National Hospital for Neurology and Neurosurgery in London from May to August 2015-22, we examined the impact of heatwaves on brain excitability. In London, a heatwave is defined as three or more consecutive days with daily maximum temperatures ≥28°C. For each participant, we counted inter-ictal epileptiform discharges using four 10-min segments within, and outside of, heatwaves during periods of intracranial EEG recording. Additionally, we counted all clinical and subclinical seizures within, and outside of, heatwaves. We searched for causal rare genetic variants and calculated the epilepsy PRS. Nine participants were included in the study (six men, three women), median age 30 years (range 24-39). During heatwaves, there was a significant increase in the number of inter-ictal epileptiform discharges in three participants. Five participants had more seizures during the heatwave period, and as a group, there were significantly more seizures during the heatwaves. Genetic data, available for eight participants, showed none had known rare, genetically-determined epilepsies, whilst all had high polygenic risk scores for epilepsy. For some people with epilepsy, and not just those with known, rare, temperature-sensitive epilepsies, there is an association between heatwaves and increased brain excitability. These preliminary data require further validation and exploration, as they raise concerns about the impact of heatwaves directly on brain health.

Experimental Evolution in a Warming World: The Omics Era

A comprehensive understanding of the genetic mechanisms that shape species responses to thermal variation is essential for more accurate predictions of the impacts of climate change on biodiversity. Experimental evolution with high-throughput resequencing approaches (evolve and resequence) is a highly effective tool that has been increasingly employed to elucidate the genetic basis of adaptation. The number of thermal evolve and resequence studies is rising, yet there is a dearth of efforts to integrate this new wealth of knowledge. Here, we review this literature showing how these studies have contributed to increase our understanding on the genetic basis of thermal adaptation. We identify two major trends: highly polygenic basis of thermal adaptation and general lack of consistency in candidate targets of selection between studies. These findings indicate that the adaptive responses to specific environments are rather independent. A review of the literature reveals several gaps in the existing research. Firstly, there is a paucity of studies done with organisms of diverse taxa. Secondly, there is a need to apply more dynamic and ecologically relevant thermal environments. Thirdly, there is a lack of studies that integrate genomic changes with changes in life history and behavioral traits. Addressing these issues would allow a more in-depth understanding of the relationship between genotype and phenotype. We highlight key methodological aspects that can address some of the limitations and omissions identified. These include the need for greater standardization of methodologies and the utilization of new technologies focusing on the integration of genomic and phenotypic variation in the context of thermal adaptation.

Benefit-Sharing by Design: A Call to Action for Human Genomics Research

The ethical standards for the responsible conduct of human research have come a long way; however, concerns surrounding equity remain in human genetics and genomics research. Addressing these concerns will help society realize the full potential of human genomics research. One outstanding concern is the fair and equitable sharing of benefits from research on human participants. Several international bodies have recognized that benefit-sharing can be an effective tool for ethical research conduct, but international laws, including the Convention on Biological Diversity and its Nagoya Protocol on Access and Benefit-Sharing, explicitly exclude human genetic and genomic resources. These agreements face significant challenges that must be considered and anticipated if similar principles are applied in human genomics research. We propose that benefit-sharing from human genomics research can be a bottom-up effort and embedded into the existing research process. We propose the development of a "benefit-sharing by design" framework to address concerns of fairness and equity in the use of human genomic resources and samples and to learn from the aspirations and decade of implementation of the Nagoya Protocol.

Conserving Evolutionary Potential: Combining Landscape Genomics with Established Methods to Inform Plant Conservation

Biodiversity conservation requires conserving evolutionary potential-the capacity for wild populations to adapt. Understanding genetic diversity and evolutionary dynamics is critical for informing conservation decisions that enhance adaptability and persistence under environmental change. We review how emerging landscape genomic methods provide plant conservation programs with insights into evolutionary dynamics, including local adaptation and its environmental drivers. Landscape genomic approaches that explore relationships between genomic variation and environments complement rather than replace established population genomic and common garden approaches for assessing adaptive phenotypic variation, population structure, gene flow, and demography. Collectively, these approaches inform conservation actions, including genetic rescue, maladaptation prediction, and assisted gene flow. The greatest on-the-ground impacts from such studies will be realized when conservation practitioners are actively engaged in research and monitoring. Understanding the evolutionary dynamics shaping the genetic diversity of wild plant populations will inform plant conservation decisions that enhance the adaptability and persistence of species in an uncertain future.

