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  1. Abstract

    Whole‐genome sequencing data allow survey of variation from across the genome, reducing the constraint of balancing genome sub‐sampling with estimating recombination rates and linkage between sampled markers and target loci. As sequencing costs decrease, low‐coverage whole‐genome sequencing of pooled or indexed‐individual samples is commonly utilized to identify loci associated with phenotypes or environmental axes in non‐model organisms. There are, however, relatively few publicly available bioinformatic pipelines designed explicitly to analyse these types of data, and fewer still that process the raw sequencing data, provide useful metrics of quality control and then execute analyses. Here, we present an updated version of a bioinformatics pipeline calledPoolParty2that can effectively handle either pooled or indexed DNA samples and includes new features to improve computational efficiency. Using simulated data, we demonstrate the ability of our pipeline to recover segregating variants, estimate their allele frequencies accurately, and identify genomic regions harbouring loci under selection. Based on the simulated data set, we benchmark the efficacy of our pipeline with another bioinformatic suite,angsd, and illustrate the compatibility and complementarity of these suites usingangsdto generate genotype likelihoods as input for identifying linkage outlier regions using alignment files and variants provided byPoolParty2. Finally, we apply our updated pipeline to an empirical dataset of low‐coverage whole genomic data from population samples of Columbia River steelhead trout (Oncorhynchus mykiss), results from which demonstrate the genomic impacts of decades of artificial selection in a prominent hatchery stock. Thus, we not only demonstrate the utility ofPoolParty2for genomic studies that combine sequencing data from multiple individuals, but also illustrate how it compliments other bioinformatics resources such asangsd.

     
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    Free, publicly-accessible full text available November 3, 2024
  2. Abstract

    Despite growing interest in conservation and re‐establishment of ecological connectivity, few studies have explored its context‐specific social–ecological outcomes. We aimed to explore social and ecological outcomes to changing stream connectivity for both stakeholders and native fish species impacted by habitat fragmentation and nonnative species. We (1) investigated stakeholder perceptions of the drivers and outcomes of stream connectivity, and (2) evaluated the effects of stakeholder‐identified connectivity and nonnative species scenarios on Yellowstone cutthroat trout (YCT) populations. Our study was conducted in the Teton River, Idaho, USA. We integrated two modeling approaches, mental modeling and individual‐based ecological modeling, to explore social–ecological outcomes for stakeholders and YCT populations. Aggregation of mental models revealed an emergent pattern of increasing complexity as more types of stakeholders were considered, as well as gaps and linkages among different stakeholder knowledge areas. These results highlight the importance of knowledge sharing among stakeholders when making decisions about connectivity. Additionally, the results from the individual‐based models suggested that the potential for a large, migratory life history form of YCT, in addition to self‐preference mating where they overlap with rainbow trout, had the strongest effects on outcomes for YCT. Exploring social and ecological drivers and outcomes to changing connectivity is useful for anticipating and adapting to unintended outcomes, as well as making decisions for desirable outcomes. The results from this study can contribute to the management dialogue surrounding stream connectivity in the Teton River, as well as to our understanding of connectivity conservation and its outcomes more broadly.

     
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  3. Abstract

    Western North America has been experiencing persistent drought exacerbated by climate change for over two decades. This extreme climate event is a clear threat to native plant communities.Artemisia tridentatais a keystone shrub species in western North America and is threatened by climate change, urbanization, and wildfire. A drought Genotype × Environment (G × E) experiment was conducted to assess phenotypic plasticity and differential gene expression inA. tridentata. The G × E experiment was performed on diploidA. tridentataseedlings from two populations (one from Idaho, USA and one from Utah, USA), which experience differing levels of drought stress during the summer months. Photosynthetic data, leaf temperature, and gene expression levels were compared between treatments and populations. The Utah population maintained higher photosynthetic rates and photosynthetic efficiency than the Idaho population under drought stress. The Utah population also exhibited far greater transcriptional plasticity than the Idaho population and expressed genes of response pathways distinct from those of the Idaho population. Populations ofA. tridentatadiffer greatly in their drought response pathways, likely due to differences in response pathways that have evolved under distinct climatic regimes. Epigenetic processes likely contribute to the observed differences between the populations.

     
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    Free, publicly-accessible full text available August 1, 2024
  4. Abstract

    Conserving species' ability to traverse the landscape is vital for maintaining biodiversity in the face of global change. Connectivity conservation requires identifying important pathways for species' movements and aligning societal support for conservation of those pathways. Contemporary connectivity analyses emphasize the impacts of topography, vegetation and human footprint on species' movements; but largely ignore the role that attitudes, economics and institutions play in practitioners' ability to conserve those movements.

