ISOLATION BY RESISTANCE

Variable habitat use supports fine-scale population differentiation of a freshwater piscivore (northern pike, Esox lucius) along salinity gradients in brackish lagoons

In mobile animals, selection pressures resulting from spatio-temporally varying ecological factors often drive adaptations in migration behavior and associated physiological phenotypes. These adaptations may manifest in ecologically and genetically distinct ecotypes within populations. We studied a meta-population of northern pike (Esox lucius) in brackish environments and examined intrapopulation divergence along environmental gradients. Behavioral phenotypes in habitat use were characterized via otolith microchemistry in 120 individuals sampled from brackish lagoons and adjacent freshwater tributaries. We genotyped 1514 individual pike at 33 highly informative genetic markers. The relationship between behavioral phenotype and genotype was examined in a subset of 101 pikes for which both phenotypic and genomic data were available. Thermosaline differences between juvenile and adult life stages indicated ontogenetic shifts from warm, low-saline early habitats towards colder, higher-saline adult habitats. Four behavioral phenotypes were found: Freshwater residents, anadromous, brackish residents, and cross-habitat individuals, the latter showing intermediary habitat use between brackish and freshwater areas. Underlying the behavioral phenotypes were four genotypes, putative freshwater, putative anadromous, and two putatively brackish genotypes. Through phenotype-genotype matching, three ecotypes were identified: (i) a brackish resident ecotype, (ii) a freshwater ecotype expressing freshwater residency or anadromy, and (iii) a previously undescribed intermediary cross-habitat ecotype adapted to intermediate salinities, showing limited reliance on freshwater. Life-time growth of all ecotypes was similar, suggesting comparable fitness. By combining genetic data with lifelong habitat use and growth as a fitness surrogate, our study revealed strong differentiation in response to abiotic environmental gradients, primarily salinity, indicating ecotype diversity in coastal northern pike is higher than previously believed.

Revealing the evolutionary history and contemporary population structure of Pacific salmon in the Fraser River through genome resequencing

The Fraser River once supported massive salmon returns. However, over the last century, the largest returns have consistently been less than half of the recorded historical maximum. There is substantial interest from surrounding communities and governments to increase salmon returns for both human use and functional ecosystems. To generate resources for this endeavor, we resequenced genomes of Chinook (Oncorhynchus tshawytscha), coho (Oncorhynchus kisutch), and sockeye salmon (Oncorhynchus nerka) from the Fraser River at moderate coverage (∼16×). A total of 954 resequenced genomes were analyzed, with 681 collected specifically for this study from tissues sampled between 1997 and 2021. An additional 273 were collected from previous studies. At the species level, Chinook salmon appeared to have 1.6-2.1× more SNPs than coho or sockeye salmon, respectively. This difference may be attributable to large historical declines of coho and sockeye salmon. At the population level, 3 Fraser River genetic groups were identified for each species using principal component and admixture analyses. These were consistent with previous research and supports the continued use of these groups in conservation and management efforts. Environmental factors and a migration barrier were identified as major factors influencing the boundaries of these genetic groups. Additionally, 20 potentially adaptive loci were identified among the genetic groups. This information may be valuable in new management and conservation efforts. Furthermore, the resequenced genomes are an important resource for contemporary genomics research on Fraser River salmon and have been made publicly available.

Testing concordance and conflict in spatial replication of landscape genetics inferences

The degree to which landscape genetics findings can be extrapolated to different areas of a species range is poorly understood. Here, we used a broadly distributed ectothermic lizard (Sceloporus occidentalis, Western Fence lizard) as a model species to evaluate the full role of topography, climate, vegetation, and roads on dispersal and genetic differentiation. We conducted landscape genetics analyses with a total of 119 individuals in five areas within the Sierra Nevada mountain range. Genetic distances calculated from thousands of ddRAD markers were used to optimize landscape resistance surfaces and infer the effects of landscape and topographic features on genetic connectivity. Across study areas, we found a great deal of consistency in the primary environmental gradients impacting genetic connectivity, along with some site-specific differences, and a range in the proportion of genetic variance explained by environmental factors across study sites. High-elevation colder areas were consistently found to be barriers to gene flow, as were areas of high ruggedness and slope. High temperature seasonality and high precipitation during the winter wet season also presented a substantial barrier to gene flow in a majority of study areas. The effect of other landscape variables on genetic differentiation was more idiosyncratic and depended on specific attributes at each site. Across study areas, canyon valleys were always implicated as facilitators to dispersal and key features linking populations and maintaining genetic connectivity, though the relative importance varied in different areas. We emphasize that spatial data layers are complex and multidimensional, and careful consideration of spatial data correlation structure and robust analytic frameworks will be critical to our continued understanding of spatial genetics processes.

Estimation of spatial demographic maps from polymorphism data using a neural network

A fundamental goal in population genetics is to understand how variation is arrayed over natural landscapes. From first principles we know that common features such as heterogeneous population densities and barriers to dispersal should shape genetic variation over space, however there are few tools currently available that can deal with these ubiquitous complexities. Geographically referenced single nucleotide polymorphism (SNP) data are increasingly accessible, presenting an opportunity to study genetic variation across geographic space in myriad species. We present a new inference method that uses geo-referenced SNPs and a deep neural network to estimate spatially heterogeneous maps of population density and dispersal rate. Our neural network trains on simulated input and output pairings, where the input consists of genotypes and sampling locations generated from a continuous space population genetic simulator, and the output is a map of the true demographic parameters. We benchmark our tool against existing methods and discuss qualitative differences between the different approaches; in particular, our program is unique because it infers the magnitude of both dispersal and density as well as their variation over the landscape, and it does so using SNP data. Similar methods are constrained to estimating relative migration rates, or require identity-by-descent blocks as input. We applied our tool to empirical data from North American grey wolves, for which it estimated mostly reasonable demographic parameters, but was affected by incomplete spatial sampling. Genetic based methods like ours complement other, direct methods for estimating past and present demography, and we believe will serve as valuable tools for applications in conservation, ecology and evolutionary biology. An open source software package implementing our method is available from https://github.com/kr-colab/mapNN.

Genetic patterns reveal geographic drivers of divergence in silvereyes (Zosterops lateralis)

Identifying mechanisms that drive population divergence under varying geographic and ecological scenarios can inform our understanding of evolution and speciation. In particular, analysis of genetic data from island populations with known colonisation timelines allows us to identify potential source populations of diverging island subspecies and current relationships among populations. Silvereyes (Zosterops lateralis) are a small passerine that have served as a valuable study system to investigate evolutionary patterns on both large and small geographic scales. We examined genetic relatedness and diversity of two silvereye subspecies, the mainland Z. l. cornwalli and island Z. l. chlorocephalus, and used 18 077 single nucleotide polymorphisms (SNPs), to compare locations across southeast Queensland, Australia. Although silvereyes are prolific island colonisers our findings revealed population divergence over relatively small spatial scales was strongly influenced by geographic isolation mediated by water barriers. Strong genetic connectivity was displayed between mainland sites, but minimal inter-island connectivity was shown despite comparable sampling distances. Genetic diversity analysis showed little difference in heterozygosity between island and mainland populations, but lower inbreeding scores among the island populations. Our study confirmed the range of the Z. l. chlorocephalus subspecies throughout the southern Great Barrier Reef. Our results show that water barriers and not geographic distance per se are important in driving incipient divergence in island populations. This helps to explain the relatively high number of phenotypically differentiated, but often geographically proximate, island silvereye subspecies compared to a lower number of phenotypically less well-defined Australian continental subspecies.

