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At least 127 records · Page 7Linked to original sources
USGS2011

Quantitative polymerase chain reaction (PCR) for detection of aquatic animal pathogens in a diagnostic laboratory setting

Real-time, or quantitative, polymerase chain reaction (qPCR) is quickly supplanting other molecular methods for detecting the nucleic acids of human and other animal pathogens owing to the speed and robustness of the technology. As the aquatic animal health community moves toward implementing national diagnostic testing schemes, it will need to evaluate how qPCR technology should be employed. This review outlines the basic principles of qPCR technology, considerations for assay development, standards and controls, assay performance, diagnostic validation, implementation in the diagnostic laboratory, and quality assurance and control measures. These factors are fundamental for ensuring the validity of qPCR assay results obtained in the diagnostic laboratory setting.

Journal of Aquatic Animal Health↗
USGS2024

A ‘how-to’ guide for estimating animal diel activity using hierarchical models

Animal diel activity patterns can aid understanding of (a) how species behaviourally adapt to anthropogenic and natural disturbances, (b) mechanisms of species co-existence through temporal partitioning, and (c) community or ecosystem effects of diel activity shifts. Activity patterns often vary spatially, a feature ignored by the kernel density estimators (KDEs) currently used for estimating diel activity. Ignoring this source of heterogeneity may lead to biased estimates of uncertainty and misleading conclusions regarding the drivers of diel activity. Thus, there is a need for more flexible statistical approaches for estimating activity patterns and testing hypotheses regarding their biotic and abiotic drivers. We illustrate how trigonometric terms and cyclic cubic splines combined with hierarchical models can provide a valuable alternative to KDEs. Like KDEs, these models accommodate circular data, but they can also account for site-to-site and other sources of variability, correlation amongst repeated measures, and variable sampling effort. They can also more readily quantify and test hypotheses related to the effects of covariates on activity patterns. Through empirical case studies, we illustrate how hierarchical models can quantify changes in activity levels due to seasonality and in response to biotic and abiotic factors (e.g. anthropogenic stressors and co-occurrence). We also describe frequentist and Bayesian approaches for quantifying site-specific (conditional) and population-averaged (marginal) activity patterns. We provide guidelines and tutorials with detailed step-by-step instructions for fitting and interpreting hierarchical models applied to time-stamped data, such as those recorded by camera traps and audio recorders. We conclude that this approach offers a viable, flexible, and effective alternative to KDEs when modelling animal activity patterns.

Journal of Animal Ecology↗
USGS2023

A field test of R package GPSeqClus: For establishing animal location clusters

The ability to track animals with Global Positioning System (GPS) collars opened an enormous potential for studying animal movements and behaviour in their natural environment. One such endeavour is to identify clusters of GPS locations as a way to estimate predator kill rate. Clapp et al. (2021) developed an R package ( GPSeqClus ) to assess a location dataset based on user-defined parameters to identify clusters and their characteristics. These characteristics can then help to distinguish resting-site clusters from kill sites of their large (>50 kg) prey. We identified location clusters of an adult male wolf Canis lupus on Ellesmere Island, Nunavut, Canada in July 2009 and tracked him until he died in April 2010. Identifying location clusters was challenging because the collar only obtained two GPS locations per day (12 h apart). In July 2010, we searched 30 of 52 location-clusters we identified as kill/scavenge sites and found 17 of them as such, given they had muskox Ovibos moschatus or caribou Rangifer tarandus pearyi remains nearby. We also documented five wolf rendezvous sites, two den sites, and the wolf's death site to total 60 location-clusters in all. We used a two-step process in testing the R Package GPSeqClus (hereafter GPSeqClus ): (1) compare the number of clusters our method discerned with the number identified by the new algorithm, and (2) compare the number of biologically significant clusters (e.g. den sites, kill/feeding sites) we found with the number the new algorithm located. We made these tests with GPSeqClus by varying the search radius, number of days at a site, and minimum number of locations required for a cluster. GPSeqClus compared well to our technique, with the best sub-algorithm among the 25 we tested only missing three of our identified clusters and yielding six additional clusters. GPSeqClus identified 16 of the 17 confirmed sites of remains, all wolf home sites, and the wolf's carcass site. Identifying clusters using a 500-m search radius, a 1.5-day window, and a minimum of two GPS locations per cluster was suitable for a coarse GPS acquisition rate of two locations per day when prey are large, such as muskox or caribou. Given that GPSeqClus performed well with our coarse location dataset, we expect it will also perform even better with a collar acquiring more than two locations per day. Having a field-tested utility such as GPSeqClus will enhance carnivore predation studies elsewhere.

