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At least 145 records · Page 8Linked to original sources
USGS2026

From understanding to action: Integrating new and old methodologies to manage marine infectious disease

Marine diseases can have far-reaching effects on population, community and ecosystem health; however, our ability to track, predict and manage these diseases has, historically, been poor. As a result, the fields of disease ecology and epidemiology have developed at a slower pace for marine than terrestrial systems [ 1 ]. New methodologies, including genomic tools for diagnostics [ 2 , 3 ], transcriptomic tools for measuring host and pathogen responses to infection (e.g. [ 4 , 5 ]), regional oceanic modelling systems that estimate environmental conditions influencing pathogen dispersal and disease progression [ 6 ], artificial intelligence methods for quantifying pathology from images (e.g. [ 7 ]) and advanced disease modelling techniques [ 8 , 9 ] are precipitating a rapid increase in our understanding of marine pathosystems. In 2016, these efforts led to the first special issue of Philosophical Transactions of the Royal Society B ( Marine diseases, volume 371, issue 1689) focused entirely on marine disease ecology and evolution, and in 2020, the first book, Marine disease ecology, was devoted to this topic [ 10 ]. This special issue, focused on marine disease management , is being published a decade after the first Philosophical Transactions special issue on marine diseases. The shift to a management focus reflects an urgent need for management strategies to address high-impact diseases and the rapid methodological advances that have resulted. The papers included in this issue demonstrate the value of combining classical approaches (e.g. routine disease surveillance, reductionistic pathogen challenge trials, rapid throughput diagnostics) with cutting-edge technologies (e.g. high-resolution oceanographic models, Bayesian models, replicated transcriptomic studies) to identify drivers of disease, quantify impacts and suggest management strategies.

Philosophical Transactions of the Royal Society, S↗
USGS2020

Influence of niche breadth and position on the historical biogeography of seafaring scincid lizards

Niche breadth and position can influence diversification among closely related species or populations, yet limited empirical data exist concerning the predictability of the outcomes. We explored the effects of these factors on the evolution of the Emoia atrocostata species group, an insular radiation of lizards in the western Pacific Ocean and Indo-Australasia composed of both endemic and widespread species that differ in niche occupancy. We used molecular data and phylogeographical diffusion models to estimate the timing and patterns of range expansion, and ancestral reconstruction methods to infer shifts in ecology. We show evidence of multidirectional spread from a centre of origin in western Micronesia, and that the phyletic diversity of the group is derived from a putative habitat specialist that survives in the littoral zone. This species is composed of paraphyletic lineages that represent stages or possible endpoints in the continuum toward speciation. Several descendant species have transitioned to either strand or interior forest habitat, but only on remote islands with depauperate terrestrial faunas. Our results suggest that the atrocostata group might be in the early phases of a Wilsonian taxon cycle and that the capacity to tolerate salt stress has promoted dispersal and colonization of remote oceanic islands. Divergence itself, however, is largely driven by geographical isolation rather than shifts in ecology.

Biological Journal of the Linnean Society↗
USGS2017

Assessing the potential of translocating vulnerable forest birds by searching for novel and enduring climatic ranges

Hawaiian forest birds are imperiled, with fewer than half the original >40 species remaining extant. Recent studies document ongoing rapid population decline and pro- ject complete climate-based range losses for the critically endangered Kaua’i endemics ‘akeke’e (Loxops caeruleirostris) and ‘akikiki (Oreomystis bairdi) by end-of-century due to projected warming. Climate change facilitates the upward expansion of avian malaria into native high elevation forests where disease was historically absent. While intensi- fied conservation efforts attempt to safeguard these species and their habitats, the magnitude of potential loss and the urgency of this situation require all conservation options to be seriously considered. One option for Kaua’i endemics is translocation to islands with higher elevation habitats. We explored the feasibility of interisland translocation by projecting baseline and future climate-based ranges of ‘akeke’e and ‘akikiki across the Hawaiian archipelago. For islands where compatible climates for these spe- cies were projected to endure through end-of-century, an additional climatic niche overlap analysis compares the spatial overlap between Kaua’i endemics and current native species on prospective destination islands. Suitable climate-based ranges exist on Maui and Hawai’i for these Kaua’i endemics that offer climatically distinct areas compared to niche distributions of destination island endemics. While we recognize that any decision to translocate birds will include assessing numerous additional social, political, and biological factors, our focus on locations of enduring and ecologically compatible climate-based ranges represents the first step to evaluate this potential conservation option. Our approach considering baseline and future distributions of species with climatic niche overlap metrics to identify undesirable range overlap provides a method that can be utilized for other climate-vulnerable species with disjointed compatible environments beyond their native range.

