Environmental and Biogeographic Drivers behind Alpine Plant Thermal Tolerance and Genetic Variation

In alpine ecosystems, elevation broadly functions as a steep thermal gradient, with plant communities exposed to regular fluctuations in hot and cold temperatures. These conditions lead to selective filtering, potentially contributing to species-level variation in thermal tolerance and population-level genetic divergence. Few studies have explored the breadth of alpine plant thermal tolerances across a thermal gradient or the underlying genetic variation thereof. We measured photosystem heat (Tcrit-hot) and cold (Tcrit-cold) thresholds of ten Australian alpine species across elevation gradients and characterised their neutral genetic variation. To reveal the biogeographical drivers of present-day genetic signatures, we also reconstructed temporal changes in habitat suitability across potential distributional ranges. We found intraspecific variation in thermal thresholds, but this was not associated with elevation, nor underpinned by genetic differentiation on a local scale. Instead, regional population differentiation and considerable homozygosity within populations may, in part, be driven by distributional contractions, long-term persistence, and migrations following habitat suitability. Our habitat suitability models suggest that cool-climate-distributed alpine plants may be threatened by a warming climate. Yet, the observed wide thermal tolerances did not reflect this vulnerability. Conservation efforts should seek to understand variations in species-level thermal tolerance across alpine microclimates.

Landscape features influencing gene flow and connectivity of an endangered passerine

Dispersal of individuals and gene flow are crucial aspects to maintain genetic diversity and viability of populations, especially in the case of threatened species. Landscape composition and structure may facilitate or limit individual movement within and among populations. We used a landscape genetics approach to assess the connectivity patterns of the threatened Dupont's lark (Chersophilus duponti subsp. duponti), considering their genetic patterns and the landscape features associated with its gene flow in Spain. We analysed the genetic relatedness based on 11 species-specific polymorphic microsatellites on 416 Dupont's lark individuals sampled across peninsular Spain between 2017 and 2019, covering most of the European distribution of the species. To assess the relationship between the landscape composition and the species gene flow, we estimated genetic distance at the individual level (Dps). Next, we built a set of environmental surfaces from two time periods (years 1990 and 2018), based on factors such as land use and topography, influencing individuals' movement. We then obtained resistance surfaces from an optimization process on landscape variables. Landscape genetics analyses were done for single and composite surface models for each year separately. Our findings from both time points show that scatter or mosaic-structured vegetation composed by low agricultural and tree cover and high presence of sclerophyllous shrubs favoured Dupont's lark dispersal, while dense and continuous tree cover, as well as areas of intensive agriculture, were limiting factors. Our results suggest the importance of steppe habitat patches for the species' establishment and dispersal. In addition, our results provide key information to develop conservation measures, including conserving and restoring steppe habitats as scattered and/or mosaic-structured vegetation that could warrant the connectivity and persistence of Dupont's lark populations.

mapmixture: An R package and web app for spatial visualisation of admixture and population structure

The mapmixture R package and interactive web app are tools to aid visualisation of admixture and population structure in geographic space. The purpose of mapmixture is to enable and encourage molecular ecologists, and in particular population geneticists and phylogeneticists, to plot their admixture, ancestry or assignment results on a map when location information is available. mapmixture accepts data in the format typically generated by admixture analyses and visualises proportions to each genetic cluster per site as pie charts on a projected (optional) map. Combining this site-based map presentation approach with the routine individual-based presentation of admixture (structure) barplots will enhance interpretation of genetic-geographic patterns. Additionally, in the context of science communication, this enables clearer transfer of spatial genetic information to readers or listeners, and especially to audiences that do not have a background in genetics but who are able to use the genetic information as evidence in conservation management. The latest version of mapmixture is available on GitHub (https://github.com/tom-jenkins/mapmixture), which details installation instructions and examples of how to use the package and interactive web app.

Synthesizing environmental, epidemiological and vector and parasite genetic data to assist decision making for disease elimination

We present a framework for identifying when conditions are favourable for transmission of vector-borne diseases between communities by incorporating predicted disease prevalence mapping with landscape analysis of sociological, environmental and host/parasite genetic data. We explored the relationship between environmental features and gene flow of a filarial parasite of humans, Onchocerca volvulus, and its vector, blackflies in the genus Simulium. We generated a baseline microfilarial prevalence map from point estimates from 47 locations in the ecological transition separating the savannah and forest in Ghana, where transmission of O. volvulus persists despite onchocerciasis control efforts. We generated movement suitability maps based on environmental correlates with mitochondrial population structure of 164 parasites from 15 communities and 93 vectors from only four sampling sites, and compared these to the baseline prevalence map. Parasite genetic distance between sampling locations was significantly associated with elevation (r = .793, p = .005) and soil moisture (r = .507, p = .002), while vector genetic distance was associated with soil moisture (r = .788, p = .0417) and precipitation (r = .835, p = .0417). The correlation between baseline prevalence and parasite resistance surface maps was stronger than that between prevalence and vector resistance surface maps. The centre of the study area had high prevalence and suitability for parasite and vector gene flow, potentially contributing to persistent transmission and suggesting the importance of re-evaluating transmission zone boundaries. With suitably dense sampling, this framework can help delineate transmission zones for onchocerciasis and would be translatable to other vector-borne diseases.

Effective dispersal patterns in prairie plant species across human-modified landscapes

Effective dispersal among plant populations is dependent on vector behaviour, landscape features and availability of adequate habitats. To capture landscape feature effects on dispersal, studies must be conducted at scales reflecting single-generation dispersal events (mesoscale). Many studies are conducted at large scales where genetic differentiation is due to dispersal occurring over multiple generations, making it difficult to interpret the effects of specific landscape features on vector behaviour. Genetic structure at the mesoscale may be determined by ecological and evolutionary processes, such as the consequences of vector behaviour on patterns of gene flow. We used chloroplast haplotypes and nuclear genome SNP surveys to identify landscape features influencing seed and pollen dispersal at a mesoscale within the Rogue River Valley in southern Oregon. We evaluated biotic and abiotic vector behaviour by contrasting two annual species with differing dispersal mechanisms; Achyrachaena mollis (Asteraceae) is a self-pollinating and anemochoric species, and Plectritis congesta (Caprifoliaceae) is biotically pollinated with barochoric seeds. Using landscape genetics methods, we identified features of the study region that conduct or restrict dispersal. We found chloroplast haplotypes were indicative of historic patterns of gene flow prior to human modification of landscapes. Seed dispersal of A. mollis was best supported by models of isolation by distance, while seed-driven gene flow of P. congesta was determined by the distribution of preserved natural spaces and quality habitat. Nuclear genetic structure was driven by both pollen and seed dispersal, and both species responded to contemporary landscape changes, such as urban and agricultural conversion, and habitat availability.

Topographic barriers drive the pronounced genetic subdivision of a range-limited fossorial rodent

Due to their limited dispersal ability, fossorial species with predominantly belowground activity usually show increased levels of population subdivision across relatively small spatial scales. This may be exacerbated in harsh mountain ecosystems, where landscape geomorphology limits species' dispersal ability and leads to small effective population sizes, making species relatively vulnerable to environmental change. To better understand the environmental drivers of species' population subdivision in remote mountain ecosystems, particularly in understudied high-elevation systems in Africa, we studied the giant root-rat (Tachyoryctes macrocephalus), a fossorial rodent confined to the afro-alpine ecosystem of the Bale Mountains in Ethiopia. Using mitochondrial and low-coverage nuclear genomes, we investigated 77 giant root-rat individuals sampled from nine localities across its entire ~1000 km2 range. Our data revealed a distinct division into a northern and southern group, with no signs of gene flow, and higher nuclear genetic diversity in the south. Landscape genetic analyses of the mitochondrial and nuclear genomes indicated that population subdivision was driven by slope and elevation differences of up to 500 m across escarpments separating the north and south, potentially reinforced by glaciation of the south during the Late Pleistocene (~42,000-16,000 years ago). Despite this landscape-scale subdivision between the north and south, weak geographic structuring of sampling localities within regions indicated gene flow across distances of at least 16 km at the local scale, suggesting high, aboveground mobility for relatively long distances. Our study highlights that despite the potential for local-scale gene flow in fossorial species, topographic barriers can result in pronounced genetic subdivision. These factors can reduce genetic variability, which should be considered when developing conservation strategies.

