Genomic insights into hybrid zone formation: The role of climate, landscape, and demography in the emergence of a novel hybrid lineage.

Population demographic changes, alongside landscape, geographic and climate heterogeneity, can influence the timing, stability and extent of introgression where species hybridise. Thus, quantifying interactions across diverged lineages, and the relative contributions of interspecific genetic exchange and selection to divergence at the genome-wide level is needed to better understand the drivers of hybrid zone formation and maintenance. We used seven latitudinally arrayed transects to quantify the contributions of climate, geography and landscape features to broad patterns of genetic structure across the hybrid zone of Populus trichocarpa and P. balsamifera and evaluated the demographic context of hybridisation over time. We found genetic structure differed among the seven transects. While ancestry was structured by climate, landscape features influenced gene flow dynamics. Demographic models indicated a secondary contact event may have influenced contemporary hybrid zone formation with the origin of a putative hybrid lineage that inhabits regions with higher aridity than either of the ancestral groups. Phylogenetic relationships based on chloroplast genomes support the origin of this hybrid lineage inferred from demographic models based on the nuclear data. Our results point towards the importance of climate and landscape patterns in structuring the contact zones between P. trichocarpa and P. balsamifera and emphasise the value whole genome sequencing can have to advancing our understanding of how neutral processes influence divergence across space and time.

A Platform Approach to Cleavable Macrocycles for the Controlled Disassembly of Mechanically Caged Molecules.

Inspired by interlocked oligonucleotides, peptides and knotted proteins, synthetic systems where a macrocycle cages a bioactive species that is "switched on" by breaking the mechanical bond have been reported. However, to date, each example uses a bespoke chemical design. Here we present a platform approach to mechanically caged structures wherein a single macrocycle precursor is diversified at a late stage to include a range of trigger units that control ring opening in response to enzymatic, chemical, or photochemical stimuli. We also demonstrate that our approach is applicable to other classes of macrocycles suitable for rotaxane and catenane formation.

From common gardens to candidate genes: exploring local adaptation to climate in red spruce.

Local adaptation to climate is common in plant species and has been studied in a range of contexts, from improving crop yields to predicting population maladaptation to future conditions. The genomic era has brought new tools to study this process, which was historically explored through common garden experiments. In this study, we combine genomic methods and common gardens to investigate local adaptation in red spruce and identify environmental gradients and loci involved in climate adaptation. We first use climate transfer functions to estimate the impact of climate change on seedling performance in three common gardens. We then explore the use of multivariate gene-environment association methods to identify genes underlying climate adaptation, with particular attention to the implications of conducting genome scans with and without correction for neutral population structure. This integrative approach uncovered phenotypic evidence of local adaptation to climate and identified a set of putatively adaptive genes, some of which are involved in three main adaptive pathways found in other temperate and boreal coniferous species: drought tolerance, cold hardiness, and phenology. These putatively adaptive genes segregated into two 'modules' associated with different environmental gradients. This study nicely exemplifies the multivariate dimension of adaptation to climate in trees.

Comparative study of a single lead ECG in a wearable device.

BACKGROUND: Technological advances have led to electrocardiograph (ECG) functionality becoming increasingly accessible in wearable health devices, which has the potential to vastly expand the clinician's ability to monitor, diagnose, and manage cardiac health conditions. However, achieving the high signal quality necessary to make an accurate and confident diagnosis is inherently challenging on consumer device-acquired ECGs. Effective signal conditioning is crucial to make ECG data from wearable devices clinically actionable. OBJECTIVE: This study evaluates the heart rate (HR) performance of ECG data collected on the HeartKey® Test Watch, a single lead, dry electrode wrist wearable, against data acquired on two criterion devices: the Bittium® Faros 180, a gold standard wet electrode ambulatory monitoring device, and the HeartKey Chest Module. METHODS: ECG data was simultaneously acquired on three devices during a multi-stage protocol (sitting, walking, standing) designed to reflect the motion noise of real-life scenarios. Raw ECGs from the HeartKey Test Watch and HeartKey Chest Module were processed through HeartKey software, and the accuracy of the outputted heart rate data was compared to that of the criterion device at each stage of the protocol. A beat rejection analysis was performed to provide insight into the degree of high-frequency noise present in ECGs recorded on the HeartKey Test Watch. RESULTS: Data acquired on the HeartKey Test Watch and processed by HeartKey software generated HR metrics that closely matched that of the criterion devices throughout the protocol. Bland-Altman analysis showed a mean absolute HR difference of 0.74, 1.21, 0.80 bpm during the sitting, walking, and standing stages respectively, which is within the ± 10% or ±5 bpm range required by ANSI EC13. ECG data from the HeartKey Test Watch had a higher beat rejection rate relative to the HeartKey Chest Module (8.5% vs ∼0%) due to the excessive high-frequency noise generated during the motion-based protocol. CONCLUSION: HeartKey software demonstrated highly accurate HR performance, comparable to that of the criterion Faros device, when processing challenging ECG data acquired on a single lead, dry electrode wrist wearable during both non-motion and motion-based protocols.

