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At least 73 records · Page 4Linked to original sources
USGS2022

Evolutionary dynamics inform management interventions of a hanging garden obligate, Carex specuicola

Uncovering the historical and contemporary processes shaping rare species with complex distributions is of growing importance due to threats such as habitat destruction and climate change. Species restricted to specialized, patchy habitat may persist by virtue of life history characteristics facilitating ongoing gene flow and dispersal, but they could also reflect the remnants of formerly widespread, suitable habitat that existed during past climate regimes. If formerly widespread species did not rely upon traits facilitating high dispersibility to persist, contemporary populations could be at high risk of extirpation or extinction. Fortunately, genomic investigations provide an opportunity to illuminate such alternative scenarios while simultaneously offering guidance for future management interventions. Herein, we test the role of these mechanisms in shaping patterns of genomic diversity and differentiation across a highly restricted and rare ecosystem: desert hanging gardens. We focus on Carex specuicola (Cyperaceae), a hanging garden obligate narrowly distributed in the Four Corners region of the southwestern United States that is listed as Threatened under the United States Endangered Species Act. Population structure and diversity analyses reveal that hanging garden populations are shaped by strong genetic drift, but that individuals in gardens are occasionally more closely related to individuals at other gardens than to individuals within the same garden. Similarly, gardens separated by long geographic distances may contain individuals that are more closely related compared to individuals in gardens separated by short geographic distances. Demographic modeling supports historical gene flow between some contemporary garden pairs, which is corroborated by low estimates of inbreeding coefficients and recent divergence times. As such, multiple lines of evidence support dispersal and gene flow across C. specuicola populations at both small and large spatial scales, indicating that even if C. specuicola was formerly more widespread, it may be well suited to persist in hanging gardens so long as suitable habitat remains available. Analyses like those demonstrated herein may be broadly applicable for understanding the short- and long-term evolutionary processes influencing rare species, and especially those having complex distributions across heterogeneous landscapes.

Arizona, Utah↗
USGS2010

New trends in species distribution modelling

Species distribution modelling has its origin in the late 1970s when computing capacity was limited. Early work in the field concentrated mostly on the development of methods to model effectively the shape of a species' response to environmental gradients (Austin 1987, Austin et al. 1990). The methodology and its framework were summarized in reviews 10–15 yr ago (Franklin 1995, Guisan and Zimmermann 2000), and these syntheses are still widely used as reference landmarks in the current distribution modelling literature. However, enormous advancements have occurred over the last decade, with hundreds – if not thousands – of publications on species distribution model (SDM) methodologies and their application to a broad set of conservation, ecological and evolutionary questions. With this special issue, originating from the third of a set of specialized SDM workshops (2008 Riederalp) entitled 'The Utility of Species Distribution Models as Tools for Conservation Ecology', we reflect on current trends and the progress achieved over the last decade.

Ecography↗
USGS2016

A field ornithologist’s guide to genomics: Practical considerations for ecology and conservation

Vast improvements in sequencing technology have made it practical to simultaneously sequence millions of nucleotides distributed across the genome, opening the door for genomic studies in virtually any species. Ornithological research stands to benefit in three substantial ways. First, genomic methods enhance our ability to parse and simultaneously analyze both neutral and non-neutral genomic regions, thus providing insight into adaptive evolution and divergence. Second, the sheer quantity of sequence data generated by current sequencing platforms allows increased precision and resolution in analyses. Third, high-throughput sequencing can benefit applications that focus on a small number of loci that are otherwise prohibitively expensive, time-consuming, and technically difficult using traditional sequencing methods. These advances have improved our ability to understand evolutionary processes like speciation and local adaptation, but they also offer many practical applications in the fields of population ecology, migration tracking, conservation planning, diet analyses, and disease ecology. This review provides a guide for field ornithologists interested in incorporating genomic approaches into their research program, with an emphasis on techniques related to ecology and conservation. We present a general overview of contemporary genomic approaches and methods, as well as important considerations when selecting a genomic technique. We also discuss research questions that are likely to benefit from utilizing high-throughput sequencing instruments, highlighting select examples from recent avian studies.