Local adaptation of Pinus leiophylla under climate and land use change models in the Avocado Belt of Michoacán

Climate change and land use change are two main drivers of global biodiversity decline, decreasing the genetic diversity that populations harbour and altering patterns of local adaptation. Landscape genomics allows measuring the effect of these anthropogenic disturbances on the adaptation of populations. However, both factors have rarely been considered simultaneously. Based on a set of 3660 SNPs from which 130 were identified as outliers by a genome-environment association analysis (LFMM), we modelled the spatial turnover of allele frequencies in 19 localities of Pinus leiophylla across the Avocado Belt in Michoacán state, Mexico. Then, we evaluated the effect of climate change and land use change scenarios, in addition to evaluating assisted gene flow strategies and connectivity metrics across the landscape to identify priority conservation areas for the species. We found that localities in the centre-east of the Avocado Belt would be more vulnerable to climate change, while localities in the western area are more threatened by land conversion to avocado orchards. Assisted gene flow actions could aid in mitigating both threats. Connectivity patterns among forest patches will also be modified by future habitat loss, with central and eastern parts of the Avocado Belt maintaining the highest connectivity. These results suggest that areas with the highest priority for conservation are in the eastern part of the Avocado Belt, including the Monarch Butterfly Biosphere Reserve. This work is useful as a framework that incorporates distinct layers of information to provide a more robust representation of the response of tree populations to anthropogenic disturbances.

Patterns and effects of gene flow on adaptation across spatial scales: implications for management

Gene flow can have rapid effects on adaptation and is an important evolutionary tool available when undertaking biological conservation and restoration. This tool is underused partly because of the perceived risk of outbreeding depression and loss of mean fitness when different populations are crossed. In this article, we briefly review some theory and empirical findings on how genetic variation is distributed across species ranges, describe known patterns of gene flow in nature with respect to environmental gradients, and highlight the effects of gene flow on adaptation in small or stressed populations in challenging environments (e.g., at species range limits). We then present a case study involving crosses at varying spatial scales among mountain populations of a trigger plant (Stylidium armeria: Stylidiaceae) in the Australian Alps to highlight how some issues around gene flow effects can be evaluated. We found evidence of outbreeding depression in seed production at greater geographic distances. Nevertheless, we found no evidence of maladaptive gene flow effects in likelihood of germination, plant performance (size), and performance variance, suggesting that gene flow at all spatial scales produces offspring with high adaptive potential. This case study demonstrates a path to evaluating how increasing sources of gene flow in managed wild and restored populations could identify some offspring with high fitness that could bolster the ability of populations to adapt to future environmental changes. We suggest further ways in which managers and researchers can act to understand and consider adaptive gene flow in natural and conservation contexts under rapidly changing conditions.

Evolutionary genomics of climatic adaptation and resilience to climate change in alfalfa

Given the escalating impact of climate change on agriculture and food security, gaining insights into the evolutionary dynamics of climatic adaptation and uncovering climate-adapted variation can empower the breeding of climate-resilient crops to face future climate change. Alfalfa (Medicago sativa subsp. sativa), the queen of forages, shows remarkable adaptability across diverse global environments, making it an excellent model for investigating species responses to climate change. In this study, we performed population genomic analyses using genome resequencing data from 702 accessions of 24 Medicago species to unravel alfalfa's climatic adaptation and genetic susceptibility to future climate change. We found that interspecific genetic exchange has contributed to the gene pool of alfalfa, particularly enriching defense and stress-response genes. Intersubspecific introgression between M. sativa subsp. falcata (subsp. falcata) and alfalfa not only aids alfalfa's climatic adaptation but also introduces genetic burden. A total of 1671 genes were associated with climatic adaptation, and 5.7% of them were introgressions from subsp. falcata. By integrating climate-associated variants and climate data, we identified populations that are vulnerable to future climate change, particularly in higher latitudes of the Northern Hemisphere. These findings serve as a clarion call for targeted conservation initiatives and breeding efforts. We also identified pre-adaptive populations that demonstrate heightened resilience to climate fluctuations, illuminating a pathway for future breeding strategies. Collectively, this study enhances our understanding about the local adaptation mechanisms of alfalfa and facilitates the breeding of climate-resilient alfalfa cultivars, contributing to effective agricultural strategies for facing future climate change.