Reconstructing the Global Migration History of Phytophthora infestans Toward Colombia

The evolution of new variants of plant pathogens is one of the biggest challenges to controlling and managing plant diseases. Of the forces driving these evolutionary processes, global migration events are particularly important for widely distributed diseases such as potato late blight, caused by the oomycete Phytophthora infestans. However, little is known about its migration routes outside North America and Europe. This work used genotypic data from population studies to elucidate the migration history originating the Colombian P. infestans population. For this purpose, a dataset of 1,706 P. infestans genotypes was recollected, representing North and South America, Europe, and Asia. Descriptive analysis and historical records from North America and Europe were used to propose three global migration hypotheses, differing on the origin of the disease (Mexico or Peru) and the hypothesis that it returned to South America from Europe. These scenarios were tested using approximate Bayesian computation. According to this analysis, the most probable scenario (posterior probability = 0.631) was the one proposing a Peruvian origin for P. infestans, an initial migration toward Colombia and Mexico, and a later event from Mexico to the United States and then to Europe and Asia, with no return to northern South America. In Colombia, the scenario considering a single migration from Peru and posterior migrations within Colombia was the most probable, with a posterior probability of 0.640. The obtained results support the hypothesis of a Peruvian origin for P. infestans followed by rare colonization events worldwide.

Landscape and conservation genetics of western black crested gibbons (Nomascus concolor) in China

Despite decades of field study, very little is known about the molecular ecology of gibbons, particularly as it relates to their ability to disperse across degraded and fragmentary landscapes. The critically endangered western black crested gibbon (Nomascus concolor) has been reduced to a small, fragmented population with about 1300 individuals. In the largest population genetic study of free-ranging gibbons to date, we sampled 47 of these gibbons from 13 sites in China and generated 15 polymorphic autosomal microsatellite markers. We identify three population clusters of N. concolor in Yunnan centered in 1) the Wuliang and Ailao Mountains, 2) the Yongde Daxueshan Mountains, and 3) an isolated remnant near the border with Vietnam. Within the Wuliang Mountains, we identified four subclusters, three of which are bounded by high-altitude rhododendron forest, and one that is isolated from the main population by ~2 km of degraded forest and pasture. Least-cost path analysis and isolation by resistance modeling demonstrates that the population genetic distances among gibbons in Wuliangshan National Nature Reserve are significantly correlated with geographic paths that avoid use of high-altitude rhododendron forest in favor of evergreen broadleaf forest. Although these gibbons have likely undergone reductions in heterozygosity from recent consanguineous mating, we suggest that their active avoidance of inbreeding on the population level maintains higher than expected levels of genetic diversity. This research provides new insights into how gibbons interact with heterogeneous environments and expands our understanding of their molecular ecology and conservation genetics.

Estimation of spatial demographic maps from polymorphism data using a neural network

A fundamental goal in population genetics is to understand how variation is arrayed over natural landscapes. From first principles we know that common features such as heterogeneous population densities and barriers to dispersal should shape genetic variation over space, however there are few tools currently available that can deal with these ubiquitous complexities. Geographically referenced single nucleotide polymorphism (SNP) data are increasingly accessible, presenting an opportunity to study genetic variation across geographic space in myriad species. We present a new inference method that uses geo-referenced SNPs and a deep neural network to estimate spatially heterogeneous maps of population density and dispersal rate. Our neural network trains on simulated input and output pairings, where the input consists of genotypes and sampling locations generated from a continuous space population genetic simulator, and the output is a map of the true demographic parameters. We benchmark our tool against existing methods and discuss qualitative differences between the different approaches; in particular, our program is unique because it infers the magnitude of both dispersal and density as well as their variation over the landscape, and it does so using SNP data. Similar methods are constrained to estimating relative migration rates, or require identity by descent blocks as input. We applied our tool to empirical data from North American grey wolves, for which it estimated mostly reasonable demographic parameters, but was affected by incomplete spatial sampling. Genetic based methods like ours complement other, direct methods for estimating past and present demography, and we believe will serve as valuable tools for applications in conservation, ecology, and evolutionary biology. An open source software package implementing our method is available from https://github.com/kr-colab/mapNN .

A rapid assessment methodology for quantifying and visualizing functional landscape connectivity

Context

The number of publications that evaluate or use landscape connectivity has grown dramatically in recent years. But the biological realism of common connectivity assessments remains limited. To address this shortcoming, I introduce a flexible methodology for evaluating functional landscape connectivity that can be quick to implement, biologically nuanced, and straightforward to interpret.

Methods

I combined a US Fish and Wildlife Service land cover map with information from existing empirical studies to develop a movement simulator for the Fender's blue butterfly, an endangered species in Oregon, USA. I use the resulting butterfly model to explore the concepts and mechanics behind my novel connectivity assessment methodology.

Results

My methods are able to identify clusters of connected resource patches, quantify and visualize movement rates between patches, and identify opportunities for enhancing connectivity through restoration and mitigation. My results include an emergent dispersal kernel that captures the influence of movement behavior on connectivity.

Discussion

The methods I introduce are capable of generating detailed yet practical connectivity analyses that can incorporate considerable biological and behavioral realism. My approach is simple to implement, and the requisite data can be modest. The toolkit I developed has the potential to standardize connectivity assessments that use either real or simulated movement data.

Genetic analysis of harvest samples reveals population structure in a highly mobile generalist carnivore

Delineating wildlife population boundaries is important for effective population monitoring and management. The bobcat (Lynx rufus) is a highly mobile generalist carnivore that is ecologically and economically important. We sampled 1225 bobcats harvested in South Dakota, USA (2014-2019), of which 878 were retained to assess genetic diversity and infer population genetic structure using 17 microsatellite loci. We assigned individuals to genetic clusters (K) using spatial and nonspatial Bayesian clustering algorithms and quantified differentiation (F ST and G ST ″ ) among clusters. We found support for population genetic structure at K = 2 and K = 4, with pairwise F ST and G ST ″ values indicating weak to moderate differentiation, respectively, among clusters. For K = 2, eastern and western clusters aligned closely with historical bobcat management units and were consistent with a longitudinal suture zone for bobcats previously identified in the Great Plains. We did not observe patterns of population genetic structure aligning with major rivers or highways. Genetic divergence observed at K = 4 aligned roughly with ecoregion breaks and may be associated with environmental gradients, but additional sampling with more precise locational data may be necessary to validate these patterns. Our findings reveal that cryptic population structure may occur in highly mobile and broadly distributed generalist carnivores, highlighting the importance of considering population structure when establishing population monitoring programs or harvest regulations. Our study further demonstrates that for elusive furbearers, harvest can provide an efficient, broad-scale sampling approach for genetic population assessments.

