Tackling intraspecific genetic structure in distribution models better reflects species geographical range

Climatic niche convergence through space and time for a potential archaeophyte (Acacia caven) in South America

Based on the niche conservatism hypothesis, i.e. the idea that niches remain unchanged over space and time, climatic niche modelling (CNM) is a useful tool for predicting the spread of introduced taxa. Recent advances have extended such predictions deeper in time for plant species dispersed by humans before the modern era. The latest CNMs successfully evaluate niche differentiation and estimate potential source areas for intriguing taxa such as archaeophytes (i.e., species introduced before 1492 AD). Here, we performed CNMs for Acacia caven, a common Fabaceae tree in South America, considered an archaeophyte west of the Andes, in Central Chile. Accounting for the infraspecific delimitation of the species, our results showed that even when climates are different, climatic spaces used by the species overlap largely between the eastern and western ranges. Despite slight variation, results were consistent when considering one, two, or even three-environmental dimensions, and in accordance with the niche conservatism hypothesis. Specific distribution models calibrated for each region (east vs west) and projected to the past, indicate a common area of occupancy available in southern Bolivia-northwest Argentina since the late Pleistocene, which could have acted as a source-area, and this signal becomes stronger through the Holocene. Then, in accordance with a taxon introduced in the past, and comparing regional vs continental distribution models calibrated at the infraspecific or species level, the western populations showed their spread status to be mostly in equilibrium with the environment. Our study thus indicates how niche and species distribution models are useful to improve our knowledge related to taxa introduced before the modern era.

Transcriptome wide analyses reveal intraspecific diversity in thermal stress responses of a dominant habitat-forming species

The impact of climate change on biodiversity has stimulated the need to understand environmental stress responses, particularly for ecosystem engineers whose responses to climate affect large numbers of associated organisms. Distinct species differ substantially in their resilience to thermal stress but there are also within-species variations in thermal tolerance for which the molecular mechanisms underpinning such variation remain largely unclear. Intertidal mussels are well-known for their role as ecosystem engineers. First, we exposed two genetic lineages of the intertidal mussel Perna perna to heat stress treatments in air and water. Next, we ran a high throughput RNA sequencing experiment to identify differences in gene expression between the thermally resilient eastern lineage and the thermally sensitive western lineage. We highlight different thermal tolerances that concord with their distributional ranges. Critically, we also identified lineage-specific patterns of gene expression under heat stress and revealed intraspecific differences in the underlying transcriptional pathways in response to warmer temperatures that are potentially linked to the within-species differences in thermal tolerance. Beyond the species, we show how unravelling within-species variability in mechanistic responses to heat stress promotes a better understanding of global evolutionary trajectories of the species as a whole in response to changing climate.

Niches of three sympatric montane ground‐dwelling squirrels: Relative importance of climate, topography, and landcover

Species with different ecological niches will likely exhibit distinct responses to a changing environment. Differences in the magnitude of niche specialization may also indicate which species may be more vulnerable to environmental change, as many life‐history characteristics are known to affect climate change vulnerability. We characterized the niche space of three sympatric high‐elevation ground‐dwelling squirrels, yellow‐bellied marmot (Marmota flaviventer), Belding's ground squirrel (Urocitellus beldingi), and golden‐mantled ground squirrel (Callospermophilus lateralis), in the alpine and upper subalpine regions of the Sierra Nevada in California. We used 5879 observations of individual squirrels, collected from 4 years (2009–2012) of transect survey data, to quantify which ecogeographical variable types (climate, topography, or landcover) were most important in defining the niche of each species. We conducted Ecological Niche Factor Analysis to quantify the niche and generate indices of “marginality” (magnitude of selection) and “specialization” (narrowness of niche space). All three species demonstrated differential use of niche space when compared to the available niche space. Moreover, the relative importance of the variables shaping the niche differed among these species. For example, the presence of meadows was important in defining the niche for U. beldingi and M. flaviventer, but the presence of conifers was important to C. lateralis. Precipitation was important in defining the niche for all three species, positively so for U. beldingi, and negatively for the other two species. The niche breadth of these three species was also positively associated with geographic range size. Mammals in high‐elevation mountain systems often are perceived as vulnerable to climate shifts, but our results underscore the importance of also including non‐climate‐based factors in defining the niche. The overall magnitude of niche selection for all three species was driven by a combination of topographic, climatic, and landcover factors; thus, efforts to forecast areas where these species can persist in the future need to evaluate from more than just a climatic perspective.

Unravelling plant diversification: Intraspecific genetic differentiation in hybridizing Anacyclus species in the western Mediterranean Basin

PREMISE

The interfertile species Anacyclus clavatus, A. homogamos, and A. valentinus represent a plant complex coexisting in large anthropic areas of the western Mediterranean Basin with phenotypically mixed populations exhibiting a great floral variation. The goal of this study was to estimate the genetic identity of each species, to infer the role of hybridization in the observed phenotypic diversity, and to explore the effect of climate on the geographic distribution of species and genetic clusters.

METHODS

We used eight nuclear microsatellites to genotype 585 individuals from 31 populations of three Anacyclus species for population genetic analyses by using clustering algorithms based on Bayesian models and ordination methods. In addition, we used ecological niche models and niche overlap analyses for both the species and genetic clusters. We used an expanded data set, including 721 individuals from 129 populations for ecological niche models of the genetic clusters.

