Search USGS⌕ Search

SEARCH · Search USGS

Results for “Animals”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2Linked to original sources
USGS2012

Prevalence, environmental loading, and molecular characterization of Cryptosporidium and Giardia</i isolates from domestic and wild animals along the Central California Coast

The risk of disease transmission from waterborne protozoa is often dependent on the origin (e.g., domestic animals versus wildlife), overall parasite load in contaminated waterways, and parasite genotype, with infections being linked to runoff or direct deposition of domestic animal and wildlife feces. Fecal samples collected from domestic animals and wildlife along the central California coast were screened to (i) compare the prevalence and associated risk factors for fecal shedding of Cryptosporidium and Giardia species parasites, (ii) evaluate the relative importance of animal host groups that contribute to pathogen loading in coastal ecosystems, and (iii) characterize zoonotic and host-specific genotypes. Overall, 6% of fecal samples tested during 2007 to 2010 were positive for Cryptosporidium oocysts and 15% were positive for Giardia cysts. Animal host group and age class were significantly associated with detection of Cryptosporidium and Giardia parasites in animal feces. Fecal loading analysis revealed that infected beef cattle potentially contribute the greatest parasite load relative to other host groups, followed by wild canids. Beef cattle, however, shed host-specific, minimally zoonotic Cryptosporidium and Giardia duodenalis genotypes, whereas wild canids shed potentially zoonotic genotypes, including G. duodenalis assemblages A and B. Given that the parasite genotypes detected in cattle were not zoonotic, the public health risk posed by protozoan parasite shedding in cattle feces may be lower than that posed by other animals, such as wild canids, that routinely shed zoonotic genotypes.

California↗
USGS2015

Using spatiotemporal statistical models to estimate animal abundance and infer ecological dynamics from survey counts

Ecologists often fit models to survey data to estimate and explain variation in animal abundance. Such models typically require that animal density remains constant across the landscape where sampling is being conducted, a potentially problematic assumption for animals inhabiting dynamic landscapes or otherwise exhibiting considerable spatiotemporal variation in density. We review several concepts from the burgeoning literature on spatiotemporal statistical models, including the nature of the temporal structure (i.e., descriptive or dynamical) and strategies for dimension reduction to promote computational tractability. We also review several features as they specifically relate to abundance estimation, including boundary conditions, population closure, choice of link function, and extrapolation of predicted relationships to unsampled areas. We then compare a suite of novel and existing spatiotemporal hierarchical models for animal count data that permit animal density to vary over space and time, including formulations motivated by resource selection and allowing for closed populations. We gauge the relative performance (bias, precision, computational demands) of alternative spatiotemporal models when confronted with simulated and real data sets from dynamic animal populations. For the latter, we analyze spotted seal ( Phoca largha ) counts from an aerial survey of the Bering Sea where the quantity and quality of suitable habitat (sea ice) changed dramatically while surveys were being conducted. Simulation analyses suggested that multiple types of spatiotemporal models provide reasonable inference (low positive bias, high precision) about animal abundance, but have potential for overestimating precision. Analysis of spotted seal data indicated that several model formulations, including those based on a log-Gaussian Cox process, had a tendency to overestimate abundance. By contrast, a model that included a population closure assumption and a scale prior on total abundance produced estimates that largely conformed to our a priori expectation. Although care must be taken to tailor models to match the study population and survey data available, we argue that hierarchical spatiotemporal statistical models represent a powerful way forward for estimating abundance and explaining variation in the distribution of dynamical populations.