Considerable genetic diversity and structure despite narrow endemism and limited ecological specialization in the Hayden's ringlet, Coenonympha haydenii

Understanding the processes that underlie the development of population genetic structure is central to the study of evolution. Patterns of genetic structure, in turn, can reveal signatures of isolation by distance (IBD), barriers to gene flow, or even the genesis of speciation. However, it is unclear how severe range restriction might impact the processes that dominate the development of genetic structure. In narrow endemic species, is population structure likely to be adaptive in nature, or rather the result of genetic drift? In this study, we investigated patterns of genetic diversity and structure in the narrow endemic Hayden's ringlet butterfly. Specifically, we asked to what degree genetic structure in the Hayden's ringlet can be explained by IBD, isolation by resistance (IBR) (in the form of geographic or ecological barriers to migration between populations), and isolation by environment (in the form of differences in host plant availability and preference). We employed a genotyping-by-sequencing (GBS) approach coupled with host preference assays, Bayesian modelling, and population genomic analyses to answer these questions. Our results suggest that despite their restricted range, levels of genetic diversity in the Hayden's ringlet are comparable to those seen in more widespread butterfly species. Hayden's ringlets showed a strong preference for feeding on grasses relative to sedges, but neither larval preference nor potential host availability at sampling sites correlated with genetic structure. We conclude that geography, in the form of IBR and simple IBD, was the major driver of contemporary patterns of differentiation in this narrow endemic species.

Lizard host abundances and climatic factors explain phylogenetic diversity and prevalence of blood parasites on an oceanic island

Host abundance might favour the maintenance of a high phylogenetic diversity of some parasites via rapid transmission rates. Blood parasites of insular lizards represent a good model to test this hypothesis because these parasites can be particularly prevalent in islands and host lizards highly abundant. We applied deep amplicon sequencing and analysed environmental predictors of blood parasite prevalence and phylogenetic diversity in the endemic lizard Gallotia galloti across 24 localities on Tenerife, an island in the Canary archipelago that has experienced increasing warming and drought in recent years. Parasite prevalence assessed by microscopy was over 94%, and a higher proportion of infected lizards was found in warmer and drier locations. A total of 33 different 18s rRNA parasite haplotypes were identified, and the phylogenetic analyses indicated that they belong to two genera of Adeleorina (Apicomplexa: Coccidia), with Karyolysus as the dominant genus. The most important predictor of between-locality variation in parasite phylogenetic diversity was the abundance of lizard hosts. We conclude that a combination of climatic and host demographic factors associated with an insular syndrome may be favouring a rapid transmission of blood parasites among lizards on Tenerife, which may favour the maintenance of a high phylogenetic diversity of parasites.

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.

Fine-scale genetic structure in the orchid Gymnadenia conopsea is not associated with local density of flowering plants

PREMISE

Density-dependent pollinator visitation can lead to density-dependent mating patterns and within-population genetic structure. In Gymnadenia conopsea, individuals in low-density patches receive more self pollen than individuals in high-density patches, suggesting higher relatedness at low density. Ongoing fragmentation is also expected to cause more local matings, potentially leading to biparental inbreeding depression.

METHODS

To evaluate whether relatedness decreases with local density, we analyzed 1315 SNP loci in 113 individuals within two large populations. We quantified within-population genetic structure in one of the populations, recorded potential habitat barriers, and visualized gene flow using estimated effective migration surfaces (EEMS). We further estimated the magnitude of biparental inbreeding depression that would result from matings restricted to within 5 m.

RESULTS

There was no significant relationship between local density and relatedness in any population. We detected significant fine-scale genetic structure consistent with isolation by distance, with positive kinship coefficients at distances below 10 m. Kinship coefficients were low, and predicted biparental inbreeding depression resulting from matings within the closest 5 m was a modest 1-3%. The EEMS suggested that rocks and bushes may act as barriers to gene flow within a population.

CONCLUSIONS

The results suggest that increased self-pollen deposition in sparse patches does not necessarily cause higher selfing rates or that inbreeding depression results in low establishment success of inbred individuals. The modest relatedness suggests that biparental inbreeding depression is unlikely to be an immediate problem following fragmentation of large populations. The results further indicate that habitat structure may contribute to governing fine-scale genetic structure in G. conopsea.

slendr: a framework for spatio-temporal population genomic simulations on geographic landscapes

One of the goals of population genetics is to understand how evolutionary forces shape patterns of genetic variation over time. However, because populations evolve across both time and space, most evolutionary processes also have an important spatial component, acting through phenomena such as isolation by distance, local mate choice, or uneven distribution of resources. This spatial dimension is often neglected, partly due to the lack of tools specifically designed for building and evaluating complex spatio-temporal population genetic models. To address this methodological gap, we present a new framework for simulating spatially-explicit genomic data, implemented in a new R package called slendr (www.slendr.net), which leverages a SLiM simulation back-end script bundled with the package. With this framework, the users can programmatically and visually encode spatial population ranges and their temporal dynamics (i.e., population displacements, expansions, and contractions) either on real Earth landscapes or on abstract custom maps, and schedule splits and gene-flow events between populations using a straightforward declarative language. Additionally, slendr can simulate data from traditional, non-spatial models, either with SLiM or using an alternative built-in coalescent msprime back end. Together with its R-idiomatic interface to the tskit library for tree-sequence processing and analysis, slendr opens up the possibility of performing efficient, reproducible simulations of spatio-temporal genomic data entirely within the R environment, leveraging its wealth of libraries for geospatial data analysis, statistics, and visualization. Here, we present the design of the slendr R package and demonstrate its features on several practical example workflows.

Community metabarcoding reveals the relative role of environmental filtering and spatial processes in metacommunity dynamics of soil microarthropods across a mosaic of montane forests

Disentangling the relative role of environmental filtering and spatial processes in driving metacommunity structure across mountainous regions remains challenging, as the way we quantify spatial connectivity in topographically and environmentally heterogeneous landscapes can influence our perception of which process predominates. More empirical data sets are required to account for taxon- and context-dependency, but relevant research in understudied areas is often compromised by the taxonomic impediment. Here we used haplotype-level community DNA metabarcoding, enabled by stringent filtering of amplicon sequence variants (ASVs), to characterize metacommunity structure of soil microarthropod assemblages across a mosaic of five forest habitats on the Troodos mountain range in Cyprus. We found similar β diversity patterns at ASV and species (OTU, operational taxonomic unit) levels, which pointed to a primary role of habitat filtering resulting in the existence of largely distinct metacommunities linked to different forest types. Within-habitat turnover was correlated to topoclimatic heterogeneity, again emphasizing the role of environmental filtering. However, when integrating landscape matrix information for the highly fragmented Quercus alnifolia habitat, we also detected a major role of spatial isolation determined by patch connectivity, indicating that stochastic and niche-based processes synergistically govern community assembly. Alpha diversity patterns varied between ASV and OTU levels, with OTU richness decreasing with elevation and ASV richness following a longitudinal gradient, potentially reflecting a decline of genetic diversity eastwards due to historical pressures. Our study demonstrates the utility of haplotype-level community metabarcoding for characterizing metacommunity structure of complex assemblages and improving our understanding of biodiversity dynamics across mountainous landscapes worldwide.