RESULTS

We found a clear correspondence between species and genetic clusters, except for A. clavatus that included up to three genetic clusters. We detected individuals with admixed genetic ancestry in A. clavatus and in mixed populations. Ecological niche models predicted similar distributions for species and genetic clusters. For the two specific genetic clusters of A. clavatus, ecological niche models predicted remarkably different areas.

CONCLUSIONS

Gene flow between Anacyclus species likely explains phenotypic diversity in contact areas. In addition, we suggest that introgression could be involved in the origin of one of the two A. clavatus genetic clusters, which also showed ecological differentiation.

Dealing with disjunct populations of vascular plants: implications for assessing the effect of climate change

Species distribution models are the most widely used tool to predict species distributions for species conservation and assessment of climate change impact. However, they usually do not consider intraspecific ecological variation exhibited by many species. Overlooking the potential differentiation among groups of populations may lead to misplacing any conservation actions. This issue may be particularly relevant in species in which few populations with potential local adaptation occur, as in species with disjunct populations. Here, we used ecological niche modeling to analyze how the projections of current and future climatically suitable areas of 12 plant species can be affected using the whole taxa occurrences compared to occurrences from geographically disjunct populations. Niche analyses suggest that usually the disjunct group of populations selects the climatic conditions as similar as possible to the other according to climate availability. Integrating intraspecific variability only slightly increases models' ability to predict species occurrences. However, it results in different predictions of the magnitude of range change. In some species, integrating or not integrating intraspecific variability may lead to opposite trend in projected range change. Our results suggest that integrating intraspecific variability does not strongly improve overall models' accuracy, but it can result in considerably different conclusions about future range change. Consequently, accounting for intraspecific differentiation may enable the detection of potential local adaptations to new climate and so to design targeted conservation strategies.

Aggregate population-level models informed by genetics predict more suitable habitat than traditional species-level model across the range of a widespread riparian tree

Identifying and predicting how species ranges will shift in response to climate change is paramount for conservation and restoration. Ecological niche models are the most common method used to estimate potential distributions of species; however, they traditionally omit knowledge of intraspecific variation that can allow populations to respond uniquely to change. Here, we aim to test how population X environment relationships influence predicted suitable geographic distributions by comparing aggregated population-level models with species-level model predictions of suitable habitat within population ranges and across the species’ range. We also test the effect of two variable selection methods on these predictions–both addressing the possibility of local adaptation: Models were built with (a) a common set, and number, of predictors and, (b) a unique combination and number of predictors specific to each group’s training extent. Our study addresses the overarching hypothesis that populations have unique environmental niches, and specifically that (1) species-level models predict more suitable habitat within the ranges of genetic populations than individual models built from those groups, particularly when compared models are built with the same set of environmental predictors; and (2) aggregated genetic population models predict more suitable habitat across the species’ range than the species-level model, an = d this difference will increase when models are trained with individualized predictors. We found the species models predicted more habitat within population ranges for two of three genetic groups regardless of variable selection, and that aggregated population models predicted more habitat than species’ models, but that individualized predictors increased this difference. Our study emphasizes the extent to which changes to model predictions depend on the inclusion of genetic information and on the type and selection of predictors. Results from these modeling decisions can have broad implications for predicting population-level ecological and evolutionary responses to climate change.

Linking ecological niche models and common garden experiments to predict phenotypic differentiation in stressful environments: Assessing the adaptive value of marginal populations in an alpine plant

Environmental variation within a species' range can create contrasting selective pressures, leading to divergent selection and novel adaptations. The conservation value of populations inhabiting environmentally marginal areas remains in debate and is closely related to the adaptive potential in changing environments. Strong selection caused by stressful conditions may generate novel adaptations, conferring these populations distinct evolutionary potential and high conservation value under climate change. On the other hand, environmentally marginal populations may be genetically depauperate, with little potential for new adaptations to emerge. Here, we explored the use of ecological niche models (ENMs) linked with common garden experiments to predict and test for genetically determined phenotypic differentiation related to contrasting environmental conditions. To do so, we built an ENM for the alpine plant Silene ciliata in central Spain and conducted common garden experiments, assessing flowering phenology changes and differences in leaf cell resistance to extreme temperatures. The suitability patterns and response curves of the ENM led to the predictions that: (1) the environmentally marginal populations experiencing less snowpack and higher minimum temperatures would have delayed flowering to avoid risks of late-spring frosts and (2) those with higher minimum temperatures and greater potential evapotranspiration would show enhanced cell resistance to high temperatures to deal with physiological stress related to desiccation and heat. The common garden experiments revealed the expected genetically based phenotypic differentiation in flowering phenology. In contrast, they did not show the expected differentiation for cell resistance, but these latter experiments had high variance and hence lower statistical power. The results highlight ENMs as useful tools to identify contrasting putative selective pressures across species ranges. Linking ENMs with common garden experiments provides a theoretically justified and practical way to study adaptive processes, including insights regarding the conservation value of populations inhabiting environmentally marginal areas under ongoing climate change.

Coupling genetic structure analysis and ecological-niche modeling in Kersting’s groundnut in West Africa

Orphan legume crops play an important role in smallholder farmers’ food systems. Though less documented, they have the potential to contribute to adequate nutrition in vulnerable communities. Unfortunately, data are scarce about the potential of those crops to withstand current and future climate variations. Using Macrotyloma geocarpum as an example, we used ecological niche modeling to explore the role of ecology on the current and future distributions of genetic populations of Kersting’s groundnut. Our findings showed that: (1) the models had good predictive power, indicating that M. geocarpum’s distribution was correlated with both climatic and soil layers; (2) identity and similarity tests revealed that the two genetic groups have identical and similar environmental niches; (3) by integrating the genetic information in niche modeling, niches projections show divergence in the response of the species and genetic populations to ongoing climate change. This study highlights the importance of incorporating genetic data into Ecological Niche Modeling (ENM) approaches to obtain a finer information of species’ future distribution, and explores the implications for agricultural adaptation, with a particular focus on identifying priority actions in orphan crops conservation and breeding.

