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At least 631 records · Page 35Linked to original sources
USGS2025

The tortoise and the antilocaprid: Adapting GPS tracking and terrain data to model wildlife walking functions

Context The relationship between slope and terrestrial animal locomotion is key to landscape ecology but underexplored across species. This is partly due to a lack of scalable methodology that applies to a diversity of wildlife. Objectives This study investigates the slope-speed relationship for two species, Texas tortoise ( Gopherus berlandieri ) and pronghorn ( Antilocapra americana ), through the combined application of remote sensing, GPS tracking, behavior models, and parametric distribution. While using readily available Digital Elevation Models (DEM) for pronghorn, we explore the use of very high-resolution lidar Digital Terrain Models (DTM) from Unoccupied Aerial Systems (UAS) to characterize tortoise movements at micro-scales. Methods After classifying animal behavior with GPS tracking data and Hidden Markov Models (HMMs), we analyzed the relationship between the speed of the animals and the slope of the terrain using a 30-m DEM for pronghorn, and a fine-scale UAS DTM for Texas tortoise, and three nonlinear models: Laplace, Gauss, and Lorentz. Results High-resolution DTM, coupled with GPS tracking, accurately models the relationship of speed and slope at a micro-scale, while a DEM is suitable for a larger scale. Laplace models best predicted the speed of both the Texas tortoise and pronghorn. Models showed tortoises, which are not known for rapid and agile movement like the pronghorn, have a broader tolerance for varying slopes at a fine scale. Conclusions These findings enhance understanding of species-specific movement offering valuable insights for habitat management and conservation tailored to species’ behaviors and capabilities.

Colorado, Texas, Wyoming↗
USGS2015

Optimal population prediction of sandhill crane recruitment based on climate-mediated habitat limitations

Prediction is fundamental to scientific enquiry and application; however, ecologists tend to favour explanatory modelling. We discuss a predictive modelling framework to evaluate ecological hypotheses and to explore novel/unobserved environmental scenarios to assist conservation and management decision-makers. We apply this framework to develop an optimal predictive model for juvenile (<1 year old) sandhill crane Grus canadensis recruitment of the Rocky Mountain Population (RMP). We consider spatial climate predictors motivated by hypotheses of how drought across multiple time-scales and spring/summer weather affects recruitment. Our predictive modelling framework focuses on developing a single model that includes all relevant predictor variables, regardless of collinearity. This model is then optimized for prediction by controlling model complexity using a data-driven approach that marginalizes or removes irrelevant predictors from the model. Specifically, we highlight two approaches of statistical regularization, Bayesian least absolute shrinkage and selection operator (LASSO) and ridge regression. Our optimal predictive Bayesian LASSO and ridge regression models were similar and on average 37% superior in predictive accuracy to an explanatory modelling approach. Our predictive models confirmed a priori hypotheses that drought and cold summers negatively affect juvenile recruitment in the RMP. The effects of long-term drought can be alleviated by short-term wet spring–summer months; however, the alleviation of long-term drought has a much greater positive effect on juvenile recruitment. The number of freezing days and snowpack during the summer months can also negatively affect recruitment, while spring snowpack has a positive effect. Breeding habitat, mediated through climate, is a limiting factor on population growth of sandhill cranes in the RMP, which could become more limiting with a changing climate (i.e. increased drought). These effects are likely not unique to cranes. The alteration of hydrological patterns and water levels by drought may impact many migratory, wetland nesting birds in the Rocky Mountains and beyond. Generalizable predictive models (trained by out-of-sample fit and based on ecological hypotheses) are needed by conservation and management decision-makers. Statistical regularization improves predictions and provides a general framework for fitting models with a large number of predictors, even those with collinearity, to simultaneously identify an optimal predictive model while conducting rigorous Bayesian model selection. Our framework is important for understanding population dynamics under a changing climate and has direct applications for making harvest and habitat management decisions.