Inferring landscape resistance to gene flow when genetic drift is spatially heterogeneous

In connectivity models, land cover types are assigned cost values characterizing their resistance to species movements. Landscape genetic methods infer these values from the relationship between genetic differentiation and cost distances. The spatial heterogeneity of population sizes, and consequently genetic drift, is rarely included in this inference although it influences genetic differentiation. Similarly, migration rates and population spatial distributions potentially influence this inference. Here, we assessed the reliability of cost value inference under several migration rates, population spatial patterns and degrees of population size heterogeneity. Additionally, we assessed whether considering intra-population variables, here using gravity models, improved the inference when drift is spatially heterogeneous. We simulated several gene flow intensities between populations with varying local sizes and spatial distributions. We then fit gravity models of genetic distances as a function of (i) the 'true' cost distances driving simulations or alternative cost distances, and (ii) intra-population variables (population sizes, patch areas). We determined the conditions making the identification of the 'true' costs possible and assessed the contribution of intra-population variables to this objective. Overall, the inference ranked cost scenarios reliably in terms of similarity with the 'true' scenario (cost distance Mantel correlations), but this 'true' scenario rarely provided the best model goodness of fit. Ranking inaccuracies and failures to identify the 'true' scenario were more pronounced when migration was very restricted (<4 dispersal events/generation), population sizes were most heterogeneous and some populations were spatially aggregated. In these situations, considering intra-population variables helps identify cost scenarios reliably, thereby improving cost value inference from genetic data.

Computing Geographical Networks Generated by Air-Mass Movement

As air masses move within the troposphere, they transport a multitude of components including gases and particles such as pollen and microorganisms. These movements generate atmospheric highways that connect geographic areas at distant, local, and global scales that particles can ride depending on their aerodynamic properties and their reaction to environmental conditions. In this article we present an approach and an accompanying web application called tropolink for measuring the extent to which distant locations are potentially connected by air-mass movement. This approach is based on the computation of trajectories of air masses with the HYSPLIT atmospheric transport and dispersion model, and on the computation of connection frequencies, called connectivities, in the purpose of building trajectory-based geographical networks. It is illustrated for different spatial and temporal scales with three case studies related to plant epidemiology. The web application that we designed allows the user to easily perform intensive computation and mobilize massive archived gridded meteorological data to build weighted directed networks. The analysis of such networks allowed us for example, to describe the potential of invasion of a migratory pest beyond its actual distribution. Our approach could also be used to compute geographical networks generated by air-mass movement for diverse application domains, for example, to assess long-term risk of spread from persistent or recurrent sources of pollutants, including wildfire smoke.

Uncovering the endemic circulation of rabies in Cambodia

In epidemiology, endemicity characterizes sustained pathogen circulation in a geographical area, which involves a circulation that is not being maintained by external introductions. Because it could potentially shape the design of public health interventions, there is an interest in fully uncovering the endemic pattern of a disease. Here, we use a phylogeographic approach to investigate the endemic signature of rabies virus (RABV) circulation in Cambodia. Cambodia is located in one of the most affected regions by rabies in the world, but RABV circulation between and within Southeast Asian countries remains understudied. Our analyses are based on a new comprehensive data set of 199 RABV genomes collected between 2014 and 2017 as well as previously published Southeast Asian RABV sequences. We show that most Cambodian sequences belong to a distinct clade that has been circulating almost exclusively in Cambodia. Our results thus point towards rabies circulation in Cambodia that does not rely on external introductions. We further characterize within-Cambodia RABV circulation by estimating lineage dispersal metrics that appear to be similar to other settings, and by performing landscape phylogeographic analyses to investigate environmental factors impacting the dispersal dynamic of viral lineages. The latter analyses do not lead to the identification of environmental variables that would be associated with the heterogeneity of viral lineage dispersal velocities, which calls for a better understanding of local dog ecology and further investigations of the potential drivers of RABV spread in the region. Overall, our study illustrates how phylogeographic investigations can be performed to assess and characterize viral endemicity in a context of relatively limited data.

Landscape genetics reveals contrasting patterns of connectivity in two newt species (Lissotriton montandoni and L. vulgaris)

Ecologically distinct species may respond to landscape changes in different ways. In addition to basic ecological data, the extent of the geographic range has been successfully used as an indicator of species sensitivity to anthropogenic landscapes, with widespread species usually found to be less sensitive compared to range-restricted species. In this study, we investigate connectivity patterns of two closely related but ecologically distinct newt species - the range-restricted, Lissotriton montandoni and the widespread, L. vulgaris - using genomic data, a highly replicated setting (six geographic regions per species), and tools from landscape genetics. Our results show the importance of forest for connectivity in both species, but at the same time suggest differential use of forested habitat, with L. montandoni and L. vulgaris showing the highest connectivity at forest-core and forest-edges, respectively. Anthropogenic landscapes (i.e., higher crop- or urban-cover) increased resistance in both species, but the effect was one to three orders of magnitude stronger in L. montandoni than in L. vulgaris. This result is consistent with a view of L. vulgaris as an ecological generalist. Even so, currently, the negative impact of anthropogenic landscapes is mainly seen in connectivity among L. vulgaris populations, which show significantly stronger isolation and lower effective sizes relative to L. montandoni. Overall, this study emphasizes how habitat destruction is compromising genetic connectivity not only in endemic, range-restricted species of conservation concern but also in widespread generalist species, despite their comparatively lower sensitivity to anthropogenic landscape changes.

Phylogeographic reconstruction of the emergence and spread of Powassan virus in the northeastern United States

Powassan virus is an emerging tick-borne virus of concern for public health, but very little is known about its transmission patterns and ecology. Here, we expanded the genomic dataset by sequencing 279 Powassan viruses isolated from Ixodes scapularis ticks from the northeastern United States. Our phylogeographic reconstructions revealed that Powassan virus lineage II was likely introduced or emerged from a relict population in the Northeast between 1940 and 1975. Sequences strongly clustered by sampling location, suggesting a highly focal geographical distribution. Our analyses further indicated that Powassan virus lineage II emerged in the northeastern United States mostly following a south-to-north pattern, with a weighted lineage dispersal velocity of ~3 km/y. Since the emergence in the Northeast, we found an overall increase in the effective population size of Powassan virus lineage II, but with growth stagnating during recent years. The cascading effect of population expansion of white-tailed deer and I. scapularis populations likely facilitated the emergence of Powassan virus in the northeastern United States.