Ecological Solutions and Evidence↗
USGS2013

Animal migration and risk of spread of viral infections

The potential contribution of migration towards the spread of disease is as varied as the ecology of the pathogens themselves and their host populations. This chapter outlines multiple examples of viral diseases in animal populations and their mechanisms of viral spread. Many species of insects, mammals, fish, and birds exhibit migratory behavior and have the potential to disperse diseases over long distances. The majority of studies available on viral zoonoses have focused on birds and bats, due to their highly migratory life histories. A number of studies have reported evidence of changes in the timing of animal migrations in response to climate change. The majority indicate an advancement of spring migration, with few or inconclusive results for fall migration. Predicting the combined effects of climate change on migratory patterns of host species and epidemiology of viral pathogens is complex and not fully realistic.

Book chapter↗
USGS2024

Treed Gaussian processes for animal movement modeling

Wildlife telemetry data may be used to answer a diverse range of questions relevant to wildlife ecology and management. One challenge to modeling telemetry data is that animal movement often varies greatly in pattern over time, and current continuous-time modeling approaches to handle such nonstationarity require bespoke and often complex models that may pose barriers to practitioner implementation. We demonstrate a novel application of treed Gaussian process (TGP) modeling, a Bayesian machine learning approach that automatically captures the nonstationarity and abrupt transitions present in animal movement. The machine learning formulation of TGPs enables modeling to be nearly automated, while their Bayesian formulation allows for the derivation of movement descriptors with associated uncertainty measures. We demonstrate the use of an existing R package to implement TGPs using the familiar Markov chain Monte Carlo algorithm. We then use estimated movement trajectories to derive movement descriptors that can be compared across individuals and populations. We applied the TGP model to a case study of lesser prairie-chickens ( Tympanuchus pallidicinctus ) to demonstrate the benefits of TGP modeling and compared distance traveled and residence times across lesser prairie-chicken individuals and populations. For broad usability, we outline all steps necessary for practitioners to specify relevant movement descriptors (e.g., turn angles, speed, contact points) and apply TGP modeling and trajectory comparison to their own telemetry datasets. Combining the predictive power of machine learning and the statistical inference of Bayesian methods to model movement trajectories allows for the estimation of statistically comparable movement descriptors from telemetry studies. Our use of an accessible R package allows practitioners to model trajectories and estimate movement descriptors, facilitating the use of telemetry data to answer applied management questions.

Ecology and Evolution↗
USGS1991

The Detroit River: Effects of contaminants and human activities on aquatic plants and animals and their habitats

Despite the extensive urbanization of its watershed, the Detroit River still supports diverse fish and wildlife populations. Conflicting uses of the river for waste disposal, water withdrawals, shipping, recreation, and fishing require innovative management. Chemicals added by man to the Detroit River have adversely affected the health and habitats of the river's plants and animals. In 1985, as part of an Upper Great Lakes Connecting Channels Study sponsored by Environment Canada and the U.S. Environmental Protection Agency, researchers exposed healthy bacteria, plankton, benthic macroinvertebrates, fish, and birds to Detroit River sediments and sediment porewater. Negative impacts included genetic mutations in bacteria; death of macroinvertebrates; accumulation of contaminants in insects, clams, fish, and ducks; and tumor formation in fish. Field surveys showed areas of the river bottom that were otherwise suitable for habitation by a variety of plants and animals were contaminated with chlorinated hydrocarbons and heavy metals and occupied only by pollution-tolerant worms. Destruction of shoreline wetlands and disposal of sewage and toxic substances in the Detroit River have reduced habitat and conflict with basic biological processes, including the sustained production of fish and wildlife. Current regulations do not adequately control pollution loadings. However, remedial actions are being formulated by the U.S. and Canada to restore degraded benthic habitats and eliminate discharges of toxic contaminants into the Detroit River.