Landscape Heterogeneity Explains the Genetic Differentiation of a Forest Bird across the Sino-Himalayan Mountains

Mountains are the world's most important centers of biodiversity. The Sino-Himalayan Mountains are global biodiversity hotspot due to their extremely high species richness and endemicity. Ample research investigated the impact of the Qinghai-Tibet Plateau uplift and Quaternary glaciations in driving species diversification in plants and animals across the Sino-Himalayan Mountains. However, little is known about the role of landscape heterogeneity and other environmental features in driving diversification in this region. We utilized whole genomes and phenotypic data in combination with landscape genetic approaches to investigate population structure, demography, and genetic diversity in a forest songbird species native to the Sino-Himalayan Mountains, the red-billed leiothrix (Leiothrix lutea). We identified 5 phylogeographic clades, including 1 in the East of China, 1 in Yunnan, and 3 in Tibet, roughly consistent with differences in song and plumage coloration but incongruent with traditional subspecies boundaries. Isolation-by-resistance model best explained population differentiation within L. lutea, with extensive secondary contact after allopatric isolation leading to admixture among clades. Ecological niche modeling indicated relative stability in the extent of suitable distribution areas of the species across Quaternary glacial cycles. Our results underscore the importance of mountains in the diversification of this species, given that most of the distinct genetic clades are concentrated in a relatively small area in the Sino-Himalayan Mountain region, while a single shallow clade populates vast lower-lying areas to the east. This study highlights the crucial role of landscape heterogeneity in promoting differentiation and provides a deep genomic perspective on the mechanisms through which diversity hotspots form.

Geographic and seasonal variation of the for gene reveal signatures of local adaptation in Drosophila melanogaster

In the early 1980s, the observation that Drosophila melanogaster larvae differed in their foraging behaviour laid the foundation for the work that would later lead to the discovery of the foraging gene (for) and its associated foraging phenotypes, rover and sitter. Since then, the molecular characterization of the for gene and our understanding of the mechanisms that maintain its phenotypic variants in the laboratory have progressed enormously. However, the significance and dynamics of such variation are yet to be investigated in nature. With the advent of next-generation sequencing, it is now possible to identify loci underlying the adaptation of populations in response to environmental variation. Here, I present the results of a genotype-environment association analysis that quantifies variation at the for gene among samples of D. melanogaster structured across space and time. These samples consist of published genomes of adult flies collected worldwide, and at least twice per site of collection (during spring and fall). Both an analysis of genetic differentiation based on Fs⁢t values and an analysis of population structure revealed an east-west gradient in allele frequency. This gradient may be the result of spatially varying selection driven by the seasonality of precipitation. These results support the hypothesis that different patterns of gene flow as expected under models of isolation by distance and potentially isolation by environment are driving genetic differentiation among populations. Overall, this study is essential for understanding the mechanisms underlying the evolution of foraging behaviour in D. melanogaster.

Genetic consequences of Last Glacial-Holocene changes in snowfall regime in Arnica mallotopus populations: A plant confined to heavy-snow areas of Japan

PREMISE

Snow is an important environmental factor affecting plant distribution. Past changes in snowfall regimes may have controlled the demographies of snow-dependent plants. However, our knowledge of changes in the distribution and demographies of such plants is limited because of the lack of fossil records.

METHODS

Population genetic and landscape genetic analyses were used to investigate the response of population dynamics of Arnica mallotopus (Asteraceae)-a plant confined to heavy-snow areas of Japan-to changes in snowfall regimes from the Last Glacial Period to the Holocene.

RESULTS

The population genetic analysis suggested that the four geographic lineages diverged during the Last Glacial Period. The interaction between reduced snowfall and lower temperatures during this period likely triggered population isolation in separate refugia. Subpopulation differentiation in the northern group was lower than in the southern group. Our ecological niche model predicted that the current distribution was patchy in the southern region; that is, the populations were isolated by topologically flat and climatically unsuitable lowlands. The landscape genetic analysis suggested that areas with little snowfall acted as barriers to the Holocene expansion of species distribution and continued limiting gene flow between local populations.

CONCLUSIONS

These findings indicate that postglacial population responses vary among regions and are controlled by environmental and geographic factors. Thus, changes in snowfall regime played a major role in shaping the distribution and genetic structure of the snow-dependent plant.

A window into local adaptation

How organisms adapt to their environment is not only a central topic of evolutionary biology but also a pressing question in the light of recent global change. Unravelling the genetic basis of these local adaptations can help to predict the response of a population to an increase in temperature or the more frequent occurrence of droughts. A popular approach to study the genes that drive local adaptation is the analysis of genotype-environment associations (GEA), testing the correlation of genomic features (typically single-nucleotide polymorphisms, SNPs) and environmental conditions. In this issue of Molecular Ecology Resources, Booker et al. (Molecular Ecology Resources, 2023) present a new approach to GEA, introducing genomic window analysis. They combine the information of neighbouring SNPs instead of analysing each SNP independently, therefore gaining power for detecting genomic signals of environmental adaptation. Using simulations of local adaptation to a heterogeneous environment as well as previously published real data from a natural population of lodgepole pine, they prove the superiority of their method over several established GEA approaches, especially in the case of small sample sizes. Leveraging the information present in closely linked genomic sites, Booker et al. (Molecular Ecology Resources, 2023) take genotype-environment association studies to the next level.

One metric or many? Refining the analytical framework of landscape resistance estimation in individual-based landscape genetic analyses

One of the allures of landscape genetics is the ability to leverage pairwise genetic distance metrics to infer how landscape features promote or constrain gene flow (i.e. landscape resistance surfaces). Critically, properly parameterized landscape resistance surfaces are foundational to applied conservation and management decisions. As such, there has been considerable effort expended assessing methods and metrics to estimate landscape resistance from genetic data (Balkenhol et al., Ecography, 32, 2009, 818; Peterman et al., Landsc. Ecol., 34, 2019, 2197; Shirk et al., Mol. Ecol. Resour., 17, 2017, 1308; Shirk et al., Mol. Ecol. Resour., 18, 2018, 55). Nonetheless, a primary challenge to assessing the effects of landscapes on gene flow is in the estimation of landscape resistance values, and this problem becomes increasingly challenging as more landscape features or land cover classes are considered. It quickly becomes infeasible to adequately assess the potential parameter space through manual or systematic assignment of resistance values. The development of ResistanceGA (Peterman, Methods Ecol. Evol., 9, 2018, 1638) provided a framework for using genetic algorithms to optimize landscape resistance values and identify the best statistical relationship between pairwise effective distances and genetic distances. ResistanceGA has seen extensive use in both population- and individual-based landscape genetic analyses. However, there has been relatively limited assessment of ResistanceGA's ability to identify the landscape features affecting gene flow (but see Peterman et al., Landsc. Ecol., 34, 2019, 2197; Winiarski et al., Mol. Ecol. Resour., 20, 2020, 1583) or the sensitivity of ResistanceGA results to the choice of genetic distance metric used. In the current issue of Molecular Ecology Resources, Beninde et al. (2023) aim to address these knowledge gaps by examining the impact of individual-based genetic distance measures on landscape genetic inference.