A universal, high-performance ECG signal processing engine to reduce clinical burden.

BACKGROUND: Electrocardiogram (ECG) signal conditioning is a vital step in the ECG signal processing chain that ensures effective noise removal and accurate feature extraction. OBJECTIVE: This study evaluates the performance of the FDA 510 (k) cleared HeartKey Signal Conditioning and QRS peak detection algorithms on a range of annotated public and proprietary ECG databases (HeartKey is a UK Registered Trademark of B-Secur Ltd). METHODS: Seven hundred fifty-one raw ECG files from a broad range of use cases were individually passed through the HeartKey signal processing engine. The algorithms include several advanced filtering steps to enable significant noise removal and accurate identification of the QRS complex. QRS detection statistics were generated against the annotated ECG files. RESULTS: HeartKey displayed robust performance across 14 ECG databases (seven public, seven proprietary), covering a range of healthy and unhealthy patient data, wet and dry electrode types, various lead configurations, hardware sources, and stationary/ambulatory recordings from clinical and non-clinical settings. Over the NSR, MIT-BIH, AHA, and MIT-AF public databases, average QRS Se and PPV values of 98.90% and 99.08% were achieved. Adaptable performance (Se 93.26%, PPV 90.53%) was similarly observed on the challenging NST database. Crucially, HeartKey's performance effectively translated to the dry electrode space, with an average QRS Se of 99.22% and PPV of 99.00% observed over eight dry electrode databases representing various use cases, including two challenging motion-based collection protocols. CONCLUSION: HeartKey demonstrated robust signal conditioning and QRS detection performance across the broad range of tested ECG signals. It should be emphasized that in no way have the algorithms been altered or trained to optimize performance on a given database, meaning that HeartKey is potentially a universal solution capable of maintaining a high level of performance across a broad range of clinical and everyday use cases.

A decade of independent prescribing in the UK: a review of progress.

BACKGROUND: 2022 marks a decade since the profession of podiatry secured independent prescribing rights in the UK. Widely viewed as a significant milestone, its advent appeared to herald a new age of practice, with increased autonomy, a broader scope of practice and improved patient care. Access to any medicine within the British National Formulary (with a few notable exceptions) seemed to signal an end to the perennial difficulties and frequent disappointments in obtaining ease of access to medicines necessary for effective practice. MAIN BODY: Recent attempts to expand the scope of prescribing practice to include access to a broader range of controlled drugs (CDs) have led to unanticipated complications which may even threaten existing rights. These issues highlight the limitations of current independent prescribing and the continuing inability of podiatrists to access certain key medicines, primarily controlled drugs. Reliance on specified 'lists' of approved medicines, whether a controlled drug list for prescribers or the use of statutory exemptions by non-prescriber podiatrists, remain inflexible and difficult to change. The data underpinning much of this paper is derived from the work undertaken by the authors as representatives of podiatry on NHS England's Chief Professions' Officers' Medicines project, in particular involving submissions to the Commission on Human Medicines and the Advisory Council on the Misuse of Medicines, spanning the years 2017-2021. It describes a complex process, and highlights a misalignment between two legislative frameworks that threaten to unravel existing rights. SHORT CONCLUSION: Ongoing difficulties relating to controlled drugs illustrate the problematic nature of current supply, administration and prescribing rights in podiatry. Efforts to keep pace with periodic legal reclassifications of medicines are constrained by limited and inflexible legal mechanisms, and formal approval for extended access via prescribing remains unpredictable and complex. For prescriber and non-prescriber1 (1Non- prescriber podiatrists are those who are neither supplementary or independent prescribers, but do enjoy existing administration and supply rights to certain medicines.) podiatrists alike, the profession of podiatry faces a new challenge to its ability to access medicines, and to realise its full clinical potential.