Sponge diversification in marine lakes: Implications for phylogeography and population genomic studies on sponges

The relative influence of geography, currents, and environment on gene flow within sessile marine species remains an open question. Detecting subtle genetic differentiation at small scales is challenging in benthic populations due to large effective population sizes, general lack of resolution in genetic markers, and because barriers to dispersal often remain elusive. Marine lakes can circumvent confounding factors by providing discrete and replicated ecosystems. Using high-resolution double digest restriction-site-associated DNA sequencing (4826 Single Nucleotide Polymorphisms, SNPs), we genotyped populations of the sponge Suberites diversicolor (n = 125) to test the relative importance of spatial scales (1-1400 km), local environmental conditions, and permeability of seascape barriers in shaping population genomic structure. With the SNP dataset, we show strong intralineage population structure, even at scales <10 km (average F ST = 0.63), which was not detected previously using single markers. Most variation was explained by differentiation between populations (AMOVA: 48.8%) with signatures of population size declines and bottlenecks per lake. Although the populations were strongly structured, we did not detect significant effects of geographic distance, local environments, or degree of connection to the sea on population structure, suggesting mechanisms such as founder events with subsequent priority effects may be at play. We show that the inclusion of morphologically cryptic lineages that can be detected with the COI marker can reduce the obtained SNP set by around 90%. Future work on sponge genomics should confirm that only one lineage is included. Our results call for a reassessment of poorly dispersing benthic organisms that were previously assumed to be highly connected based on low-resolution markers.

Estimating resistance surfaces using gradient forest and allelic frequencies

Understanding landscape connectivity has become a global priority for mitigating the impact of landscape fragmentation on biodiversity. Connectivity methods that use link-based methods traditionally rely on relating pairwise genetic distance between individuals or demes to their landscape distance (e.g., geographic distance, cost distance). In this study, we present an alternative to conventional statistical approaches to refine cost surfaces by adapting the gradient forest approach to produce a resistance surface. Used in community ecology, gradient forest is an extension of random forest, and has been implemented in genomic studies to model species genetic offset under future climatic scenarios. By design, this adapted method, resGF, has the ability to handle multiple environmental predicators and is not subjected to traditional assumptions of linear models such as independence, normality and linearity. Using genetic simulations, resistance Gradient Forest (resGF) performance was compared to other published methods (maximum likelihood population effects model, random forest-based least-cost transect analysis and species distribution model). In univariate scenarios, resGF was able to distinguish the true surface contributing to genetic diversity among competing surfaces better than the compared methods. In multivariate scenarios, the gradient forest approach performed similarly to the other random forest-based approach using least-cost transect analysis but outperformed MLPE-based methods. Additionally, two worked examples are provided using two previously published data sets. This machine learning algorithm has the potential to improve our understanding of landscape connectivity and inform long-term biodiversity conservation strategies.

Linking life history to landscape for threatened species conservation in a multiuse region

Landscape-scale conservation that considers metapopulation dynamics will be essential for preventing declines of species facing multiple threats to their survival. Toward this end, we developed a novel approach that combines occurrence records, spatial-environmental data, and genetic information to model habitat, connectivity, and patterns of genetic structure and link spatial attributes to underlying ecological mechanisms. Using the threatened northern quoll (Dasyurus hallucatus) as a case study, we applied this approach to address the need for conservation decision-making tools that promote resilient metapopulations of this threatened species in the Pilbara, Western Australia, a multiuse landscape that is a hotspot for biodiversity and mining. Habitat and connectivity were predicted by different landscape characteristics. Whereas habitat suitability was overwhelmingly driven by terrain ruggedness, dispersal was facilitated by proximity to watercourses. Although there is limited evidence for major physical barriers in the Pilbara, areas with high silt and clay content (i.e., alluvial and hardpan plains) showed high resistance to dispersal. Climate subtlety shaped distributions and patterns of genetic turnover, suggesting the potential for local adaptation. By understanding these spatial-environmental associations and linking them to life-history and metapopulation dynamics, we highlight opportunities to provide targeted species management. To support this, we have created habitat, connectivity, and genetic uniqueness maps for conservation decision-making in the region. These tools have the potential to provide a more holistic approach to conservation in multiuse landscapes globally.

The ties that bind the sagebrush biome: integrating genetic connectivity into range-wide conservation of greater sage-grouse

Conserving genetic connectivity is fundamental to species persistence, yet rarely is made actionable into spatial planning for imperilled species. Climate change and habitat degradation have added urgency to embrace connectivity into networks of protected areas. Our two-step process integrates a network model with a functional connectivity model, to identify population centres important to maintaining genetic connectivity then to delineate those pathways most likely to facilitate connectivity thereamong for the greater sage-grouse (Centrocercus urophasianus), a species of conservation concern ranging across eleven western US states and into two Canadian provinces. This replicable process yielded spatial action maps, able to be prioritized by importance to maintaining range-wide genetic connectivity. We used these maps to investigate the efficacy of 3.2 million ha designated as priority areas for conservation (PACs) to encompass functional connectivity. We discovered that PACs encompassed 41.1% of cumulative functional connectivity-twice the amount of connectivity as random-and disproportionately encompassed the highest-connectivity landscapes. Comparing spatial action maps to impedances to connectivity such as cultivation and woodland expansion allows both planning for future management and tracking outcomes from past efforts.

Circuit theory-based ecological security pattern could promote ecological protection in the Heihe River Basin of China

Building ecological security patterns is essential to maintain regional ecological security and achieve sustainable development in the inland river basins with ecologically vulnerable environment. Numerous methods have been developed to build the ecological security pattern. However, to our knowledge, rare studies have quantified to what extent the derived pattern can improve ecological protection in the future. Taking Heihe River Basin (HRB), the second largest inland river basin in China, as the study area, we applied the circuit theory to build the ecological security pattern of HRB, and simulated how our built pattern contributed to ecological protection using the CLUMondo model. The results showed that the ecological security pattern of HRB contained 17 ecological sources, 35 key ecological corridors, and some ecological strategic points. The ecological sources were distributed in areas with better ecological conditions such as the Qilian Mountain Nature Reserve and Heihe National Wetland Park. The ecological corridors showed a pattern of "two horizontal and three vertical belts." Pinch points were mostly close to ecological sources or distributed on the corridors that played a key role in landscape connectivity, while barriers were mainly distributed on the corridors with large ecological resistance in the middle and lower reaches. The optimal ecological security pattern presented a "one screen, one belt, four districts and multiple centers" shape in HRB and could more effectively promote ecological protection compared to current development and protection scenarios. Our study provides a reliable decision-making guide for ecological protection and restoration of HRB, and can be extended to build ecological security patterns for broad-scale arid areas.

