Conserving threatened riparian ecosystems in the American West: Precipitation gradients and river networks drive genetic connectivity and diversity in a foundation riparian tree ( Populus angustifolia )

Stacked distribution models predict climate-driven loss of variation in leaf phenology at continental scales

Climate change is having profound effects on species distributions and is likely altering the distribution of genetic variation across landscapes. Maintaining population genetic diversity is essential for the survival of species facing rapid environmental change, and variation loss will further ecological and evolutionary change. We used trait values of spring foliar leaf-out phenology of 400 genotypes from three geographically isolated populations of Populus angustifolia grown under common conditions, in concert with stacked species distribution modeling, to ask: (a) How will climate change alter phenological variation across the P. angustifolia species-range, and within populations; and (b) will the distribution of phenological variation among and within populations converge (become more similar) in future climatic conditions? Models predicted a net loss of phenological variation in future climate scenarios on 20-25% of the landscape across the species’ range, with the trailing edge population losing variation on as much as 47% of the landscape. Our models also predicted that population’s phenological trait distributions will become more similar over time. This stacked distribution model approach allows for the identification of areas expected to experience the greatest loss of genetically based functional trait variation and areas that may be priorities to conserve as future genetic climate refugia.

Integrating stacked distribution models with genetically-based trait diversity of Populus angustifolia reveals how phenological variation can change differently across populations in response to climate change.

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.

Evidence of spatial genetic structure in a snow leopard population from Gansu, China

Understanding the spatial structure of genetic diversity provides insights into a populations' genetic status and enables assessment of its capacity to counteract the effects of genetic drift. Such knowledge is particularly scarce for the snow leopard, a conservation flagship species of Central Asia mountains. Focusing on a snow leopard population in the Qilian mountains of Gansu Province, China, we characterised the spatial genetic patterns by incorporating spatially explicit indices of diversity and multivariate analyses, based on different inertia levels of Principal Component Analysis (PCA). We compared two datasets differing in the number of loci and individuals. We found that genetic patterns were significantly spatially structured and were characterised by a broad geographical division coupled with a fine-scale cline of differentiation. Genetic admixture was detected in two adjoining core areas characterised by higher effective population size and allelic diversity, compared to peripheral localities. The power to detect significant spatial relationships depended primarily on the number of loci, and secondarily on the number of PCA axes. Spatial patterns and indices of diversity highlighted the cryptic structure of snow leopard genetic diversity, likely driven by its ability to disperse over large distances. In combination, the species' low allelic richness and large dispersal ability result in weak genetic differentiation related to major geographical features and isolation by distance. This study illustrates how cryptic genetic patterns can be investigated and analysed at a fine spatial scale, providing insights into the spatially variable isolation effects of both geographic distance and landscape resistance.

Genetic connectivity of two marine gastropods in the Mediterranean Sea: seascape genetics reveals species-specific oceanographic drivers of gene flow

Oceanographic features such as currents, waves, temperature and salinity, together with life history traits, control patterns and rates of gene flow and contribute to shaping the population genetic structure of marine organisms. Seascape genetics is an emerging discipline that adopts a spatially explicit approach to examine biotic and abiotic factors that drive gene flow in marine environments. In this study, we examined factors that contribute to genetic differentiation in two coastal Mediterranean gastropods whose geographical ranges overlap but which inhabit different environments. The two species differ in several life history traits and in their dispersal capabilities. Genetic differentiation was relatively low for the trochid species Gibbula divaricata (F_ST  =0.059), and high for the vermetid species Dendropoma lebeche (F_ST  =0.410). Salinity emerged as the most important variable explaining the genetic structure of both species; sea surface temperature was also important for G. divaricata. For the more sessile D. lebeche, the coastline was predicted to provide important pathways for stepping-stone connectivity and gene flow. Our results provide a greater understanding of the factors influencing marine population connectivity, which may be useful to guide marine conservation and management in the Mediterranean.