Seeing the forest for the trees: Assessing genetic offset predictions from gradient forest.

Gradient Forest (GF) is a machine learning algorithm designed to analyze spatial patterns of biodiversity as a function of environmental gradients. An offset measure between the GF-predicted environmental association of adapted alleles and a new environment (GF Offset) is increasingly being used to predict the loss of environmentally adapted alleles under rapid environmental change, but remains mostly untested for this purpose. Here, we explore the robustness of GF Offset to assumption violations, and its relationship to measures of fitness, using SLiM simulations with explicit genome architecture and a spatial metapopulation. We evaluate measures of GF Offset in: (1) a neutral model with no environmental adaptation; (2) a monogenic "population genetic" model with a single environmentally adapted locus; and (3) a polygenic "quantitative genetic" model with two adaptive traits, each adapting to a different environment. We found GF Offset to be broadly correlated with fitness offsets under both single locus and polygenic architectures. However, neutral demography, genomic architecture, and the nature of the adaptive environment can all confound relationships between GF Offset and fitness. GF Offset is a promising tool, but it is important to understand its limitations and underlying assumptions, especially when used in the context of predicting maladaptation.

Genotypic variation and plasticity in climate-adaptive traits after range expansion and fragmentation of red spruce (Picea rubens Sarg.).

Shifting range limits are predicted for many species as the climate warms. However, the rapid pace of climate change will challenge the natural dispersal capacity of long-lived, sessile organisms such as forest trees. Adaptive responses of populations will, therefore, depend on levels of genetic variation and plasticity for climate-responsive traits, which likely vary across the range due to expansion history and current patterns of selection. Here, we study levels of genetic and plastic variation for phenology and growth traits in populations of red spruce (Picea rubens), from the range core to the highly fragmented trailing edge. We measured more than 5000 offspring sampled from three genetically distinct regions (core, margin and edge) grown in three common gardens replicated along a latitudinal gradient. Genetic variation in phenology and growth showed low to moderate heritability and differentiation among regions, suggesting some potential to respond to selection. Phenology traits were highly plastic, but this plasticity was generally neutral or maladaptive in the effect on growth, revealing a potential liability under warmer climates. These results suggest future climate adaptation will depend on the regional availability of genetic variation in red spruce and provide a resource for the design and management of assisted gene flow. This article is part of the theme issue 'Species' ranges in the face of changing environments (Part II)'.

Simulation Tests of Methods in Evolution, Ecology, and Systematics: Pitfalls, Progress, and Principles.

Complex statistical methods are continuously developed across the fields of ecology, evolution, and systematics (EES). These fields, however, lack standardized principles for evaluating methods, which has led to high variability in the rigor with which methods are tested, a lack of clarity regarding their limitations, and the potential for misapplication. In this review, we illustrate the common pitfalls of method evaluations in EES, the advantages of testing methods with simulated data, and best practices for method evaluations. We highlight the difference between method evaluation and validation and review how simulations, when appropriately designed, can refine the domain in which a method can be reliably applied. We also discuss the strengths and limitations of different evaluation metrics. The potential for misapplication of methods would be greatly reduced if funding agencies, reviewers, and journals required principled method evaluation.

Relationships between climate and phylogenetic community structure of fossil pollen assemblages are not constant during the last deglaciation.

Disentangling the influence of environmental drivers on community assembly is important to understand how multiple processes influence biodiversity patterns and can inform understanding of ecological responses to climate change. Phylogenetic Community Structure (PCS) is increasingly used in community assembly studies to incorporate evolutionary perspectives and as a proxy for trait (dis)similarity within communities. Studies often assume a stationary relationship between PCS and climate, though few studies have tested this assumption over long time periods with concurrent community data. We estimated two PCS metrics-Nearest Taxon Index (NTI) and Net Relatedness index (NRI)-of fossil pollen assemblages of Angiosperms in eastern North America over the last 21 ka BP at 1 ka intervals. We analyzed spatiotemporal relationships between PCS and seven climate variables, evaluated the potential impact of deglaciation on PCS, and tested for the stability of climate-PCS relationships through time. The broad scale geographic patterns of PCS remained largely stable across time, with overdispersion tending to be most prominent in the central and southern portion of the study area and clustering dominating at the longitudinal extremes. Most importantly, we found that significant relationships between climate variables and PCS (slope) were not constant as climate changed during the last deglaciation and new ice-free regions were colonized. We also found weak, but significant relationships between both PCS metrics (i.e., NTI and NRI) and climate and time-since-deglaciation that also varied through time. Overall, our results suggest that (1) PCS of fossil Angiosperm assemblages during the last 21ka BP have had largely constant spatial patterns, but (2) temporal variability in the relationships between PCS and climate brings into question their usefulness in predictive modeling of community assembly.

