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USGS2002

Antimicrobial residues in animal waste and water resources proximal to large-scale swine and poultry feeding operations

Expansion and intensification of large-scale animal feeding operations (AFOs) in the United States has resulted in concern about environmental contamination and its potential public health impacts. The objective of this investigation was to obtain background data on a broad profile of antimicrobial residues in animal wastes and surface water and groundwater proximal to large-scale swine and poultry operations. The samples were measured for antimicrobial compounds using both radioimmunoassay and liquid chromatography/electrospray ionization-mass spectrometry (LC/ESI-MS) techniques. Multiple classes of antimicrobial compounds (commonly at concentrations of >100 μg/l) were detected in swine waste storage lagoons. In addition, multiple classes of antimicrobial compounds were detected in surface and groundwater samples collected proximal to the swine and poultry farms. This information indicates that animal waste used as fertilizer for crops may serve as a source of antimicrobial residues for the environment. Further research is required to determine if the levels of antimicrobials detected in this study are of consequence to human and/or environmental ecosystems. A comparison of the radioimmunoassay and LC/ESI-MS analytical methods documented that radioimmunoassay techniques were only appropriate for measuring residues in animal waste samples likely to contain high levels of antimicrobials. More sensitive LC/ESI-MS techniques are required in environmental samples, where low levels of antimicrobial residues are more likely.

Science of the Total Environment↗

USGS2019

Detection of spring viraemia of carp virus in imported amphibians reveals an unanticipated foreign animal disease threat

Global translocation of plants and animals is a well-recognized mechanism for introduction of pathogens into new regions. To mitigate this risk, various tools such as preshipment health certificates, quarantines, screening for specific disease agents and outright bans have been implemented. However, such measures only target known infectious agents and their hosts and may fail to prevent translocation of even well-recognized pathogens if they are carried by novel host species. In a recent example, we screened an imported shipment of Chinese firebelly newts ( Cynops orientalis ) for Batrachochytrium salamandrivorans , an emergent fungal pathogen of salamanders. All animals tested negative for the fungus. However, a virus was cultured from internal organs from 7 of the 11 individual dead salamanders and from two pools of tissues from four additional dead animals. Sequencing of a portion of the glycoprotein gene from all viral isolates indicated 100 % identity and that they were most closely related to spring viraemia of carp virus (SVCV). Subsequently, SVCV-specific PCR testing indicated the presence of virus in internal organs from each of the four animals previously pooled, and whole-genome sequencing of one of the viral isolates confirmed genomic arrangement characteristic of SVCV. SVCV is a rhabdovirus pathogen of cyprinid fish that is listed as notifiable to the Office International des Epizooties. This discovery reveals a novel route for potential spillover of this economically important pathogen as rhabdovirus has not previously been documented in amphibians.

Emerging Microbes & Infections↗

USGS2025

The influence of human presence and footprint on animal space use in US national parks

Given the importance of protected areas for biodiversity, the growth of visitation to many areas has raised concerns about the effects of humans on wildlife. In 2020, the COVID-19 pandemic led to temporary closure of national parks in the United States, offering a pseudonatural experiment to tease apart the effects of permanent infrastructure and transient human presence on animals. We compiled GPS tracking data from 229 individuals of 10 mammal species in 14 parks and used third-order hierarchical resource selection functions to evaluate the influence of the human footprint on animal space use in 2019 and 2020. Averaged across all parks and species, animals avoided the human footprint, whether the park was open or closed. However, although animals in remote areas showed consistent avoidance, on average those in more developed areas switched from avoidance to selection when protected areas were closed. Findings varied across species: some responded consistently negatively to the footprint (wolves, mountain goats), some positively (mule deer, red fox) and others had a strong exposure-mediated response (elk, mountain lion). Furthermore, some species responded more strongly to the park closure (black bear, moose). This study advances our understanding of complex interactions between recreation and wildlife in protected areas.

western United States↗

USGS2019

Accounting for phenology in the analysis of animal movement

The analysis of animal tracking data provides important scientific understanding and discovery in ecology. Observations of animal trajectories using telemetry devices provide researchers with information about the way animals interact with their environment and each other. For many species, specific geographical features in the landscape can have a strong effect on behavior. Such features may correspond to a single point (eg, dens or kill sites), or to higher dimensional subspaces (eg, rivers or lakes). Features may be relatively static in time (eg, coastlines or home‐range centers), or may be dynamic (eg, sea ice extent or areas of high‐quality forage for herbivores). We introduce a novel model for animal movement that incorporates active selection for dynamic features in a landscape. Our approach is motivated by the study of polar bear (Ursus maritimus) movement. During the sea ice melt season, polar bears spend much of their time on sea ice above shallow, biologically productive water where they hunt seals. The changing distribution and characteristics of sea ice throughout the year mean that the location of valuable habitat is constantly shifting. We develop a model for the movement of polar bears that accounts for the effect of this important landscape feature. We introduce a two‐stage procedure for approximate Bayesian inference that allows us to analyze over 300 000 observed locations of 186 polar bears from 2012 to 2016. We use our model to estimate a spatial boundary of interest to wildlife managers that separates two subpopulations of polar bears from the Beaufort and Chukchi seas.