Journal of Animal Ecology↗
USGS2014

Pedological and geological relationships with soil lichen and moss distribution in the eastern Mojave Desert, CA, USA

Biological soil crusts (biocrusts) are ubiquitous in drylands globally. Lichens and mosses are essential biocrust components and provide a variety of ecosystem services, making their conservation and management of interest. Accordingly, understanding what factors are correlated with their distribution is important to land managers. We hypothesized that cover would be related to geologic and pedologic factors. We sampled 32 sites throughout the eastern Mojave Desert, stratifying by parent material and the age of the geomorphic surfaces. The cover of lichens and mosses on ‘available ground’ (L + M av ; available ground excludes ground covered by rocks or plant stems) was higher on limestone and quartzite-derived soils than granite-derived soils. Cover was also higher on moderately younger-aged geomorphic surfaces (Qya2, Qya3, Qya4) and cutbanks than on very young (Qya1), older-aged surfaces (Qia1, Qia2), or soils associated with coppice mounds or animal burrowing under Larrea tridentata. When all sites and parent materials were combined, soil texture was the most important factor predicting the occurrence of L + M av , with cover positively associated with higher silt, very fine sand, and fine sand fractions and negatively associated with the very coarse sand fraction. When parent materials were examined separately, nutrients such as available potassium, iron, and calcium became the most important predictors of L + M av cover.

California↗
USGS2004

Evaluating mixed samples as a source of error in non-invasive genetic studies using microsatellites

The use of noninvasive genetic sampling (NGS) for surveying wild populations is increasing rapidly. Currently, only a limited number of studies have evaluated potential biases associated with NGS. This paper evaluates the potential errors associated with analysing mixed samples drawn from multiple animals. Most NGS studies assume that mixed samples will be identified and removed during the genotyping process. We evaluated this assumption by creating 128 mixed samples of extracted DNA from brown bear (Ursus arctos) hair samples. These mixed samples were genotyped and screened for errors at six microsatellite loci according to protocols consistent with those used in other NGS studies. Five mixed samples produced acceptable genotypes after the first screening. However, all mixed samples produced multiple alleles at one or more loci, amplified as only one of the source samples, or yielded inconsistent electropherograms by the final stage of the error-checking process. These processes could potentially reduce the number of individuals observed in NGS studies, but errors should be conservative within demographic estimates. Researchers should be aware of the potential for mixed samples and carefully design gel analysis criteria and error checking protocols to detect mixed samples.

Molecular Ecology↗
USGS2013

The δ2H and δ18O of tap water from 349 sites in the United States and selected territories

Because the stable isotopic compositions of hydrogen (δ 2 H) and oxygen (δ 18 O) of animal (including human) tissues, such as hair, nail, and urine, reflect the δ 2 H and δ 18 O of water and food ingested by an animal or a human and because the δ 2 H and δ 18 O of environmental waters vary geographically, δ 2 H and δ 18 O values of tap water samples collected in 2007-2008 from 349 sites in the United States and three selected U.S. territories have been measured in support of forensic science applications, creating one of the largest databases of tap water δ 2 H and δ 18 O values to date. The results of replicate isotopic measurements for these tap water samples confirm that the expanded uncertainties (U = 2μ c ) obtained over a period of years by the Reston Stable Isotope Laboratory from δ 2 H and δ 18 O dual-inlet mass spectrometric measurements are conservative, at ±2‰ and ±0.2 ‰, respectively. These uncertainties are important because U.S. Geological Survey data may be needed for forensic science applications, including providing evidence in court cases. Half way through the investigation, an isotope-laser spectrometer was acquired, enabling comparison of dual-inlet isotope-ratio mass spectrometric results with isotope-laser spectrometric results. The uncertainty of the laser-based δ 2 H measurement results for these tap water samples is comparable to the uncertainty of the mass spectrometric method, with the laser-based method having a slightly lower uncertainty. However, the δ 18 O uncertainty of the laser-based method is more than a factor of ten higher than that of the dual-inlet isotoperatio mass spectrometric method.