Hydrobiologia↗
USGS2014

Standardized phenology monitoring methods to track plant and animal activity for science and resource management applications

Phenology offers critical insights into the responses of species to climate change; shifts in species’ phenologies can result in disruptions to the ecosystem processes and services upon which human livelihood depends. To better detect such shifts, scientists need long-term phenological records covering many taxa and across a broad geographic distribution. To date, phenological observation efforts across the USA have been geographically limited and have used different methods, making comparisons across sites and species difficult. To facilitate coordinated cross-site, cross-species, and geographically extensive phenological monitoring across the nation, the USA National Phenology Network has developed in situ monitoring protocols standardized across taxonomic groups and ecosystem types for terrestrial, freshwater, and marine plant and animal taxa. The protocols include elements that allow enhanced detection and description of phenological responses, including assessment of phenological “status”, or the ability to track presence–absence of a particular phenophase, as well as standards for documenting the degree to which phenological activity is expressed in terms of intensity or abundance. Data collected by this method can be integrated with historical phenology data sets, enabling the development of databases for spatial and temporal assessment of changes in status and trends of disparate organisms. To build a common, spatially, and temporally extensive multi-taxa phenological data set available for a variety of research and science applications, we encourage scientists, resources managers, and others conducting ecological monitoring or research to consider utilization of these standardized protocols for tracking the seasonal activity of plants and animals.

International Journal of Biometeorology↗
USGS2014

Fitness in animals correlates with proximity to discontinuities in body mass distributions.

Discontinuous structure in landscapes may cause discontinuous, aggregated species body-mass patterns, reflecting the scales of structure available to animal communities within a landscape. Empirical analyses have shown that the location of species within body mass aggregations, which reflect this scale-specific organization, is non-random with regard to several ecological phenomena, including species extinctions. The propensity of declining species to have body masses proximate to discontinuities suggests that transition zones between scaling regimes ultimately decreases the ecological fitness for some species. We test this proposition using vulnerable and unthreatened fish species in Mediterranean streams with differing levels of human impact. We show that the proximity to discontinuities in body mass aggregations (“distance-to-edge”) of more vs. less fit individuals within vulnerable and unthreatened populations differs. Specifically, regression analysis between the scaled mass index, a proxy of animal fitness, and distance-to-edge reveals negative and positive relationships for vulnerable and unthreatened species, respectively. That is, fitness is higher close to discontinuities in vulnerable populations and toward the center of body mass aggregation groups in unthreatened populations. Our results demonstrate the suitability of the discontinuity framework for scrutinizing non-random patterns of environmental impact in populations. Further exploration of the usefulness of this method across other ecosystems and organism groups is warranted.

Ecological Complexity↗
USGS2005

Animating the biodynamics of soil thickness using process vector analysis: A dynamic denudation approach to soil formation

This paper expands the dynamic denudation framework of landscape evolution by providing new process insights and details on how soil and its signature morphological feature, the biomantle, form and function in the environment. We examine soils and their biomantles from disparate parts of the world, from the tropics through midlatitudes and hyperarid through perhumid, a range that exhibits varying environments for, and of, life. We then explicate the process pathways that cause soils to thicken and thin, and to even disappear, then reform. We do this by examining thickness relationships, where soil thickness stand biomantle thickness bt are functions of upbuilding u and deepening d minus removal r processes, hence st/bt=f(u+d-r). Upbuilding has two subsets, u1, which includes all exogenous (allochthonous-outside) mineral and/or organic inputs to the soil system, and u2, which includes all endogenous (autochthonous-in situ) processes and productions, including weathering. Exogenous u1 inputs include eolian and slopewash inputs (sedimentations) of mineral and organic materials, mass wasting accumulations and the like. Endogenous u2 processes and productions include the sum of in situ bioturbations, biosynthetic productions, organic accumulations, biovoid productions, weathering and volume increases caused by their sum. Endogenous upbuildings, which dominantly occur in the biomantle, are basically biodynamic bd processes and productions, hence u2=bd. Therefore, if exogenous upbuildings u1 are minimal or zero, then biomantle thickness bt is expressed by bt=f(u2-r) or bt=f(bd-r). Drawing on these relationships, we employ a graphic-conceptual device called process vector analysis in a digital animation (see supplementary materials or cf. https://netfiles.uiuc.edu/jdomier/www/temp/ biomantle.html) that illustrates the main pathways that form both Earth's soil and its unique epidermis, the biomantle. We then discuss the main elements of the animation using still frames that represent thickness turning points. We end by encouraging researchers, instructors and students to view Earth's landforms and soils as integrated dynamic entities that are constantly coevolving elements of a global subaerial-subaqueous continuum. ?? 2004 Elsevier B.V. All rights reserved.