    We introduce implementation resistance as an analogue of biophysical resistance that combines social, economic and institutional factors that promote or impede connectivity conservation. We demonstrate the utility of integrating implementation resistance as a means of choosing between competing connectivity conservation strategies using wolves in Colorado (USA) as a case study.

    Our analysis of five potential corridor locations based on biophysical costs revealed substantial differences in the social costs associated with implementing each corridor despite relatively minimal differences in the biophysical costs.

    Our comparison of hypothetical interventions to reduce implementation resistance illustrates that interventions that reduce conflicts between land use and wolves may substantially reduce overall resistance, those reductions are not as well aligned with connectivity priorities as those resulting from changes in land management agency policy.

    Our results highlight the need to design conservation interventions that fit both the social and ecological landscape and provide a framework for developing robust, interdisciplinary methods that facilitate implementable connectivity conservation.

    Read the freePlain Language Summaryfor this article on the Journal blog.

     
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  5. Abstract

    Adaptive capacity can present challenges for modelling as it encompasses multiple ecological and evolutionary processes such as natural selection, genetic drift, gene flow and phenotypic plasticity. Spatially explicit, individual‐based models provide an outlet for simulating these complex interacting eco‐evolutionary processes. We expanded the existing Cost‐Distance Meta‐POPulation (CDMetaPOP) framework with inducible plasticity modelled as a habitat selection behaviour, using temperature or habitat quality variables, with a genetically based selection threshold conditioned on past individual experience. To demonstrate expected results in the new module, we simulated hypothetical populations and then evaluated model performance in populations of redband trout (Oncorhynchus mykiss gairdneri) across three watersheds where temperatures induce physiological stress in parts of the stream network. We ran simulations using projected warming stream temperature data under four scenarios for alleles that: (1) confer thermal tolerance, (2) bestow plastic habitat selection, (3) give both thermal tolerance and habitat selection preference and (4) do not provide either thermal tolerance or habitat selection. Inclusion of an adaptive allele decreased declines in population sizes, but this impact was greatly reduced in the relatively cool stream networks. As anticipated with the new module, high‐temperature patches remained unoccupied by individuals with the allele operating plastically after exposure to warm temperatures. Using complete habitat avoidance above the stressful temperature threshold, habitat selection reduced the overall population size due to the opportunity cost of avoiding areas with increased, but not guaranteed, mortality. Inclusion of plasticity within CDMetaPOP will provide the potential for genetic or plastic traits and ‘rescue’ to affect eco‐evolutionary dynamics for research questions and conservation applications.

     
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  6. Abstract

    Understanding interactions between environmental stress and genetic variation is crucial to predict the adaptive capacity of species to climate change. Leaf temperature is both a driver and a responsive indicator of plant physiological response to thermal stress, and methods to monitor it are needed. Foliar temperatures vary across leaf to canopy scales and are influenced by genetic factors, challenging efforts to map and model this critical variable. Thermal imagery collected using unoccupied aerial systems (UAS) offers an innovative way to measure thermal variation in plants across landscapes at leaf‐level resolutions. We used a UAS equipped with a thermal camera to assess temperature variation among genetically distinct populations of big sagebrush (Artemisia tridentata), a keystone plant species that is the focus of intensive restoration efforts throughout much of western North America. We completed flights across a growing season in a sagebrush common garden to map leaf temperature relative to subspecies and cytotype, physiological phenotypes of plants, and summer heat stress. Our objectives were to (1) determine whether leaf‐level stomatal conductance corresponds with changes in crown temperature; (2) quantify genetic (i.e., subspecies and cytotype) contributions to variation in leaf and crown temperatures; and (3) identify how crown structure, solar radiation, and subspecies‐cytotype relate to leaf‐level temperature. When considered across the whole season, stomatal conductance was negatively, non‐linearly correlated with crown‐level temperature derived from UAS. Subspecies identity best explained crown‐level temperature with no difference observed between cytotypes. However, structural phenotypes and microclimate best explained leaf‐level temperature. These results show how fine‐scale thermal mapping can decouple the contribution of genetic, phenotypic, and microclimate factors on leaf temperature dynamics. As climate‐change‐induced heat stress becomes prevalent, thermal UAS represents a promising way to track plant phenotypes that emerge from gene‐by‐environment interactions.