Guam, Puerto Rico, St. John, U.S. Virgin Islands↗
USGS2008

Role of patch size, disease, and movement in rapid extinction of bighorn sheep

The controversy (Berger 1990, 1999; Wehausen 1999) over rapid extinction in bighorn sheep ( Ovis canadensis ) has focused on population size alone as a correlate to persistence time. We report on the persistence and population performance of 24 translocated populations of bighorn sheep. Persistence in these sheep was strongly correlated with larger patch sizes, greater distance to domestic sheep, higher population growth rates, and migratory movements, as well as to larger population sizes. Persistence was also positively correlated with larger average home-range size ( p = 0.058, n = 10 translocated populations) and home-range size of rams ( p = 0.087, n = 8 translocated populations). Greater home-range size and dispersal rates of bighorn sheep were positively correlated to larger patches. We conclude that patch size and thus habitat carrying capacity, not population size per se, is the primary correlate to both population performance and persistence. Because habitat carrying capacity defines the upper limit to population size, clearly the amount of suitable habitat in a patch is ultimately linked to population size. Larger populations (250+ animals) were more likely to recover rapidly to their pre-epizootic survey number following an epizootic ( p = 0.019), although the proportion of the population dying in the epizootic also influenced the probability of recovery ( p = 0.001). Expensive management efforts to restore or increase bighorn sheep populations should focus on large habitat patches located ≥23 km from domestic sheep, and less effort should be expended on populations in isolated, small patches of habitat.

Conservation Biology↗
USGS2026

Annual grass invasion is transforming the sagebrush biome’s songbird communities

Novel stressors like climate change and biological invasions alter ecological communities, resulting in changes to ecosystem services and biodiversity (that is, ecological transformation). Most ecological transformation research focuses on plants, but animals are likely affected by and plausibly mediate the extent, impact, and pace of transformations. In western North America, where invasive annual grasses are transforming sagebrush-steppe ecosystems, we quantified how transformation in vegetation drives songbird community change. We hypothesized that transformation of vegetation communities via invasion alters wildlife communities by favoring generalists over specialists, albeit with extinction debts that may temporarily obscure transformations’ consequences. Although local-scale songbird diversity increased with grass invasion, we found that this shift was accompanied by ongoing reorganization of songbird communities at larger scales (across the sagebrush biome), driven by heterogeneous impacts of invasion among species and guilds. Through our biome-wide analysis, we were also able to identify high-priority regions for conservation of sensitive songbird species. Our research provides evidence that wildlife communities are transforming alongside vegetation communities and offers insight into the approaches required to quantify nascent community turnover.

western United States↗
USGS2010

Regional climate change-Science in the Southeast

Resource managers are at the forefront of a new era of management. They must consider the potential impacts of climate change on the Nation's resources and proactively develop strategies for dealing with those impacts on plants, animals, and ecosystems. This requires rigorous, scientific understanding of environmental change. The role of the U.S. Geological Survey (USGS) in this effort is to analyze climate-change data and develop tools for assessing how changing conditions are likely to impact resources. This information will assist Federal, State, local, and tribal partners manage resources strategically. The 2008 Omnibus Budget Act and Secretarial Order 3289 established a new network of eight Department of Interior Regional Climate Science Centers to provide technical support for resource managers. The Southeast Regional Assessment Project (SERAP) is the first regional assessment to be funded by the USGS National Climate Change and Wildlife Science Center (http://nccw.usgs.gov/). The USGS is working closely with the developing Department of Interior Landscape Conservation Cooperatives to ensure that the project will meet the needs of resource managers in the Southeast. In addition, the U.S. Fish and Wildlife Service is providing resources to the SERAP to expand the scope of the project.