Environmental Niche Dynamics of Blue Grama (Bouteloua gracilis) Ecotypes in Northern Mexico: Genetic Structure and Implications for Restoration Management

Understanding the genetic structure adopted by natural populations and its relation to environmental adaptation is critical for the success of restoration programs. We evaluated the genetic structure and temporal environmental niche dynamics of blue grama (Bouteloua gracilis) in 48 populations. The genetic evaluation was performed through amplified fragment length polymorphism (AFLP) molecular markers. The maximum entropy method was used to model the past, present, and future environmental niches of the three clusters derived from the genetic analysis. The environmental niches of the three genetic clusters showed dynamic overlaps and isolations during the last interglacial and glacial maximum. The paleoclimatic events, which occurred during those periods, may have reinforced genetic exchange among populations and affected their genetic structure. Genetic clusters also presented different environmental niches in the present. Thus, they can be considered as three distinct ecotypes and restoration programs must be carried out using local germplasm from each environmental niche to increase their chance of success. Based on the environmental niches of the genetic clusters, changes are expected in the near and mid-century future. Therefore, climate change must be considered for species conservation management and future restoration programs.

Depicting the phenotypic space of the annual plant Diplotaxis acris in hyperarid deserts

The phenotypic space encompasses the assemblage of trait combinations yielding well-suited integrated phenotypes. At the population level, understanding the phenotypic space structure requires the quantification of among- and within-population variations in traits and the correlation pattern among them. Here, we studied the phenotypic space of the annual plant Diplotaxis acris occurring in hyperarid deserts. Given the advance of warming and aridity in vast regions occupied by drylands, D. acris can indicate the successful evolutionary trajectory that many other annual plant species may follow in expanding drylands. To this end, we conducted a greenhouse experiment with 176 D. acris individuals from five Saudi populations to quantify the genetic component of variation in architectural and life history traits. We found low among-population divergence but high among-individual variation in all traits. In addition, all traits showed a high degree of genetic determination in our study experimental conditions. We did not find significant effects of recruitment and fecundity on fitness. Finally, all architectural traits exhibited a strong correlation pattern among them, whereas for life history traits, only higher seed germination implied earlier flowering. Seed weight appeared to be an important trait in D. acris as individuals with heavier seeds tended to advance flowering and have a more vigorous branching pattern, which led to higher fecundity. Population divergence in D. acris might be constrained by the severity of the hyperarid environment, but populations maintain high among-individual genetic variation in all traits. Furthermore, D. acris showed phenotypic integration for architectural traits and, to a lesser extent, for life history traits. Overall, we hypothesize that D. acris may be fine-tuned to its demanding extreme environments. Evolutionary speaking, annual plants facing increasing warming, aridity, and environmental seasonality might modify their phenotypic spaces toward new phenotypic configurations strongly dominated by correlated architectural traits enhancing fecundity and seed-related traits advancing flowering time.

Genetic structure and ecological niche segregation of Indian gray mongoose (Urva edwardsii) in Iran

Combining genetic data with ecological niche models is an effective approach for exploring climatic and nonclimatic environmental variables affecting spatial patterns of intraspecific genetic variation. Here, we adopted this combined approach to evaluate genetic structure and ecological niche of the Indian gray mongoose (Urva edwardsii) in Iran, as the most western part of the species range. Using mtDNA, we confirmed the presence of two highly differentiated clades. Then, we incorporated ensemble of small models (ESMs) using climatic and nonclimatic variables with genetic data to assess whether genetic differentiation among clades was coupled with their ecological niche. Climate niche divergence was also examined based on a principal component analysis on climatic factors only. The relative habitat suitability values predicted by the ESMs for both clades revealed their niche separation. Between-clade climate only niche comparison revealed that climate space occupied by clades is similar to some extent, but the niches that they utilize differ between the distribution ranges of clades. We found that in the absence of evidence for recent genetic exchanges, distribution models suggest the species occurs in different niches and that there are apparent areas of disconnection across the species range. The estimated divergence time between the two Iranian clades (4.9 Mya) coincides with the uplifting of the Zagros Mountains during the Early Pliocene. The Zagros mountain-building event seems to have prevented the distribution of U. edwardsii populations between the western and eastern parts of the mountains as a result of vicariance events. Our findings indicated that the two U. edwardsii genetic clades in Iran can be considered as two conservation units and can be utilized to develop habitat-specific and climate change-integrated management strategies.