Ecological Monographs↗
USGS2004

An animal location-based habitat suitability model for bighorn sheep and wild horses in Bighorn Canyon National Recreation Area and the Pryor Mountain Wild Horse Range, Montana, and Wyoming

The purpose of this habitat suitability model is to provide a tool that will help managers and researchers better manage bighorn sheep and wild horses in the Bighorn Canyon National Recreation Area (BICA) and Pryor Mountain Wild Horse Range (PMWHR). A concern in the management of the Pryor Mountain wild horse population is whether or not the wild horses compete with bighorn sheep for available forage or available space. Two studies have been conducted that have shown no obvious, convincing competition between the two species. A study of diets and habitat-use of both species revealed substantial diet overlap only during some seasons, but there were considerable spatial and habitat separations between wild horses and bighorns during all seasons (Kissell and others, 1996). This empirical data was then used in a modeling exercise that predicted that neither the current (about 160 horses at the time of the analysis) nor larger numbers of wild horses on the area (e.g., about 200 horses) would result in reduced numbers or condition of bighorn sheep (Coughenour 1999). But competition is a very complex biological process to document. Bighorns might have already been spatially avoiding wild horses when these studies were conducted. A second concern for managers is that earlier studies suggest both species are not using many areas of the range that appear to be suitable (Gudorf and others, 1996; Kissell and others, 1996). A primary goal for the management of both species is to increase their numbers for purposes of genetic conservation and viability. The bighorn sheep population declined during the mid-1990’s from a peak of about 211 animals to ~ 100 animals at present. Absolute minimum goals for genetic viability in the bighorn sheep herd (genetic effective population size of N >50) suggest at least 150 animals should be present, while studies of persistence suggest populations of 250+ are e more likely to recover rapidly and persist should the population experience an epizootic die-off (Singer and others, 2001). Since all bighorn sheep populations are potentially vulnerable to disease epizootics, managing for larger populations of 200–300 animals appears to increase the potential for long-term persistence (Berger, 1990; Singer and others, 2001). Wild horses are not prone to rapid disease die-offs. However, minimum goals for genetic viability in the Pryor Mountain wild horses ( Ne > 50) require that at least 160 animals be present on the range (Singer and others, 2000). Since the Ne > 50 goal is set for the breeding of domestic animals, and since the vagaries of drought, severe winters, predation, and other stochastic events cause stress in wild animals, larger goals for Ne (e.g. Ne > 100) for wild horses are even more desirable (USDI, BLM, 1999; Gross, 2000). Expanding the area of the wild horse range is one option, but the prospects for expanding the range do not appear to be great (L. Coates-Markle, BLM, oral comm.). A second option would be to increase the amount of useable habitat for horses on the existing range. One goal of this modeling effort was to use GIS-based habitat analyses to determine the reason wild horses are not using some areas of the range, and to explore the potential for making some of these areas useable. The National Park Service (NPS) has shown considerable interest in management actions within BICA that will increase the range, useable habitat, and population size of bighorn sheep. There has also been interest expressed by the Bureau of Land Management (BLM) and wild horse advocates to improve the useable habitat for wild horses and to possibly increase the size of the horse range.

Report↗
USGS2016

Temporal segmentation of animal trajectories informed by habitat use

Most animals live in seasonal environments and experience very different conditions throughout the year. Behavioral strategies like migration, hibernation, and a life cycle adapted to the local seasonality help to cope with fluctuations in environmental conditions. Thus, how an individual utilizes the environment depends both on the current availability of habitat and the behavioral prerequisites of the individual at that time. While the increasing availability and richness of animal movement data has facilitated the development of algorithms that classify behavior by movement geometry, changes in the environmental correlates of animal movement have so far not been exploited for a behavioral annotation. Here, we suggest a method that uses these changes in individual–environment associations to divide animal location data into segments of higher ecological coherence, which we term niche segmentation. We use time series of random forest models to evaluate the transferability of habitat use over time to cluster observational data accordingly. We show that our method is able to identify relevant changes in habitat use corresponding to both changes in the availability of habitat and how it was used using simulated data, and apply our method to a tracking data set of common teal (Anas crecca). The niche segmentation proved to be robust, and segmented habitat suitability outperformed models neglecting the temporal dynamics of habitat use. Overall, we show that it is possible to classify animal trajectories based on changes of habitat use similar to geometric segmentation algorithms. We conclude that such an environmentally informed classification of animal trajectories can provide new insights into an individuals' behavior and enables us to make sensible predictions of how suitable areas might be connected by movement in space and time.