Comprehensive evaluation of the Ruoergai Prairie ecosystem upstream of the Yellow River

With complex and diverse ecosystem types and complete ecological elements such as mountains, rivers, forests, farmlands, lakes, grasslands, sand, and glaciers, the Ruoergai Prairie upstream of the Yellow River is an integral part of the Qinghai-Tibet Ecological barrier and a critical area for ensuring the ecological security of China. In the Ruoergai Prairie, climate change and human activities have led to grassland degradation, water and soil loss, and a shrinking forest area, which has highlighted the need for ecological restoration. Therefore, a comprehensive ecosystem evaluation is of great significance for ecosystem restoration. This study evaluated the ecosystem quality, ecosystem service function importance, ecological vulnerability, ecological protection importance, ecological resilience, and ecological landscape patterns of prairies, wetlands, and forests. The ecosystem quality of the study area was medium to good. The ecosystem service function of the study area with weak ecosystem resilience is important. However, the ecological landscape in the study area has been heavily degraded. Therefore, the protection and restoration of mountains, waters, forests, farmlands, lakes, grasslands, sand, and glaciers are needed.

How ancient forest fragmentation and riparian connectivity generate high levels of genetic diversity in a microendemic Malagasy tree

Understanding landscape changes is central to predicting evolutionary trajectories and defining conservation practices. While human-driven deforestation is intense throughout Madagascar, exceptions in areas such as the Loky-Manambato region (north) raise questions regarding the causes and age of forest fragmentation. The Loky-Manambato region also harbours a rich and endemic flora, whose evolutionary origin remains poorly understood. We assessed the genetic diversity of an endangered microendemic Malagasy olive species (Noronhia spinifolia Hong-Wa) to better understand the vegetation dynamics in the Loky-Manambato region and its influence on past evolutionary processes. We characterized 72 individuals sampled across eight forests through nuclear and mitochondrial restriction-associated DNA sequencing data and chloroplast microsatellites. Combined population and landscape genetics analyses indicate that N. spinifolia diversity is largely explained by the current forest cover, highlighting a long-standing habitat mosaic in the region. This sustains a major and long-term role of riparian corridors in maintaining connectivity across these antique mosaic habitats, calling for the study of organismal interactions that promote gene flow.

Ecosystem Health Evaluation and Ecological Security Patterns Construction Based on VORSD and Circuit Theory: A Case Study in the Three Gorges Reservoir Region in Chongqing, China

Constructing ecological security patterns (ESPs) is an important approach to maintaining regional ecological security and achieving sustainable development. Most previous studies on ESPs mainly focused on the supply of ecosystem services (ESs) yet did not fully consider the ecosystem health and human demand for ESs, which lacked evaluation from the perspective of human nature. Therefore, based on ecosystem health and ESs demand, this paper constructed the "vigor, organization, resilience, ESs supply-demand ratio" (VORSD) ecosystem health evaluation system and combined it with circuit theory to develop a new and comprehensive ESPs identification framework. Taking the Three Gorges Reservoir Area in Chongqing section (TGRAC) as a case study, the results showed that the general ecosystem health of the TGRAC was not optimistic, and there was still a long way to go for ecological treatment and restoration. From the perspective of spatial distribution, there were significant differences in the ecosystem health between regions, and the eastern region was higher than the western region. The ecological sources area of the TGRAC was about 25,350.16 km², mainly distributed in the northeast and southeast of forestland, grassland, and cultivated land. The total length of ecological corridors was 2291.41 km, linking the northeastern, southeastern, middle, and southwestern regions of the TGRAC. There were 82 ecological nodes and 30 ecological barriers, most of which were concentrated on the construction land and cultivated land in the southwest and should be regarded as priority areas for ecological conservation. The research results verify the regional suitability and rationality of integrating the VORSD model and circuit theory to construct ESPs, which can provide an important reference for regional ecological protection and land use pattern optimization.

Potential Distribution and Connectivity for Two Plethodontid Salamanders: Conservation Areas and Landscape Corridors for Two Endemic Species of México and Guatemala

Habitat loss is one of the most important threats to biodiversity; it alters the habitat connectivity of species and is among the main causes of the global amphibian extinction crisis. Identifying the potential areas of distribution and connectivity of species is of the utmost importance so that informed decisions can be made for the conservation of vulnerable amphibian populations. In this study, we performed species distribution models and used circuit theory to model omnidirectional connectivity for two plethodontid salamanders of conservation concern distributed in the forests of Chiapas, Mexico, and Guatemala (Bolitoglossa franklini and Bolitoglossa lincolni). Potential distribution maps show an affinity for well-preserved montane forests for both species. Likewise, we found that the niches of the species are not similar. The connectivity models show that the main areas of connectivity are in the Meseta Central de Chiapas, Sierra Madre de Chiapas, and the Cordillera Volcánica Guatemalense, in this last range, important areas of connectivity were located, as well as least-cost paths and barriers to the movement of both species. We identified that important areas of climatic suitability and connectivity are not within the protected natural areas and may be threatened by the increasing influence of anthropogenic activities. The results of our study show the importance of preserving the regional forests to ensure the persistence of species with arboreal habits and high sensitivity to habitat transformation, as well as to recognize and prioritize potential areas for management and protection in both southern Mexico and Guatemala.

Host association, environment, and geography underlie genomic differentiation in a major forest pest

Diverse geographic, environmental, and ecological factors affect gene flow and adaptive genomic variation within species. With recent advances in landscape ecological modelling and high-throughput DNA sequencing, it is now possible to effectively quantify and partition their relative contributions. Here, we use landscape genomics to identify determinants of genomic differentiation in the forest tent caterpillar, Malacosoma disstria, a widespread and irruptive pest of numerous deciduous tree species in North America. We collected larvae from multiple populations across Eastern Canada, where the species experiences a diversity of environmental gradients and feeds on a number of different host tree species, including trembling aspen (Populus tremuloides), sugar maple (Acer saccharum), red oak (Quercus rubra), and white birch (Betula papyrifera). Using a combination of reciprocal causal modelling (RCM) and distance-based redundancy analyses (dbRDA), we show that differentiation of thousands of genome-wide single nucleotide polymorphisms (SNPs) among individuals is best explained by a combination of isolation by distance, isolation by environment (spatial variation in summer temperatures and length of the growing season), and differences in host association. Configuration of suitable habitat inferred from ecological niche models was not significantly related to genomic differentiation, suggesting that M. disstria dispersal is agnostic with respect to habitat quality. Although population structure was not discretely related to host association, our modelling framework provides the first molecular evidence of host-associated differentiation in M. disstria, congruent with previous documentation of reduced growth and survival of larvae moved between natal host species. We conclude that ecologically mediated selection is contributing to variation within M. disstria, and that divergent adaptation related to both environmental conditions and host association should be considered in ongoing research and management of this important forest pest.