The Auk↗
USGS2024

Molecular sexing of birds using quantitative PCR (qPCR) of sex-linked genes and logistic regression models

The ability to sex individuals is an important component of many behavioural and ecological investigations and provides information for demographic models used in conservation and species management. However, many birds are difficult to sex using morphological characters or traditional molecular sexing methods. In this study, we developed probabilistic models for sexing birds using quantitative PCR (qPCR) data. First, we quantified distributions of gene copy numbers at a set of six sex-linked genes, including the sex-determining gene DMRT1 , for individuals across 17 species and seven orders of birds ( n = 150). Using these data, we built predictive logistic models for sex identification and tested their performance with independent samples from 51 species and 13 orders ( n = 209). Models using the two loci most highly correlated with sex had greater accuracy than models using the full set of sex-linked loci, across all taxonomic levels of analysis. Sex identification was highly accurate when individuals to be assigned were of species used in model building. Our analytical approach was widely applicable across diverse neognath bird lineages spanning millions of years of evolutionary divergence. Unlike previous methods, our probabilistic framework incorporates uncertainty around qPCR measurements as well as biological variation within species into decision-making rules. We anticipate that this method will be useful for sexing birds, including those of high conservation concern and/or subsistence value, that have proven difficult to sex using traditional approaches. Additionally, the general analytical framework presented in this paper may also be applicable to other organisms with sex chromosomes.

Molecular Ecology Resources↗
USGS1981

Cenozoic coccoliths from the Deep Sea Drilling Project

Coccoliths, as the dominant constituent of many Deep Sea Drilling Project cores, have provided the means of rapid and detailed biostratigraphic zonation to help guide ocean-sediment coring operations aboard D.V. Glomar Challenger. The Cenozoic has been divided into 50 to 60 zones and subzones which are most effective for middle- and low- latitude sites. Because key stratigraphic coccoliths have proved more resistant to diagenetic change than planktic foraminifers, they contributed to dating of sedimentary beds within and just above basalt, directly demonstrating the correctness of the sea-floor spreading hypothesis. An unexpected discovery of Braarudosphaera beds in the South Atlantic produced valuable speculation on the response of coccolithophorids to paleoceanographic changes. Samples from the diversity of oceanic terrains explored by early cruises of Glomar Challenger helped in the recognition of the effects of differential preservation —etching and overgrowth from species to species —and in the determination of biogeographic ranges which would affect the taxonomic, paleoecologic and biostratigraphic assignments of coccoliths. DSDP sites have provided the matrix needed to outline depth sequences based on dissolution rank, and paleotemperature sequences based on abundance along latitudinal traverses. New Hydraulic Piston Corer capabilities will make possible application of magnetic reversal stratigraphy to undisturbed cores where coccolith evolutionary transitions and datum-interval stratigraphy can be established.

Book chapter↗
USGS2010

Occam's shadow: levels of analysis in evolutionary ecology - where to next?

Evolutionary ecology is the study of evolutionary processes, and the ecological conditions that influence them. A fundamental paradigm underlying the study of evolution is natural selection. Although there are a variety of operational definitions for natural selection in the literature, perhaps the most general one is that which characterizes selection as the process whereby heritable variation in fitness associated with variation in one or more phenotypic traits leads to intergenerational change in the frequency distribution of those traits. The past 20 years have witnessed a marked increase in the precision and reliability of our ability to estimate one or more components of fitness and characterize natural selection in wild populations, owing particularly to significant advances in methods for analysis of data from marked individuals. In this paper, we focus on several issues that we believe are important considerations for the application and development of these methods in the context of addressing questions in evolutionary ecology. First, our traditional approach to estimation often rests upon analysis of aggregates of individuals, which in the wild may reflect increasingly non-random (selected) samples with respect to the trait(s) of interest. In some cases, analysis at the aggregate level, rather than the individual level, may obscure important patterns. While there are a growing number of analytical tools available to estimate parameters at the individual level, and which can cope (to varying degrees) with progressive selection of the sample, the advent of new methods does not reduce the need to consider carefully the appropriate level of analysis in the first place. Estimation should be motivated a priori by strong theoretical analysis. Doing so provides clear guidance, in terms of both (i) assisting in the identification of realistic and meaningful models to include in the candidate model set, and (ii) providing the appropriate context under which the results are interpreted. Second, while it is true that selection (as defined) operates at the level of the individual, the selection gradient is often (if not generally) conditional on the abundance of the population. As such, it may be important to consider estimating transition rates conditional on both the parameter values of the other individuals in the population (or at least their distribution), and population abundance. This will undoubtedly pose a considerable challenge, for both single- and multi-strata applications. It will also require renewed consideration of the estimation of abundance, especially for open populations. Thirdly, selection typically operates on dynamic, individually varying traits. Such estimation may require characterizing fitness in terms of individual plasticity in one or more state variables, constituting analysis of the norms of reaction of individuals to variable environments. This can be quite complex, especially for traits that are under facultative control. Recent work has indicated that the pattern of selection on such traits is conditional on the relative rates of movement among and frequency of spatially heterogeneous habitats, suggesting analyses of evolution of life histories in open populations can be misleading in some cases.