Ecosphere↗
USGS2021

An integrated path for spatial capture–recapture and animal movement modeling

Ecologists and conservation biologists increasingly rely on spatial capture–recapture (SCR) and movement modeling to study animal populations. Historically, SCR has focused on population-level processes (e.g., vital rates, abundance, density, and distribution), whereas animal movement modeling has focused on the behavior of individuals (e.g., activity budgets, resource selection, migration). Even though animal movement is clearly a driver of population-level patterns and dynamics, technical and conceptual developments to date have not forged a firm link between the two fields. Instead, movement modeling has typically focused on the individual level without providing a coherent scaling from individual- to population-level processes, whereas SCR has typically focused on the population level while greatly simplifying the movement processes that give rise to the observations underlying these models. In our view, the integration of SCR and animal movement modeling has tremendous potential for allowing ecologists to scale up from individuals to populations and advancing the types of inferences that can be made at the intersection of population, movement, and landscape ecology. Properly accounting for complex animal movement processes can also potentially reduce bias in estimators of population-level parameters, thereby improving inferences that are critical for species conservation and management. This introductory article to the Special Feature reviews recent advances in SCR and animal movement modeling, establishes a common notation, highlights potential advantages of linking individual-level (Lagrangian) movements to population-level (Eulerian) processes, and outlines a general conceptual framework for the integration of movement and SCR models. We then identify important avenues for future research, including key challenges and potential pitfalls in the developments and applications that lie ahead.

Ecology↗
USGS2017

Imputation approaches for animal movement modeling

The analysis of telemetry data is common in animal ecological studies. While the collection of telemetry data for individual animals has improved dramatically, the methods to properly account for inherent uncertainties (e.g., measurement error, dependence, barriers to movement) have lagged behind. Still, many new statistical approaches have been developed to infer unknown quantities affecting animal movement or predict movement based on telemetry data. Hierarchical statistical models are useful to account for some of the aforementioned uncertainties, as well as provide population-level inference, but they often come with an increased computational burden. For certain types of statistical models, it is straightforward to provide inference if the latent true animal trajectory is known, but challenging otherwise. In these cases, approaches related to multiple imputation have been employed to account for the uncertainty associated with our knowledge of the latent trajectory. Despite the increasing use of imputation approaches for modeling animal movement, the general sensitivity and accuracy of these methods have not been explored in detail. We provide an introduction to animal movement modeling and describe how imputation approaches may be helpful for certain types of models. We also assess the performance of imputation approaches in two simulation studies. Our simulation studies suggests that inference for model parameters directly related to the location of an individual may be more accurate than inference for parameters associated with higher-order processes such as velocity or acceleration. Finally, we apply these methods to analyze a telemetry data set involving northern fur seals ( Callorhinus ursinus ) in the Bering Sea. Supplementary materials accompanying this paper appear online.

Journal of Agricultural, Biological, and Environme↗
USGS2007

Incidence of the enterococcal surface protein ( esp ) gene in human and animal fecal sources