Predictors of phylogeographic structure among codistributed taxa across the complex Australian monsoonal tropics

Differences in the geographic scale and depth of phylogeographic structure across codistributed taxa can reveal how microevolutionary processes such as population isolation and persistence drive diversification. In turn, environmental heterogeneity, species' traits, and historical biogeographic barriers may influence the potential for isolation and persistence. Using extensive SNP data and a combination of population genetic summary statistics and landscape genomic analyses, we explored predictors of the scale and depth of phylogeographic structure in codistributed lizard taxa from the topographically and climatically complex monsoonal tropics (AMT) of Australia. We first resolved intraspecific lineages and then tested whether genetic divergence across space within lineages is related to isolation by distance, resistance and/or environment and whether these factors differ across genera or between rock-related versus habitat generalist taxa. We then tested whether microevolutionary processes within lineages explain differences in the geographic scale and depth of intraspecific phylogeographic lineages. The results indicated that landscape predictors of phylogeographic structure differ between taxa. Within lineages, there was prevalent isolation by distance, but the strength of isolation by distance is independent of the taxonomic family, habitat specialization, and climate. Isolation by environment is the strongest predictor of landscape-scale genetic divergence for all taxa, with both temperature and precipitation acting as limiting factors. The strength of isolation by distance does not predict the geographic scale of the phylogeographic structure. However, more localized lineages had higher mean individual heterozygosity and less negative Tajima's D. This result implies that finer-scale phylogeographic structuring within species is associated with larger and more stable populations and, hence, persistence.

Heterozygous Trees Rebound the Fastest after Felling by Beavers to Positively Affect Arthropod Community Diversity

Although genetic diversity within stands of trees is known to have community-level consequences, whether such effects are present at an even finer genetic scale is unknown. We examined the hypothesis that genetic variability (heterozygosity) within an individual plant would affect its dependent community, which adds a new dimension to the importance of genetic diversity. Our study contrasted foliar arthropod community diversity and microsatellite marker-derived measures of genetic diversity of cottonwood (Populus fremontii) trees that had been felled by beavers (Castor canadensis) and were resprouting, relative to adjacent standing, unfelled trees. Three patterns emerged: 1. Productivity (specific leaf area), phytochemical defenses (salicortin), and arthropod community richness, abundance, and diversity were positively correlated with the heterozygosity of individual felled trees, but not with that of unfelled trees; 2. These relationships were not explained by population substructure, genetic relatedness of the trees, or hybridization; 3. The underlying mechanism appears to be that beaver herbivory stimulates increased productivity (i.e., 2× increase from the most homozygous to the most heterozygous tree) that is the greatest in more heterozygous trees. Salicortin defenses in twigs were also expressed at higher concentrations in more heterozygous trees (i.e., 3× increase from the most homozygous to the most heterozygous tree), which suggests that this compound may dissuade further herbivory by beavers, as has been found for other mammalian herbivores. We suggest that high stress to trees as a consequence of felling reveals a heterozygosity–productivity linkage, which in turn is attractive to arthropods. Although experiments are required to demonstrate causality, these results link the genetic diversity of individual trees to community diversity, supporting the hypothesis that interactions among foundation species (beavers and trees) have community-level effects, and underscores the importance of genetic diversity for biodiversity, conservation, and restoration.

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.

The use and misuse of regression models in landscape genetic analyses

The field of landscape genetics has been rapidly evolving, adopting and adapting analytical frameworks to address research questions. Current studies are increasingly using regression-based frameworks to infer the individual contributions of landscape and habitat variables on genetic differentiation. This paper outlines appropriate and inappropriate uses of multiple regression for these purposes, and demonstrates through simulation the limitations of different analytical frameworks for making correct inference. Of particular concern are recent studies seeking to explain genetic differences by fitting regression models with effective distance variables calculated independently on separate landscape resistance surfaces. When moving across the landscape, organisms cannot respond independently and uniquely to habitat and landscape features. Analyses seeking to understand how landscape features affect gene flow should model a single conductance or resistance surface as a parameterized function of relevant spatial covariates, and estimate the values of these parameters by linking a single set of resistance distances to observed genetic dissimilarity via a loss function. While this loss function may involve a regression-like step, the associated nuisance parameters are not interpretable in terms of organismal movement and should not be conflated with what is actually of interest: the mapping between spatial covariates and conductance/resistance. The growth and evolution of landscape genetics as a field has been rapid and exciting. It is the goal of this paper to highlight past missteps and demonstrate limitations of current approaches to ensure that future use of regression models will appropriately consider the process being modeled, which will provide clarity to model interpretation.