High gene flow in polar cod (Boreogadus saida) from West-Svalbard and the Eurasian Basin

The current and projected environmental change of the Arctic Ocean contrasts sharply with the limited knowledge of its genetic biodiversity. Polar cod Boreogadus saida (Lepechin, 1774) is an abundant circumpolar marine fish and ecological key species. The central role of polar cod in the Arctic marine food web warrants a better understanding of its population structure and connectivity. In this study, the genetic population structure of 171 juveniles, collected from several fjords off West-Svalbard (Billefjorden, Hornsund and Kongsfjorden), the northern Sophia Basin and the Eurasian Basin of the Arctic Ocean, was analysed using nine DNA microsatellite loci. Genetic analyses indicated moderate to high genetic diversity, but absence of spatial population structure and isolation-by-distance, suggesting ongoing gene flow between the studied sampling regions. High levels of connectivity may be key for polar cod to maintain populations across wide spatial scales. The adaptive capacity of the species will be increasingly important to face challenges such as habitat fragmentation, ocean warming and changes in prey composition. In view of a limited understanding of the population dynamics and evolution of polar cod, a valuable next step to predict future developments should be an integrated biological evaluation, including population genomics, a life-history approach, and habitat and biophysical dispersal modelling.

Genomics-informed models reveal extensive stretches of coastline under threat by an ecologically dominant invasive species

Explaining why some species are widespread, while others are not, is fundamental to biogeography, ecology, and evolutionary biology. A unique way to study evolutionary and ecological mechanisms that either limit species' spread or facilitate range expansions is to conduct research on species that have restricted distributions. Nonindigenous species, particularly those that are highly invasive but have not yet spread beyond the introduced site, represent ideal systems to study range size changes. Here, we used species distribution modeling and genomic data to study the restricted range of a highly invasive Australian marine species, the ascidian Pyura praeputialis This species is an aggressive space occupier in its introduced range (Chile), where it has fundamentally altered the coastal community. We found high genomic diversity in Chile, indicating high adaptive potential. In addition, genomic data clearly showed that a single region from Australia was the only donor of genotypes to the introduced range. We identified over 3,500 km of suitable habitat adjacent to its current introduced range that has so far not been occupied, and importantly species distribution models were only accurate when genomic data were considered. Our results suggest that a slight change in currents, or a change in shipping routes, may lead to an expansion of the species' introduced range that will encompass a vast portion of the South American coast. Our study shows how the use of population genomics and species distribution modeling in combination can unravel mechanisms shaping range sizes and forecast future range shifts of invasive species.

MYB transcription factors drive evolutionary innovations in Arabidopsis fruit trichome patterning

Both inter- and intra-specific diversity has been described for trichome patterning in fruits, which is presumably involved in plant adaptation. However, the mechanisms underlying this developmental trait have been hardly addressed. Here we examined natural populations of Arabidopsis (Arabidopsis thaliana) that develop trichomes in fruits and pedicels, phenotypes previously not reported in the Arabidopsis genus. Genetic analyses identified five loci, MALAMBRUNO 1-5 (MAU1-5), with MAU2, MAU3, and MAU5 showing strong epistatic interactions that are necessary and sufficient to display these traits. Functional characterization of these three loci revealed cis-regulatory mutations in TRICHOMELESS1 and TRIPTYCHON, as well as a structural mutation in GLABRA1. Therefore, the multiple mechanisms controlled by three MYB transcription factors of the core regulatory network for trichome patterning have jointly been modulated to trigger trichome development in fruits. Furthermore, analyses of worldwide accessions showed that these traits and mutations only occur in a highly differentiated relict lineage from the Iberian Peninsula. In addition, these traits and alleles were associated with low spring precipitation, which suggests that trichome development in fruits and pedicels might be involved in climatic adaptation. Thus, we show that the combination of synergistic mutations in a gene regulatory circuit has driven evolutionary innovations in fruit trichome patterning in Arabidopsis.

Capturing response differences of species distribution to climate and human pressures by incorporating local adaptation: Implications for the conservation of a critically endangered species

Considering local adaptation has been increasingly involved in forecasting species distributions under climate change and the management of species conservation. Herein, we take the critically endangered Chinese giant salamander (Andrias davidianus) that has both a low dispersal ability and distinct population divergence in different regions as an example. Basin-scale models that represent different populations in the Huanghe River Basin (HRB), the Yangtze River Basin (YRB), and the Pearl River Basin (PRB) were established using ensemble species distribution models. The species ranges under the future human population density (HPD) and climate change were predicted, and the range loss was evaluated for local basins in 2050 and 2070. Our results showed that the predominant factors affecting species distributions differed among basins, and the responses of the species occurrence to HPD and climate factors were distinctly different from northern to southern basins. Future HPD changes would be the most influential factor that engenders negative impacts on the species distribution in all three basins, especially in the HRB. Climate change will likely be less prominent in decreasing the species range, excluding in the YRB and PRB under the highest-emissions scenario in 2050. Overall, the high-emissions scenario would more significantly aggravate the negative impacts produced by HPD change in both 2050 and 2070, with maximum losses of species ranges in the HRB, YRB, and PRB of 83.4%, 60.0%, and 53.5%, respectively, under the scenarios of the combined impacts of HPD and climate changes. We proposed adapted conservation policies to effectively protect the habitat of this critically endangered animal in different basins based on the outcomes. Our research addresses the importance of incorporating local adaptation into species distribution modeling to inform conservation and management decisions.