Incorporating adaptive genomic variation into predictive models for invasion risk assessment

Global climate change is expected to accelerate biological invasions, necessitating accurate risk forecasting and management strategies. However, current invasion risk assessments often overlook adaptive genomic variation, which plays a significant role in the persistence and expansion of invasive populations. Here we used Molgula manhattensis, a highly invasive ascidian, as a model to assess its invasion risks along Chinese coasts under climate change. Through population genomics analyses, we identified two genetic clusters, the north and south clusters, based on geographic distributions. To predict invasion risks, we employed the gradient forest and species distribution models to calculate genomic offset and species habitat suitability, respectively. These approaches yielded distinct predictions: the gradient forest model suggested a greater genomic offset to future climatic conditions for the north cluster (i.e., lower invasion risks), while the species distribution model indicated higher future habitat suitability for the same cluster (i.e, higher invasion risks). By integrating these models, we found that the south cluster exhibited minor genome-niche disruptions in the future, indicating higher invasion risks. Our study highlights the complementary roles of genomic offset and habitat suitability in assessing invasion risks under climate change. Moreover, incorporating adaptive genomic variation into predictive models can significantly enhance future invasion risk predictions and enable effective management strategies for biological invasions in the future.

Genomics for monitoring and understanding species responses to global climate change

All life forms across the globe are experiencing drastic changes in environmental conditions as a result of global climate change. These environmental changes are happening rapidly, incur substantial socioeconomic costs, pose threats to biodiversity and diminish a species' potential to adapt to future environments. Understanding and monitoring how organisms respond to human-driven climate change is therefore a major priority for the conservation of biodiversity in a rapidly changing environment. Recent developments in genomic, transcriptomic and epigenomic technologies are enabling unprecedented insights into the evolutionary processes and molecular bases of adaptation. This Review summarizes methods that apply and integrate omics tools to experimentally investigate, monitor and predict how species and communities in the wild cope with global climate change, which is by genetically adapting to new environmental conditions, through range shifts or through phenotypic plasticity. We identify advantages and limitations of each method and discuss future research avenues that would improve our understanding of species' evolutionary responses to global climate change, highlighting the need for holistic, multi-omics approaches to ecosystem monitoring during global climate change.

Genomic insights into local adaptation and phenotypic diversity of Wenchang chickens

Wenchang chicken, a prized local breed in Hainan Province of China renowned for its exceptional adaptability to tropical environments and good meat quality, is deeply favored by the public. However, an insufficient understanding of its population architecture and the unclear genetic basis that governs its typical attributes have posed challenges in the protection and breeding of this precious breed. To address these gaps, we conducted whole-genome resequencing on 200 Wenchang chicken samples derived from 10 distinct strains, and we gathered data on an array of 21 phenotype traits. Population genomics analysis unveiled distinctive population structures in Wenchang chickens, primarily attributed to strong artificial selection for different feather colors. Selection sweep analysis identified a group of candidate genes, including PCDH9, DPF3, CDIN1, and SUGCT, closely linked to adaptations that enhance resilience in tropical island habitats. Genome-wide association studies (GWAS) highlighted potential candidate genes associated with diverse feather color traits, encompassing TYR, RAB38, TRPM1, GABARAPL2, CDH1, ZMIZ1, LYST, MC1R, and SASH1. Through the comprehensive analysis of high-quality genomic and phenotypic data across diverse Wenchang chicken resource groups, this study unveils the intricate genetic backgrounds and population structures of Wenchang chickens. Additionally, it identifies multiple candidate genes linked to environmental adaptation, feather color variations, and production traits. These insights not only provide genetic reference for the purification and breeding of Wenchang chickens but also broaden our understanding of the genetic basis of phenotypic diversity in chickens.

Genomic evidence for rediploidization and adaptive evolution following the whole-genome triplication

Whole-genome duplication (WGD), or polyploidy, events are widespread and significant in the evolutionary history of angiosperms. However, empirical evidence for rediploidization, the major process where polyploids give rise to diploid descendants, is still lacking at the genomic level. Here we present chromosome-scale genomes of the mangrove tree Sonneratia alba and the related inland plant Lagerstroemia speciosa. Their common ancestor has experienced a whole-genome triplication (WGT) approximately 64 million years ago coinciding with a period of dramatic global climate change. Sonneratia, adapting mangrove habitats, experienced extensive chromosome rearrangements post-WGT. We observe the WGT retentions display sequence and expression divergence, suggesting potential neo- and sub-functionalization. Strong selection acting on three-copy retentions indicates adaptive value in response to new environments. To elucidate the role of ploidy changes in genome evolution, we improve a model of the polyploidization-rediploidization process based on genomic evidence, contributing to the understanding of adaptive evolution during climate change.