The occurrence of the enterococcal surface protein ( esp ) gene in the opportunistic pathogens Enterococcus faecalis and E. faecium is well-documented in clinical research. Recently, the esp gene has been proposed as a marker of human pollution in environmental waters; however, information on its relative incidence in various human and animal fecal sources is limited. We have determined the occurrence of the esp gene in enterococci from human ( n = 64) and animal ( n = 233) fecal samples by polymerase chain reaction using two primer sets: one presumably specific for E. faecium ( esp fm ) and the other for both E. faecalis and E. faecium ( esp fs/fm ). We believe that this research is the first to explore the use of esp fs/fm for the detection of human waste in natural environmental settings. The incidence in human sources was 93.1% esp fm and 100% esp fs/fm in raw sewage influent; 30% for both esp fm and esp fs/fm in septic waste; and 0% esp fm and 80% esp fs/fm in active pit toilets. The overall occurrence of the gene in animal feces was 7.7% ( esp fs/fm ) and 4.7% ( esp fm ); animal types with positive results included dogs (9/43, all esp fm ), gulls (10/34, esp fs/fm ; 2/34, esp fm ), mice (3/22, all esp fs/fm ), and songbirds (5/55, all esp fs/fm ). The esp gene was not detected in cat (0/34), deer (0/4), goose (0/18), or raccoon (0/23) feces. The inconsistent occurrence, especially in septic and pit toilet sewage, suggests a low statistical power of discrimination between animal and human sources, which means a large number of replicates should be collected. Both esp fm and esp fs/fm were common in raw sewage, but neither one efficiently differentiated between animal and other human sources.

Environmental Science & Technology↗
USGS2024

Estimation of contact time among animals from telemetry data

Continuous processes in most applications are measured discretely with error. This complicates the task of detecting intersections and the number of intersections between two continuous processes (i.e., when the processes have the same value). Intersections of continuous processes are scientifically important but challenging to estimate from data. For example, in the field of animal ecology, intersections of the paths of moving animals tracked with satellite technologies can be used to understand disease transmission. We illustrate how to quantify contact between animals using telemetry data (i.e., the recorded locations of an animal over time). We introduce our method to quantify contact time with accessible concepts from introductory stochastic process literature, such as Brownian motion. Then, we provide two data examples using white-tailed deer ( Odocoileus virginianus ) and mule deer ( Odocoileus hemionus) telemetry data in a region with high prevalence of chronic wasting disease. Our work provides a needed connection between existing model-based literature for animal movement and rule-based literature for animal interaction. Further, our work illustrates a unique statistical problem receiving minimal attention with broad applicability in human and livestock tracking.

The American Statistician↗
USGS2016

Teaching animal habitat selection using wildlife tracking equipment

We present a hands-on outdoor activity coupled with classroom discussion to teach students about wildlife habitat selection, the process by which animals choose where to live. By selecting locations or habitats with many benefits (e.g., food, shelter, mates) and few costs (e.g., predators), animals improve their ability to survive and reproduce. Biologists track animal movement using radio telemetry technology to study habitat selection so they can better provide species with habitats that promote population growth. We present a curriculum in which students locate “animals” (transmitters) using radio telemetry equipment and apply math skills (use of fractions and percentages) to assess their “animal's” habitat selection by comparing the availability of habitat types with the proportion of “animals” they find in each habitat type.

Science Activities↗
USGS2018

Animal movement models for migratory individuals and groups

Animals often exhibit changes in their behaviour during migration. Telemetry data provide a way to observe geographic position of animals over time, but not necessarily changes in the dynamics of the movement process. Continuous‐time models allow for statistical predictions of the trajectory in the presence of measurement error and during periods when the telemetry device did not record the animal's position. However, continuous‐time models capable of mimicking realistic trajectories with sufficient detail are computationally challenging to fit to large datasets. Furthermore, basic continuous‐time model specifications (e.g. Brownian motion) lack realism in their ability to capture nonstationary dynamics. We present a unified class of animal movement models that are computationally efficient and provide a suite of approaches for accommodating nonstationarity in continuous trajectories due to migration and interactions among individuals. Our approach uses process convolutions to allow for flexibility in the movement process while facilitating implementation and incorporating location uncertainty. We show how to nest convolution models to incorporate interactions among migrating individuals to account for nonstationarity and provide inference about dynamic migratory networks. We demonstrate these approaches in two case studies involving migratory birds. Specifically, we used process convolution models with temporal deformation to account for heterogeneity in individual greater white‐fronted goose migrations in Europe and Iceland, and we used nested process convolutions to model dynamic migratory networks in sandhill cranes in North America. The approach we present accounts for various forms of temporal heterogeneity in animal movement and is not limited to migratory applications. Furthermore, our models rely on well‐established principles for modelling‐dependent data and leverage modern approaches for modelling dynamic networks to help explain animal movement and social interaction.