Genetic data improves niche model discrimination and alters the direction and magnitude of climate change forecasts

Ecological niche models (ENMs) have classically operated under the simplifying assumptions that there are no barriers to gene flow, species are genetically homogeneous (i.e., no population-specific local adaptation), and all individuals share the same niche. Yet, these assumptions are violated for most broadly distributed species. Here, we incorporate genetic data from the widespread riparian tree species narrowleaf cottonwood (Populus angustifolia) to examine whether including intraspecific genetic variation can alter model performance and predictions of climate change impacts. We found that (1) P. angustifolia is differentiated into six genetic groups across its range from México to Canada and (2) different populations occupy distinct climate niches representing unique ecotypes. Comparing model discriminatory power, (3) all genetically informed ecological niche models (gENMs) outperformed the standard species-level ENM (3-14% increase in AUC; 1-23% increase in pROC). Furthermore, (4) gENMs predicted large differences among ecotypes in both the direction and magnitude of responses to climate change and (5) revealed evidence of niche divergence, particularly for the Eastern Rocky Mountain ecotype. (6) Models also predicted progressively increasing fragmentation and decreasing overlap between ecotypes. Contact zones are often hotspots of diversity that are critical for supporting species' capacity to respond to present and future climate change, thus predicted reductions in connectivity among ecotypes is of conservation concern. We further examined the generality of our findings by comparing our model developed for a higher elevation Rocky Mountain species with a related desert riparian cottonwood, P. fremontii. Together our results suggest that incorporating intraspecific genetic information can improve model performance by addressing this important source of variance. gENMs bring an evolutionary perspective to niche modeling and provide a truly "adaptive management" approach to support conservation genetic management of species facing global change.

Integrating intraspecific variation in species distribution models by quantifying niche differentiation

Intraspecific variation provides insight into heterogeneous demography and adaptive history across distribution ranges of organisms. Most species distribution models assume that species respond to the environment as a single undifferentiated entity across their entire distribution. However, populations occupying different niches might differ in their ability to cope with climate change. Here, we assessed potential climatic niche differentiation at the species and subspecies levels and identified the palaeoclimatic range of three cold-adapted, low-dispersal beetle species: Carabus irregularis, Platycerus albisomni and Platycerus takakuwai. Our results showed that: (1) MaxEnt models incorporating information derived from intraspecific variation outperformed the species-level models; (2) tests of niche similarity revealed niche conservatism in most subspecies, except for two subspecies of C. irregularis, C. i. irregularis and C. i. bucephalus; and (3) historical predictions suggested substantial shifts within species ranges, with multiple glacial refugia during the Last Glacial Maximum. In conclusion, we recommend closer examination of intraspecific variation when predicting species distributions, in order to obtain more accurate generalizations regarding range shifts under climate change.

Molecular systematics and phylogeography of a widespread Neotropical avian lineage: evidence for cryptic speciation with protracted gene flow throughout the Late Quaternary

Here we use an integrative approach, including coalescent-based methods, isolation–migration and species distribution models, to infer population structure, divergence times and diversification in the two species of the genus Cymbilaimus (Aves, Thamnophilidae). Our results support a recent and rapid diversification with both incomplete lineage sorting and gene flow shaping the evolutionary history of Cymbilaimus. The spatio-temporal pattern of cladogenesis suggests that Cymbilaimus originated in the north/western portion of cis-Andean South America and then diversified into the Brazilian Shield and Central America after consolidation of the modern Amazonian drainage and the Andean range. This evolutionary scenario is explained by cycles of range expansion and dispersal, followed by isolation, and recurrent gene flow, during the last 1.2 Myr. Our results agree with those recently reported for other closely related suboscine lineages, whereby the window of introgression between closely related taxa remains open for up to a few million years after their original split. In Cymbilaimus, introgression was recurrent between C. lineatus and C. sanctaemariae, even after they acquired vocal and ecological differentiation, supporting the claim that at least in Neotropical suboscines, full reproductive compatibility may take millions of years to evolve and cannot be interpreted as synonymous with a lack of speciation.

Toward reliable habitat suitability and accessibility models in an era of multiple environmental stressors

Global biodiversity declines, largely driven by climate and land-use changes, urge the development of transparent guidelines for effective conservation strategies. Species distribution modeling (SDM) is a widely used approach for predicting potential shifts in species distributions, which can in turn support ecological conservation where environmental change is expected to impact population and community dynamics. Improvements in SDM accuracy through incorporating intra- and interspecific processes have boosted the SDM field forward, but simultaneously urge harmonizing the vast array of SDM approaches into an overarching, widely adoptable, and scientifically justified SDM framework. In this review, we first discuss how climate warming and land-use change interact to govern population dynamics and species' distributions, depending on species' dispersal and evolutionary abilities. We particularly emphasize that both land-use and climate change can reduce the accessibility to suitable habitat for many species, rendering the ability of species to colonize new habitat and to exchange genetic variation a crucial yet poorly implemented component of SDM. We then unite existing methodological SDM practices that aim to increase model accuracy through accounting for multiple global change stressors, dispersal, or evolution, while shifting our focus to model feasibility. We finally propose a roadmap harmonizing model accuracy and feasibility, applicable to both common and rare species, particularly those with poor dispersal abilities. This roadmap (a) paves the way for an overarching SDM framework allowing comparison and synthesis of different SDM studies and (b) could advance SDM to a level that allows systematic integration of SDM outcomes into effective conservation plans.

Distribution modelling of an introduced species: do adaptive genetic markers affect potential range?