Climatic and soil characteristics account for the genetic structure of the invasive cactus moth Cactoblastis cactorum, in its native range in Argentina

Background

Knowledge of the physical and environmental conditions that may limit the migration of invasive species is crucial to assess the potential for expansion outside their native ranges. The cactus moth, Cactoblastis cactorum, is native to South America (Argentina, Paraguay, Uruguay and Brazil) and has been introduced and invaded the Caribbean and southern United States, among other regions. In North America there is an ongoing process of range expansion threatening cacti biodiversity of the genus Opuntia and the commercial profits of domesticated Opuntia ficus-indica.

Methods

To further understand what influences the distribution and genetic structure of this otherwise important threat to native and managed ecosystems, in the present study we combined ecological niche modeling and population genetic analyses to identify potential environmental barriers in the native region of Argentina. Samples were collected on the host with the wider distribution range, O. ficus-indica.

Results

Significant genetic structure was detected using 10 nuclear microsatellites and 24 sampling sites. At least six genetic groups delimited by mountain ranges, salt flats and wetlands were mainly located to the west of the Dry Chaco ecoregion. Niche modeling supports that this region has high environmental suitability where the upper soil temperature and humidity, soil carbon content and precipitation were the main environmental factors that explain the presence of the moth. Environmental filters such as the upper soil layer may be critical for pupal survival and consequently for the establishment of populations in new habitats, whereas the presence of available hosts is a necessary conditions for insect survival, upper soil and climatic characteristics will determine the opportunities for a successful establishment.

Genomics empowering conservation action and improvement of celery in the face of climate change

MAIN CONCLUSION

Integration of genomic approaches like whole genome sequencing, functional genomics, evolutionary genomics, and CRISPR/Cas9-based genome editing has accelerated the improvement of crop plants including leafy vegetables like celery in the face of climate change. The anthropogenic climate change is a real peril to the existence of life forms on our planet, including human and plant life. Climate change is predicted to be a significant threat to biodiversity and food security in the coming decades and is rapidly transforming global farming systems. To avoid the ghastly future in the face of climate change, the elucidation of shifts in the geographical range of plant species, species adaptation, and evolution is necessary for plant scientists to develop climate-resilient strategies. In the post-genomics era, the increasing availability of genomic resources and integration of multifaceted genomics elements is empowering biodiversity conservation action, restoration efforts, and identification of genomic regions adaptive to climate change. Genomics has accelerated the true characterization of crop wild relatives, genomic variations, and the development of climate-resilient varieties to ensure food security for 10 billion people by 2050. In this review, we have summarized the applications of multifaceted genomic tools, like conservation genomics, whole genome sequencing, functional genomics, genome editing, pangenomics, in the conservation and adaptation of plant species with a focus on celery, an aromatic and medicinal Apiaceae vegetable. We focus on how conservation scientists can utilize genomics and genomic data in conservation and improvement.

Comparative Study of Potential Habitats for Simulium qinghaiense (Diptera: Simuliidae) in the Huangshui River Basin, Qinghai-Tibet Plateau: An Analysis Using Four Ecological Niche Models and Optimized Approaches