Journal of Applied Statistics↗
USGS2023

Improving ecological data science with workflow management software

Pressing environmental research questions demand the integration of increasingly diverse and large-scale ecological datasets as well as complex analytical methods, which require specialized tools and resources. Computational training for ecological and evolutionary sciences has become more abundant and accessible over the past decade, but tool development has outpaced the availability of specialized training. Most training for scripted analyses focuses on individual analysis steps in one script rather than creating a scripted pipeline, where modular functions comprise an ecosystem of interdependent steps. Although current computational training creates an excellent starting place, linear styles of scripting can risk becoming labor- and time-intensive and less reproducible by often requiring manual execution. Pipelines, however, can be easily automated or tracked by software to increase efficiency and reduce potential errors. Ecology and evolution would benefit from techniques that reduce these risks by managing analytical pipelines in a modular, readily parallelizable format with clear documentation of dependencies. Workflow management software (WMS) can aid in the reproducibility, intelligibility and computational efficiency of complex pipelines. To date, WMS adoption in ecology and evolutionary research has been slow. We discuss the benefits and challenges of implementing WMS and illustrate its use through a case study with the targets r package to further highlight WMS benefits through workflow automation, dependency tracking and improved clarity for reviewers. Although WMS requires familiarity with function-oriented programming and careful planning for more advanced applications and pipeline sharing, investment in training will enable access to the benefits of WMS and impart transferable computing skills that can facilitate ecological and evolutionary data science at large scales.

Methods in Ecology and Evolution↗
USGS2014

Genetic tools for wildlife management

Granted interim status in November, 2013, The Wildlife Society’s (TWS) Molecular Ecology Working Group aims to promote scientific advancement by applying molecular techniques to wildlife ecology, management, and conservation. The working group—composed of sci - entists from diverse backgrounds—met for the first time in Pittsburgh at the TWS Annual Conference held in October. Our overarching goal is to enhance awareness of molecular ecology and genetic applica - tions to wildlife biology and act as an informational and networking resource. During the group’s interim status, which runs for three years, we intend to focus on a broad scope of molecular ecology that is applicable to wildlife including genetic and ge - nomic methods, conservation genetics, non-invasive genetic population monitoring, landscape genetics, evolutionary genetics, and molecular forensics

The Wildlife Professional↗
USGS2009

Application of the Hydroecological Integrity Assessment Process for Missouri Streams