Geomorphology↗
USGS2018

Foraging and fasting can influence contaminant concentrations in animals: an example with mercury contamination in a free-ranging marine mammal

Large fluctuations in animal body mass in relation to life-history events can influence contaminant concentrations and toxicological risk. We quantified mercury concentrations in adult northern elephant seals (Mirounga angustirostris) before and after lengthy at sea foraging trips (n = 89) or fasting periods on land (n = 27), and showed that mercury concentrations in blood and muscle changed in response to these events. The highest blood mercury concentrations were observed after the breeding fast, whereas the highest muscle mercury concentrations were observed when seals returned to land to moult. Mean female blood mercury concentrations decreased by 30% across each of the two annual foraging trips, demonstrating a foraging-associated dilution of mercury concentrations as seals gained mass. Blood mercury concentrations increased by 103% and 24% across the breeding and moulting fasts, respectively, demonstrating a fasting-associated concentration of mercury as seals lost mass. In contrast to blood, mercury concentrations in female's muscle increased by 19% during the post-breeding foraging trip and did not change during the post-moulting foraging trip. While fasting, female muscle mercury concentrations increased 26% during breeding, but decreased 14% during moulting. Consequently, regardless of exposure, an animal's contaminant concentration can be markedly influenced by their annual life-history events.

Proceedings of the Royal Society B↗
USGS2018

The ecology of movement and behaviour: a saturated tripartite network for describing animal contacts

Ecologists regularly use animal contact networks to describe interactions underlying pathogen transmission, gene flow, and information transfer. However, empirical descriptions of contact often overlook some features of individual movement, and decisions about what kind of network to use in a particular setting are commonly ad hoc . Here, we relate individual movement trajectories to contact networks through a tripartite network model of individual, space, and time nodes. Most networks used in animal contact studies (e.g. individual association networks, home range overlap networks, and spatial networks) are simplifications of this tripartite model. The tripartite structure can incorporate a broad suite of alternative ecological metrics like home range sizes and patch occupancy patterns into inferences about contact network metrics such as modularity and degree distribution. We demonstrate the model's utility with two simulation studies using alternative forms of ecological data to constrain the tripartite network's structure and inform expectations about the harder-to-measure metrics related to contact.

Proceedings of the Royal Society B: Biological Sci↗
USGS2014

A reference system for animal biometrics: application to the northern leopard frog

Reference systems and public databases are available for human biometrics, but to our knowledge nothing is available for animal biometrics. This is surprising because animals are not required to give their agreement to be in a database. This paper proposes a reference system and database for the northern leopard frog (Lithobates pipiens). Both are available for reproducible experiments. Results of both open set and closed set experiments are given.