Experimental support for genomic prediction of climate maladaptation using the machine learning approach Gradient Forests.

Gradient Forests (GF) is a machine learning algorithm that is gaining in popularity for studying the environmental drivers of genomic variation and for incorporating genomic information into climate change impact assessments. Here we (i) provide the first experimental evaluation of the ability of "genomic offsets" - a metric of climate maladaptation derived from Gradient Forests - to predict organismal responses to environmental change, and (ii) explore the use of GF for identifying candidate SNPs. We used high-throughput sequencing, genome scans, and several methods, including GF, to identify candidate loci associated with climate adaptation in balsam poplar (Populus balsamifera L.). Individuals collected throughout balsam poplar's range also were planted in two common garden experiments. We used GF to relate candidate loci to environmental gradients and predict the expected magnitude of the response (i.e., the genetic offset metric of maladaptation) of populations when transplanted from their "home" environment to the common gardens. We then compared the predicted genetic offsets from different sets of candidate and randomly selected SNPs to measurements of population performance in the common gardens. We found the expected inverse relationship between genetic offset and performance: populations with larger predicted genetic offsets performed worse in the common gardens than populations with smaller offsets. Also, genetic offset better predicted performance than did "naive" climate transfer distances. However, sets of randomly selected SNPs predicted performance slightly better than did candidate SNPs. Our study provides evidence that genetic offsets represent a first order estimate of the degree of expected maladaptation of populations exposed to rapid environmental change and suggests GF may have some promise as a method for identifying candidate SNPs.

Chiral, sequence-definable foldamer-derived macrocycles.

Nature's oligomeric macromolecules have been a long-standing source of inspiration for chemists producing foldamers. Natural systems are frequently conformationally stabilised by macrocyclisation, yet this approach has been rarely adopted in the field of foldamer chemistry. Here we present a new class of chiral cyclic trimers and tetramers formed by macrocyclisation of open-chain foldamer precursors. Symmetrical products are obtained via a [2 + 2] self-assembly approach, while full sequence control is demonstrated through linear synthesis and cyclisation of an unsymmetrical trimer. Structural characterisation is achieved through a combined X-ray and DFT approach, which indicates the tetramers adopt a near-planar conformation, while the trimers adopt a shallow bowl-like shape. Finally, a proof-of-concept experiment is conducted to demonstrate the macrocycles' capacity for cation binding.

Whole-exome sequencing reveals a long-term decline in effective population size of red spruce (Picea rubens).

Understanding the factors influencing the current distribution of genetic diversity across a species range is one of the main questions of evolutionary biology, especially given the increasing threat to biodiversity posed by climate change. Historical demographic processes such as population expansion or bottlenecks and decline are known to exert a predominant influence on past and current levels of genetic diversity, and revealing this demo-genetic history can have immediate conservation implications. We used a whole-exome capture sequencing approach to analyze polymorphism across the gene space of red spruce (Picea rubens Sarg.), an endemic and emblematic tree species of eastern North America high-elevation forests that are facing the combined threat of global warming and increasing human activities. We sampled a total of 340 individuals, including populations from the current core of the range in northeastern USA and southeastern Canada and from the southern portions of its range along the Appalachian Mountains, where populations occur as highly fragmented mountaintop "sky islands." Exome capture baits were designed from the closely relative white spruce (P. glauca Voss) transcriptome, and sequencing successfully captured most regions on or near our target genes, resulting in the generation of a new and expansive genomic resource for studying standing genetic variation in red spruce applicable to its conservation. Our results, based on over 2 million exome-derived variants, indicate that red spruce is structured into three distinct ancestry groups that occupy different geographic regions of its highly fragmented range. Moreover, these groups show small Ne , with a temporal history of sustained population decline that has been ongoing for thousands (or even hundreds of thousands) of years. These results demonstrate the broad potential of genomic studies for revealing details of the demographic history that can inform management and conservation efforts of nonmodel species with active restoration programs, such as red spruce.