Landscape genetics of a sub-alpine toad: climate change predicted to induce upward range shifts via asymmetrical migration corridors

Climate change is expected to have a major hydrological impact on the core breeding habitat and migration corridors of many amphibians in the twenty-first century. The Yosemite toad (Anaxyrus canorus) is a species of meadow-specializing amphibian endemic to the high-elevation Sierra Nevada Mountains of California. Despite living entirely on federal lands, it has recently faced severe extirpations, yet our understanding of climatic influences on population connectivity is limited. In this study, we used a previously published double-digest RADseq dataset along with numerous remotely sensed habitat features in a landscape genetics framework to answer two primary questions in Yosemite National Park: (1) Which fine-scale climate, topographic, soil, and vegetation features most facilitate meadow connectivity? (2) How is climate change predicted to influence both the magnitude and net asymmetry of genetic migration? We developed an approach for simultaneously modeling multiple toad migration paths, akin to circuit theory, except raw environmental features can be separately considered. Our workflow identified the most likely migration corridors between meadows and used the unique cubist machine learning approach to fit and forecast environmental models of connectivity. We identified the permuted modeling importance of numerous snowpack-related features, such as runoff and groundwater recharge. Our results highlight the importance of considering phylogeographic structure, and asymmetrical migration in landscape genetics. We predict an upward elevational shift for this already high-elevation species, as measured by the net vector of anticipated genetic movement, and a north-eastward shift in species distribution via the network of genetic migration corridors across the park.

Forest cover and geographical distance influence fine-scale genetic structure of leaf-toed geckos in the tropical dry forests of western Mexico

The biodiversity within tropical dry forests (TDFs) is astounding and yet poorly catalogued due to inadequate sampling and the presence of cryptic species. In the Mexican TDF, endemic species are common, and the landscape has been continually altered by geological and anthropogenic changes. To understand how landscape and environmental variables have shaped the population structure of endemic species, we studied the recently described species of leaf-toed gecko, Phyllodactylus benedettii, in coastal western Mexico. Using double-digest restriction site-associated DNA sequencing data, we first explore population structure and estimate the number of ancestral populations. The results indicate a high degree of genetic structure with little admixture, and patterns corresponding to both latitudinal and altitudinal gradients. We find that genetic structure cannot be explained purely by geographical distance, and that ecological corridors may facilitate dispersal and gene flow. We then model the spatial distribution of P. benedettii in the TDF through time and find that the coastline has been climatically suitable for the species since the Last Glacial Maximum. Landscape genetic analyses suggest that the combination of isolation by distance (IBD) and isolation by resistance (IBR; forest cover) has influenced the spatial genetic structure of the species. Overall, our genomic data demonstrate fine-scale population structure in TDF habitat, a complex colonization history, and spatial patterns consistent with both IBD and other ecological factors. These results further highlight the Mexican TDF as a diversity hotspot and suggest that continued anthropogenic changes are likely to affect native fauna.

Predicting the evolution of the Lassa virus endemic area and population at risk over the next decades

Lassa fever is a severe viral hemorrhagic fever caused by a zoonotic virus that repeatedly spills over to humans from its rodent reservoirs. It is currently not known how climate and land use changes could affect the endemic area of this virus, currently limited to parts of West Africa. By exploring the environmental data associated with virus occurrence using ecological niche modelling, we show how temperature, precipitation and the presence of pastures determine ecological suitability for virus circulation. Based on projections of climate, land use, and population changes, we find that regions in Central and East Africa will likely become suitable for Lassa virus over the next decades and estimate that the total population living in ecological conditions that are suitable for Lassa virus circulation may drastically increase by 2070. By analysing geotagged viral genomes using spatially-explicit phylogeography and simulating virus dispersal, we find that in the event of Lassa virus being introduced into a new suitable region, its spread might remain spatially limited over the first decades.

Genetic structure of wild rice Zizania latifolia in an expansive heterogeneous landscape along a latitudinal gradient

Global aquatic habitats are undergoing rapid degradation and fragmentation as a result of climate change and changes in land use. Understanding the genetic variability and adaptive potential of aquatic plant species is thus important for conservation purposes. In this study, we investigated the genetic diversity and structure of the extant natural populations of Zizania latifolia from five river basins in China based on 46 microsatellite markers. We tested isolation by environment (IBE), isolation by resistance (IBR), and isolation by distance (IBD) patterns using a reciprocal causal model (RCM). Furthermore, we elucidated the impact of the environment on Z. latifolia genetic diversity using generalized linear models (GLMs) and spatially explicit mixed models. Low genetic diversity (HE = 0.125–0.433) and high genetic differentiation (FST = 0.641, Øpt = 0.654) were found. Higher historical gene flow (MH = 0.212–2.354) than contemporary gene flow (MC = 0.0112–0.0247) and significant bottlenecks in almost all populations were identified, highlighting the negative impact of wetland fragmentation. The IBE model was exclusively supported for all populations and in three river basins. The IBD and IBR models were supported in one river basin each. The maximum temperature of the warmest month and precipitation seasonality were the plausible environmental parameters responsible for the observed pattern of genetic diversity. Local adaptation signatures were found, with nine loci identified as outliers, four of which were gene-linked and associated with environmental variables. Based on these findings, IBE is more important than IBD and IBR in shaping the genetic structure of Z. latifolia.

Eco-evolutionary model on spatial graphs reveals how habitat structure affects phenotypic differentiation

Differentiation mechanisms are influenced by the properties of the landscape over which individuals interact, disperse and evolve. Here, we investigate how habitat connectivity and habitat heterogeneity affect phenotypic differentiation by formulating a stochastic eco-evolutionary model where individuals are structured over a spatial graph. We combine analytical insights into the eco-evolutionary dynamics with numerical simulations to understand how the graph topology and the spatial distribution of habitat types affect differentiation. We show that not only low connectivity but also heterogeneity in connectivity promotes neutral differentiation, due to increased competition in highly connected vertices. Habitat assortativity, a measure of habitat spatial auto-correlation in graphs, additionally drives differentiation under habitat-dependent selection. While assortative graphs systematically amplify adaptive differentiation, they can foster or depress neutral differentiation depending on the migration regime. By formalising the eco-evolutionary and spatial dynamics of biological populations on graphs, our study establishes fundamental links between landscape features and phenotypic differentiation.

Functional connectivity of the world's protected areas

Global policies call for connecting protected areas (PAs) to conserve the flow of animals and genes across changing landscapes, yet whether global PA networks currently support animal movement-and where connectivity conservation is most critical-remain largely unknown. In this study, we map the functional connectivity of the world's terrestrial PAs and quantify national PA connectivity through the lens of moving mammals. We find that mitigating the human footprint may improve connectivity more than adding new PAs, although both strategies together maximize benefits. The most globally important areas of concentrated mammal movement remain unprotected, with 71% of these overlapping with global biodiversity priority areas and 6% occurring on land with moderate to high human modification. Conservation and restoration of critical connectivity areas could safeguard PA connectivity while supporting other global conservation priorities.