Hawaii↗
USGS2001

Monitoring of biological diversity in space and time

Monitoring programmes are being used increasingly to assess spatial and temporal trends of biological diversity, with an emphasis on evaluating the efficiency of management policies. Recent reviews of the existing programmes, with a focus on their design in particular, have highlighted the main weaknesses: the lack of well-articulated objectives and the neglect of different sources of error in the estimation of biological diversity. We review recent developments in methods and designs that aim to integrate sources of error to provide unbiased estimates of change in biological diversity and to suggest the potential causes.

Trends in Ecology and Evolution↗
USGS2013

Evolution of a reassortant North American gull influenza virus lineage: drift, shift and stability

Background: The role of gulls in the ecology of avian influenza (AI) is different than that of waterfowl. Different constellations of subtypes circulate within the two groups of birds and AI viruses isolated from North American gulls frequently possess reassortant genomes with genetic elements from both North America and Eurasian lineages. A 2008 isolate from a Newfoundland Great Black-backed Gull contained a mix of North American waterfowl, North American gull and Eurasian lineage genes. Methods: We isolated, sequenced and phylogenetically compared avian influenza viruses from 2009 Canadian wild birds. Results: We analyzed six 2009 virus isolates from Canada and found the same phylogenetic lineage had persisted over a larger geographic area, with an expanded host range that included dabbling and diving ducks as well as gulls. All of the 2009 virus isolates contained an internal protein coding set of genes of the same Eurasian lineage genes except PB1 that was from a North American lineage, and these genes continued to evolve by genetic drift. We show evidence that the 2008 Great Black-backed Gull virus was derived from this lineage with a reassortment of a North American PA gene into the more stable core set of internal protein coding genes that has circulated in avian populations for at least 2 years. From this core, the surface glycoprotein genes have switched several times creating H13N6, H13N2, and H16N3 subtypes. These gene segments were from North American lineages except for the H16 and N3 vRNAs. Conclusions: This process appears similar to genetic shifts seen with swine influenza where a stable "triple reassortant internal gene" core has circulated in swine populations with genetic shifts occurring with hemaggluttinin and neuraminidase proteins getting periodically switched. Thus gulls may serve as genetic mixing vessels for different lineages of avian influenza, similar to the role of swine with regards to human influenza. These findings illustrate the need for continued surveillance in gull and waterfowl populations, both on the Pacific and especially Atlantic coasts of North America, to document virus intercontinental movement and the role of gull species in the evolution and epidemiology of AI.

Virology Journal↗
USGS2025

Sapsucker wells as a keystone nutritional resource: Evaluating methods for detection of secondary sap consumers

North American sapsuckers are considered double keystone species because they (1) excavate nest cavities that are used by other birds, small mammals, and invertebrates, and (2) create and maintain sap wells, a temporary nutritional resource available to a variety of secondary consumers. Most previous reports of secondary sap consumption relied on human observers and were based on either brief or incidental observations. However, modern technology can greatly enhance observational techniques and provide additional insights into the functional, community-level importance of sap wells. We used visual surveys, camera traps, and environmental DNA (eDNA) to identify secondary consumers of sap from wells created by red-naped ( Sphyrapicus nuchalis ) and Williamson's ( S. thyroideus ) sapsuckers among three functional groups of shrubs and trees in south-central Colorado: shrub willows ( Salix spp.), Rocky Mountain maple ( Acer glabrum ), and conifer trees (Pinopsida). Camera traps and eDNA revealed additional sap-well visitors not identified from direct observations. Camera traps were effective for detecting nocturnal sap-well visitors such as small rodents as well as occasional diurnal visitors. Environmental DNA analyses corroborated findings from other methods and identified four additional taxa as possible sap consumers. The physiology of sap-well visitors, such as the ability to taste and assimilate compounds within sap, may aid in determining consumption versus contact when evaluating the results of eDNA analyses. Total vertebrate taxa detected using all 3 methods included 17 bird taxa in 10 families within 3 orders and 8 mammal taxa in 6 families within 4 orders. Shrub-willow sap wells attracted the most diverse vertebrate taxa (23), followed by Rocky Mountain maple (13) and conifer trees (10). Invertebrates in 13 families within 3 orders were observed feeding from sap wells during visual surveys. Because many secondary sap consumers perform ecological services such as pollination, seed dispersal, and pest control, the methods described here may aid in elucidating the importance of sap-well creators in supporting biodiversity and ecosystem functioning.