Conservation macrogenetics: harnessing genetic data to meet conservation commitments

Genetic biodiversity is rapidly gaining attention in global conservation policy. However, for almost all species, conservation relevant, population-level genetic data are lacking, limiting the extent to which genetic diversity can be used for conservation policy and decision-making. Macrogenetics is an emerging discipline that explores the patterns and processes underlying population genetic composition at broad taxonomic and spatial scales by aggregating and reanalyzing thousands of published genetic datasets. Here we argue that focusing macrogenetic tools on conservation needs, or conservation macrogenetics, will enhance decision-making for conservation practice and fill key data gaps for global policy. Conservation macrogenetics provides an empirical basis for better understanding the complexity and resilience of biological systems and, thus, how anthropogenic drivers and policy decisions affect biodiversity.

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.

Corridor-based approach with spatial cross-validation reveals scale-dependent effects of geographic distance, human footprint and canopy cover on grizzly bear genetic connectivity

Understanding how human infrastructure and other landscape attributes affect genetic differentiation in animals is an important step for identifying and maintaining dispersal corridors for these species. We built upon recent advances in the field of landscape genetics by using an individual-based and multiscale approach to predict landscape-level genetic connectivity for grizzly bears (Ursus arctos) across ~100,000 km2 in Canada's southern Rocky Mountains. We used a genetic dataset with 1156 unique individuals genotyped at nine microsatellite loci to identify landscape characteristics that influence grizzly bear gene flow at multiple spatial scales and map predicted genetic connectivity through a matrix of rugged terrain, large protected areas, highways and a growing human footprint. Our corridor-based modelling approach used a machine learning algorithm that objectively parameterized landscape resistance, incorporated spatial cross validation and variable selection and explicitly accounted for isolation by distance. This approach avoided overfitting, discarded variables that did not improve model performance across withheld test datasets and spatial predictive capacity compared to random cross-validation. We found that across all spatial scales, geographic distance explained more variation in genetic differentiation in grizzly bears than landscape variables. Human footprint inhibited connectivity across all spatial scales, while open canopies inhibited connectivity at the broadest spatial scale. Our results highlight the negative effect of human footprint on genetic connectivity, provide strong evidence for using spatial cross-validation in landscape genetics analyses and show that multiscale analyses provide additional information on how landscape variables affect genetic differentiation.

Multiscale landscape genetic analysis identifies major waterways as a barrier to dispersal of feral pigs in north Queensland, Australia

Feral pigs (Sus scrofa) are a destructive and widespread invasive pest in Australia. An understanding of feral pig movement is required to develop management strategies to control feral pigs in Australia. Because landscape structure can have a strong influence on animal movement, it is important to determine how landscape features facilitate or impede the movement of feral pigs. Consequently, we conducted a landscape genetic analysis of feral pig populations in the Herbert region of far north Queensland, Australia, to determine management units and provide recommendations to better inform feral pig population control strategies. Using microsatellite data obtained from 256 feral pig samples from 44 sites, we examined feral pig population structure at multiple spatial scales for univariate and multivariate landscape resistance surfaces to determine the optimal spatial scale and to identify which of the nine landscape features tested impede or facilitate feral pig gene flow. Only weak genetic structure was found among the 44 sampling sites, but major waterways were identified as a minor barrier to gene flow, and an isolation by distance model was supported. We also found that highways facilitated gene flow across the study area, and this suggests that they may act as movement corridors or indicate translocation of feral pigs. Additionally, incorporating a second spatial scale enhanced the ability of our landscape genetics analysis to detect the influence of landscape structure on gene flow. We identified three management units based on natural barriers to gene flow and future targeted control should be undertaken in these management units to deliver sustained reduction of feral pig populations in the Herbert region. This study demonstrates how a landscape genetic approach can be used to gain insight into the ecology of an invasive pest species and be used to develop population control strategies which utilise natural barriers to movement.

Population dynamics in newts of the Carpathian Mountains

Rarity, range restriction, and narrow endemism tend to carry dire and urgent conservation implications for imperilled species. What is also clear is that human-associated extinction risk factors such as urbanization and deforestation pose overwhelming threats to range-restricted species. In this issue of Molecular Ecology, Antunes et al. (2022) demonstrate that these threats can also impact widespread species. By comparing newts in the genus Lissotriton that co-occur in the same geographical region, they expose the distinctness of risks facing species with different habitat preferences. Their study emphasizes the importance of local-scale landscape genetics to reveal the nuances of population connectivity that might otherwise be missed by studying a broader spatial scale.

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.

Population genomic analysis reveals geographic structure and climatic diversification for Macrophomina phaseolina isolated from soybean and dry bean across the United States, Puerto Rico, and Colombia

Macrophomina phaseolina causes charcoal rot, which can significantly reduce yield and seed quality of soybean and dry bean resulting from primarily environmental stressors. Although charcoal rot has been recognized as a warm climate-driven disease of increasing concern under global climate change, knowledge regarding population genetics and climatic variables contributing to the genetic diversity of M. phaseolina is limited. This study conducted genome sequencing for 95 M. phaseolina isolates from soybean and dry bean across the continental United States, Puerto Rico, and Colombia. Inference on the population structure using 76,981 single nucleotide polymorphisms (SNPs) revealed that the isolates exhibited a discrete genetic clustering at the continental level and a continuous genetic differentiation regionally. A majority of isolates from the United States (96%) grouped in a clade with a predominantly clonal genetic structure, while 88% of Puerto Rican and Colombian isolates from dry bean were assigned to a separate clade with higher genetic diversity. A redundancy analysis (RDA) was used to estimate the contributions of climate and spatial structure to genomic variation (11,421 unlinked SNPs). Climate significantly contributed to genomic variation at a continental level with temperature seasonality explaining the most variation while precipitation of warmest quarter explaining the most when spatial structure was accounted for. The loci significantly associated with multivariate climate were found closely to the genes related to fungal stress responses, including transmembrane transport, glycoside hydrolase activity and a heat-shock protein, which may mediate climatic adaptation for M. phaseolina. On the contrary, limited genome-wide differentiation among populations by hosts was observed. These findings highlight the importance of population genetics and identify candidate genes of M. phaseolina that can be used to elucidate the molecular mechanisms that underly climatic adaptation to the changing climate.

Climate lags and genetics determine phenology in quaking aspen (Populus tremuloides)

Spatiotemporal patterns of phenology may be affected by mosaics of environmental and genetic variation. Environmental drivers may have temporally lagged impacts, but patterns and mechanisms remain poorly known. We combine multiple genomic, remotely sensed, and physically modeled datasets to determine the spatiotemporal patterns and drivers of canopy phenology in quaking aspen, a widespread clonal dioecious tree species with diploid and triploid cytotypes. We show that over 391 km² of southwestern Colorado: greenup date, greendown date, and growing season length vary by weeks and differ across sexes, cytotypes, and genotypes; phenology has high phenotypic plasticity and heritabilities of 31-61% (interquartile range); and snowmelt date, soil moisture, and air temperature predict phenology, at temporal lags of up to 3 yr. Our study shows that lagged environmental effects are needed to explain phenological variation and that the effect of cytotype on phenology is obscured by its correlation with topography. Phenological patterns are consistent with responses to multiyear accumulation of carbon deficit or hydraulic damage.