Distinct fungal successional trajectories following wildfire between soil horizons in a cold-temperate forest.

Soil fungi represent a major component of below-ground biodiversity that determines the succession and recovery of forests after disturbance. However, their successional trajectories and driving mechanisms following wildfire remain unclear. We examined fungal biomass, richness, composition and enzymes across three soil horizons (Oe, A1 and A2) along a near-complete fire chronosequence (1, 2, 8, 14, 30, 49 and c. 260 yr) in cold-temperate forests of the Great Khingan Mountains, China. The importance of soil properties, spatial distance and tree composition were also tested. Ectomycorrhizal fungal richness and ß-glucosidase activity were strongly reduced by burning and significantly increased with 'time since fire' in the Oe horizon but not in the mineral horizons. Time since fire and soil C : N ratio were the primary drivers of fungal composition in the Oe and A1/A2 horizons, respectively. Ectomycorrhizal fungal composition was remarkably sensitive to fire history in the Oe horizon, while saprotroph community was strongly affected by time since fire in the deeper soil horizon and this effect emerged 18 years after fire in the A2 horizon. Our study demonstrates pronounced horizon-dependent successional trajectories following wildfire and indicates interactive effects of time since fire, soil stoichiometry and spatial distance in the reassembly of below-ground fungal communities in a cold and fire-prone region.

Bacteriophage-mediated identification of bacteria using photoacoustic flow cytometry.

Infection with resistant bacteria has become an ever increasing problem in modern medical practice. Currently, broad spectrum antibiotics are prescribed until bacteria can be identified through blood cultures, a process that can take two to three days and is unable to provide quantitative information. To detect and quantify bacteria rapidly in blood samples, we designed a method using labeled bacteriophage in conjunction with photoacoustic flow cytometry (PAFC). PAFC is the generation of ultrasonic waves created by the absorption of laser light in particles under flow. Bacteriophage is a virus that infects bacteria and possesses the ability to discriminate bacterial surface antigens, allowing the bacteriophage to bind only to their target bacteria. Bacteria can be tagged with dyed phage and processed through a photoacoustic flow cytometer where they are detected by the acoustic response. We demonstrate that E. coli; can be detected and discriminated from Salmonella; using this method. Our goal is to develop a method to determine bacterial content in blood samples. We hope to develop this technology into future clinical use and decrease the time required to identify bacterial species from 3 to 4 days to less than 1 hour.

Contemporary climatic analogs for 540 North American urban areas in the late 21st century.

A major challenge in articulating human dimensions of climate change lies in translating global climate forecasts into impact assessments that are intuitive to the public. Climate-analog mapping involves matching the expected future climate at a location (e.g., a person's city of residence) with current climate of another, potentially familiar, location - thereby providing a more relatable, place-based assessment of climate change. For 540 North American urban areas, we used climate-analog mapping to identify the location that has a contemporary climate most similar to each urban area's expected 2080's climate. We show that climate of most urban areas will shift considerably and become either more akin to contemporary climates hundreds of kilometers away and mainly to the south or will have no modern equivalent. Combined with an interactive web application, we provide an intuitive means of raising public awareness of the implications of climate change for 250 million urban residents.

The Past, Present, and Future of the Hemlock Woolly Adelgid (Adelges tsugae) and Its Ecological Interactions with Eastern Hemlock (Tsuga canadensis) Forests.

The nonnative hemlock woolly adelgid is steadily killing eastern hemlock trees in many parts of eastern North America. We summarize impacts of the adelgid on these forest foundation species; review previous models and analyses of adelgid spread dynamics; and examine how previous forecasts of adelgid spread and ecosystem dynamics compare with current conditions. The adelgid has reset successional sequences, homogenized biological diversity at landscape scales, altered hydrological dynamics, and changed forest stands from carbon sinks into carbon sources. A new model better predicts spread of the adelgid in the south and west of the range of hemlock, but still under-predicts its spread in the north and east. Whether these underpredictions result from inadequately modeling accelerating climate change or accounting for people inadvertently moving the adelgid into new locales needs further study. Ecosystem models of adelgid-driven hemlock dynamics have consistently forecast that forest carbon stocks will be little affected by the shift from hemlock to early-successional mixed hardwood stands, but these forecasts have assumed that the intermediate stages will remain carbon sinks. New forecasting models of adelgid-driven hemlock decline should account for observed abrupt changes in carbon flux and ongoing and accelerating human-driven land-use and climatic changes.