Methods in Ecology and Evolution↗
USGS2022

A review of supervised learning methods for classifying animal behavioural states from environmental features

Accurately predicting behavioural modes of animals in response to environmental features is important for ecology and conservation. Supervised learning (SL) methods are increasingly common in animal movement ecology for classifying behavioural modes. However, few examples exist of applying SL to classify polytomous animal behaviour from environmental features especially in the context of millions of animal observations. We review SL methods (weighted k -nearest neighbours; neural nets; random forests; and boosted classification trees with XGBoost) for classifying polytomous animal behaviour from environmental predictors. We also describe tuning parameter selection and assessment strategies, approaches for visualizing relationships between predictors and class outputs, and computational considerations. We demonstrate these methods by predicting three categories of risk to bald eagles from colliding with wind turbines using, as predictors, 12 environmental state features associated with 1.7 million GPS telemetry data points from 57 eagles. Of the SL methods we considered, XGBoost yielded the most accurate model with 86.2% classification accuracy and pairwise-averaged area under the ROC curve of 90.6. Computational time of XGBoost scaled better to large data than any other SL method. We also show how SHAP values integrated in the R package ( xgboost ) facilitate investigation of variable relationships and importance. For big data applications, XGBoost appears to provide superior classification accuracy and computational efficiency. Our results suggest XGBoost should be considered as an early modelling option in situations where the intent is to classify millions of animal behaviour observations from environmental predictors and to understand relationships between those predictors and movement behaviours. We also offer a tutorial to assist researchers in implementing this method.

Methods in Ecology and Evolution↗
USGS2014

When to be discrete: The importance of time formulation in understanding animal movement

Animal movement is essential to our understanding of population dynamics, animal behavior, and the impacts of global change. Coupled with high-resolution biotelemetry data, exciting new inferences about animal movement have been facilitated by various specifications of contemporary models. These approaches differ, but most share common themes. One key distinction is whether the underlying movement process is conceptualized in discrete or continuous time. This is perhaps the greatest source of confusion among practitioners, both in terms of implementation and biological interpretation. In general, animal movement occurs in continuous time but we observe it at fixed discrete-time intervals. Thus, continuous time is conceptually and theoretically appealing, but in practice it is perhaps more intuitive to interpret movement in discrete intervals. With an emphasis on state-space models, we explore the differences and similarities between continuous and discrete versions of mechanistic movement models, establish some common terminology, and indicate under which circumstances one form might be preferred over another. Counter to the overly simplistic view that discrete- and continuous-time conceptualizations are merely different means to the same end, we present novel mathematical results revealing hitherto unappreciated consequences of model formulation on inferences about animal movement. Notably, the speed and direction of movement are intrinsically linked in current continuous-time random walk formulations, and this can have important implications when interpreting animal behavior. We illustrate these concepts in the context of state-space models with multiple movement behavior states using northern fur seal ( Callorhinus ursinus ) biotelemetry data.

Movement Ecology↗
USGS1965

Effects of field applications of heptachlor on bobwhite quail and other wild animals