Colorado↗
USGS2017

Developing approaches for linear mixed modeling in landscape genetics through landscape-directed dispersal simulations

Dispersal can impact population dynamics and geographic variation, and thus, genetic approaches that can establish which landscape factors influence population connectivity have ecological and evolutionary importance. Mixed models that account for the error structure of pairwise datasets are increasingly used to compare models relating genetic differentiation to pairwise measures of landscape resistance. A model selection framework based on information criteria metrics or explained variance may help disentangle the ecological and landscape factors influencing genetic structure, yet there are currently no consensus for the best protocols. Here, we develop landscape-directed simulations and test a series of replicates that emulate independent empirical datasets of two species with different life history characteristics (greater sage-grouse; eastern foxsnake). We determined that in our simulated scenarios, AIC and BIC were the best model selection indices and that marginal R 2 values were biased toward more complex models. The model coefficients for landscape variables generally reflected the underlying dispersal model with confidence intervals that did not overlap with zero across the entire model set. When we controlled for geographic distance, variables not in the underlying dispersal models (i.e., nontrue) typically overlapped zero. Our study helps establish methods for using linear mixed models to identify the features underlying patterns of dispersal across a variety of landscapes.

Ecology and Evolution↗
USGS2021

Morphology and composition of Goldeye (Hiodontidae; Hiodon alosoides) otoliths

We provide up-to-date morphological and compositional data on otoliths of the osteoglossomorph Goldeye ( Hiodon alosoides ). Using computed tomography (CT) X-ray, we documented the location of each of the three pairs of otoliths (lapilli, sagittae, and asterisci) in relation to the swim bladder, which extended forward in close proximity to the sagittae and asterisci. The lappili were the largest otoliths in terms of surface area and volume, but the sagittae were highly modified, appearing spiral in shape when viewed dorsally, with a surface area to volume ratio more than double that of the lapilli. Using scanning electron microscopy, the surface of each otolith was viewable in great detail, and small otoconia (~10.5 μm diameter) were observed on each, but were most numerous on the sagittae. On scanning electron micrographs, the sagittae appeared to be bi-lobed, with asymmetrical lobes each oriented in the same general direction. Using neutron and X-ray diffraction methods, we found three polymorphs of calcium carbonate crystals (aragonite, vaterite, and calcite), sometimes all within the same otolith. However, in general, lapilli and sagittae were composed predominately of aragonite whereas asterisci were composed chiefly of vaterite. With these results, we provide information on a unique species, whose inclusion in future studies would benefit our understanding of fish hearing, fish evolution, and fisheries ecology.

Journal of Morphology↗
USGS2024

Population and spatial dynamics of desert bighorn sheep in Grand Canyon during an outbreak of respiratory pneumonia

Introduction: Terrestrial species in riverine ecosystems face unique constraints leading to diverging patterns of population structure, connectivity, and disease dynamics. Desert bighorn sheep ( Ovis canadensis nelsoni ) in Grand Canyon National Park, a large native population in the southwestern USA, offer a unique opportunity to evaluate population patterns and processes in a remote riverine system with ongoing anthropogenic impacts. We integrated non-invasive, invasive, and citizen-science methods to address questions on abundance, distribution, disease status, genetic structure, and habitat fragmentation. Methods: We compiled bighorn sightings collected during river trips by park staff, commercial guides, and private citizens from 2000–2018 and captured bighorn in 2010–2016 to deploy GPS collars and test for disease. From 2011–2015, we non-invasively collected fecal samples and genotyped them at 9–16 microsatellite loci for individual identification and genetic structure. We used assignment tests to evaluate genetic structure and identify subpopulations, then estimated gene flow and recent migration to evaluate fragmentation. We used spatial capture-recapture to estimate annual population size, distribution, and trends after accounting for spatial variation in detection with a resource selection function model. Results and discussion: From 2010–2018, 3,176 sightings of bighorn were reported, with sightings of 56–145 bighorn annually on formal surveys. From 2012–2016, bighorn exhibiting signs of respiratory disease were observed along the river throughout the park. Of 25 captured individuals, 56% were infected by Mycoplasma ovipneumoniae , a key respiratory pathogen, and 81% were recently exposed. Pellet sampling for population estimation from 2011–2015 yielded 1,250 genotypes and 453 individuals. We detected 6 genetic clusters that exhibited mild to moderate genetic structure ( F ST 0.022–0.126). The river, distance, and likely topography restricted recent gene flow, but we detected cross-river movements in one section via genetic recaptures, no subpopulation appeared completely isolated, and genetic diversity was among the highest reported. Recolonization of one large stretch of currently empty habitat appears limited by the constrained topology of this system. Annual population estimates ranged 536–552 (95% CrI range 451–647), lamb:ewe ratios varied, and no significant population decline was detected. We provide a multi-method sampling framework useful for sampling other wildlife in remote riverine systems.