The Huangshui River, a vital tributary in the upper reaches of the Yellow River within the eastern Qinghai-Tibet Plateau, is home to the endemic black fly species S. qinghaiense. In this study, we conducted a systematic survey of the distribution of the species in the Huangshui River basin, revealing its predominant presence along the river's main stem. Based on four ecological niche models-MaxEnt with parameter optimization; GARP; BIOCLIM; and DOMAIN-we conduct a comparative analysis; evaluating the accuracy of AUC and Kappa values. Our findings indicate that optimizing parameters significantly improves the MaxEnt model's predictive accuracy by reducing complexity and overfitting. Furthermore, all four models exhibit higher accuracy compared to a random model, with MaxEnt demonstrating the highest AUC and Kappa values (0.9756 and 0.8118, respectively), showcasing significant superiority over the other models (p < 0.05). Evaluation of predictions from the four models elucidates that potential areas of S. qinghaiense in the Huangshui River basin are primarily concentrated in the central and southern areas, with precipitation exerting a predominant influence. Building upon these results, we utilized the MaxEnt model to forecast changes in suitable areas and distribution centers during the Last Interglacial (LIG), Mid-Holocene (MH), and future periods under three climate scenarios. The results indicate significantly smaller suitable areas during LIG and MH compared to the present, with the center of distribution shifting southeastward from the Qilian Mountains to the central part of the basin. In the future, suitable areas under different climate scenarios are expected to contract, with the center of distribution shifting southeastward. These findings provide important theoretical references for monitoring, early warning, and control measures for S. qinghaiense in the region, contributing to ecological health assessment.

Genomic insights into endangerment and conservation of the garlic-fruit tree (Malania oleifera), a plant species with extremely small populations

BACKGROUND

Advanced whole-genome sequencing techniques enable covering nearly all genome nucleotide variations and thus can provide deep insights into protecting endangered species. However, the use of genomic data to make conservation strategies is still rare, particularly for endangered plants. Here we performed comprehensive conservation genomic analysis for Malania oleifera, an endangered tree species with a high amount of nervonic acid. We used whole-genome resequencing data of 165 samples, covering 16 populations across the entire distribution range, to investigate the formation reasons of its extremely small population sizes and to evaluate the possible genomic offsets and changes of ecology niche suitability under future climate change.

RESULTS

Although M. oleifera maintains relatively high genetic diversity among endangered woody plants (θπ = 3.87 × 10-3), high levels of inbreeding have been observed, which have reduced genetic diversity in 3 populations (JM, NP, and BM2) and caused the accumulation of deleterious mutations. Repeated bottleneck events, recent inbreeding (∼490 years ago), and anthropogenic disturbance to wild habitats have aggravated the fragmentation of M. oleifera and made it endangered. Due to the significant effect of higher average annual temperature, populations distributed in low altitude exhibit a greater genomic offset. Furthermore, ecological niche modeling shows the suitable habitats for M. oleifera will decrease by 71.15% and 98.79% in 2100 under scenarios SSP126 and SSP585, respectively.

CONCLUSIONS

The basic realizations concerning the threats to M. oleifera provide scientific foundation for defining management and adaptive units, as well as prioritizing populations for genetic rescue. Meanwhile, we highlight the importance of integrating genomic offset and ecological niche modeling to make targeted conservation actions under future climate change. Overall, our study provides a paradigm for genomics-directed conservation.

Space-for-time substitutions in climate change ecology and evolution

In an epoch of rapid environmental change, understanding and predicting how biodiversity will respond to a changing climate is an urgent challenge. Since we seldom have sufficient long-term biological data to use the past to anticipate the future, spatial climate-biotic relationships are often used as a proxy for predicting biotic responses to climate change over time. These 'space-for-time substitutions' (SFTS) have become near ubiquitous in global change biology, but with different subfields largely developing methods in isolation. We review how climate-focussed SFTS are used in four subfields of ecology and evolution, each focussed on a different type of biotic variable - population phenotypes, population genotypes, species' distributions, and ecological communities. We then examine the similarities and differences between subfields in terms of methods, limitations and opportunities. While SFTS are used for a wide range of applications, two main approaches are applied across the four subfields: spatial in situ gradient methods and transplant experiments. We find that SFTS methods share common limitations relating to (i) the causality of identified spatial climate-biotic relationships and (ii) the transferability of these relationships, i.e. whether climate-biotic relationships observed over space are equivalent to those occurring over time. Moreover, despite widespread application of SFTS in climate change research, key assumptions remain largely untested. We highlight opportunities to enhance the robustness of SFTS by addressing key assumptions and limitations, with a particular emphasis on where approaches could be shared between the four subfields.