Biometrics↗

USGS2025

Beyond habitat: Memory versus environment in shaping animal space use

For nearly half a century, ecologists have sought to explain animal space use through characteristics of the environment (i.e., habitat). Recent evidence suggests animals also use memory of previous experiences to decide when and where to move. Yet, the relative influence of the two in explaining animal space use has not been resolved. Using six large ungulate species in the Rocky Mountains (USA), we evaluated the performance of a habitat selection model with 16 environmental variables and another with two variables representing previous use (i.e., memory). While memory outperformed the environment for two species and the environment outperformed memory for four species, the influence of memory and the environment was overall comparable. The environment best explained the space use of specialists, while memory best explained species with strong site fidelity. Our work challenges traditional habitat selection theory, showcasing that animals build their spatial preferences through experience just as much as merely responding to their environment.

Wyoming↗

USGS2010

Use of spatial capture-recapture modeling and DNA data to estimate densities of elusive animals

Assessment of abundance, survival, recruitment rates, and density (i.e., population assessment) is especially challenging for elusive species most in need of protection (e.g., rare carnivores). Individual identification methods, such as DNA sampling, provide ways of studying such species efficiently and noninvasively. Additionally, statistical methods that correct for undetected animals and account for locations where animals are captured are available to efficiently estimate density and other demographic parameters. We collected hair samples of European wildcat ( Felis silvestris ) from cheek-rub lure sticks, extracted DNA from the samples, and identified each animals' genotype. To estimate the density of wildcats, we used Bayesian inference in a spatial capture-recapture model. We used WinBUGS to fit a model that accounted for differences in detection probability among individuals and seasons and between two lure arrays. We detected 21 individual wildcats (including possible hybrids) 47 times. Wildcat density was estimated at 0.29/km 2 (SE 0.06), and 95% of the activity of wildcats was estimated to occur within 1.83 km from their home-range center. Lures located systematically were associated with a greater number of detections than lures placed in a cell on the basis of expert opinion. Detection probability of individual cats was greatest in late March. Our model is a generalized linear mixed model; hence, it can be easily extended, for instance, to incorporate trap- and individual-level covariates. We believe that the combined use of noninvasive sampling techniques and spatial capture-recapture models will improve population assessments, especially for rare and elusive animals.

Conservation Biology↗

USGS2017

Animal movement in the absence of predation: environmental drivers of movement strategies in a partial migration system

Animal movement strategies including migration, dispersal, nomadism, and residency are shaped by broad-scale spatial-temporal structuring of the environment, including factors such as the degrees of spatial variation, seasonality and inter-annual predictability. Animal movement strategies, in turn, interact with the characteristics of individuals and the local distribution of resources to determine local patterns of resource selection with complex and poorly understood implications for animal fitness. Here we present a multi-scale investigation of animal movement strategies and resource selection. We consider the degree to which spatial variation, seasonality, and inter-annual predictability in resources drive migration patterns among different taxa and how movement strategies in turn shape local resource selection patterns. We focus on adult Galapagos giant tortoises Chelonoidis spp. as a model system since they display many movement strategies and evolved in the absence of predators of adults. Specifically, our analysis is based on 63 individuals among four taxa tracked on three islands over six years and almost 10 6 tortoise re-locations. Tortoises displayed a continuum of movement strategies from migration to sedentarism that were linked to the spatio-temporal scale and predictability of resource distributions. Movement strategies shaped patterns of resource selection. Specifically, migratory individuals displayed stronger selection toward areas where resources were more predictable among years than did non-migratory individuals, which indicates a selective advantage for migrants in seasonally structured, more predictable environments. Our analytical framework combines large-scale predictions for movement strategies, based on environmental structuring, with finer-scale analysis of space-use. Integrating different organizational levels of analysis provides a deeper understanding of the eco-evolutionary dynamics at play in the emergence and maintenance of migration and the critical role of resource predictability. Our results highlight that assessing the potential benefits of differential behavioral responses first requires an understanding of the interactions among movement strategies, resource selection and individual characteristics.