Biological invasions have increased in the last few decades mostly due to anthropogenic causes such as globalization of trade. Because invaders sometimes cause large economic losses and ecological disturbances, estimating their origin and potential geographical ranges is useful. Drosophila subobscura is native to the Old World but was introduced in the New World in the late 1970s and spread widely. We incorporate information on adaptive genetic markers into ecological niche modelling and then estimate the most probable geographical source of colonizers; evaluate whether the genetic bottleneck experienced by founders affects their potential distribution; and finally test whether this species has spread to all its potential suitable habitats worldwide. We find the environmental space occupied by this species in its native and introduced distributions are notably the same, although the introduced niche has shifted slightly towards higher temperature and lower precipitation. The genetic bottleneck of founding individuals was a key factor limiting the spread of this introduced species. We also find that regions in the Mediterranean and north-central Portugal show the highest probability of being the origin of the colonizers. Using genetically informed environmental niche modelling can enhance our understanding of the initial colonization and spread of invasive species, and also elucidate potential areas of future expansions worldwide.

Ecological, genetic and evolutionary drivers of regional genetic differentiation in Arabidopsis thaliana

BACKGROUND

Disentangling the drivers of genetic differentiation is one of the cornerstones in evolution. This is because genetic diversity, and the way in which it is partitioned within and among populations across space, is an important asset for the ability of populations to adapt and persist in changing environments. We tested three major hypotheses accounting for genetic differentiation-isolation-by-distance (IBD), isolation-by-environment (IBE) and isolation-by-resistance (IBR)-in the annual plant Arabidopsis thaliana across the Iberian Peninsula, the region with the largest genomic diversity. To that end, we sampled, genotyped with genome-wide SNPs, and analyzed 1772 individuals from 278 populations distributed across the Iberian Peninsula.

RESULTS

IBD, and to a lesser extent IBE, were the most important drivers of genetic differentiation in A. thaliana. In other words, dispersal limitation, genetic drift, and to a lesser extent local adaptation to environmental gradients, accounted for the within- and among-population distribution of genetic diversity. Analyses applied to the four Iberian genetic clusters, which represent the joint outcome of the long demographic and adaptive history of the species in the region, showed similar results except for one cluster, in which IBR (a function of landscape heterogeneity) was the most important driver of genetic differentiation. Using spatial hierarchical Bayesian models, we found that precipitation seasonality and topsoil pH chiefly accounted for the geographic distribution of genetic diversity in Iberian A. thaliana.

CONCLUSIONS

Overall, the interplay between the influence of precipitation seasonality on genetic diversity and the effect of restricted dispersal and genetic drift on genetic differentiation emerges as the major forces underlying the evolutionary trajectory of Iberian A. thaliana.

Niche divergence corresponds to genetic differentiation within the parrot-beaked tortoise Homopus areolatus (Reptilia: Testudinidae), endemic to South Africa

We assessed genetic differentiation and habitat suitability for Homopus areolatus during current and Last Glacial Maximum (LGM) conditions. The ND4 locus retrieved two monophyletic mtDNA clades with lower diversity in clade 1, in the west, than in clade 2, in the south-east. Clade 1 showed a north–south and clade 2 a west-to-east genetic divergence, and the clades co-occur in the syntaxis zone of the Cape Fold Mountains. The clades occupy distinct niches with limited overlap. Rainfall seasonality contributed most to habitat suitability, with clade 1 being restricted to winter rainfall and clade 2 to all-year rainfall regions. Precipitation variables contributed 90% and 60%, respectively, to habitat suitability of clades 1 and 2, with temperature, particularly mean temperature of the driest quarter, being of greater importance for clade 2 than clade 1. Suitable habitat shrank from the LGM to current conditions, probably due to reduced rainfall in the west and higher temperatures in most regions. We conclude that patterns of genetic divergence are strongly associated with ecological niche divergence of H. areolatus clades. More studies are needed to assess the taxonomic status of clade 1, particularly in view of its shrinking habitat due to climate change and anthropogenic factors.

Locally-adapted reproductive photoperiodism determines population vulnerability to climate change in burying beetles

Understanding how phenotypic traits vary among populations inhabiting different environments is critical for predicting a species' vulnerability to climate change. Yet, little is known about the key functional traits that determine the distribution of populations and the main mechanisms-phenotypic plasticity vs. local adaptation-underlying intraspecific functional trait variation. Using the Asian burying beetle Nicrophorus nepalensis, we demonstrate that mountain ranges differing in elevation and latitude offer unique thermal environments in which two functional traits-thermal tolerance and reproductive photoperiodism-interact to shape breeding phenology. We show that populations on different mountain ranges maintain similar thermal tolerances, but differ in reproductive photoperiodism. Through common garden and reciprocal transplant experiments, we confirm that reproductive photoperiodism is locally adapted and not phenotypically plastic. Accordingly, year-round breeding populations on mountains of intermediate elevation are likely to be most susceptible to future warming because maladaptation occurs when beetles try to breed at warmer temperatures.

Experimental migration upward in elevation is associated with strong selection on life history traits

One of the strongest biological impacts of climate change has been the movement of species poleward and upward in elevation. Yet, what is not clear is the extent to which the spatial distribution of locally adapted lineages and ecologically important traits may also shift with continued climate change. Here, we take advantage of a transplant experiment mimicking up-slope seed dispersal for a suite of ecologically diverse populations of yellow monkeyflower (Mimulus guttatus sensu lato) into a high-elevation common garden during an extreme drought period in the Sierra Nevada mountains, California, USA. We use a demographic approach to quantify fitness and test for selection on life history traits in local versus lower-elevation populations and in normal versus drought years to test the potential for up-slope migration and phenotypic selection to alter the distribution of key life history traits in montane environments. We find that lower-elevation populations tend to outperform local populations, confirming the potential for up-slope migration. Although selection generally favored some local montane traits, including larger flowers and larger stem size at flowering, drought conditions tended to select for earlier flowering typical of lower-elevation genotypes. Taken together, this suggests that monkeyflower lineages moving upward in elevation could experience selection for novel trait combinations, particularly under warmer and drier conditions that are predicted to occur with continued climate change.