Glacial vicariance and oceanic circulation shape population structure of the coastal legume Derris trifoliata in the Indo-West Pacific

PREMISE

The phylogeography of coastal plant species is shaped by contemporary and historical biogeographic processes. In this study, we aim to decipher the phylogeography of Derris trifoliata, a woody legume of relatively recent origin and wide distribution, in coastal areas in the Indo-West Pacific (IWP) region.

METHODS

Genetic diversity and population structure were assessed by analyzing six nuclear and three chloroplast DNA sequences from 30 populations across the species' range. Phylogeography was inferred by estimating gene flow, divergence time, historical population size changes, and historical habitat suitability using paleoclimatic niche modeling.

RESULTS

High genetic diversity was observed at the species level. The populations of three oceanic regions included in this study (i.e., Indian Ocean, South China Sea, and Pacific Ocean) formed distinct clades and likely diverged during the late Pleistocene. Potential barriers to gene flow were identified, including the Sunda and Sahul shelves, geographic distance, and current patterns of oceanic circulation. Analysis of changes in population size supported the bottleneck model, which was strengthened by estimates of habitat suitability across paleoclimatic conditions.

CONCLUSIONS

The once widespread distribution of D. trifoliata was fragmented by changes in climatic suitability and biogeographic barriers that arose following sea-level changes during the Pleistocene. In addition, contemporary patterns of oceanic circulation and geographic distance between populations appear to maintain genetic differentiation across its distribution in the IWP.

Construction of Ecological Security Patterns Based on Circuit Theory under the Resistance Distance Principle

Against the background of China’s advocating ecological civilisation construction, an urgent task and a major challenge are to identify key places for ecological protection and restoration and then propose optimisation strategies for future land use, especially in the Pearl River Delta (PRD), one of the regions in China that has the highest urbanisation level. In this study, we find the key places by constructing ecological security patterns and proposing optimisation strategies for future land use by analysing land-use status. We also propose a source identification method based on the resistance distance principle. Results show that forty-six sources were mainly distributed in the mountainous areas surrounding PRD but were less distributed along both sides of the Pearl River estuary. The difference in the spatial distribution of sources is remarkable. Eighty-four corridors generally had spider-like shapes. In the central plain of PRD, corridors were relatively long and narrow. Ninety pinch points were concentrated on existing rivers. Three barriers were located in the corridors between adjacent sources. Two artificial corridors were proposed to be established, which can improve the ecological network connectivity. The method for extracting sources based on the resistance distance principle is proven to be advantageous for improving the integrity of source extraction results and making ecological security patterns more reasonable.

Population and Landscape Genetics Provide Insights Into Species Conservation of Two Evergreen Oaks in Qinghai-Tibet Plateau and Adjacent Regions

The combination of population and landscape genetics can facilitate the understanding of conservation strategy under the changing climate. Here, we focused on the two most diverse and ecologically important evergreen oaks: Quercus aquifolioides and Quercus spinosa in Qinghai-Tibetan Plateau (QTP), which is considered as world's biodiversity hotspot. We genotyped 1,657 individuals of 106 populations at 15 nuclear microsatellite loci throughout the species distribution range. Spatial patterns of genetic diversity were identified by mapping the allelic richness (AR) and locally common alleles (LCA) according to the circular neighborhood methodology. Migration routes from QTP were detected by historical gene flow estimation. The response pattern of genetic variation to environmental gradient was assessed by the genotype-environment association (GEA) analysis. The overall genetic structure showed a high level of intra-species genetic divergence of a strong west-east pattern. The West-to-East migration route indicated the complex demographic history of two oak species. We found evidence of isolation by the environment in Q. aqu-East and Q. spi-West lineage but not in Q. aqu-West and Q. spi-East lineage. Furthermore, priority for conservation should be given to populations that retain higher spatial genetic diversity or isolated at the edge of the distribution range. Our findings indicate that knowledge of spatial diversity and migration route can provide valuable information for the conservation of existing populations. This study provides an important guide for species conservation for two oak species by the integration of population and landscape genetic methods.

Study on the Structural Properties of an Ecospatial Network in Inner Mongolia and Its Relationship with NPP

In the context of strengthening the construction of ecological civilization and accelerating the “carbon peak” in China, the regional ecological pattern and its connection with carbon sink capacity have become an urgent topic. Given that Inner Mongolia is a large carbon emission province and the conflict between economic development and ecological protection is particularly prominent, we took Inner Mongolia as an example to extract its ecospatial network, then calculated the integrity index, topological indices, and recovery robustness of the network and evaluated integrity and other properties of the ecospatial network structure by combining them with the ecological background. In addition, we analyzed the relationship between the topological indices and net primary productivity (NPP). The results showed that the network was scale-free and heterogeneous, with low integrity, connectivity and stability, which were the focus of future optimization. The nodes with important functions were mainly distributed in the farm-forest ecotone, grasslands, and the agro-pastoral ecotone; under the simulation attack, the node recovery robustness was stronger than the corridor recovery robustness, and NPP was negatively and significantly correlated with the woodland nodes and grassland nodes. In terms of ecological restoration, the unused land in the west is a key area, and it is necessary to add new ecological nodes and corridors. In terms of enhancing carbon sequestration capacity, under the premise of ensuring network connectivity, the appropriate and rational merging of ecological nodes and corridors within woodlands and grasslands is a particularly effective means. This study provides a reference for evaluating and optimizing the ecological pattern of areas with prominent ecological problems and improving the carbon sink of ecosystems in terms of their ecospatial network structure.

Scale-dependent influence of the sagebrush community on genetic connectivity of the sagebrush obligate Gunnison sage-grouse

Habitat fragmentation and degradation impacts an organism's ability to navigate the landscape, ultimately resulting in decreased gene flow and increased extinction risk. Understanding how landscape composition impacts gene flow (i.e., connectivity) and interacts with scale is essential to conservation decision‐making. We used a landscape genetics approach implementing a recently developed statistical model based on the generalized Wishart probability distribution to identify the primary landscape features affecting gene flow and estimate the degree to which each component influences connectivity for Gunnison sage‐grouse (Centrocercus minimus). We were interested in two spatial scales: among distinct populations rangewide and among leks (i.e., breeding grounds) within the largest population, Gunnison Basin. Populations and leks are nested within a landscape fragmented by rough terrain and anthropogenic features, although requisite sagebrush habitat is more contiguous within populations. Our best fit models for each scale confirm the importance of sagebrush habitat in connectivity, although the important sagebrush characteristics differ. For Gunnison Basin, taller shrubs and higher quality nesting habitat were the primary drivers of connectivity, while more sagebrush cover and less conifer cover facilitated connectivity rangewide. Our findings support previous assumptions that Gunnison sage‐grouse range contraction is largely the result of habitat loss and degradation. Importantly, we report direct estimates of resistance for landscape components that can be used to create resistance surfaces for prioritization of specific locations for conservation or management (i.e., habitat preservation, restoration, or development) or as we demonstrated, can be combined with simulation techniques to predict impacts to connectivity from potential management actions.