Arizona↗
USGS2025

Control of a dominant predator influences the occurrence of a mesocarnivore of conservation concern

Context Interspecific interactions shape ecological communities, influence community dynamics, and drive co-evolution. Despite their ecological significance, predation and competition remain understudied in plains spotted skunks ( Spilogale interrupta ), a species of conservation concern. Clarifying how predator management influences their occurrence is crucial for effective conservation. Aims We investigated how coyote ( Canis latrans ) management affects the occupancy of plains spotted skunks and whether interspecific interactions with domestic cats ( Felis catus ) and striped skunks ( Mephitis mephitis ) influence plains spotted skunk occurrence. Methods We analysed live-trap data from east-central South Dakota collected in spring of 2021 and 2022. The study area encompassed portions of counties that implemented disparate predator management regimes, including one with systematic annual coyote removal and another without. We used single-species occupancy models to estimate detection and occupancy probabilities for plains spotted skunks, domestic cats, and striped skunks, incorporating environmental factors, including the site-specific predator control regime. We then applied conditional two-species occupancy models to test whether cats and striped skunks influenced plains spotted skunk occurrence. Key results Plains spotted skunks had the lowest occupancy, followed by domestic cats, and striped skunks. Our findings showed significant associations between coyote removal and occupancy probabilities for each mesocarnivore species. Plains spotted skunks had higher occupancy in areas where coyotes were annually removed. Spotted skunk occurrence was not conditional on either domestic cat or striped skunk occurrence. Conclusions In our study system, cats appear to pose less predation risk to spotted skunks than do other predators, reducing the likelihood that cats significantly influence spotted skunk occupancy. Defensive behaviours and use of spatial refugia by plains spotted skunks may further mitigate predation risk. In addition, co-evolutionary pressures may have led to trait adaptations that facilitate the independent co-occurrence of plains spotted skunks and striped skunks. Implications Our findings highlighted the ecological consequences of predator management and the importance of considering predator–prey dynamics in conservation and management planning. Strategies aimed at conserving plains spotted skunks should integrate predator control measures while considering broader mesocarnivore community interactions.

South Dakota↗
USGS2015

Using sutures to attach miniature tracking tags to small bats for multimonth movement and behavioral studies

1. Determining the detailed movements of individual animals often requires them to carry tracking devices, but tracking broad-scale movement of small bats (< 30g) has been limited by transmitter technology and long-term attachment methods. This limitation inhibits our understanding of bat dispersal and migration, particularly in the context of emerging conservation issues like fatalities at wind turbines and diseases. 2. We tested a novel method of attaching lightweight global positioning system (GPS) tags and geolocating data loggers to small bats. We used monofilament, synthetic, absorbable sutures to secure GPS tags and data loggers to the skin of anesthetized big brown bats (Eptesicus fuscus) in Colorado and hoary bats (Lasiurus cinereus) in California. 3. GPS tags and data loggers were sutured to 17 bats in this study. Three tagged bats were recaptured seven months after initial deployment, with tags still attached; none of these bats showed ill effects from the tag. No severe injuries were apparent upon recapture of 6 additional bats that carried tags up to 26 days after attachment, however one of the bats exhibited skin chafing. 4. Use of absorbable sutures to affix small tracking devices seems to be a safe, effective method for studying movements of bats over multiple months, although additional testing is warranted. This new attachment method has the potential to quickly advance our understanding of small bats, particularly as more-sophisticated miniature tracking devices (e.g., satellite tags) become available.