Biodiversity protection against anthropogenic climate change: Conservation prioritization of Castanea sativa in the South Caucasus based on genetic and ecological metrics

The climate drives species distribution and genetic diversity; the latter defines the adaptability of populations and species. The ongoing climate crisis induces tree decline in many regions, compromising the mitigation potential of forests. Scientific-based strategies for prioritizing forest tree populations are critical to managing the impact of climate change. Identifying future climate refugia, which are locations naturally buffering the negative impact of climate change, may facilitate local conservation. In this work, we conducted the populations' prioritization for Castanea sativa (sweet chestnut), a Neogene relict growing in the Caucasus global biodiversity hotspot. We generated genetic and ecological metrics for 21 sites in Georgia and Azerbaijan, which cover the natural range of sweet chestnut across the region. We demonstrated that climate primarily drives the pattern of genetic diversity in C. sativa, proved with a significant isolation-by-environment model. In future, climate change may significantly reorganize the species' genetic diversity, inducing even some genetic loss, especially in the very distinct eastern fringe of the species range in Azerbaijan. Based on our combined approach, we mapped populations suitable for ex situ and in situ conservation, accounting for genetic variability and the location of future climate refugia.

Empirical landscape genetic comparison of single nucleotide polymorphisms and microsatellites in three arid-zone mammals with high dispersal capacity

Landscape genetics is increasingly transitioning away from microsatellites, with single nucleotide polymorphisms (SNPs) providing increased resolution for detecting patterns of spatial-genetic structure. This is particularly pertinent for research in arid-zone mammals due to challenges associated with unique life history traits, such as boom-bust population dynamics and long-distance dispersal capacities. Here, we provide a case study comparing SNPs versus microsatellites for testing three explicit landscape genetic hypotheses (isolation-by-distance, isolation-by-barrier, and isolation-by-resistance) in a suite of small, arid-zone mammals in the Pilbara region of Western Australia. Using clustering algorithms, Mantel tests, and linear mixed effects models, we compare functional connectivity between genetic marker types and across species, including one marsupial, Ningaui timealeyi, and two native rodents, Pseudomys chapmani and P. hermannsburgensis. SNPs resolved subtle genetic structuring not detected by microsatellites, particularly for N. timealeyi where two genetic clusters were identified. Furthermore, stronger signatures of isolation-by-distance and isolation-by-resistance were detected when using SNPs, and model selection based on SNPs tended to identify more complex resistance surfaces (i.e., composite surfaces of multiple environmental layers) in the best-performing models. While we found limited evidence for physical barriers to dispersal across the Pilbara for all species, we found that topography, substrate, and soil moisture were the main environmental drivers shaping functional connectivity. Our study demonstrates that new analytical and genetic tools can provide novel ecological insights into arid landscapes, with potential application to conservation management through identifying dispersal corridors to mediate the impacts of ongoing habitat fragmentation in the region.

Simulating the effects of long-distance dispersal and landscape heterogeneity on the eco-evolutionary outcomes of range expansion in an invasive riverine fish, Tench (Tinca tinca)

Predicting how quickly populations expand their range and whether they will retain genetic diversity when they are introduced to new regions or track environmental conditions suited to their survival is an important applied and theoretical challenge. The literature suggests that long-distance dispersal, landscape heterogeneity and the evolution of dispersal influence populations' expansion rates and genetic diversity. We used individual-based spatially explicit simulations to examine these relationships for Tench (Tinca tinca), an invasive fish expanding its geographical range in eastern North America since the 1990s. Simulated populations varied greatly in expansion rates (1.1-28.6 patches year^-1 ) and genetic diversity metrics, including changes in observed heterozygosity (-19 to +0.8%) and effective number of alleles (-0.32 to -0.01). Populations with greater dispersal distances expanded faster than those with smaller dispersal distances but exhibited considerable variation in expansion rate among local populations, implying less predictable expansions. However, they tended to retain genetic diversity as they expanded, suggesting more predictable evolutionary trajectories. In contrast, populations with smaller dispersal distances spread predictably more slowly but exhibited more variability among local populations in genetic diversity losses. Consistent with empirical data, populations spreading in a longer, narrower dispersal corridor lost more neutral genetic variation to the stochastic fixation of alleles. Given the unprecedented pace of anthropogenic environmental change and the increasing need to manage range-expanding populations, our results have conservation ramifications as they imply that the evolutionary trajectories of populations characterised by shorter dispersal distances spreading in narrower landscapes are more variable and, therefore, less predictable.

Implementing landscape genetics in molecular epidemiology to determine drivers of vector-borne disease: A malaria case study

This study employs landscape genetics to investigate the environmental drivers of a deadly vector-borne disease, malaria caused by Plasmodium falciparum, in a more spatially comprehensive manner than any previous work. With 1804 samples from 44 sites collected in western Kenya in 2012 and 2013, we performed resistance surface analysis to show that Lake Victoria acts as a barrier to transmission between areas north and south of the Winam Gulf. In addition, Mantel correlograms clearly showed significant correlations between genetic and geographic distance over short distances (less than 70 km). In both cases, we used an identity-by-state measure of relatedness tailored to find highly related individual parasites in order to focus on recent gene flow that is more relevant to disease transmission. To supplement these results, we performed conventional population genetics analyses, including Bayesian clustering methods and spatial ordination techniques. These analyses revealed some differentiation on the basis of geography and elevation and a cluster of genetic similarity in the lowlands north of the Winam Gulf of Lake Victoria. Taken as a whole, these results indicate low overall genetic differentiation in the Lake Victoria region, but with some separation of parasite populations north and south of the Winam Gulf that is explained by the presence of the lake as a geographic barrier to gene flow. We recommend similar landscape genetics analyses in future molecular epidemiology studies of vector-borne diseases to extend and contextualize the results of traditional population genetics.

Demographic and spatially-explicit landscape genomic analyses in a tropical oak reveal the impacts of late Quaternary climate change on Andean montane forests

Tropical Andes are one of the most important biodiversity hotspots on earth, yet our understanding on how their biotas have responded to Quaternary climatic oscillations is extraordinarily limited and the alternative models proposed to explain their demographic dynamics have been seldom formally evaluated. Here, we test the hypothesis that the interplay between the spatial configuration of geographical barriers to dispersal and elevational displacements driven by Quaternary cooling-warming cycles have shaped the demographic trajectories of montane oak forests (Quercus humboldtii) from the Colombian Andes. Specifically, we integrate genomic data and environmental niche modelling at fine temporal resolution to test competing spatially-explicit demographic and coalescent models, including scenarios considering (i) isotropic gene flow through the landscape, (ii) the hypothetical impact of contemporary barriers to dispersal (i.e., inter-Andean valleys), and (ii) distributional shifts of montane oak forests from the Last Glacial Maximum to present. Although our data revealed a marked genetic fragmentation of montane oak forests, statistical support for isolation-with-migration models indicate that geographically separated populations from the different Andean Cordilleras regularly exchange gene flow. Accordingly, spatiotemporally-explicit demographic analyses supported a model of flickering connectivity, with scenarios considering isotropic gene flow or currently unsuitable habitats as persistent barriers to dispersal providing a comparatively worse fit to empirical genomic data. Overall, these results emphasize the role of landscape heterogeneity on shaping spatial patterns of genomic variation in montane oak forests, rejecting the hypothesis of genetic continuity and supporting a significant impact of Quaternary climatic oscillations on their demographic trajectories.