Oikos↗

USGS2020

Ecological insights from three decades of animal movement tracking across a changing Arctic

The Arctic is entering a new ecological state, with alarming consequences for humanity. Animal-borne sensors offer a window into these changes. Although substantial animal tracking data from the Arctic and subarctic exist, most are difficult to discover and access. Here, we present the new Arctic Animal Movement Archive (AAMA), a growing collection of more than 200 standardized terrestrial and marine animal tracking studies from 1991 to the present. The AAMA supports public data discovery, preserves fundamental baseline data for the future, and facilitates efficient, collaborative data analysis. With AAMA-based case studies, we document climatic influences on the migration phenology of eagles, geographic differences in the adaptive response of caribou reproductive phenology to climate change, and species-specific changes in terrestrial mammal movement rates in response to increasing temperature.

Science↗

USGS2016

Flexible characterization of animal movement pattern using net squared displacement and a latent state model

Background Characterizing the movement patterns of animals is an important step in understanding their ecology. Various methods have been developed for classifying animal movement at both coarse (e.g., migratory vs. sedentary behavior) and fine (e.g., resting vs. foraging) scales. A popular approach for classifying movements at coarse resolutions involves fitting time series of net-squared displacement (NSD) to models representing different conceptualizations of coarse movement strategies (i.e., migration, nomadism, sedentarism, etc.). However, the performance of this method in classifying actual (as opposed to simulated) animal movements has been mixed. Here, we develop a more flexible method that uses the same NSD input, but relies on an underlying discrete latent state model. Using simulated data, we first assess how well patterns in the number of transitions between modes of movement and the duration of time spent in a mode classify movement strategies. We then apply our approach to elucidate variability in the movement strategies of eight giant tortoises ( Chelonoidis sp.) using a multi-year (2009–2014) GPS dataset from three different Galapagos Islands. Results With respect to patterns of time spent and the number of transitions between modes, our approach out-performed previous efforts to distinguish among migration, dispersal, and sedentary behavior. We documented marked inter-individual variation in giant tortoise movement strategies, with behaviors indicating migration, dispersal, nomadism and sedentarism, as well as hybrid behaviors such as “exploratory residence”. Conclusions Distilling complex animal movement into discrete modes remains a fundamental challenge in movement ecology, a problem made more complex by the ever-longer duration, ever-finer resolution, and gap-ridden trajectories recorded by GPS devices. By clustering into modes, we derived information on the time spent within one mode and the number of transitions between modes which enabled finer differentiation of movement strategies over previous methods. Ultimately, the techniques developed here address limitations of previous approaches and provide greater insights with respect to characterization of movement strategies across scales by more fully utilizing long-term GPS telemetry datasets.

Movement Ecology↗

USGS2016

Animal movement constraints improve resource selection inference in the presence of telemetry error

Multiple factors complicate the analysis of animal telemetry location data. Recent advancements address issues such as temporal autocorrelation and telemetry measurement error, but additional challenges remain. Difficulties introduced by complicated error structures or barriers to animal movement can weaken inference. We propose an approach for obtaining resource selection inference from animal location data that accounts for complicated error structures, movement constraints, and temporally autocorrelated observations. We specify a model for telemetry data observed with error conditional on unobserved true locations that reflects prior knowledge about constraints in the animal movement process. The observed telemetry data are modeled using a flexible distribution that accommodates extreme errors and complicated error structures. Although constraints to movement are often viewed as a nuisance, we use constraints to simultaneously estimate and account for telemetry error. We apply the model to simulated data, showing that it outperforms common ad hoc approaches used when confronted with measurement error and movement constraints. We then apply our framework to an Argos satellite telemetry data set on harbor seals ( Phoca vitulina ) in the Gulf of Alaska, a species that is constrained to move within the marine environment and adjacent coastlines.

Ecology↗

USGS1990

Error in telemetry studies: Effects of animal movement on triangulation

We used Monte Carlo simulations to investigate the effects of animal movement on error of estimated animal locations derived from radio-telemetry triangulation of sequentially obtained bearings. Simulated movements of 0-534 m resulted in up to 10-fold increases in average location error but <10% decreases in location precision when observer-to-animal distances were <1,000 m. Location error and precision were minimally affected by censorship of poor locations with Chi-square goodness-of-fit tests. Location error caused by animal movement can only be eliminated by taking simultaneous bearings.