Landscape genomics analysis provides insights into future climate change-driven risk in rhesus macaque

Climate change significantly affects the suitability of wildlife habitats. Thus, understanding how animals adapt ecologically and genetically to climate change is important for targeted species protection. Rhesus macaques (Macaca mulatta) are widely distributed and multi-climatically adapted primates. This study explored how rhesus macaques adapt to climate change by integrating ecological and genetic methods and applying species distribution models (SDMs) and a gradient forest (GF) model. The findings suggested that temperature seasonality primarily affects habitat suitability and indicated that climate change will have a dramatic impact on macaque populations in the future. We also applied genotype-environment association (GEA) analyses and selection signature analyses to identify genes associated with climate change and provide possible explanations for the adaptation of rhesus macaques to climatic environments. The population genomics analyses suggested that the Taihang population has the highest genomic vulnerability with inbreeding and low heterozygosity. Combined with the higher ecological vulnerability, additional conservation strategies are required for this population under higher risk of climate change. Our work measured the impact of climate change and enabled the identification of populations that exhibit high vulnerability to severe climate change. Such information is useful for selecting populations of rhesus macaques as subject of long-term monitoring or evolutionary rescue under future climate change.

Contrasting whole-genome and reduced representation sequencing for population demographic and adaptive inference: an alpine mammal case study

Genomes capture the adaptive and demographic history of a species, but the choice of sequencing strategy and sample size can impact such inferences. We compared whole genome and reduced representation sequencing approaches to study the population demographic and adaptive signals of the North American mountain goat (Oreamnos americanus). We applied the restriction site-associated DNA sequencing (RADseq) approach to 254 individuals and whole genome resequencing (WGS) approach to 35 individuals across the species range at mid-level coverage (9X) and to 5 individuals at high coverage (30X). We used ANGSD to estimate the genotype likelihoods and estimated the effective population size (Ne), population structure, and explicitly modelled the demographic history with δaδi and MSMC2. The data sets were overall concordant in supporting a glacial induced vicariance and extremely low Ne in mountain goats. We evaluated a set of climatic variables and geographic location as predictors of genetic diversity using redundancy analysis. A moderate proportion of total variance (36% for WGS and 21% for RADseq data sets) was explained by geography and climate variables; both data sets support a large impact of drift and some degree of local adaptation. The empirical similarities of WGS and RADseq presented herein reassuringly suggest that both approaches will recover large demographic and adaptive signals in a population; however, WGS offers several advantages over RADseq, such as inferring adaptive processes and calculating runs-of-homozygosity estimates. Considering the predicted climate-induced changes in alpine environments and the genetically depauperate mountain goat, the long-term adaptive capabilities of this enigmatic species are questionable.

Impact of climate change on the geographical distribution and niche dynamics of Gastrodia elata

Background

Gastrodia elata is widely used in China as a valuable herbal medicine. Owing to its high medicinal and nutrient value, wild resources of G. elata have been overexploited and its native areas have been severely damaged. Understanding the impacts of climate change on the distribution of this endangered species is important for the conservation and sustainable use of G. elata.

Methods

We used the optimized maximum entropy model to simulate the potential distribution of G. elata under contemporary and future time periods (1970-2000, 2050s, 2070s, and 2090s) and different climate change scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). Under these conditions, we investigated the key environmental factors influencing the distribution of G. elata as well as the spatial and temporal characteristics of its niche dynamics.

Results

With high Maxent model accuracy (AUCmean = 0.947 ± 0.012, and the Kappa value is 0.817), our analysis revealed that annual precipitation, altitude, and mean temperature of driest quarter are the most important environmental factors influencing the distribution of G. elata. Under current bioclimatic conditions, the potentially suitable area for G. elata in China is 71.98 × 10⁴ km², while the highly suitable region for G. elata growth is 7.28 × 10⁴ km². Our models for three future periods under four climate change scenarios indicate that G. elata can maintain stable distributions in southern Shaanxi, southwestern Hubei, and around the Sichuan basin, as these areas are highly suitable for its growth. However, the center of the highly suitable areas of G. elata shift depending on different climatic scenarios. The values of niche overlap for G. elata show a decreasing trend over the forecasted periods, of which the niche overlap under the SSP3-7.0 scenario shows the greatest decrease.

Discussions

Under the condition of global climate change in the future, our study provides basic reference data for the conservation and sustainable utilization of the valuable and endangered medicinal plant G. elata. It is important to carefully choose the protection area of G. elata wild resources according the suitable area conditions modeled. Moreover, these findings will be valuable for providing insights into the breeding and artificial cultivation of this plant, including the selection of suitable areas for planting.