Conference Paper↗
USGS2021

Behavioral state-dependent habitat selection and implications for animal translocations

Post-release monitoring of translocated animals is often used to inform future translocation protocols. Quantifying habitat selection of translocated individuals may help identify features that characterize good settlement habitat and thus inform the choice of future release sites. However, translocated animals often undergo post-release behavioural modification, and their habitat selection may vary depending on the underlying behavioural state. To investigate this, we analysed behavioural state-dependent habitat selection in female greater sage-grouse Centrocercus urophasianus translocated from Wyoming to North Dakota, USA, using Hidden Markov Models combined with Integrated Step Selection Analysis. We segmented individual trajectories into behavioural phases corresponding to an exploratory state, characterized by broad and directed movements, and a restricted state, characterized by short and tortuous movements. Then, we quantified habitat selection in each state while accounting for seasonality and individual reproductive status. While in the exploratory state, sage-grouse exhibited natal habitat preference induction by selecting for high sagebrush cover, which is typical of their natal area in Wyoming but not of the release area in North Dakota. In the restricted state, sage-grouse selected for gentle topography and also adjusted their habitat selection to constraints imposed by seasonality and reproductive needs by selecting for high herbaceous cover during brood rearing. Synthesis and applications . Habitat selection of translocated sage-grouse differed between the post-release exploration and the settlement phase. Features selected after settling, not during exploration, are likely indicative of suitable settlement habitat. Our results suggest that areas characterized by gentle topography and high herbaceous cover are well-suited as release sites for sage-grouse translocated during the summer, especially brood-rearing females, and that sagebrush cover may not be a critical factor in determining the appropriateness of release sites for sage-grouse in North Dakota. Our findings highlight the need to consider behaviour when using habitat selection estimates to inform the choice of future release sites.

North Dakota, Wyoming↗
USGS2012

Representing the acquisition and use of energy by individuals in agent-based models of animal populations

1. Agent-based models (ABMs) are widely used to predict how populations respond to changing environments. As the availability of food varies in space and time, individuals should have their own energy budgets, but there is no consensus as to how these should be modelled. Here, we use knowledge of physiological ecology to identify major issues confronting the modeller and to make recommendations about how energy budgets for use in ABMs should be constructed. 2. Our proposal is that modelled animals forage as necessary to supply their energy needs for maintenance, growth and reproduction. If there is sufficient energy intake, an animal allocates the energy obtained in the order: maintenance, growth, reproduction, energy storage, until its energy stores reach an optimal level. If there is a shortfall, the priorities for maintenance and growth/reproduction remain the same until reserves fall to a critical threshold below which all are allocated to maintenance. Rates of ingestion and allocation depend on body mass and temperature. We make suggestions for how each of these processes should be modelled mathematically. 3. Mortality rates vary with body mass and temperature according to known relationships, and these can be used to obtain estimates of background mortality rate. 4. If parameter values cannot be obtained directly, then values may provisionally be obtained by parameter borrowing, pattern-oriented modelling, artificial evolution or from allometric equations. 5. The development of ABMs incorporating individual energy budgets is essential for realistic modelling of populations affected by food availability. Such ABMs are already being used to guide conservation planning of nature reserves and shell fisheries, to assess environmental impacts of building proposals including wind farms and highways and to assess the effects on nontarget organisms of chemicals for the control of agricultural pests.

Methods in Ecology and Evolution↗
USGS2023

Positioning aquatic animals with acoustic transmitters

Geolocating aquatic animals with acoustic tags has been ongoing for decades, relying on the detection of acoustic signals at multiple receivers with known positions to calculate a 2D or 3D position, and ultimately recreate the path of an aquatic animal from detections at fixed stations. This method of underwater geolocation is evolving with new software and hardware options available to help investigators design studies and calculate positions using solvers based predominantly on time-difference-of-arrival and time-of-arrival. We provide an overview of the considerations necessary to implement positioning in aquatic acoustic telemetry studies, including how to design arrays of receivers, test performance, synchronize receiver clocks and calculate positions from the detection data. We additionally present some common positioning algorithms, including both the free open-source solvers and the ‘black-box’ methods provided by some manufacturers for calculating positions. This paper is the first to provide a comprehensive overview of methods and considerations for designing and implementing better positioning studies that will support users, and encourage further knowledge advances in aquatic systems.