     
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  7. Abstract

    The structure and composition of plant communities in drylands are highly variable across scales, from microsites to landscapes. Fine spatial resolution field surveys of dryland plants are essential to unravel the impact of climate change; however, traditional field data collection is challenging considering sampling efforts and costs. Unoccupied aerial systems (UAS) can alleviate this challenge by providing standardized measurements of plant community attributes with high resolution. However, given widespread heterogeneity in plant communities in drylands, and especially across environmental gradients, the transferability of UAS imagery protocols is unclear. Plant functional types (PFTs) are a classification scheme that aggregates the diversity of plant structure and function. We mapped and modeled PFTs and fractional photosynthetic cover using the same UAS imagery protocol across three dryland communities, differentiated by a landscape‐scale gradient of elevation and precipitation. We compared the accuracy of the UAS products between the three dryland sites. PFT classifications and modeled photosynthetic cover had highest accuracies at higher elevations (2241 m) with denser vegetation. The lowest site (1101 m), with more bare ground, had the least agreement with the field data. Notably, shrub cover was well predicted across the gradient of elevation and precipitation (~230–1100 mm/year). UAS surveys captured the heterogeneity of plant cover across sites and presented options to measure leaf‐level composition and structure at landscape levels. Our results demonstrate that some PFTs (i.e., shrubs) can readily be detected across sites using the same UAS imagery protocols, while others (i.e., grasses) may require site‐specific flight protocols for best accuracy. As UAS are increasingly used to monitor dryland vegetation, developing protocols that maximize information and efficiency is a research and management priority.

     
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  8. Abstract

    Accurate predictions of ecological restoration outcomes are needed across the increasingly large landscapes requiring treatment following disturbances. However, observational studies often fail to account for nonrandom treatment application, which can result in invalid inference. Examining a spatiotemporally extensive management treatment involving post-fire seeding of declining sagebrush shrubs across semiarid areas of the western USA over two decades, we quantify drivers and consequences of selection biases in restoration using remotely sensed data. From following more than 1,500 wildfires, we find treatments were disproportionately applied in more stressful, degraded ecological conditions. Failure to incorporate unmeasured drivers of treatment allocation led to the conclusion that costly, widespread seedings were unsuccessful; however, after considering sources of bias, restoration positively affected sagebrush recovery. Treatment effects varied with climate, indicating prioritization criteria for interventions. Our findings revise the perspective that post-fire sagebrush seedings have been broadly unsuccessful and demonstrate how selection biases can pose substantive inferential hazards in observational studies of restoration efficacy and the development of restoration theory.

     
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  9. Abstract

    Snake River Sockeye SalmonOncorhynchus nerka, listed as an endangered species in 1991, currently inhabit three nursery lakes (Redfish, Pettit, and Alturas lakes) in the Sawtooth Valley, Idaho. Conspecific kokanee (lacustrine Sockeye Salmon) are also present in the lakes. Snake River Sockeye Salmon recovery efforts, initially focused on genetic conservation, are now attempting to rebuild naturally spawning populations using hatchery supplementation. However, in Sockeye Salmon nursery lakes, density dependence is frequently observed when elevatedO. nerkaabundance leads to declines in zooplankton biomass, body size, and shifts in community composition. In turn, these changes lead to reductions in juvenileO. nerkagrowth rates, survival, and adult returns. We examined a long‐term data set ofO. nerkapopulation metrics and associated zooplankton community metrics. We found evidence of density dependence within and among nursery lakes. We detected differences in zooplankton biomass, lengths of preferred zooplankton prey (Daphniaspp. and cyclopoid copepods), parr growth rates, and age‐1 smolt size among the three lakes. We found negative relationships betweenO. nerkadensity and zooplankton biomass and size. We identified positive relationships between zooplankton biomass and two response variables: smolt size at migration and growth rates of hatchery parr. The relationships were generally similar among lakes. Variable outcomes were a result of differences inO. nerkadensity (or zooplankton biomass), controlled primarily by the relative proportion of spawning and rearing habitat in each lake. Understanding unique lake habitats, ecological interactions, and the role of density dependence is germane to management of Snake River Sockeye Salmon populations.

     
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  10. Abstract

    Open science and open data within scholarly research programs are growing both in popularity and by requirement from grant funding agencies and journal publishers. A central component of open data management, especially on collaborative, multidisciplinary, and multi-institutional science projects, is documentation of complete and accurate metadata, workflow, and source code in addition to access to raw data and data products to uphold FAIR (Findable, Accessible, Interoperable, Reusable) principles. Although best practice in data/metadata management is to use established internationally accepted metadata schemata, many of these standards are discipline-specific making it difficult to catalog multidisciplinary data and data products in a way that is easily findable and accessible. Consequently, scattered and incompatible metadata records create a barrier to scientific innovation, as researchers are burdened to find and link multidisciplinary datasets. One possible solution to increase data findability, accessibility, interoperability, reproducibility, and integrity within multi-institutional and interdisciplinary projects is a centralized and integrated data management platform. Overall, this type of interoperable framework supports reproducible open science and its dissemination to various stakeholders and the public in a FAIR manner by providing direct access to raw data and linking protocols, metadata and supporting workflow materials.

     
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