Terrain Ruggedness and Canopy Height Predict Short-Range Dispersal in the Critically Endangered Black-and-White Ruffed Lemur

Dispersal is a fundamental aspect of primates' lives and influences both population and community structuring, as well as species evolution. Primates disperse within an environmental context, where both local and intervening environmental factors affect all phases of dispersal. To date, research has primarily focused on how the intervening landscape influences primate dispersal, with few assessing the effects of local habitat characteristics. Here, we use a landscape genetics approach to examine between- and within-site environmental drivers of short-range black-and-white ruffed lemur (Varecia variegata) dispersal in the Ranomafana region of southeastern Madagascar. We identified the most influential drivers of short-range ruffed lemur dispersal as being between-site terrain ruggedness and canopy height, more so than any within-site habitat characteristic evaluated. Our results suggest that ruffed lemurs disperse through the least rugged terrain that enables them to remain within their preferred tall-canopied forest habitat. Furthermore, we noted a scale-dependent environmental effect when comparing our results to earlier landscape characteristics identified as driving long-range ruffed lemur dispersal. We found that forest structure drives short-range dispersal events, whereas forest presence facilitates long-range dispersal and multigenerational gene flow. Together, our findings highlight the importance of retaining high-quality forests and forest continuity to facilitate dispersal and maintain functional connectivity in ruffed lemurs.

Inferring population connectivity in eastern massasauga rattlesnakes (Sistrurus catenatus) using landscape genetics

Assessing the environmental factors that influence the ability of a threatened species to move through a landscape can be used to identify conservation actions that connect isolated populations. However, direct observations of species' movement are often limited, making the development of alternate approaches necessary. Here we use landscape genetic analyses to assess the impact of landscape features on the movement of individuals between local populations of a threatened snake, the eastern massasauga rattlesnake (Sistrurus catenatus). We linked connectivity data with habitat information from two landscapes of similar size: a large region of unfragmented habitat and a previously studied fragmented landscape consisting of isolated patches of habitat. We used this analysis to identify features of the landscape where modification or acquisition would enhance population connectivity in the fragmented region. We found evidence that current connectivity was impacted by both contemporary land-cover features, especially roads, and inherent landscape features such as elevation. Next, we derived estimates of expected movement ability using a recently developed pedigree-based approach and least-cost paths through the unfragmented landscape. We then used our pedigree and resistance map to estimate resistance polygons of the potential extent for S. catenatus movement in the fragmented landscape. These polygons identify possible sites for future corridors connecting currently isolated populations in this landscape by linking the impact of future habitat modification or land acquisition to dispersal ability in this species. Overall, our study shows how modeling landscape resistance across differently fragmented landscapes can identify habitat features that affect contemporary movement in threatened species in fragmented landscapes and how this information can be used to guide mitigation actions whose goal is to connect isolated populations.

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.

Pilot Study on the Geographical Mapping of Genetic Diversity among European Chestnut (Castanea sativa Mill.) Cultivars in Southern Italy

Knowledge of the spatial distribution of European chestnut (Castanea sativa Mill.) cultivar diversity is essential for managing and conserving the genetic resources of this fruit tree species in Southern Italy. To this goal, the present work investigated the feasibility of mapping, through spatial representation, the distribution of genetic diversity of traditional chestnut varieties in the area of the Roccamonfina Regional Park in the Campania Region. After Principal Coordinates Analysis (PCoA) of molecular-genetic data, chestnuts formed varietal groups in a leopard spot on PCoA plots with a relatively high degree of genetic diversity. Successively, a Geographic Information System (GIS) tool utilized these molecular-genetic data to create a genetic divergence surface by geospatial interpolation on the geographic map of the Regional Park corresponding to each chestnut variety. The regions containing more biodiversity richness resulted in differentially colored from those containing cultivars less genetically distant from each other; thus, the area in study was consistently colored according to the allelic richness as evaluated by molecular-genetic markers. The combined use of tools for molecular and spatial analysis allowed for drafting genetic landscapes with the aim of extracting useful information for the safeguarding of the chestnut biodiversity at risk.

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.

Validating graph-based connectivity models with independent presence-absence and genetic data sets

Habitat connectivity is a key objective of current conservation policies and is commonly modeled by landscape graphs (i.e., sets of habitat patches [nodes] connected by potential dispersal paths [links]). These graphs are often built based on expert opinion or species distribution models (SDMs) and therefore lack empirical validation from data more closely reflecting functional connectivity. Accordingly, we tested whether landscape graphs reflect how habitat connectivity influences gene flow, which is one of the main ecoevolutionary processes. To that purpose, we modeled the habitat network of a forest bird (plumbeous warbler [Setophaga plumbea]) on Guadeloupe with graphs based on expert opinion, Jacobs' specialization indices, and an SDM. We used genetic data (712 birds from 27 populations) to compute local genetic indices and pairwise genetic distances. Finally, we assessed the relationships between genetic distances or indices and cost distances or connectivity metrics with maximum-likelihood population-effects distance models and Spearman correlations between metrics. Overall, the landscape graphs reliably reflected the influence of connectivity on population genetic structure; validation R² was up to 0.30 and correlation coefficients were up to 0.71. Yet, the relationship among graph ecological relevance, data requirements, and construction and analysis methods was not straightforward because the graph based on the most complex construction method (species distribution modeling) sometimes had less ecological relevance than the others. Cross-validation methods and sensitivity analyzes allowed us to make the advantages and limitations of each construction method spatially explicit. We confirmed the relevance of landscape graphs for conservation modeling but recommend a case-specific consideration of the cost-effectiveness of their construction methods. We hope the replication of independent validation approaches across species and landscapes will strengthen the ecological relevance of connectivity models.

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.

Landscape Genomics to Enable Conservation Actions: The California Conservation Genomics Project

The California Conservation Genomics Project (CCGP) is a unique, critically important step forward in the use of comprehensive landscape genetic data to modernize natural resource management at a regional scale. We describe the CCGP, including all aspects of project administration, data collection, current progress, and future challenges. The CCGP will generate, analyze, and curate a single high-quality reference genome and 100-150 resequenced genomes for each of 153 species projects (representing 235 individual species) that span the ecological and phylogenetic breadth of California's marine, freshwater, and terrestrial ecosystems. The resulting portfolio of roughly 20 000 resequenced genomes will be analyzed with identical informatic and landscape genomic pipelines, providing a comprehensive overview of hotspots of within-species genomic diversity, potential and realized corridors connecting these hotspots, regions of reduced diversity requiring genetic rescue, and the distribution of variation critical for rapid climate adaptation. After 2 years of concerted effort, full funding ($12M USD) has been secured, species identified, and funds distributed to 68 laboratories and 114 investigators drawn from all 10 University of California campuses. The remaining phases of the CCGP include completion of data collection and analyses, and delivery of the resulting genomic data and inferences to state and federal regulatory agencies to help stabilize species declines. The aspirational goals of the CCGP are to identify geographic regions that are critical to long-term preservation of California biodiversity, prioritize those regions based on defensible genomic criteria, and provide foundational knowledge that informs management strategies at both the individual species and ecosystem levels.

Genetic diversity pattern reveals the primary determinant of burcucumber (Sicyos angulatus L.) invasion in Korea

Biological invasion is a complex process associated with propagule pressure, dispersal ability, environmental constraints, and human interventions, which leave genetic signatures. The population genetics of an invasive species thus provides invaluable insights into the patterns of invasion. Burcucumber, one of the most detrimental weeds for soybean production in US, has recently colonized Korea and rapidly spread posing a great threat to the natural ecosystem. We aim to infer the determinants of the rapid burcucumber invasion by examining the genetic diversity, demography, and spread pattern with advanced genomic tools. We employed 2,696 genome-wide single-nucleotide polymorphisms to assess the level of diversity and the spatial pattern associated with the landscape factors and to infer the demographic changes of 24 populations (364 genotypes) across four major river basins with the east coastal streams in South Korea. Through the approximate Bayesian computation, we inferred the likely invasion scenario of burcucumber in Korea. The landscape genetics approach adopting the circuit theory and MaxEnt model was applied to determine the landscape contributors. Our data suggested that most populations have experienced population bottlenecks, which led to lowered within-population genetic diversity and inflated population divergences. Burcucumber colonization in Korea has strongly been affected by demographic bottlenecks and multiple introductions, whereas environmental factors were not the primary determinant of the invasion. Our work highlighted the significance of preventing secondary introductions, particularly for aggressive weedy plants such as the burcucumber.