Key triggers of adaptive genetic variability of sessile oak [Q. petraea (Matt.) Liebl.] from the Balkan refugia: outlier detection and association of SNP loci from ddRAD-seq data

Knowledge on the genetic composition of Quercus petraea in south-eastern Europe is limited despite the species' significant role in the re-colonisation of Europe during the Holocene, and the diverse climate and physical geography of the region. Therefore, it is imperative to conduct research on adaptation in sessile oak to better understand its ecological significance in the region. While large sets of SNPs have been developed for the species, there is a continued need for smaller sets of SNPs that are highly informative about the possible adaptation to this varied landscape. By using double digest restriction site associated DNA sequencing data from our previous study, we mapped RAD-seq loci to the Quercus robur reference genome and identified a set of SNPs putatively related to drought stress-response. A total of 179 individuals from eighteen natural populations at sites covering heterogeneous climatic conditions in the southeastern natural distribution range of Q. petraea were genotyped. The detected highly polymorphic variant sites revealed three genetic clusters with a generally low level of genetic differentiation and balanced diversity among them but showed a north-southeast gradient. Selection tests showed nine outlier SNPs positioned in different functional regions. Genotype-environment association analysis of these markers yielded a total of 53 significant associations, explaining 2.4-16.6% of the total genetic variation. Our work exemplifies that adaptation to drought may be under natural selection in the examined Q. petraea populations.

Multigenic resistance to Xylella fastidiosa in wild grapes (Vitis sps.) and its implications within a changing climate

Xylella fastidiosa is a bacterium that infects crops like grapevines, coffee, almonds, citrus and olives. There is little understanding of the genes that contribute to plant resistance, the genomic architecture of resistance, and the potential role of climate in shaping resistance, in part because major crops like grapevines (Vitis vinifera) are not resistant to the bacterium. Here we study a wild grapevine species, V. arizonica, that segregates for resistance. Using genome-wide association, we identify candidate resistance genes. Resistance-associated kmers are shared with a sister species of V. arizonica but not with more distant species, suggesting that resistance evolved more than once. Finally, resistance is climate dependent, because individuals from low ( < 10 °C) temperature locations in the wettest quarter were typically susceptible to infection, likely reflecting a lack of pathogen pressure in colder climates. In fact, climate is as effective a predictor of resistance phenotypes as some genetic markers. We extend our climate observations to additional crops, predicting that increased pathogen pressure is more likely for grapevines and almonds than some other susceptible crops.

Genomic insights into genetic diversity and local adaptation of a dominant desert steppe feather grass, Stipa breviflora Griseb

Investigating the genetic mechanisms of local adaptation is critical to understanding how species adapt to heterogeneous environments. In the present study, we analyzed restriction site-associated DNA sequencing (RADseq) data in order to explore genetic diversity, genetic structure, genetic differentiation, and local adaptation of Stipa breviflora. In total, 135 individual plants were sequenced and 25,786 polymorphic loci were obtained. We found low genetic diversity (He = 0.1284) within populations of S. breviflora. Four genetic clusters were identified along its distribution range. The Mantel test, partial Mantel test, and multiple matrix regression with randomization (MMRR) indicate that population differentiation was caused by both geographic distance and environmental factors. Through the F_ST outlier test and environmental association analysis (EAA), 113 candidate loci were identified as putatively adaptive loci. RPK2 and CPRF1, which are associated with meristem maintenance and light responsiveness, respectively, were annotated. To explore the effects of climatic factors on genetic differentiation and local adaptation of S. breviflora, gradient forest (GF) analysis was applied to 25,786 single nucleotide polymorphisms (SNPs) and 113 candidate loci, respectively. The results showed that both temperature and precipitation affected the genetic differentiation of S. breviflora, and precipitation was strongly related to local adaptation. Our study provides a theoretical basis for understanding the local adaptation of S. breviflora.

An integrated eco-evolutionary framework to predict population-level responses of climate-sensitive pathogens

It is critical to gain insight into how climate change impacts evolutionary responses within climate-sensitive pathogen populations, such as increased resilience, opportunistic responses and the emergence of dominant variants from highly variable genomic backgrounds and subsequent global dispersal. This review proposes a framework to support such analysis, by combining genomic evolutionary analysis with climate time-series data in a novel spatiotemporal dataframe for use within machine learning applications, to understand past and future evolutionary pathogen responses to climate change. Recommendations are presented to increase the feasibility of interdisciplinary applications, including the importance of robust spatiotemporal metadata accompanying genome submission to databases. Such workflows will inform accessible public health tools and early-warning systems, to aid decision-making and mitigate future human health threats.