Fact Sheet↗
USGS2024

Real-time invasive sea lamprey detection using machine learning classifier models on embedded systems

Invasive sea lamprey ( Petromyzon marinus ) has historically inflicted considerable economic and ecological damage in the Great Lakes and continues to be a major threat. Accurately monitoring sea lampreys are critical to enabling the deployment of more targeted and effective control measures to minimize the impact associated with this species. This paper presents the first stand-alone system for real-time detection of sea lamprey attachment on underwater surfaces through the use of classifier models deployed on a microcontroller system. A range of low-complexity models was explored: single-layer artificial neural networks, logistic regression, Gaussian Naive-Bayes, decision trees, random forest, and Scalable, Efficient, and Fast classifieR (SEFR). Threshold models tuned using a multi-objective optimization formulation were also considered. Classifier models were trained with a dataset generated through live animal testing and presented accuracies between 80 and 86%. The models were deployed on an Arduino microcontroller platform and compared in classification accuracy, detection performance, time complexity, and memory size using real-time detection testing. Classification accuracies between 65 and 75% were observed during validation. Models demonstrated good capture rates for lamprey attachments (63–85%), and average detection delays ranging from 9 to 36 s. A video demonstrating the operation of the system during a real-time validation test is also included in this work. While there is room for improving the accuracy of the system, this research presents the first step toward an electronic sea lamprey monitoring system that can provide a detailed view of sea lamprey activity enhancing control and conservation efforts across its entire range.

Neural Computing and Applications↗
USGS2008

Multi-scale occupancy estimation and modelling using multiple detection methods

Occupancy estimation and modelling based on detection–nondetection data provide an effective way of exploring change in a species’ distribution across time and space in cases where the species is not always detected with certainty. Today, many monitoring programmes target multiple species, or life stages within a species, requiring the use of multiple detection methods. When multiple methods or devices are used at the same sample sites, animals can be detected by more than one method. We develop occupancy models for multiple detection methods that permit simultaneous use of data from all methods for inference about method-specific detection probabilities. Moreover, the approach permits estimation of occupancy at two spatial scales: the larger scale corresponds to species’ use of a sample unit, whereas the smaller scale corresponds to presence of the species at the local sample station or site. We apply the models to data collected on two different vertebrate species: striped skunks Mephitis mephitis and red salamanders Pseudotriton ruber . For striped skunks, large-scale occupancy estimates were consistent between two sampling seasons. Small-scale occupancy probabilities were slightly lower in the late winter/spring when skunks tend to conserve energy, and movements are limited to males in search of females for breeding. There was strong evidence of method-specific detection probabilities for skunks. As anticipated, large- and small-scale occupancy areas completely overlapped for red salamanders. The analyses provided weak evidence of method-specific detection probabilities for this species. Synthesis and applications. Increasingly, many studies are utilizing multiple detection methods at sampling locations. The modelling approach presented here makes efficient use of detections from multiple methods to estimate occupancy probabilities at two spatial scales and to compare detection probabilities associated with different detection methods. The models can be viewed as another variation of Pollock's robust design and may be applicable to a wide variety of scenarios where species occur in an area but are not always near the sampled locations. The estimation approach is likely to be especially useful in multispecies conservation programmes by providing efficient estimates using multiple detection devices and by providing device-specific detection probability estimates for use in survey design.

Journal of Applied Ecology↗
USGS2001

Status and distribution of the West Indian manatee, Trichechus manatus manatus, in Colombia

Historical and recent information on the status and distribution of West Indian manatee, Trichechus manatus manatus, in Colombia was reviewed. Opportunistic and systematic interviews were also conducted. Historical information suggested that the distribution of manatees had been reduced in the Caribbean basin. Manatees can be found in the Atrato, Sinu??, San Jorge, Cauca, Cesar and Magdalena rivers and the Cie??naga Grande de Santa Marta marsh in the Caribbean basin, and in the Meta River in the Orinoco basin. The Magdalena riparian system provides the largest area of suitable habitat, which also has the highest frequency of captures. Most animals (81.20%) were killed for sale or to share meat in a subsistence base. Hunting is apparently increasing but capture with nets still represents the species' major direct threat. Habitat destruction occurs in all areas. International and national laws protect the species, however, funding is inadequate for effective enforcement of present laws. ?? 2001 Published by Elsevier Science Ltd. All rights reserved.