Dominance-diversity relationships in ant communities differ with invasion.

The relationship between levels of dominance and species richness is highly contentious, especially in ant communities. The dominance-impoverishment rule states that high levels of dominance only occur in species-poor communities, but there appear to be many cases of high levels of dominance in highly diverse communities. The extent to which dominant species limit local richness through competitive exclusion remains unclear, but such exclusion appears more apparent for non-native rather than native dominant species. Here we perform the first global analysis of the relationship between behavioral dominance and species richness. We used data from 1,293 local assemblages of ground-dwelling ants distributed across five continents to document the generality of the dominance-impoverishment rule, and to identify the biotic and abiotic conditions under which it does and does not apply. We found that the behavioral dominance-diversity relationship varies greatly, and depends on whether dominant species are native or non-native, whether dominance is considered as occurrence or relative abundance, and on variation in mean annual temperature. There were declines in diversity with increasing dominance in invaded communities, but diversity increased with increasing dominance in native communities. These patterns occur along the global temperature gradient. However, positive and negative relationships are strongest in the hottest sites. We also found that climate regulates the degree of behavioral dominance, but differently from how it shapes species richness. Our findings imply that, despite strong competitive interactions among ants, competitive exclusion is not a major driver of local richness in native ant communities. Although the dominance-impoverishment rule applies to invaded communities, we propose an alternative dominance-diversification rule for native communities.

How will climate novelty influence ecological forecasts? Using the Quaternary to assess future reliability.

Future climates are projected to be highly novel relative to recent climates. Climate novelty challenges models that correlate ecological patterns to climate variables and then use these relationships to forecast ecological responses to future climate change. Here, we quantify the magnitude and ecological significance of future climate novelty by comparing it to novel climates over the past 21,000 years in North America. We then use relationships between model performance and climate novelty derived from the fossil pollen record from eastern North America to estimate the expected decrease in predictive skill of ecological forecasting models as future climate novelty increases. We show that, in the high emissions scenario (RCP 8.5) and by late 21st century, future climate novelty is similar to or higher than peak levels of climate novelty over the last 21,000 years. The accuracy of ecological forecasting models is projected to decline steadily over the coming decades in response to increasing climate novelty, although models that incorporate co-occurrences among species may retain somewhat higher predictive skill. In addition to quantifying future climate novelty in the context of late Quaternary climate change, this work underscores the challenges of making reliable forecasts to an increasingly novel future, while highlighting the need to assess potential avenues for improvement, such as increased reliance on geological analogs for future novel climates and improving existing models by pooling data through time and incorporating assemblage-level information.

Influence of Range Position on Locally Adaptive Gene-Environment Associations in Populus Flowering Time Genes.

Local adaptation is pervasive in forest trees, which are characterized by large effective population sizes spanning broad climatic gradients. In addition to having relatively contiguous populations, many species also form isolated populations along the rear edge of their range. These rear-edge populations may contain unique adaptive diversity reflecting a history of selection in marginal environments. Thus, discovering genomic regions conferring local adaptation in rear edge populations is a key priority for landscape genomics to ensure conservation of genetic resources under climate change. Here, we report on adaptive gene-environment associations in single nucleotide polymorphisms (SNPs) from 27 genes in the Populus flowering time gene network, analyzed on a range-wide collection of >1000 balsam poplar trees, including dense sampling of the southern range edge. We use a combined approach of local adaptation scans to identify candidate SNPs, followed by modeling the compositional turnover of adaptive SNPs along multivariate climate gradients using gradient forests (GF). Flowering time candidate genes contained extensive evidence of climate adaptation, namely outlier population structure and gene-environment associations, along with allele frequency divergence between the core and edge of the range. GF showed strong allele frequency turnover along gradients of elevation and diurnal and temperature variability, as well as threshold responses to summer temperature and precipitation, with turnover especially strong in edge populations that occur at high elevation but southerly latitudes. We discuss these results in light of how climate may disrupt locally adaptive gene-environment relationships, and suggest that rear edge populations hold climate-adaptive variants that should be targeted for conservation.