Adaptive capacity in the foundation tree species Populus fremontii: implications for resilience to climate change and non-native species invasion in the American Southwest

Populus fremontii (Fremont cottonwood) is recognized as one of the most important foundation tree species in the southwestern USA and northern Mexico because of its ability to structure communities across multiple trophic levels, drive ecosystem processes and influence biodiversity via genetic-based functional trait variation. However, the areal extent of P. fremontii cover has declined dramatically over the last century due to the effects of surface water diversions, non-native species invasions and more recently climate change. Consequently, P. fremontii gallery forests are considered amongst the most threatened forest types in North America. In this paper, we unify four conceptual areas of genes to ecosystems research related to P. fremontii's capacity to survive or even thrive under current and future environmental conditions: (i) hydraulic function related to canopy thermal regulation during heat waves; (ii) mycorrhizal mutualists in relation to resiliency to climate change and invasion by the non-native tree/shrub, Tamarix; (iii) phenotypic plasticity as a mechanism for coping with rapid changes in climate; and (iv) hybridization between P. fremontii and other closely related Populus species where enhanced vigour of hybrids may preserve the foundational capacity of Populus in the face of environmental change. We also discuss opportunities to scale these conceptual areas from genes to the ecosystem level via remote sensing. We anticipate that the exploration of these conceptual areas of research will facilitate solutions to climate change with a foundation species that is recognized as being critically important for biodiversity conservation and could serve as a model for adaptive management of arid regions in the southwestern USA and around the world.

Candidate gene SNP variation in floodplain populations of pedunculate oak (Quercus robur L.) near the species' southern range margin: Weak differentiation yet distinct associations with water availability

Populations residing near species' low-latitude range margins (LLMs) often occur in warmer and drier environments than those in the core range. Thus, their genetic composition could be shaped by climatic drivers that differ from those occurring at higher latitudes, resulting in potentially adaptive variants of conservation value. Such variants could facilitate the adaptation of populations from other portions of the geographical range to similar future conditions anticipated under ongoing climate change. However, very few studies have assessed standing genetic variation at potentially adaptive loci in natural LLM populations. We investigated standing genetic variation at single nucleotide polymorphisms (SNPs) located within 117 candidate genes and its links to putative climatic selection pressures across 19 pedunculate oak (Quercus robur L.) populations distributed along a regional climatic gradient near the species' southern range margin in southeastern Europe. These populations are restricted to floodplain forests along large lowland rivers, whose hydric regime is undergoing significant shifts under modern rapid climate change. The populations showed very weak geographical structure, suggesting extensive genetic connectivity and gene flow or shared ancestry. We identified eight (6.2%) positive F_ST -outlier loci, and genotype-environment association analyses revealed consistent associations between SNP allele frequencies and several climatic variables linked to water availability. A total of 61 associations involving 37 SNPs (28.5%) from 35 annotated genes provided important insights into putative functional mechanisms in our system. Our findings provide empirical support for the role of LLM populations as sources of potentially adaptive variation that could enhance species' resilience to climate change-related pressures.

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.

Genetic diversity and population structure of black cottonwood (Populus deltoides) revealed using simple sequence repeat markers

Background

Black cottonwood (Populus deltoides) is one of the keystone forest tree species, and has become the main breeding parents in poplar hybrid breeding. However, the genetic diversity and population structure of the introduced resources are not fully understood.

Results

In the present study, five loci containing null alleles were excluded and 15 pairs of SSR (simple sequence repeat) primers were used to analyze the genetic diversity and population structure of 384 individuals from six provenances (Missouri, Iowa, Washington, Louisiana, and Tennessee (USA), and Quebec in Canada) of P. deltoides. Ultimately, 108 alleles (N_a) were detected; the expected heterozygosity (H_e) per locus ranged from 0.070 to 0.905, and the average polymorphic information content (PIC) was 0.535. The provenance ‘Was’ had a relatively low genetic diversity, while ‘Que’, ‘Lou’, and ‘Ten’ provenances had high genetic diversity, with Shannon’s information index (I) above 1.0. The mean coefficient of genetic differentiation (F_st) and gene flow (N_m) were 0.129 and 1.931, respectively. Analysis of molecular variance (AMOVA) showed that 84.88% of the genetic variation originated from individuals. Based on principal coordinate analysis (PCoA) and STRUCTURE cluster analysis, individuals distributed in the Mississippi River Basin were roughly classified as one group, while those distributed in the St. Lawrence River Basin and Columbia River Basin were classified as another group. The cluster analysis based on the population level showed that provenance ‘Iow’ had a small gene flow and high degree of genetic differentiation compared with the other provenances, and was classified into one group. There was a significant relationship between genetic distance and geographical distance.