Natural flow regime concepts and theories have established the justification for maintaining or restoring the range of natural hydrologic variability so that physiochemical processes, native biodiversity, and the evolutionary potential of aquatic and riparian assemblages can be sustained. A synthesis of recent research advances in hydroecology, coupled with stream classification using hydroecologically relevant indices, has produced the Hydroecological Integrity Assessment Process (HIP). HIP consists of (1) a regional classification of streams into hydrologic stream types based on flow data from long-term gaging-station records for relatively unmodified streams, (2) an identification of stream-type specific indices that address 11 subcomponents of the flow regime, (3) an ability to establish environmental flow standards, (4) an evaluation of hydrologic alteration, and (5) a capacity to conduct alternative analyses. The process starts with the identification of a hydrologic baseline (reference condition) for selected locations, uses flow data from a stream-gage network, and proceeds to classify streams into hydrologic stream types. Concurrently, the analysis identifies a set of non-redundant and ecologically relevant hydrologic indices for 11 subcomponents of flow for each stream type. Furthermore, regional hydrologic models for synthesizing flow conditions across a region and the development of flow-ecology response relations for each stream type can be added to further enhance the process. The application of HIP to Missouri streams identified five stream types ((1) intermittent, (2) perennial runoff-flashy, (3) perennial runoff-moderate baseflow, (4) perennial groundwater-stable, and (5) perennial groundwater-super stable). Two Missouri-specific computer software programs were developed: (1) a Missouri Hydrologic Assessment Tool (MOHAT) which is used to establish a hydrologic baseline, provide options for setting environmental flow standards, and compare past and proposed hydrologic alterations; and (2) a Missouri Stream Classification Tool (MOSCT) designed for placing previously unclassified streams into one of the five pre-defined stream types.

Open-File Report↗
USGS2013

Taming wildlife disease: bridging the gap between science and management

1.Parasites and pathogens of wildlife can threaten biodiversity, infect humans and domestic animals, and cause significant economic losses, providing incentives to manage wildlife diseases. Recent insights from disease ecology have helped transform our understanding of infectious disease dynamics and yielded new strategies to better manage wildlife diseases. Simultaneously, wildlife disease management (WDM) presents opportunities for large-scale empirical tests of disease ecology theory in diverse natural systems. 2.To assess whether the potential complementarity between WDM and disease ecology theory has been realized, we evaluate the extent to which specific concepts in disease ecology theory have been explicitly applied in peer-reviewed WDM literature. 3.While only half of WDM articles published in the past decade incorporated disease ecology theory, theory has been incorporated with increasing frequency over the past 40 years. Contrary to expectations, articles authored by academics were no more likely to apply disease ecology theory, but articles that explain unsuccessful management often do so in terms of theory. 4.Some theoretical concepts such as density-dependent transmission have been commonly applied, whereas emerging concepts such as pathogen evolutionary responses to management, biodiversity–disease relationships and within-host parasite interactions have not yet been fully integrated as management considerations. 5.Synthesis and applications. Theory-based disease management can meet the needs of both academics and managers by testing disease ecology theory and improving disease interventions. Theoretical concepts that have received limited attention to date in wildlife disease management could provide a basis for improving management and advancing disease ecology in the future.

Journal of Applied Ecology↗
USGS2018

A causal partition of trait correlations: using graphical models to derive statistical models from theoretical language

Recent studies hypothesize various causes of species‐level trait covariation, namely size (e.g., metabolic theory of ecology and leaf economics spectrum), pace‐of‐life (e.g., slow‐to‐fast continuum; lifestyle continuum), evolutionary history (e.g., phylogenetic conservatism), and ecological conditions (e.g., stabilizing selection). Various methods have been used in attempts to partition trait correlation among these influences (e.g., univariate analysis, principal components analysis, and factor analysis). However, it is not clear that the implied causal structure assumed by these methods matches the hypothesized causal structure driving trait correlations, a situation that can potentially lead to biased estimates and incorrect partitioning among mechanisms. Here, we propose the application of graphical causal models (GCM) for across‐kingdom synthesis and to aid researchers in their selection of correct analytical strategies. Graphical causal models use causal diagrams (i.e., box‐and‐arrow graphs) to represent expert knowledge of the data‐generating processes to analytically investigate the possibility of identifying hypothesized causal associations. We developed a causal diagram that synthesizes prominent hypotheses of trait covariation. Using the causal diagram, we (1) derived a quantitative expression to partition trait covariance among its hypothesized causal elements (i.e., size, pace‐of‐life, evolutionary history, and ecological conditions) and (2) developed analytic strategies to attribute trait covariance among the hypothesized causal elements under real‐world data availability, namely unobserved variables (i.e., pace‐of‐life) and confounding variables (i.e., evolutionary history and ecological conditions). Finally, we tested each analytic strategy by simulating trait datasets and, after incorporating the data limitations, tested their ability to correctly partition trait covariance. The analytical strategies were able to correctly partition trait covariance into the hypothesized causal elements of size, pace‐of‐life, and the historical effects of evolutionary history and ecological conditions. We demonstrate the efficacy of these strategies by applying them to a widely used trait dataset. Overall, the application of GCM revealed that researchers have used inappropriate measures to represent their theoretical constructs and have relied on analytical strategies that violated their causal assumptions, likely resulting in biased estimates. We discuss how this mismatch between theoretical language and statistical methods is prevalent in species‐level, trait‐based research and call for future studies to address these limitations.