Methods in Ecology and Evolution↗
USGS2008

Modeling unobserved sources of heterogeneity in animal abundance using a Dirichlet process prior

In surveys of natural populations of animals, a sampling protocol is often spatially replicated to collect a representative sample of the population. In these surveys, differences in abundance of animals among sample locations may induce spatial heterogeneity in the counts associated with a particular sampling protocol. For some species, the sources of heterogeneity in abundance may be unknown or unmeasurable, leading one to specify the variation in abundance among sample locations stochastically. However, choosing a parametric model for the distribution of unmeasured heterogeneity is potentially subject to error and can have profound effects on predictions of abundance at unsampled locations. In this article, we develop an alternative approach wherein a Dirichlet process prior is assumed for the distribution of latent abundances. This approach allows for uncertainty in model specification and for natural clustering in the distribution of abundances in a data-adaptive way. We apply this approach in an analysis of counts based on removal samples of an endangered fish species, the Okaloosa darter. Results of our data analysis and simulation studies suggest that our implementation of the Dirichlet process prior has several attractive features not shared by conventional, fully parametric alternatives. ?? 2008, The International Biometric Society.

Biometrics↗
USGS2017

Quantifying animal movement for caching foragers: the path identification index (PII) and cougars, Puma concolor

Relocation studies of animal movement have focused on directed versus area restricted movement, which rely on correlations between step-length and turn angles, along with a degree of stationarity through time to define behavioral states. Although these approaches may work well for grazing foraging strategies in a patchy landscape, species that do not spend a significant amount of time searching out and gathering small dispersed food items, but instead feed for short periods on large, concentrated sources or cache food result in movements that maybe difficult to analyze using turning and velocity alone. We use GPS telemetry collected from a prey-caching predator, the cougar (Puma concolor), to test whether adding additional movement metrics capturing site recursion, to the more traditional velocity and turning, improve the ability to identify behaviors. We evaluated our movement index’s ability to identify behaviors using field investigations. We further tested for statistical stationarity across behaviors for use of topographic view-sheds. We found little correlation between turn angle, velocity, tortuosity, and site fidelity and combined them into a movement index used to identify movement paths (temporally autocorrelated movements) related to fast directed movements (taxis), area restricted movements (search), and prey caching (foraging). Changes in the frequency and duration of these movements were helpful for identifying seasonal activities such as migration and denning in females. Comparison of field investigations of cougar activities to behavioral classes defined using the movement index and found an overall classification accuracy of 81%. Changes in behaviors resulted in changes in how cougars used topographic view-sheds, showing statistical non-stationarity over time. The movement index shows promise for identifying behaviors in species that frequently return to specific locations such as food caches, watering holes, or dens, and highlights the role memory and cognitive abilities may play in determining animal movements. With the addition of measures capturing site recursion the temporal structure in movements of a caching forager was revealed.

Movement Ecology↗
USGS2021

Caution is warranted when using animal space-use and movement to infer behavioral states

Background Identifying the behavioral state for wild animals that can’t be directly observed is of growing interest to the ecological community. Advances in telemetry technology and statistical methodologies allow researchers to use space-use and movement metrics to infer the underlying, latent, behavioral state of an animal without direct observations. For example, researchers studying ungulate ecology have started using these methods to quantify behaviors related to mating strategies. However, little work has been done to determine if assumed behaviors inferred from movement and space-use patterns correspond to actual behaviors of individuals. Methods Using a dataset with male and female white-tailed deer location data, we evaluated the ability of these two methods to correctly identify male-female interaction events (MFIEs). We identified MFIEs using the proximity of their locations in space as indicators of when mating could have occurred. We then tested the ability of utilization distributions (UDs) and hidden Markov models (HMMs) rendered with single sex location data to identify these events. Results For white-tailed deer, male and female space-use and movement behavior did not vary consistently when with a potential mate. There was no evidence that a probability contour threshold based on UD volume applied to an individual’s UD could be used to identify MFIEs. Additionally, HMMs were unable to identify MFIEs, as single MFIEs were often split across multiple states and the primary state of each MFIE was not consistent across events. Conclusions Caution is warranted when interpreting behavioral insights rendered from statistical models applied to location data, particularly when there is no form of validation data. For these models to detect latent behaviors, the individual needs to exhibit a consistently different type of space-use and movement when engaged in the behavior. Unvalidated assumptions about that relationship may lead to incorrect inference about mating strategies or other behaviors.

Movement Ecology↗