Pleistocene-Holocene vicariance, not Anthropocene landscape change, explains the genetic structure of American black bear (Ursus americanus) populations in the American Southwest and northern Mexico

The phylogeography of the American black bear (Ursus americanus) is characterized by isolation into glacial refugia, followed by population expansion and genetic admixture. Anthropogenic activities, including overharvest, habitat loss, and transportation infrastructure, have also influenced their landscape genetic structure. We describe the genetic structure of the American black bear in the American Southwest and northern Mexico and investigate how prehistoric and contemporary forces shaped genetic structure and influenced gene flow. Using a suite of microsatellites and a sample of 550 bears, we identified 14 subpopulations organized hierarchically following the distribution of ecoregions and mountain ranges containing black bear habitat. The pattern of subdivision we observed is more likely a product of postglacial habitat fragmentation during the Pleistocene and Holocene, rather than a consequence of contemporary anthropogenic barriers to movement during the Anthropocene. We used linear mixed‐effects models to quantify the relationship between landscape resistance and genetic distance among individuals, which indicated that both isolation by resistance and geographic distance govern gene flow. Gene flow was highest among subpopulations occupying large tracts of contiguous habitat, was reduced among subpopulations in the Madrean Sky Island Archipelago, where montane habitat exists within a lowland matrix of arid lands, and was essentially nonexistent between two isolated subpopulations. We found significant asymmetric gene flow supporting the hypothesis that bears expanded northward from a Pleistocene refugium located in the American Southwest and northern Mexico and that major highways were not yet affecting gene flow. The potential vulnerability of the species to climate change, transportation infrastructure, and the US–Mexico border wall highlights conservation challenges and opportunities for binational collaboration.

Breeding system and geospatial variation shape the population genetics of Triodanis perfoliata

Both intrinsic and extrinsic forces work together to shape connectivity and genetic variation in populations across the landscape. Here we explored how geography, breeding system traits, and environmental factors influence the population genetic patterns of Triodanis perfoliata, a widespread mix‐mating annual plant in the contiguous US. By integrating population genomic data with spatial analyses and modeling the relationship between a breeding system and genetic diversity, we illustrate the complex ways in which these forces shape genetic variation. Specifically, we used 4705 single nucleotide polymorphisms to assess genetic diversity, structure, and evolutionary history among 18 populations. Populations with more obligately selfing flowers harbored less genetic diversity (π: R² = .63, p = .01, n = 9 populations), and we found significant population structuring (F_ST = 0.48). Both geographic isolation and environmental factors played significant roles in predicting the observed genetic diversity: we found that corridors of suitable environments appear to facilitate gene flow between populations, and that environmental resistance is correlated with increased genetic distance between populations. Last, we integrated our genetic results with species distribution modeling to assess likely patterns of connectivity among our study populations. Our landscape and evolutionary genetic results suggest that T. perfoliata experienced a complex demographic and evolutionary history, particularly in the center of its distribution. As such, there is no singular mechanism driving this species' evolution. Together, our analyses support the hypothesis that the breeding system, geography, and environmental variables shape the patterns of diversity and connectivity of T. perfoliata in the US.

Natural and anthropogenic landscape factors shape functional connectivity of an ecological specialist in urban Southern California

Identifying how natural (i.e., unaltered by human activity) and anthropogenic landscape variables influence contemporary functional connectivity in terrestrial organisms can elucidate the genetic consequences of environmental change. We examine population genetic structure and functional connectivity among populations of a declining species, the Blainville's horned lizard (Phrynosoma blainvillii), in the urbanized landscape of the Greater Los Angeles Area in Southern California, USA. Using single nucleotide polymorphism data, we assessed genetic structure among populations occurring at the interface of two abutting evolutionary lineages, and at a fine scale among habitat fragments within the heavily urbanized area. Based on the ecology of P. blainvillii, we predicted which environmental variables influence population structure and gene flow and used gravity models to distinguish among hypotheses to best explain population connectivity. Our results show evidence of admixture between two evolutionary lineages and strong population genetic structure across small habitat fragments. We also show that topography, microclimate, and soil and vegetation types are important predictors of functional connectivity, and that anthropogenic disturbance, including recent fire history and urban development, are key factors impacting contemporary population dynamics. Examining how natural and anthropogenic sources of landscape variation affect contemporary population genetics is critical to understanding how to best manage sensitive species in a rapidly changing landscape.

Seizing the Moment: The opportunity and relevance of the California Conservation Genomics Project to state and federal conservation policy

Conservation science and environmental regulation are sibling constructs of the latter half of the 20th century, part of a more general awakening to humanity's effect on the natural world in the wake of two world wars. Efforts to understand the evolution of biodiversity using the models of population genetics and the data derived from DNA sequencing, paired with legal and political mandates to protect biodiversity through novel laws, regulations, and conventions arose concurrently. The extremely rapid rate of development of new molecular tools to document and compare genetic identities, and the global goal of prioritizing species and habitats for protection are separate enterprises that have benefited from each other, ultimately leading to improved outcomes for each. In this article, we explore how the California Conservation Genomics Project has, and should, contribute to ongoing and future conservation implementation, and how it serves as a model for other geopolitical regions and taxon-oriented conservation efforts. One of our primary conclusions is that conservation genomics can now be applied, at scale, to inform decision-makers and identify regions and their contained species that are most resilient, and most in need of conservation interventions.

The phylogeny of California, and how it informs setting multi-species conservation priorities

Incorporating measures of taxonomic diversity into research and management plans has long been a tenet of conservation science. Increasingly, active conservation programs are turning towards multi-species landscape and regional conservation actions, and away from single species approaches. This is both a reflection of changing trends in conservation science and advances in foundational technologies, including genomics and geospatial science. Multi-species approaches may provide more fundamental insights into evolutionary processes and equip managers with a more holistic understanding of the landscapes under their jurisdiction. Central to this approach are data generation and analyses which embrace and reflect a broad range of taxonomic diversity. Here we examine the family-level phylogenetic breadth of the California Conservation Genomics Project (CCGP) based on family-level phylogenetic diversity, family-level phylogenetic distinctness, and family richness. We place this in the context of the diversity present in California and compare it to the 35-plus years of genetic research compiled in the CaliPopGen Database. We found that the family-level phylogenetic diversity in the CCGP reflected that of California very well, slightly over-representing chordates and under-representing arthropods, and that 42% of CCGP phylogenetic diversity represented new contributions to genetic data for the state. In one focused effort, the CCGP was able to achieve roughly half the family-level phylogenetic diversity studied over the last several decades. To maximize studied phylogenetic diversity, future work should focus on arthropods, a conclusion that likely reflects the overall lack of attention to this hyper diverse clade.