Journal of Wildlife Management↗

USGS2014

Book review: Fowler's zoo and wild animal medicine (volume 8)

In the eighth volume of Fowler's Zoo and Wild Animal Medicine , the editors have returned to the original, comprehensive, taxa-based format last used in the fifth volume that was released in 2003. The book consists of 82 chapters, divided into taxonomic classes that include amphibians, reptiles, birds, and mammals, and a general topics section. The editors deliberately selected new senior authors who are expert veterinary advisors for the various taxa. This international assemblage of authors is impressive, although the book would have benefited from a greater diversity of disciplinary expertise. Synthesis of the large and expanding body of knowledge about zoo and wild animal medicine is a Sisyphean task, but one that the editors have accomplished well. The chapters were well written and are beautifully illustrated with high-quality images and generally well referenced. Much of the information is summarized in tabular format, which I found both a blessing and a curse. Tabulation of hematologic variables and anesthetic doses is helpful; however, tabulation of information regarding infectious and parasitic diseases results in a loss of detail. For example, methods of diagnosis for some diseases are omitted from some tables. The need for succinctness results in trade-offs, and statements such as “ Batrachochytrium dendrobatidis … is one of the most well described pathogens of anurans” with no further information leaves readers unsated. In addition, the book does not have any chapters on fish or invertebrates, which are notable omissions given the importance of these species. Those quibbles aside, this is a must-have book for all zoo and wild animal medicine students and practitioners. However, perhaps it is time to recognize that, during the 36 years since the first volume was published, this discipline has become too large to be contained in 1 book. This is largely because of the success of this book series, and it is a nice problem to have. Review info: Fowler's Zoo and Wild Animal Medicine (Volume 8). By R. Eric Miller & Murray E. Fowler, 2015. ISBN 978-1455773978, 773 pp.

Journal of the American Veterinary Medical Associa↗

USGS1998

County-based estimates of nitrogen and phosphorus content of animal manure in the United States for 1982, 1987, and 1992

This data set contains county estimates of nitrogen and phosphorus content of animal wastes produced annually for the years 1982, 1987, and 1992. The estimates are based on animal populations for those years from the 1992 Census of Agriculture (U.S. Bureau of the Census, 1995) and methods for estimating the nutrient content of manure from the Soil Conservation Service (1992). The data set includes several components.. 1. Spatial component - generalized county boundaries in ARC/INFO format/1/, including nine INFO lookup tables containing animal counts and nutrient estimates keyed to the county polygons using county code. (The county lines were not used in the nutrient computations and are provided for displaying the data as a courtesy to the user.) The data is organized by 5-digit state/county FIPS (Federal Information Processing Standards) code. Another INFO table lists the county names that correspond to the FIPS codes. 2. Tabular component - Nine tab-delimited ASCII lookup tables of animal counts and nutrient estimates organized by 5-digit state/county FIPS (Federal Information Processing Standards) code. Another table lists the county names that correspond to the FIPS codes. The use of trade names is for identification purposes only and does not constitute endorsement by the U.S. Geological Survey.

Report↗

USGS2022

Eastern Ecological Science Center — Fish and aquatic animal health

Science provided by the U.S. Geological Survey (USGS) Eastern Ecological Science Center (EESC) helps to protect fish and aquatic animal health and support disease management of our Nation’s fisheries and aquatic animal populations. Our capabilities and expertise span diverse, yet highly integrated disciplines related to all aspects of biology, ecology, and animal health. Our scientists work to identify novel and emerging pathogens and diseases to assess fish and aquatic animal responses to parasites, pathogens, adverse environmental conditions, and chemical exposures. Eastern Ecological Science Center research is conducted both in laboratories and in the field in various aquatic environments ranging from headwater streams to the ocean. The EESC team provides science leadership and support for fisheries and aquatic species specialists nationwide.

Fact Sheet↗

USGS2021

Animal reservoirs and hosts for emerging alphacoronaviruses and betacoronaviruses

The ongoing global pandemic caused by coronavirus disease has once again demonstrated the role of the family Coronaviridae in causing human disease outbreaks. Because severe acute respiratory syndrome coronavirus 2 was first detected in December 2019, information on its tropism, host range, and clinical manifestations in animals is limited. Given the limited information, data from other coronaviruses might be useful for informing scientific inquiry, risk assessment, and decision-making. We reviewed endemic and emerging infections of alphacoronaviruses and betacoronaviruses in wildlife, livestock, and companion animals and provide information on the receptor use, known hosts, and clinical signs associated with each host for 15 coronaviruses detected in humans and animals. This information can be used to guide implementation of a One Health approach that involves human health, animal health, environmental, and other relevant partners in developing strategies for preparedness, response, and control to current and future coronavirus disease threats.