Ecology and Evolution↗
USGS2022

A call to action: Standardizing white-tailed deer harvest data in the Midwestern United States and implications for quantitative analysis and disease management

Recreational hunting has been the dominant game management and conservation mechanism in the United States for the past century. However, there are numerous modern-day issues that reduce the viability and efficacy of hunting-based management, such as fewer hunters, overabundant wildlife populations, limited access, and emerging infectious diseases in wildlife. Quantifying the drivers of recreational harvest by hunters could inform potential management actions to address these issues, but this is seldom comprehensively accomplished because data collection practices limit some analytical applications (e.g., differing spatial scales of harvest regulations and harvest data). Additionally, managing large-scale issues, such as infectious diseases, requires collaborations across management agencies, which is challenging or impossible if data are not standardized. Here we discuss modern issues with the prevailing wildlife management framework in the United States from an analytical point of view with a case study of white-tailed deer ( Odocoileus virginianus ) in the Midwest. We have four aims: (1) describe the interrelated processes that comprise hunting and suggest improvements to current data collections systems, (2) summarize data collection systems employed by state wildlife management agencies in the Midwestern United States and discuss potential for large-scale data standardization, (3) assess how aims 1 and 2 influence managing infectious diseases in hunted wildlife, and (4) suggest actionable steps to help guide data collection standards and management practices. To achieve these goals, Wisconsin Department of Natural Resources disseminated a questionnaire to state wildlife agencies (Illinois, Indiana, Iowa, Kentucky, Michigan, Minnesota, Missouri, Ohio, Wisconsin), and we report and compare their harvest management structures, data collection practices, and responses to chronic wasting disease. We hope our “call to action” encourages re-evaluation, coordination, and improvement of harvest and management data collection practices with the goal of improving the analytical potential of these data. A deeper understanding of the strengths and deficiencies of our current management systems in relation to harvest and management data collection methods could benefit the future development of comprehensive and collaborative management and research initiatives (e.g., adaptive management) for wildlife and their diseases.

Illinois, Indiana, Iowa, Kentucky, Michigan, Minne↗
USGS2025

Expanding national-scale wildlife disease surveillance systems with research networks

Efficient learning about disease dynamics in free-ranging wildlife systems can benefit from active surveillance that is standardized across different ecological contexts. For example, active surveillance that targets specific individuals and populations with standardized sampling across ecological contexts (landscape-scale targeted surveillance) is important for developing a mechanistic understanding of disease emergence, which is the foundation for improving risk assessment of zoonotic or wildlife-livestock disease outbreaks and predicting hotspots of disease emergence. However, landscape-scale targeted surveillance systems are rare and challenging to implement. Increasing experience and infrastructure for landscape-scale targeted surveillance will improve readiness for rapid deployment of this type of surveillance in response to new disease emergence events. Here, we describe our experience developing and rapidly deploying a landscape-scale targeted surveillance system for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in two free-ranging deer species across their ranges in the United States. Our surveillance system was designed to collect data across individual, population, and landscape scales for future analyses aimed at understanding mechanisms and risk factors of SARS-CoV-2 transmission, evolution, and persistence. Our approach leveraged partnerships between state and federal public service sectors and academic researchers in a landscape-scale targeted surveillance research network. Methods describe our approach to developing the surveillance network and sampling design. Results report challenges with implementing our intended sampling design, specifically how the design was adapted as different challenges arose and summarize the sampling design that has been implemented thus far. In the discussion, we describe strategies that were important for the successful deployment of landscape-scale targeted surveillance, development and operation of the research network, construction of similar networks in the future, and analytical approaches for the data based on the sampling design.