Genome Scan of Rice Landrace Populations Collected Across Time Revealed Climate Changes' Selective Footprints in the Genes Network Regulating Flowering Time

Analyses of the genetic bases of plant adaptation to climate changes, using genome-scan approaches, are often conducted on natural populations, under hypothesis of out-crossing reproductive regime. We report here on a study based on diachronic sampling (1980 and 2011) of the autogamous crop species, Oryza sativa and Oryza glaberrima, in the tropical forest and the Sudanian savannah of West Africa. First, using historical meteorological data we confirmed changes in temperatures (+ 1 °C on average) and rainfall regime (less predictable and reduced amount) in the target areas. Second, phenotyping the populations for phenology, we observed significantly earlier heading time in the 2010 samples. Third, implementing two genome-scan methods (one of which specially developed for selfing species) on genotyping by sequencing genotypic data of the two populations, we detected 31 independent selection footprints. Gene ontology analysis detected significant enrichment of these selection footprints in genes involved in reproductive processes. Some of them bore known heading time QTLs and genes, including OsGI, Hd1 and OsphyB. This rapid adaptive evolution, originated from subtle changes in the standing variation in genetic network regulating heading time, did not translate into predominance of multilocus genotypes, as it is often the case in selfing plants, and into notable selective sweeps. The high adaptive potential observed results from the multiline genetic structure of the rice landraces, and the rather large and imbricated genetic diversity of the rice meta-population at the farm, the village and the region levels, that hosted the adaptive variants in multiple genetic backgrounds before the advent of the environmental selective pressure. Our results illustrate the evolution of in situ diversity through processes of human and natural selection, and provide a model for rice breeding and cultivars deployment strategies aiming resilience to climate changes. It also calls for further development of population genetic models for adaptation of plant populations to environmental changes. To our best knowledge, this is the first study dealing with climate-changes' selective footprint in crops.

Population genomics unravels the Holocene history of bread wheat and its relatives

Deep knowledge of crop biodiversity is essential to improving global food security. Despite bread wheat serving as a keystone crop worldwide, the population history of bread wheat and its relatives, both cultivated and wild, remains elusive. By analysing whole-genome sequences of 795 wheat accessions, we found that bread wheat originated from the southwest coast of the Caspian Sea and underwent a slow speciation process, lasting ~3,300 yr owing to persistent gene flow from its relatives. Soon after, bread wheat spread across Eurasia and reached Europe, South Asia and East Asia ~7,000 to ~5,000 yr ago, shaping a diversified but occasionally convergent adaptive landscape in novel environments. By contrast, the cultivated relatives of bread wheat experienced a population decline by ~82% over the past ~2,000 yr due to the food choice shift of humans. Further biogeographical modelling predicted a continued population shrinking of many bread wheat relatives in the coming decades because of their vulnerability to the changing climate. These findings will guide future efforts in protecting and utilizing wheat biodiversity to enhance global wheat production.

Molecular mechanisms of adaptive evolution in wild animals and plants

Wild animals and plants have developed a variety of adaptive traits driven by adaptive evolution, an important strategy for species survival and persistence. Uncovering the molecular mechanisms of adaptive evolution is the key to understanding species diversification, phenotypic convergence, and inter-species interaction. As the genome sequences of more and more non-model organisms are becoming available, the focus of studies on molecular mechanisms of adaptive evolution has shifted from the candidate gene method to genetic mapping based on genome-wide scanning. In this study, we reviewed the latest research advances in wild animals and plants, focusing on adaptive traits, convergent evolution, and coevolution. Firstly, we focused on the adaptive evolution of morphological, behavioral, and physiological traits. Secondly, we reviewed the phenotypic convergences of life history traits and responding to environmental pressures, and the underlying molecular convergence mechanisms. Thirdly, we summarized the advances of coevolution, including the four main types: mutualism, parasitism, predation and competition. Overall, these latest advances greatly increase our understanding of the underlying molecular mechanisms for diverse adaptive traits and species interaction, demonstrating that the development of evolutionary biology has been greatly accelerated by multi-omics technologies. Finally, we highlighted the emerging trends and future prospects around the above three aspects of adaptive evolution.