Ecosphere↗
USGS2013

Refinement of late-Early and Middle Miocene diatom biostratigraphy for the east coast of the United States

Integrated Ocean Drilling Program (IODP) Expedition 313 continuously cored Lower to Middle Miocene sequences at three continental shelf sites off New Jersey, USA. The most seaward of these, Site M29, contains a well-preserved Early and Middle Miocene succession of planktonic diatoms that have been independently correlated with the geomagnetic polarity time scale derived in studies from the equatorial and North Pacific. Shallow water diatoms (species of Delphineis, Rhaphoneis, and Sceptroneis) dominate in onshore sequences in Maryland and Virginia, forming the basis for the East Coast Diatom Zones (ECDZ). Integrated study of both planktonic and shallow water diatoms in Hole M29A as well as in onshore sequences in Maryland (the Baltimore Gas and Electric Company well) and Delaware (the Ocean Drilling Program Bethany Beach corehole) allows the refinement of ECDZ zones into a high-resolution biochronology that can be successfully applied in both onshore and offshore regions of the East Coast of the United States. Strontium isotope stratigraphy supports the diatom biochronology, although for much of the Middle Miocene it suggests ages that are on average 0.4 m.y. older. The ECDZ zonal definitions are updated to include evolutionary events of Delphineis species, and regional occurrences of important planktonic diatom marker taxa are included. Updated taxonomy, reference to published figures, and photographic images are provided that will aid in the application of this diatom biostratigraphy.

East Coast↗
USGS2003

Isolation and characterization of novel waterfowl microsatellite loci: Cross-species comparisons and research applications

Waterfowl constitute an ecologically diverse group which are the subject of extensive research (e.g. see reviews in Batt et al . 1992), and are intensively managed (Nichols et al .1995). Genetic studies utilizing allozyme electrophoresis and mitochondrial (mt)DNA have provided valuable information on waterfowl ecology and evolutionary history (Cooke & Buckley 1987). However, highly variable molecular genetic markers (e.g. multilocus minisatellites; Triggs et al. 1992) have not generally been identified for this group.

Molecular Ecology↗
USGS2007

Development of the Hydroecological Integrity Assessment Process for Determining Environmental Flows for New Jersey Streams

The natural flow regime paradigm and parallel stream ecological concepts and theories have established the benefits of maintaining or restoring the full range of natural hydrologic variation for physiochemical processes, biodiversity, and the evolutionary potential of aquatic and riparian communities. A synthesis of recent advances in hydroecological research coupled with stream classification has resulted in a new process to determine environmental flows and assess hydrologic alteration. This process has national and international applicability. It allows classification of streams into hydrologic stream classes and identification of a set of non-redundant and ecologically relevant hydrologic indices for 10 critical sub-components of flow. Three computer programs have been developed for implementing the Hydroecological Integrity Assessment Process (HIP): (1) the Hydrologic Indices Tool (HIT), which calculates 171 ecologically relevant hydrologic indices on the basis of daily-flow and peak-flow stream-gage data; (2) the New Jersey Hydrologic Assessment Tool (NJHAT), which can be used to establish a hydrologic baseline period, provide options for setting baseline environmental-flow standards, and compare past and proposed streamflow alterations; and (3) the New Jersey Stream Classification Tool (NJSCT), designed for placing unclassified streams into pre-defined stream classes. Biological and multivariate response models including principal-component, cluster, and discriminant-function analyses aided in the development of software and implementation of the HIP for New Jersey. A pilot effort is currently underway by the New Jersey Department of Environmental Protection in which the HIP is being used to evaluate the effects of past and proposed surface-water use, ground-water extraction, and land-use changes on stream ecosystems while determining the most effective way to integrate the process into ongoing regulatory programs. Ultimately, this scientifically defensible process will help to quantify the effects of anthropogenic changes and development on hydrologic variability and help planners and resource managers balance current and future water requirements with ecological needs.