Ecology and Evolution↗
USGS2019

Disease‐structured N‐mixture models: A practical guide to model disease dynamics using count data

Obtaining inferences on disease dynamics (e.g., host population size, pathogen prevalence, transmission rate, host survival probability) typically requires marking and tracking individuals over time. While multistate mark–recapture models can produce high‐quality inference, these techniques are difficult to employ at large spatial and long temporal scales or in small remnant host populations decimated by virulent pathogens, where low recapture rates may preclude the use of mark–recapture techniques. Recently developed N ‐mixture models offer a statistical framework for estimating wildlife disease dynamics from count data. N ‐mixture models are a type of state‐space model in which observation error is attributed to failing to detect some individuals when they are present (i.e., false negatives). The analysis approach uses repeated surveys of sites over a period of population closure to estimate detection probability. We review the challenges of modeling disease dynamics and describe how N ‐mixture models can be used to estimate common metrics, including pathogen prevalence, transmission, and recovery rates while accounting for imperfect host and pathogen detection. We also offer a perspective on future research directions at the intersection of quantitative and disease ecology, including the estimation of false positives in pathogen presence, spatially explicit disease‐structured N ‐mixture models, and the integration of other data types with count data to inform disease dynamics. Managers rely on accurate and precise estimates of disease dynamics to develop strategies to mitigate pathogen impacts on host populations. At a time when pathogens pose one of the greatest threats to biodiversity, statistical methods that lead to robust inferences on host populations are critically needed for rapid, rather than incremental, assessments of the impacts of emerging infectious diseases.

Ecology and Evolution↗
USGS2022

Identifying shared priorities for a bioregional approach to restoration in the Northern Gulf of Mexico

Natural resource management is often challenged with a mismatch between the scale of decision-making and the scale of the biological, ecological, and physical processes that control a system. Bioregional approaches to adaptive management have emerged as an approach to inform natural resource management at ecologically relevant scales and across multi-level governance structures. The implementation of adaptive management requires the determination of ecological and social priorities that can inform a desired system state across multiple governing bodies. We use the Northern Gulf of Mexico, United States, as a case study for a bioregional approach to adaptive management and illustrate a method for developing objectives and management priorities across programs and jurisdictions. Through this synthesis, using qualitative coding methods to develop a shared vocabulary across the diverse dataset, we identified commonalities and differences in ecological and human community priorities across the five states which line the Northern Gulf of Mexico. Using these shared priorities, we conceptualize a network of priority-focused objectives as a starting point for further stakeholder engagement and effectively monitoring and evaluating progress across boundaries. This approach serves as a framework for cross-program adaptive management by illustrating a desired system state that reflects the shared priorities among decision-making authorities in this region and offering individual programs or projects a method to articulate their contributions to the broader set of shared priorities Gulf-wide. This method can be used by restoration managers in any region of the world to align project objectives within cross-jurisdictional boundaries and illustrate the value of a bioregional approach to restoration.

Gulf of Mexico↗
USGS1999

Assessing biological effects from highway-runoff constituents

Increased emphasis on evaluation of nonpoint-source pollution has intensified the need for techniques that can be used to discern the toxicological effects of complex chemical mixtures. In response, the use of biological assessment techniques is receiving increased regulatory emphasis. When applied with documented habitat assessment and chemical analysis, these techniques can increase our understanding of the influence of environmental contaminants on the biological integrity and ecological function of aquatic communities. The contaminants of greatest potential concern in highway runoff are those that arise from highway construction, maintenance, and use. The major contaminants of interest are deicers; nutrients; metals; petroleum-related organic compounds, such as polycyclic aromatic hydrocarbons (PAHs), benzene, toluene, ethylbenzene, and xylene (BTEX), and methyl tert -butyl ether (MTBE); sediment washed off the road surface; and agricultural chemicals used in highway maintenance. Hundreds, if not thousands, of biological endpoints (measurable responses of living organisms) may be either directly or associatively affected by contaminant exposure. Measurable effects can occur throughout ecosystem processes across the wide range of biological complexity, ranging from responses at the biochemical level to the community level. The challenge to the environmental scientist is to develop an understanding of the relationship of effects at various levels of biological organization in order to determine whether a causal relationship exists between chemical exposure and substantial ecological impairment. This report provides a brief history of the evolution of biological assessment techniques, a description of the major classes of contaminants that are of particular interest in highway runoff, an overview of representative biological assessment techniques, and a discussion of data-quality considerations. Published reports with a focus on the effects of highway runoff on the local ecosystem were reviewed to provide information on (1) the suitability of the existing data for a quantitative national synthesis, (2) the methods available to study the effects of highway runoff on local ecosystems, and (3) the potential for adverse effects on the roadside environment and receiving waters. Although many biological studies have been done, the use of different methods and a general lack of sufficient documentation precludes a quantitative national synthesis on the basis of the existing data. The Federal Highway Administration, the U.S. Environmental Protection Agency, the U.S. Geological Survey, the Intergovernmental Task Force on Monitoring Water Quality, and the National Resources Conservation Service all have developed and documented methods for assessing the effects of contaminants on ecosystems in receiving waters. These published methods can be used to formulate a set of protocols to provide consistent information from highway-runoff studies. Review of the literature indicates (qualitatively) that highway runoff (even from highways with high traffic volume) may not usually be acutely toxic. Tissue analysis and community assessments, however, indicate effects from highway- runoff sediments near discharge points (even from sites near highways with relatively low traffic volumes). At many sites, elevated concentrations of highway-runoff constituents were measured in tissues of species associated with aquatic sediments. Community assessments also indicate decreases in the diversity and productivity of aquatic ecosystems at some sites receiving highway runoff. These results are not definitive, however, and depend on many site-specific criteria that were not sufficiently documented in most of the studies reviewed.