Conclusions

P. deltoides resources have high genetic diversity and there is a moderate level of genetic differentiation among provenances. Geographical isolation and natural conditions may be the main factors causing genetic differences among individuals. Individuals reflecting population genetic information can be selected to build a core germplasm bank. Meanwhile, the results could provide theoretical support for the scientific management and efficient utilization of P. deltoides genetic resources, and promote the development of molecular marker-assisted breeding of poplar.

Going with the flow: Intraspecific variation may act as a natural ally to counterbalance the impacts of global change for the riparian species Populus deltoides

The speed and magnitude of global change will have major impacts on riparian ecosystems, thereby leading to greater forest vulnerability. Assessing species' adaptive capacities to provide relevant information for vulnerability assessments remains challenging, especially for nonmodel species like the North American Populus deltoides W. Bartram ex Marshall. The objective of this study was to understand how genomic diversity of this foundation species was shaped by its environment (climate, soil, and biotic interactions) to gauge its adaptive capacity. We used two complementary approaches to get a full portrait of P. deltoides genetic diversity at both the species and whole-genome ranges. First, we used a set of 93 nuclear and three chloroplastic SNP markers in 946 individuals covering most of the species' natural distribution. Then, to measure the degree of intraspecific divergence at the whole-genome level and to support the outlier and genomic-environment association analyses, we used a sequence capture approach on DNA pools. Three distinct lineages for P. deltoides were detected, and their current distribution was associated with abiotic and biotic variations. The comparison between both cpDNA and ncDNA patterns showed that gene flow between the lineages is unbalanced. The southern and northeastern populations may benefit from the input, through river flow, of novel alleles located upstream to their local gene pools. These alleles could migrate from populations that are already adapted to conditions that fit the predicted climates in the receiving local populations, hotter at the northeastern limit and drier in the Central United States. These "preadapted" incoming alleles may help to cope with maladaptation in populations facing changing conditions.

Identifying wildlife corridors for the restoration of regional habitat connectivity: A multispecies approach and comparison of resistance surfaces

Many large-scale connectivity initiatives have been proposed around the world with the aim of maintaining or restoring connectivity to offset the impacts on biodiversity of habitat loss and fragmentation. Frequently, these are based on the requirements of a single focal species of concern, but there is growing attention to identifying connectivity requirements for multi-species assemblages. A number of methods for modelling connectivity have been developed; likewise, different approaches have been used to construct resistance surfaces, the basic input data for connectivity analyses. In this study we modelled connectivity for a multi-species group of vertebrates representative of heavily fragmented forests in north-central Victoria, Australia. For each species, we used least-cost modelling and compared two alternate resistance surfaces, based on species distribution models and on expert opinion, respectively. We integrated the connectivity results across individual species to obtain a multi-species connectivity map for the region. A resistance surface based on expert assessment of the relative use of land-cover classes by the target species was more informative than one based on species distribution models. The former resulted in pathways more strongly aligned with existing patches and strips of native vegetation. In this region, pathways aligned with streams and their associated riparian vegetation have relatively high ecological potential and feasibility to contribute to regional connectivity for the assemblage of forest vertebrates.

Habitat Fragmentation Reduces Genetic Diversity and Connectivity of the Mexican Spotted Owl: A Simulation Study Using Empirical Resistance Models

We evaluated how differences between two empirical resistance models for the same geographic area affected predictions of gene flow processes and genetic diversity for the Mexican spotted owl (Strix occidentalis lucida). The two resistance models represented the landscape under low- and high-fragmentation parameters. Under low fragmentation, the landscape had larger but highly concentrated habitat patches, whereas under high fragmentation, the landscape had smaller habitat patches that scattered across a broader area. Overall habitat amount differed little between resistance models. We tested eight scenarios reflecting a factorial design of three factors: resistance model (low vs. high fragmentation), isolation hypothesis (isolation-by-distance, IBD, vs. isolation-by-resistance, IBR), and dispersal limit of species (200 km vs. 300 km). Higher dispersal limit generally had a positive but small influence on genetic diversity. Genetic distance increased with both geographic distance and landscape resistance, but landscape resistance displayed a stronger influence. Connectivity was positively related to genetic diversity under IBR but was less important under IBD. Fragmentation had a strong negative influence on the spatial patterns of genetic diversity and effective population size (Ns). Despite habitats being more concentrated and less widely distributed, the low-fragmentation landscape had greater genetic diversity than the high-fragmentation landscape, suggesting that highly concentrated but larger habitat patches may provide a genetic refuge for the Mexican spotted owl.