Elevated inbreeding in Heliconia tortuosa is determined by tropical forest stand age, isolation, and loss of hummingbird functional diversity

Forest conversion and habitat loss are major threats to biological diversity. Forest regeneration can mitigate the negative effects of old growth forest loss on species diversity, but less is known about the extent to which forest loss reduces genetic diversity in remnant populations and whether secondary forests play a role in the maintenance of genetic diversity. We quantified genetic diversity in a tropical hummingbird-pollinated understory herb, Heliconia tortuosa, across a landscape mosaic of primary and secondary forest regrowth. Using microsatellite genotypes from >850 adult and juvenile plants within 33 forest patches and extensive bird surveys, we examined the effect of contemporary and historical landscape features including forest age (primary vs. secondary forest), stand isolation, and pollinator assemblages on genetic diversity and levels of inbreeding in H. tortuosa. We found that inbreeding was up to 3x higher in secondary forest, and this effect was amplified with reductions in primary forest in the surrounding landscape through reduced observed heterozygosity in isolated fragments. Inbreeding in forest patches was negatively correlated with the local frequency of specialist long-distance foraging traplining hummingbirds. Traplining hummingbirds therefore appear to facilitate mating among unrelated plants - an inference we tested using empirically parameterized simulations. Higher levels of inbreeding in H. tortuosa are therefore associated with reduced functional diversity of hummingbirds in secondary forests and forest patches isolated from primary forests. Our findings suggest a cryptic consequence of primary forest loss and secondary forest regeneration through the disruption of mutualistic interactions resulting in the erosion of genetic diversity in a common understory plant.

Population demography maintains biogeographic boundaries

Global biodiversity is organised into biogeographic regions that comprise distinct biotas. The contemporary factors maintaining differences in species composition between regions are poorly understood. Given evidence that populations with sufficient genetic variation can adapt to fill new habitats, it is surprising that more homogenisation of species assemblages across regions has not occurred. Theory suggests that expansion across biogeographic regions could be limited by reduced adaptive capacity due to demographic variation along environmental gradients, but this possibility has not been empirically explored. Using three independently curated data sets describing continental patterns of mammalian demography and population genetics, we show that populations near biogeographic boundaries have lower effective population sizes and genetic diversity, and are more genetically differentiated. These patterns are consistent with reduced adaptive capacity in areas where one biogeographic region transitions into the next. That these patterns are replicated across mammals suggests they are stable and generalisable in their contribution to long-term limits on biodiversity homogenisation. Understanding the contemporary processes that maintain compositional differences among regional biotas is crucial for our understanding of the current and future organisation of global biodiversity.

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.

Main roads and land cover shaped the genetic structure of a Mediterranean island wild boar population

Patterns of genetic differentiation within and among animal populations might vary due to the simple effect of distance or landscape features hindering gene flow. An assessment of how landscape connectivity affects gene flow can help guide management, especially in fragmented landscapes. Our objective was to analyze population genetic structure and landscape genetics of the native wild boar (Sus scrofa meridionalis) population inhabiting the island of Sardinia (Italy), and test for the existence of Isolation-by-Distance (IBD), Isolation-by-Barrier (IBB), and Isolation-by-Resistance (IBR). A total of 393 Sardinian wild boar samples were analyzed using a set of 16 microsatellite loci. Signals of genetic introgression from introduced non-native wild boars or from domestic pigs were revealed by a Bayesian cluster analysis including 250 reference individuals belonging to European wild populations and domestic breeds. After removal of introgressed individuals, genetic structure in the population was investigated by different statistical approaches, supporting a partition into five discrete subpopulations, corresponding to five geographic areas on the island: north-west (NW), central west (CW), south-west (SW), north-central east (NCE), and south-east (SE). To test the IBD, IBB, and IBR hypotheses, we optimized resistance surfaces using genetic algorithms and linear mixed-effects models with a maximum likelihood population effects parameterization. Landscape genetics analyses revealed that genetic discontinuities between subpopulations can be explained by landscape elements, suggesting that main roads, urban settings, and intensively cultivated areas are hampering gene flow (and thus individual movements) within the Sardinian wild boar population. Our results reveal how human-transformed landscapes can affect genetic connectivity even in a large-sized and highly mobile mammal such as the wild boar, and provide crucial information to manage the spread of pathogens, including the African Swine Fever virus, endemic in Sardinia.

Remote sensing of cytotype and its consequences for canopy damage in quaking aspen

Mapping geographic mosaics of genetic variation and their consequences via genotype x environment interactions at large extents and high resolution has been limited by the scalability of DNA sequencing. Here, we address this challenge for cytotype (chromosome copy number) variation in quaking aspen, a drought-impacted foundation tree species. We integrate airborne imaging spectroscopy data with ground-based DNA sequencing data and canopy damage data in 391 km² of southwestern Colorado. We show that (1) aspen cover and cytotype can be remotely sensed at 1 m spatial resolution, (2) the geographic mosaic of cytotypes is heterogeneous and interdigitated, (3) triploids have higher leaf nitrogen, canopy water content, and carbon isotope shifts (δ¹³ C) than diploids, and (4) canopy damage varies among cytotypes and depends on interactions with topography, canopy height, and trait variables. Triploids are at higher risk in hotter and drier conditions.

Species-landscape interactions drive divergent population trajectories in four forest-dependent Afromontane forest songbird species within a biodiversity hotspot in South Africa

Species confined to naturally fragmented habitats may exhibit intrinsic population complexity which may challenge interpretations of species response to anthropogenic landscape transformation. In South Africa, where native forests are naturally fragmented, forest-dependent birds have undergone range declines since 1992, most notably among insectivores. These insectivores appear sensitive to the quality of natural matrix habitats, and it is unknown whether transformation of the landscape matrix has disrupted gene flow in these species. We undertook a landscape genetics study of four forest-dependent insectivorous songbirds across southeast South Africa. Microsatellite data were used to conduct a priori optimization of landscape resistance surfaces (land cover, rivers and dams, and elevation) using cost-distances along least-cost pathway (LCP), and resistance distances (IBR). We detected pronounced declines in effective population sizes over the past two centuries for the endemic forest specialist Cossypha dichroa and Batis capensis, alongside recent gene flow disruption in B. capensis, C. dichroa and Pogonocichla stellata. Landscape resistance modelling showed both native forest and dense thicket configuration facilitates gene flow in P. stellata, B. capensis and C. dichroa. Facultative dispersal of P. stellata through dense thicket likely aided resilience against historic landscape transformation, whereas combined forest-thicket degradation adversely affected the forest generalist B. capensis. By contrast, Phylloscopus ruficapilla appears least reliant upon landscape features to maintain gene flow and was least impacted by anthropogenic landscape transformation. Collectively, gene flow in all four species is improved at lower elevations, along river valleys, and riparian corridors- where native forest and dense thicket better persist. Consistent outperformance of LCP over IBR land-cover models for P. stellata, B. capensis and C. dichroa demonstrates the benefits of wildlife corridors for South African forest-dependent bird conservation, to ameliorate the extinction debts from past and present anthropogenic forest exploitation.

Agricultural intensification alters marbled newt genetic diversity and gene flow through density and dispersal reduction

Recent agricultural intensification threatens global biodiversity with amphibians being one of the most impacted groups. Because of their biphasic life cycle, amphibians are particularly vulnerable to habitat loss and fragmentation that often result in small, isolated populations and loss of genetic diversity. Here, we studied how landscape heterogeneity affects genetic diversity, gene flow and demographic parameters in the marbled newt, Triturus marmoratus, over a hedgerow network landscape in Western France. While the northern part of the study area consists of preserved hedged farmland, the southern part was more profoundly converted for intensive arable crops production after WWII. Based on 67 sampled ponds and 10 microsatellite loci, we characterized regional population genetic structure and evaluated the correlation between landscape variables and (i) local genetic diversity using mixed models and (ii) genetic distance using multiple regression methods and commonality analysis. We identified a single genetic population characterized by a spatially heterogeneous isolation-by-distance pattern. Pond density in the surrounding landscape positively affected local genetic diversity while arable crop land cover negatively affected gene flow and connectivity. We used demographic inferences to quantitatively assess differences in effective population density and dispersal between the contrasted landscapes characterizing the northern and southern parts of the study area. Altogether, results suggest recent land conversion affected T. marmoratus through reduction in both effective population density and dispersal due to habitat loss and reduced connectivity.