Scientific Investigations Report↗
USGS2015

Geological processes and orchid biogeography with applications to southeast central America

This contribution owes its origins to a paper presentation by Dr. Calloway H. Dodson at the Second International Conference on Neotropical Orchidology held in San José, Costa Rica in May of2003 (Dodson 2003). Dr. Dodson outlined some ofthe reasons to suspect that regional geological fac-tors may play important roles in orchid speciation and biogeography and gave examples from the northwestern South America. He also suggested that evolutionary change in orchid might occur over fairly short time periods, perhaps even as short as decades, centuries or millennia (Dodson 2003, SHK lecture notes). These ideas stimulated the author, a professional earth scientist, to begin thinking about how these exciting ideas could begin to be tested in Costa Rica neighboring and Central American countries, an area that has drawn him to return frequently over the last decade. The present contribution is a proposal for integrating geological observations, such as the chronology of arc volcanic activity in Nicaragua,Costa Rica, and Panama, in hypothesis forming and testing of the geographic distribution of orchids (and possibly other biota). I initially focus on comparisons between orchid inventories on the windward slopes of mountainous regions (elevation > 1000 m)with high rainfall (> 1-2 m) in tropical regions, the so-called tropical cloud forests. These regions represent the tropical pre-montane rain forestto lower montane tropical rain forest life zones of Holdridge(1967) and the montane vegetation zone applied to Costa Rica and Panama by Dressler (1993). An important message of this paper is that such tropical mountainous regions are not necessarily static, but may change in elevation over geologic time due to active tectonic deformation and uplift and that the presence of active volcanism in a mountain range may also introduce additional chemical factors, such as volcanic gases, acid rain, and volcanic soils, and also physical factors, such as interruption of gene flow by explosive eruptions and coverage by their air fall products such as ash (tephra), lava flows, and lahars (volcanic mudflows). Thus over a given geological time interval, forests may be slowly increasing in elevation by tectonic uplift or by the accumulation of volcanic products such as steep-sided strato volcanoes (built from both lavas and tephra), or by down-slope accumulations of lava flows or lahars. Mountains may also lose elevation by erosion or by tectonic subsidence. As we shall see, tropical Central America shows an extraordinarily high level of tectonic and volcanic history that has changed its geography and, by implication, climate, life zones,and likely orchid distribution. My working hypo thesis put forward for testing is that orchid adaptations to these changes may have led to the development of new species and endemism in this region.

Lankesteriana↗
USGS2021

Species and population specific gene expression in blood transcriptomes of marine turtles

Background Transcriptomic data has demonstrated utility to advance the study of physiological diversity and organisms’ responses to environmental stressors. However, a lack of genomic resources and challenges associated with collecting high-quality RNA can limit its application for many wild populations. Minimally invasive blood sampling combined with de novo transcriptomic approaches has great potential to alleviate these barriers. Here, we advance these goals for marine turtles by generating high quality de novo blood transcriptome assemblies to characterize functional diversity and compare global transcriptional profiles between tissues, species, and foraging aggregations. Results We generated high quality blood transcriptome assemblies for hawksbill ( Eretmochelys imbricata ) , loggerhead ( Caretta caretta ), green ( Chelonia mydas ), and leatherback ( Dermochelys coriacea ) turtles. The functional diversity in assembled blood transcriptomes was comparable to those from more traditionally sampled tissues. A total of 31.3% of orthogroups identified were present in all four species, representing a core set of conserved genes expressed in blood and shared across marine turtle species. We observed strong species-specific expression of these genes, as well as distinct transcriptomic profiles between green turtle foraging aggregations that inhabit areas of greater or lesser anthropogenic disturbance. Conclusions Obtaining global gene expression data through non-lethal, minimally invasive sampling can greatly expand the applications of RNA-sequencing in protected long-lived species such as marine turtles. The distinct differences in gene expression signatures between species and foraging aggregations provide insight into the functional genomics underlying the diversity in this ancient vertebrate lineage. The transcriptomic resources generated here can be used in further studies examining the evolutionary ecology and anthropogenic impacts on marine turtles.