Emerging Infectious Diseases↗

USGS2018

Challenges and opportunities developing mathematical models of shared pathogens of domestic and wild animals

Diseases that affect both wild and domestic animals can be particularly difficult to prevent, predict, mitigate, and control. Such multi-host diseases can have devastating economic impacts on domestic animal producers and can present significant challenges to wildlife populations, particularly for populations of conservation concern. Few mathematical models exist that capture the complexities of pathogens, yet development of such models would allow us to estimate and compare the potential effectiveness of management actions for mitigating or suppressing disease in wildlife and/or livestock host populations. We conducted a workshop in March 2014 to identify the challenges associated with developing models of pathogen transmission across the wildlife-livestock interface. The development of mathematical models of pathogen transmission at this interface is hampered by the difficulties associated with describing the host-pathogen systems including: 1) the identity of wildlife hosts, their distributions, and movement patterns, 2) the pathogen transmission pathways between wildlife and domestic animals, 3) the effects of the disease and concomitant mitigation efforts on wild and domestic animal populations, and 4) barriers to communication between sectors. To promote the development of mathematical models of transmission at this interface, we recommend further integration of modern quantitative techniques and improvement of communication among wildlife biologists, mathematical modelers, veterinary medicine professionals, producers, and other stakeholders concerned with the consequences of pathogen transmission at this important, yet poorly understood, interface.

Veterinary Sciences↗

USGS2018

Density estimation of sound-producing terrestrial animals using single automatic acoustic recorders and distance sampling

Obtaining accurate information on the distribution, density, and abundance of animals is an important first step toward their conservation. Methodological approaches using automatic acoustic recorders for species that communicate acoustically are gaining increased interest because of their advantages over traditional sampling methods. In this study, we created and evaluated a protocol to estimate population density, which can be used to compute abundance of terrestrial sound-producing animals from single automatic acoustic recorders and using an automatic detection algorithm. The protocol uses cue rates from the target species, environmental conditions, and an estimate of the distance of the individual to the recorder based on the power of the received sound. We applied our protocol to estimate the density of a Hawaiian forest bird species (Hawaiˊi ˊAmakihi [ Chlorodrepanis virens ]) on the island of Hawaiˊi, USA. We validated our approach by comparing our density estimates with those calculated at the same stations using a traditional point-transect distance sampling method based on human observations. Overall density estimates based on recorded signals were lower than those based on human observations, but 95% confidence intervals of the two density estimates overlapped. This study presents a relatively simple but effective protocol for estimating animal density using single automatic acoustic recorders. Our protocol may easily be adapted to other sound-emitting terrestrial animals.

Avian Conservation and Ecology↗

USGS1994

Horvitz-Thompson survey sample methods for estimating large-scale animal abundance

Large-scale surveys to estimate animal abundance can be useful for monitoring population status and trends, for measuring responses to management or environmental alterations, and for testing ecological hypotheses about abundance. However, large-scale surveys may be expensive and logistically complex. To ensure resources are not wasted on unattainable targets, the goals and uses of each survey should be specified carefully and alternative methods for addressing these objectives always should be considered. During survey design, the impoflance of each survey error component (spatial design, propofiion of detected animals, precision in detection) should be considered carefully to produce a complete statistically based survey. Failure to address these three survey components may produce population estimates that are inaccurate (biased low), have unrealistic precision (too precise) and do not satisfactorily meet the survey objectives. Optimum survey design requires trade-offs in these sources of error relative to the costs of sampling plots and detecting animals on plots, considerations that are specific to the spatial logistics and survey methods. The Horvitz-Thompson estimators provide a comprehensive framework for considering all three survey components during the design and analysis of large-scale wildlife surveys. Problems of spatial and temporal (especially survey to survey) heterogeneity in detection probabilities have received little consideration, but failure to account for heterogeneity produces biased population estimates. The goal of producing unbiased population estimates is in conflict with the increased variation from heterogeneous detection in the population estimate. One solution to this conflict is to use an MSE-based approach to achieve a balance between bias reduction and increased variation. Further research is needed to develop methods that address spatial heterogeneity in detection, evaluate the effects of temporal heterogeneity on survey objectives and optimize decisions related to survey bias and variance. Finally, managers and researchers involved in the survey design process must realize that obtaining the best survey results requires an interactive and recursive process of survey design, execution, analysis and redesign. Survey refinements will be possible as further knowledge is gained on the actual abundance and distribution of the population and on the most efficient techniques for detection animals.

Transactions of the North American Wildlife and Na↗