Location and Species Matters: Variable Influence of the Environment on the Gene Flow of Imperiled, Native and Invasive Cottontails

The environment plays an important role in the movement of individuals and their associated genes among populations, which facilitates gene flow. Gene flow can help maintain the genetic diversity both within and between populations and counter the negative impact of genetic drift, which can decrease the fitness of individuals. Sympatric species can have different habitat preferences, and thus can exhibit different patterns of genetic variability and population structure. The specialist-generalist variation hypothesis (SGVH) predicts that specialists will have lower genetic diversity, lower effective population sizes (Ne), and less gene flow among populations. In this study, we used spatially explicit, individual-based comparative approaches to test SGVH predictions in two sympatric cottontail species and identify environmental variables that influence their gene flow. New England cottontail (Sylvilagus transitionalis) is the only native cottontail in the Northeast US, an early successional habitat specialist, and a species of conservation concern. Eastern cottontail (S. floridanus) is an invasive species in the Northeast US and a habitat generalist. We characterized each species' genomic variation by developing double-digest Restriction-site Associated DNA sequence single nucleotide polymorphism markers, quantified their habitat with Geographic Information System environmental variables, and conducted our analyses at multiple scales. Surprisingly, both species had similar levels of genetic diversity and eastern cottontail's Ne was only higher than New England cottontail in one of three subregions. At a regional level, the population clusters of New England cottontail were more distinct than eastern cottontail, but the subregional levels showed more geographic areas of restricted gene flow for eastern cottontail than New England cottontail. In general, the environmental variables had the predicted effect on each species' gene flow. However, the most important environmental variable varied by subregion and species, which shows that location and species matter. Our results provide partial support for the SGVH and the identification of environmental variables that facilitate or impede gene flow can be used to help inform management decisions to conserve New England cottontail.

Strip spraying delays pyrethroid resistance in the redlegged earth mite, Halotydeus destructor: a novel refuge strategy

BACKGROUND

Pesticide resistance has seen control options for the redlegged earth mite (RLEM), Halotydeus destructor, dwindle for Australian grain farmers. The recent discovery of high recessiveness for pyrethroid resistance in RLEM provided an opportunity to examine the feasibility of a refuge strategy to slow the evolution of resistance. Unlike lepidopterous pests in Bt crops, where refuge strategies are routinely practiced, RLEM is a slow-moving pest, which will impact the design of susceptible refuges.

RESULTS

Firstly, we confirmed the pyrethroid resistant allele is recessive to the susceptible (wildtype) allele (in terms of resistance) across spatially separated Australian populations. Secondly, we demonstrated that a small, localized resistant mite population can revert to susceptibility at field relevant scales and conditions. Next, we used a simulation modelling approach to design a practical refuge strategy to maintain susceptibility to pyrethroids in populations with a low incidence of resistance. Certain configurations (e.g. a pesticide strip width of 50 m and refuge spacing of 10 m) maintained low levels of resistance across a 10-year time horizon, with lower mite abundance and minimal yield loss. A larger refuge proportion did not always delay resistance, and, under certain conditions, increased resistance frequency.

CONCLUSION

Strip spraying to maintain refuges can be readily incorporated into RLEM management programs where sprayer widths in commercial cropping contexts are typically between 20-40 m. A refuge approach to RLEM management that uses strip spraying may enhance long term control options in the absence of new chemical registrations but will now require field validation. © 2021 Society of Chemical Industry.

Dispersal behaviour and riverine network connectivity shape the genetic diversity of freshwater amphipod metapopulations

Theory predicts that the distribution of genetic diversity in a landscape is strongly dependent on the connectivity of the metapopulation and the dispersal of individuals between patches. However, the influence of explicit spatial configurations such as dendritic landscapes on the genetic diversity of metapopulations is still understudied, and theoretical corroborations of empirical patterns are largely lacking. Here, we used microsatellite data and stochastic simulations of two metapopulations of freshwater amphipods in a 28,000 km² riverine network to study the influence of spatial connectivity and dispersal strategies on the spatial distribution of their genetic diversity. We found a significant imprint of the effects of riverine network connectivity on the local and global genetic diversity of both amphipod species. Data from 95 sites showed that allelic richness significantly increased towards more central nodes of the network. This was also seen for observed heterozygosity, yet not for expected heterozygosity. Genetic differentiation increased with instream distance. In simulation models, depending on the mutational model assumed, upstream movement probability and dispersal rate, respectively, emerged as key factors explaining the empirically observed distribution of local genetic diversity and genetic differentiation. Surprisingly, the role of site‐specific carrying capacities, for example by assuming a direct dependency of population size on local river size, was less clear cut: while our best fitting model scenario included this feature, over all simulations, scaling of carrying capacities did not increase data‐model fit. This highlights the importance of dispersal behaviour along spatial networks in shaping population genetic diversity.

Habitat-linked genetic structure for white-crowned sparrow (Zonotrichia leucophrys): Local factors shape population genetic structure

Ecological, environmental, and geographic factors all influence genetic structure. Species with broad distributions are ideal systems because they cover a range of ecological and environmental conditions allowing us to test which components predict genetic structure. This study presents a novel, broad geographic approach using molecular markers, morphology, and habitat modeling to investigate rangewide and local barriers causing contemporary genetic differentiation within the geographical range of three white-crowned sparrow (Zonotrichia leucophrys) subspecies: Z. l. gambelii, Z. l. oriantha, and Z. l. pugetensis. Three types of genetic markers showed geographic distance between sampling sites, elevation, and ecosystem type are key factors contributing to population genetic structure. Microsatellite markers revealed white-crowned sparrows do not group by subspecies, but instead indicated four groupings at a rangewide scale and two groupings based on coniferous and deciduous ecosystems at a local scale. Our analyses of morphological variation also revealed habitat differences; sparrows from deciduous ecosystems are larger than individuals from coniferous ecosystems based on principal component analyses. Habitat modeling showed isolation by distance was prevalent in describing genetic structure, but isolation by resistance also had a small but significant influence. Not only do these findings have implications concerning the accuracy of subspecies delineations, they also highlight the critical role of local factors such as habitat in shaping contemporary population genetic structure of species with high dispersal ability.

MrIML: Multi-response interpretable machine learning to model genomic landscapes

We introduce a new R package "MrIML" ("Mister iml"; Multi-response Interpretable Machine Learning). MrIML provides a powerful and interpretable framework that enables users to harness recent advances in machine learning to quantify multilocus genomic relationships, to identify loci of interest for future landscape genetics studies, and to gain new insights into adaptation across environmental gradients. Relationships between genetic variation and environment are often nonlinear and interactive; these characteristics have been challenging to address using traditional landscape genetic approaches. Our package helps capture this complexity and offers functions that fit and interpret a wide range of highly flexible models that are routinely used for single-locus landscape genetics studies but are rarely extended to estimate response functions for multiple loci. To demonstrate the package's broad functionality, we test its ability to recover landscape relationships from simulated genomic data. We also apply the package to two empirical case studies. In the first, we model genetic variation of North American balsam poplar (Populus balsamifera, Salicaceae) populations across environmental gradients. In the second case study, we recover the landscape and host drivers of feline immunodeficiency virus genetic variation in bobcats (Lynx rufus). The ability to model thousands of loci collectively and compare models from linear regression to extreme gradient boosting, within the same analytical framework, has the potential to be transformative. The MrIML framework is also extendable and not limited to modelling genetic variation; for example, it can quantify the environmental drivers of microbiomes and coinfection dynamics.