BMC Genomics↗
USGS2019

Evolutionary history predicts high-impact invasions by herbivorous insects

A long‐standing goal of invasion biology is to identify factors driving highly variable impacts of non‐native species. Although hypotheses exist that emphasize the role of evolutionary history (e.g., enemy release hypothesis & defense‐free space hypothesis), predicting the impact of non‐native herbivorous insects has eluded scientists for over a century. Using a census of all 58 non‐native conifer‐specialist insects in North America, we quantified the contribution of over 25 factors that could affect the impact they have on their novel hosts, including insect traits (fecundity, voltinism, native range, etc.), host traits (shade tolerance, growth rate, wood density, etc.), and evolutionary relationships (between native and novel hosts and insects). We discovered that divergence times between native and novel hosts, the shade and drought tolerance of the novel host, and the presence of a coevolved congener on a shared host, were more predictive of impact than the traits of the invading insect. These factors built upon each other to strengthen our ability to predict the risk of a non‐native insect becoming invasive. This research is the first to empirically support historically assumed hypotheses about the importance of evolutionary history as a major driver of impact of non‐native herbivorous insects. Our novel, integrated model predicts whether a non‐native insect not yet present in North America will have a one in 6.5 to a one in 2,858 chance of causing widespread mortality of a conifer species if established (R2 = 0.91) Synthesis and applications. With this advancement, the risk to other conifer host species and regions can be assessed, and regulatory and pest management efforts can be more efficiently prioritized.

Ecology and Evolution↗
USGS2020

Estimating population-specific predation effects on Chinook salmon via data integration

Recent success in the conservation of many marine mammals has resulted in new management challenges due to increasing conflict with fisheries. Increasing predation by pinnipeds on threatened salmon is of particular concern. Seemingly, pinniped conservation is now in conflict with the recovery of threatened salmon, creating a dilemma for managers. We use the Lower Columbia River as a case study for examining the relationship between seasonal California sea lion Zalophus californianus abundance and survival of threatened salmon. To quantify mortality associated with increasing sea lion abundance, we examined the effect of seasonal sea lion abundance on adult Chinook salmon Oncorhynchus tshawytscha survival during migrations through the Lower Columbia River. We integrated data on survival with data on population-specific migration timing, allowing quantification of the relationship between sea lion abundance and survival in 18 populations of spring–summer Chinook salmon listed as Threatened or Endangered under the U.S. Endangered Species Act. Of the 18 populations examined, earlier migrating populations experienced lower survival in association with increased exposure to higher sea lion abundance. We estimated that in years with high sea lion abundance, the nine earliest-migrating populations experienced an additional 21.1% (95% CI = 16.3–26.1) mortality compared to years with baseline sea lion abundance, while the nine latest migrating populations experienced an additional 10.1% (7.5–13.0). Synthesis and applications . Integrating datasets on seasonal survival and migration timing made it possible for us to estimate population-specific mortality associated with increased sea lion abundance in the Lower Columbia River. This information could not be produced from any one dataset, highlighting the utility of data integration approaches. The mortality experienced by early migrating Chinook salmon suggests the potential for demographic and evolutionary consequences. Management actions such as hazing, relocating, or removing individuals that are frequent predators on salmon have been proposed. Identifying the management actions that will allow for socially and legally acceptable trade-offs between multiple conservation and other social values will be facilitated by development of explicit multi-species management frameworks. Continued monitoring will help to reduce the substantial uncertainty about the effect of pinnipeds on salmon and the predicted outcomes of alternative management actions.

Oregon, Washington↗