Open-File Report↗
USGS2024

Large-scale assessment of genetic structure to assess risk of populations of a large herbivore to disease

Chronic wasting disease (CWD) can spread among cervids by direct and indirect transmission, the former being more likely in emerging areas. Identifying subpopulations allows the delineation of focal areas to target for intervention. We aimed to assess the population structure of white-tailed deer ( Odocoileus virginianus ) in the northeastern United States at a regional scale to inform managers regarding gene flow throughout the region. We genotyped 10 microsatellites in 5701 wild deer samples from Maryland, New York, Ohio, Pennsylvania, and Virginia. We evaluated the distribution of genetic variability through spatial principal component analysis and inferred genetic structure using non-spatial and spatial Bayesian clustering algorithms (BCAs). We simulated populations representing each inferred wild cluster, wild deer in each state and each physiographic province, total wild population, and a captive population. We conducted genetic assignment tests using these potential sources, calculating the probability of samples being correctly assigned to their origin. Non-spatial BCA identified two clusters across the region, while spatial BCA suggested a maximum of nine clusters. Assignment tests correctly placed deer into captive or wild origin in most cases (94%), as previously reported, but performance varied when assigning wild deer to more specific origins. Assignments to clusters inferred via non-spatial BCA performed well, but efficiency was greatly reduced when assigning samples to clusters inferred via spatial BCA. Differences between spatial BCA clusters are not strong enough to make assignment tests a reliable method for inferring the geographic origin of deer using 10 microsatellites. However, the genetic distinction between clusters may indicate natural and anthropogenic barriers of interest for management.

Maryland, New York, Ohio, Pennsylvania, West Virgi↗
USGS2017

Creating multithemed ecological regions for macroscale ecology: Testing a flexible, repeatable, and accessible clustering method

Understanding broad-scale ecological patterns and processes often involves accounting for regional-scale heterogeneity. A common way to do so is to include ecological regions in sampling schemes and empirical models. However, most existing ecological regions were developed for specific purposes, using a limited set of geospatial features and irreproducible methods. Our study purpose was to: (1) describe a method that takes advantage of recent computational advances and increased availability of regional and global data sets to create customizable and reproducible ecological regions, (2) make this algorithm available for use and modification by others studying different ecosystems, variables of interest, study extents, and macroscale ecology research questions, and (3) demonstrate the power of this approach for the research question—How well do these regions capture regional-scale variation in lake water quality? To achieve our purpose we: (1) used a spatially constrained spectral clustering algorithm that balances geospatial homogeneity and region contiguity to create ecological regions using multiple terrestrial, climatic, and freshwater geospatial data for 17 northeastern U.S. states (~1,800,000 km 2 ); (2) identified which of the 52 geospatial features were most influential in creating the resulting 100 regions; and (3) tested the ability of these ecological regions to capture regional variation in water nutrients and clarity for ~6,000 lakes. We found that: (1) a combination of terrestrial, climatic, and freshwater geospatial features influenced region creation, suggesting that the oft-ignored freshwater landscape provides novel information on landscape variability not captured by traditionally used climate and terrestrial metrics; and (2) the delineated regions captured macroscale heterogeneity in ecosystem properties not included in region delineation—approximately 40% of the variation in total phosphorus and water clarity among lakes was at the regional scale. Our results demonstrate the usefulness of this method for creating customizable and reproducible regions for research and management applications.

Ecology and Evolution↗