A hierarchical Bayesian Beta regression approach to study the effects of geographical genetic structure and spatial autocorrelation on species distribution range shifts

Global climate change (GCC) may be causing distribution range shifts in many organisms worldwide. Multiple efforts are currently focused on the development of models to better predict distribution range shifts due to GCC. We addressed this issue by including intraspecific genetic structure and spatial autocorrelation (SAC) of data in distribution range models. Both factors reflect the joint effect of ecoevolutionary processes on the geographical heterogeneity of populations. We used a collection of 301 georeferenced accessions of the annual plant Arabidopsis thaliana in its Iberian Peninsula range, where the species shows strong geographical genetic structure. We developed spatial and nonspatial hierarchical Bayesian models (HBMs) to depict current and future distribution ranges for the four genetic clusters detected. We also compared the performance of HBMs with Maxent (a presence-only model). Maxent and nonspatial HBMs presented some shortcomings, such as the loss of accessions with high genetic admixture in the case of Maxent and the presence of residual SAC for both. As spatial HBMs removed residual SAC, these models showed higher accuracy than nonspatial HBMs and handled the spatial effect on model outcomes. The ease of modelling and the consistency among model outputs for each genetic cluster was conditioned by the sparseness of the populations across the distribution range. Our HBMs enrich the toolbox of software available to evaluate GCC-induced distribution range shifts by considering both genetic heterogeneity and SAC, two inherent properties of any organism that should not be overlooked.

Incorporating local adaptation into forecasts of species' distribution and abundance under climate change

Populations of many species are genetically adapted to local historical climate conditions. Yet most forecasts of species' distributions under climate change have ignored local adaptation (LA), which may paint a false picture of how species will respond across their geographic ranges. We review recent studies that have incorporated intraspecific variation, a potential proxy for LA, into distribution forecasts, assess their strengths and weaknesses, and make recommendations for how to improve forecasts in the face of LA. The three methods used so far (species distribution models, response functions, and mechanistic models) reflect a trade-off between data availability and the ability to rigorously demonstrate LA to climate. We identify key considerations for incorporating LA into distribution forecasts that are currently missing from many published studies, including testing the spatial scale and pattern of LA, the confounding effects of LA to nonclimatic or biotic drivers, and the need to incorporate empirically based dispersal or gene flow processes. We suggest approaches to better evaluate these aspects of LA and their effects on species-level forecasts. In particular, we highlight demographic and dynamic evolutionary models as promising approaches to better integrate LA into forecasts, and emphasize the importance of independent model validation. Finally, we urge closer examination of how LA will alter the responses of central vs. marginal populations to allow stronger generalizations about changes in distribution and abundance in the face of LA.

Incorporating Local Adaptation Into Species Distribution Modeling of Paeonia mairei, an Endemic Plant to China

Paeonia (Paeoniaceae), a culturally and economically important plant genus, has an isolated taxonomy while the evolution of this genus is unclear. A plant species endemic to southwest China, Paeonia mairei is precious germplasm for evolution-related research and cultivar improvement, and its conservation is urgent. However, little is known about its patterns of habitat distribution and responses to climate change. Using 98 occurrence sites and data of 19 bioclimatic variables, we conducted principal component analysis and hierarchical cluster analysis to delineate different climatic populations. Maximum entropy algorithm (MaxEnt) was applied to each population to evaluate the importance of environmental variables in shaping their distribution, and to identify distribution shifts under different climate change scenarios. We also applied MaxEnt to all of the P. mairei presence sites (P_Whole) to evaluate the need to construct separate species distribution models for separate populations rather than a common approach by treating them as a whole. Our results show that local adaptation exists within the distribution range of P. mairei and that all presence sites were clustered into a western population (P_West) and an eastern population (P_East). Two variables (precipitation of the driest month and temperature seasonality) are important when shaping the distribution of P_West, and another two variables (mean diurnal range and mean temperature of the wettest quarter) are important for P_East. Both populations are likely to shift upward under climate change, while P_East may lose most current suitable areas while P_West may not. P_Whole produced a narrower area compared to the combination of P_West and P_East but a suitable area (south Chongqing) may have been missed in the prediction. Accordingly, a population-based approach in constructing a species distribution model is needed to provide a detailed appreciation of the distribution of P. mairei, allowing for a population-based conservation strategy. In this case, it could include assisted migration to new and suitable distribution areas for P_West and in situ conservation in high elevation regions for P_East. The results of our study could be a useful reference for implementing the long-term conservation and further research of P. mairei.

Combining Bayesian genetic clustering and ecological niche modeling: Insights into wolf intraspecific genetic structure

The distribution of intraspecific genetic variation and how it relates to environmental factors is of increasing interest to researchers in macroecology and biogeography. Recent studies investigated the relationships between the environment and patterns of intraspecific genetic variation across species ranges but only few rigorously tested the relation between genetic groups and their ecological niches. We quantified the relationship of genetic differentiation (F ST) and the overlap of ecological niches (as measured by n-dimensional hypervolumes) among genetic groups resulting from spatial Bayesian genetic clustering in the wolf (Canis lupus) in the Italian peninsula. Within the Italian wolf population, four genetic clusters were detected, and these clusters showed different ecological niches. Moreover, different wolf clusters were significantly related to differences in land cover and human disturbance features. Such differences in the ecological niches of genetic clusters should be interpreted in light of neutral processes that hinder movement, dispersal, and gene flow among the genetic clusters, in order to not prematurely assume any selective or adaptive processes. In the present study, we found that both the plasticity of wolves-a habitat generalist-to cope with different environmental conditions and the occurrence of barriers that limit gene flow lead to the formation of genetic intraspecific genetic clusters and their distinct ecological niches.