A study of the effects of field applications of heptachlor on bobwhite quail ( Colinus uirginianus ) and other animals was conducted on three similar areas, two in Decatur County, Georgia, and one in Escambia County, Alabama, from February, 1958, to March, 1962. Heptachlor in granules was applied by aircraft on the Georgia areas for eradication of the imported fire ant ( Solenopsis saevissima ). Applications were directed by personnel of the U. S. Department of Agriculture, Plant Pest Control Division. The Alabama area remained untreated. Transects where whistling cocks were counted were superimposed on areas where coveys were counted. Size of areas varied from 14,000 to 20,000 acres. Each area had six transects, totaling 11,000 acres. Whistling cock bobwhites and coveys averaged 28 and 20 per 1,000 acres, respectively, the year before treatment on a Georgia area, and cocks and coveys averaged 25 per 1,000 acres for the duration of the study on the untreated Alabama area. Where portions of an area were treated at 2 pounds of heptachlor per acre, whistling cocks and coveys were reduced significantly, with a greater reduction where a greater amount of land was treated on the area or its transects. A decline of cocks and coveys also followed 1/2-pound applications (approaching statistical significance for coveys). Three years after treatment, cock and covey numbers were below those recorded before treatment. Whistling cocks and coveys also declined on adjoining land which remained untreated (significant for cocks, approaching significance for coveys). This decline was attributed to movements of bobwhites from untreated land to repopulate treated land. There is evidence that some loss occurred in bobwhites after they moved from untreated to treated land; the decrease in each instance was ascribed to the application of heptachlor. Songbirds were listed on the two Georgia areas. The first summer, eight more species and 458 more individuals of permanent resident birds were listed on the untreated area than on the treated area. After half of the originally untreated area was treated with heptachlor at 2 pounds per acre the following winter, the number of resident birds declined 37 percent. Some species of summer resident birds could not be found on treated land after heptachlor was applied. A small plot of 4 acres was intensively searched for dead and dying animals, and observations were made on living animals. Forty-seven days after treatment, no live animals were seen or heard on the plot, and a total of 38 dead animals had been found. Soils were sampled twice after treatment, and residues had declined in the second lot of samples. Twice animals also were obtained for analysis, and residues declined in the second group. Numbers of birds increased in the same period.

Alabama, Georgia↗
USGS2020

Evaluating contributions of recent tracking-based animal movement ecology to conservation management

The use of animal-born sensors for location-based tracking and bio-logging in terrestrial systems has expanded dramatically in the past 10 years. This rapid expansion has generated new data on how animals interact with and respond to variation in their environment, resulting in important ecological, physiological, and evolutionary insights. Although understanding the finer details of animal locations has important management relevance, applied studies are not prominent in the movement ecology literature. This is despite the long history of applied studies of animal movement and the urgent and growing need for evidence-based conservation guidance, especially in the challenging field of human-wildlife interactions. The goal of this review is to evaluate the realized contribution of tracking-based animal movement ecology to solving specific conservation problems, and to identify barriers that may hinder expansion of that contribution. To do this, we (a) briefly review the history and technologies used in animal tracking and bio-logging, (b) use a series of literature searches to evaluate the frequency with which movement ecology studies are designed to solve specific conservation problems, and (c) use this information to identify challenges that may limit the applied relevance of the field of movement ecology, and to propose pathways to expand that applied relevance. Our literature review quantifies the limited extent to which research in the field of movement ecology is designed to solve specific conservation problems, but also the fact that such studies are slowly becoming more prevalent. We discuss how barriers that limit application of these principles are likely due to constraints imposed by the types of data used commonly in the field. Problems of scale mismatch, error compounding, and data paucity all create challenges that are relevant to the field of movement ecology but may be especially pertinent in applied situations. Finding solutions to these problems will create new opportunity for movement ecologists to contribute to conservation science.

Frontiers in Ecology and Evolution↗
USGS2001

Critical habitat for ovigerous Dungeness crabs

The Dungeness crab, Cancer magister , supports an important fishery in the northeastern Pacific Ocean, yet there is limited knowledge of ovigerous female brooding locations and brooding behavior. Our earlier research suggests that ovigerous crabs aggregate at the same brooding locations for many years. Within these locations, ovigerous females occur in high densities, with the majority of the aggregation buried within the sediment. These locations often have similar water depths and sediment types and appear to be critical for this life history stage. Our study was designed to examine the bathymetric distribution of Dungeness crabs in bays with and without sea otters at eight locations within the Glacier Bay area by conducting transects with a video-equipped manned submersible. Two of the bays investigated contained large aggregations of ovigerous females. At both sites the substrate was composed primarily of sand. However, only a small percentage of the 33 km of transects were classified as sand. These data suggest that sand substrate may be a limiting resource. Since crab brooding aggregations represent a large portion of the crab population within a small area, and because they are a critical component of Dungeness life history, areas with these characteristics need to be investigated, mapped, and protected from development or exploitation. The areas requiring protection from the impact of anthropogenic wastes, fishing, and logging activities could be quite small, thus limiting conflict with alternative users.

Conference Paper↗
USGS2025

Animal trajectory imputation and uncertainty quantification via deep learning

Imputing missing data in animal trajectories is crucial for understanding animal movements during unobserved periods. However, the traditional methods, such as linear interpolation and the continuous-time correlated random walk model, are often inadequate to capture the complexity of animal movements. Here, we develop a deep learning approach to animal trajectory imputation by a conditional diffusion model. Unlike the traditional methods, our deep learning method uses observed data and external covariates to impute missing positions along an animal trajectory, capturing periodic patterns and the influence of covariates, which leads to more accurate imputations. In a case study of imputing deer trajectories, our method not only provides more accurate deterministic imputations than existing approaches but also achieves uncertainty quantification through probabilistic imputation.

Environmetrics↗
USGS2018

Linking animals aloft with the terrestrial landscape

Despite using the aerosphere for many facets of their life, most flying animals (i.e., birds, bats, some insects) are still bound to terrestrial habitats for resting, feeding, and reproduction. Comprehensive broad-scale observations by weather surveillance radars of animals as they leave terrestrial habitats for migration or feeding flights can be used to map their terrestrial distributions either as point locations (e.g., communal roosts) or as continuous surface layers (e.g., animal densities in habitats across a landscape). We discuss some of the technical challenges to reducing measurement biases related to how radars sample the aerosphere and the flight behavior of animals. We highlight a recently developed methodological approach that precisely and quantitatively links the horizontal spatial structure of birds aloft to their terrestrial distributions and provides novel insights into avian ecology and conservation across broad landscapes. Specifically, we present case studies that (1) elucidate how migrating birds contend with crossing ecological barriers and extreme weather events, (2) identify important stopover areas and habitat use patterns of birds along their migration routes, and (3) assess waterfowl response to wetland habitat management and restoration. These studies aid our understanding of how anthropogenic modification of the terrestrial landscape (e.g., urbanization, habitat management), natural geographic features, and weather (e.g., hurricanes) can affect the terrestrial distributions of flying animals.

Book chapter↗
USGS2019

The missing dead: The lost role of animal remains in nutrient cycling in North American Rivers

While leaf litter, wood, and other plant remnants are known to play a central role in lotic ecosystems, animal remains (carcasses, bones, shells) have received less attention. We propose a simple classification scheme for animal remains in rivers based on origin (authochthonous vs. allochthonous) and frequency (pulsed vs continuous). We then present case studies in which we estimate the former biomass of several taxonomic groups that are now diminished in abundance to determine whether their remains could have historically constituted a significant flux of nutrients in rivers of North America. We focus on bones and shells, which decompose slowly and could provide long-term reservoirs of nutrients. We find that carcasses of alligator snapping turtles, once abundant in southeastern rivers, could have provided an amount of phosphorus equivalent to about 1% of total phosphorus (TP) load at median flow, and more at low flows. Mussel shells could have contributed a similar amount (0.8% of TP) but the contribution of beaver carcasses, even at former abundances, was likely small. In contrast, a single documented mass drowning of bison in the Assiniboine River could have contributed half the annual TP load for that river. Such drownings could have been a common occurrence prior to the loss of most wild terrestrial megafauna in North America. We conclude that animal remnants, particularly allochthonous remains from terrestrial animals, formerly played a substantial role in nutrient cycling. Existing models of ecosystem function under reference conditions are incomplete without consideration of these lost animal legacies.

Food Webs↗