Quantifying temporal change in plant population attributes: insights from a resurrection approach

Rapid evolution in annual plants can be quantified by comparing phenotypic and genetic changes between past and contemporary individuals from the same populations over several generations. Such knowledge will help understand the response of plants to rapid environmental shifts, such as the ones imposed by global climate change. To that end, we undertook a resurrection approach in Spanish populations of the annual plant Arabidopsis thaliana that were sampled twice over a decade. Annual weather records were compared to their historical records to extract patterns of climatic shifts over time. We evaluated the differences between samplings in flowering time, a key life-history trait with adaptive significance, with a field experiment. We also estimated genetic diversity and differentiation based on neutral nuclear markers and nucleotide diversity in candidate flowering time (FRI and FLC) and seed dormancy (DOG1) genes. The role of genetic drift was estimated by computing effective population sizes with the temporal method. Overall, two climatic scenarios were detected: intense warming with increased precipitation and moderate warming with decreased precipitation. The average flowering time varied little between samplings. Instead, within-population variation in flowering time exhibited a decreasing trend over time. Substantial temporal changes in genetic diversity and differentiation were observed with both nuclear microsatellites and candidate genes in all populations, which were interpreted as the result of natural demographic fluctuations. We conclude that drought stress caused by moderate warming with decreased precipitation may have the potential to reduce within-population variation in key life-cycle traits, perhaps as a result of stabilizing selection on them, and to constrain the genetic differentiation over time. Besides, the demographic behaviour of populations probably accounts for the substantial temporal patterns of genetic variation, while keeping rather constant those of phenotypic variation.

Temperature fine-tunes Mediterranean Arabidopsis thaliana life-cycle phenology geographically

To understand how adaptive evolution in life-cycle phenology operates in plants, we need to unravel the effects of geographic variation in putative agents of natural selection on life-cycle phenology by considering all key developmental transitions and their co-variation patterns. We address this goal by quantifying the temperature-driven and geographically varying relationship between seed dormancy and flowering time in the annual Arabidopsis thaliana across the Iberian Peninsula. We used data on genetic variation in two major life-cycle traits, seed dormancy (DSDS50) and flowering time (FT), in a collection of 300 A. thaliana accessions from the Iberian Peninsula. The geographically varying relationship between life-cycle traits and minimum temperature, a major driver of variation in DSDS50 and FT, was explored with geographically weighted regressions (GWR). The environmentally varying correlation between DSDS50 and FT was analysed by means of sliding window analysis across a minimum temperature gradient. Maximum local adjustments between minimum temperature and life-cycle traits were obtained in the southwest Iberian Peninsula, an area with the highest minimum temperatures. In contrast, in off-southwest locations, the effects of minimum temperature on DSDS50 were rather constant across the region, whereas those of minimum temperature on FT were more variable, with peaks of strong local adjustments of GWR models in central and northwest Spain. Sliding window analysis identified a minimum temperature turning point in the relationship between DSDS50 and FT around a minimum temperature of 7.2 °C. Above this minimum temperature turning point, the variation in the FT/DSDS50 ratio became rapidly constrained and the negative correlation between FT and DSDS50 did not increase any further with increasing minimum temperatures. The southwest Iberian Peninsula emerges as an area where variation in life-cycle phenology appears to be restricted by the duration and severity of the hot summer drought. The temperature-driven varying relationship between DSDS50 and FT detected environmental boundaries for the co-evolution between FT and DSDS50 in A. thaliana. In the context of global warming, we conclude that A. thaliana phenology from the southwest Iberian Peninsula, determined by early flowering and deep seed dormancy, might become the most common life-cycle phenotype for this annual plant in the region.

Genetically informed ecological niche models improve climate change predictions

We examined the hypothesis that ecological niche models (ENMs) more accurately predict species distributions when they incorporate information on population genetic structure, and concomitantly, local adaptation. Local adaptation is common in species that span a range of environmental gradients (e.g., soils and climate). Moreover, common garden studies have demonstrated a covariance between neutral markers and functional traits associated with a species' ability to adapt to environmental change. We therefore predicted that genetically distinct populations would respond differently to climate change, resulting in predicted distributions with little overlap. To test whether genetic information improves our ability to predict a species' niche space, we created genetically informed ecological niche models (gENMs) using Populus fremontii (Salicaceae), a widespread tree species in which prior common garden experiments demonstrate strong evidence for local adaptation. Four major findings emerged: (i) gENMs predicted population occurrences with up to 12-fold greater accuracy than models without genetic information; (ii) tests of niche similarity revealed that three ecotypes, identified on the basis of neutral genetic markers and locally adapted populations, are associated with differences in climate; (iii) our forecasts indicate that ongoing climate change will likely shift these ecotypes further apart in geographic space, resulting in greater niche divergence; (iv) ecotypes that currently exhibit the largest geographic distribution and niche breadth appear to be buffered the most from climate change. As diverse agents of selection shape genetic variability and structure within species, we argue that gENMs will lead to more accurate predictions of species distributions under climate change.