Biological Conservation↗
USGS2018

Climatically driven changes in primary production propagate through trophic levels

Climate and land‐use change are the major drivers of global biodiversity loss. Their effects are particularly acute for wide‐ranging consumers, but little is known about how these factors interact to affect the abundance of large carnivores and their herbivore prey. We analyzed population densities of a primary and secondary consumer (mule deer, Odocoileus hemionus , and mountain lion, Puma concolor ) across a climatic gradient in western North America by combining satellite‐based maps of plant productivity with estimates of animal abundance and foraging area derived from Global Positioning Systems telemetry data (GPS). Mule deer density exhibited a positive, linear relationship with plant productivity ( r 2 = 0.58), varying by a factor of 18 across the climate‐vegetation gradient (range: 38–697 individuals/100 km 2 ). Mountain lion home range size decreased in response to increasing primary productivity and consequent changes in the abundance of their herbivore prey (range: 20–450 km 2 ). This pattern resulted in a strong, positive association between plant productivity and mountain lion density ( r 2 = 0.67). Despite varying densities, the ratio of prey to predator remained constant across the climatic gradient (mean ± SE = 363 ± 29 mule deer/mountain lion), suggesting that the determinacy of the effect of primary productivity on consumer density was conserved across trophic levels. As droughts and longer term climate changes reduce the suitability of marginal habitats, consumer home ranges will expand in order for individuals to meet basic nutritional requirements. These changes portend decreases in the abundance of large‐bodied, wide‐ranging wildlife through climatically driven reductions in carrying capacity, as well as increased human–wildlife interactions stemming from anthropogenic land use and habitat fragmentation.

Colorado Plateau, Great Basin, Mojave Desert↗
USGS2022

Climate change and ‘alien species in National Parks’: Revisited

The US National Park Service mission includes conserving native species and historical landscapes ‘unimpaired for the enjoyment of future generations’. However, humans have increased the introduction of non-native species that can become invasive and which have harmful impacts on native species and landscapes. We revisit two previous papers, ‘Alien Species in National Parks: Drawing Lines in Space and Time’, published in 1995 by D.B. Houston and E.G. Schreiner, and ‘Climate Change and “Alien Species in National Parks”: Revisited’, published in 2014 by T.J. Stohlgren, J.R. Resnik and G.E. Plumb, to demonstrate the organizational progress that has been made in reducing impacts of invasive species despite the increasing pressure of increasing numbers of non-native species. The National Park Service has continued efforts on invasive plant management, established an Invasive Animal Program in 2018 and developed a Pest & Invasive Species Project Kit to compile information to inform management regardless of taxonomic group. Additionally, the Park Service has expanded their toolset to make decisions related to invasive species and climate change to focus on achievable goals. Since the 1995 publication, the scale of invasion has increased, and impacts of climate change are more noticeable since the 2014 publication, increasing the complexity in trying to achieve the National Park Service mission.

Book chapter↗
USGS2022

Influence of offshore oil and gas structures on seascape ecological connectivity

Offshore platforms, subsea pipelines, wells and related fixed structures supporting the oil and gas (O&G) industry are prevalent in oceans across the globe, with many approaching the end of their operational life and requiring decommissioning. Although structures can possess high ecological diversity and productivity, information on how they interact with broader ecological processes remains unclear. Here, we review the current state of knowledge on the role of O&G infrastructure in maintaining, altering or enhancing ecological connectivity with natural marine habitats. There is a paucity of studies on the subject with only 33 papers specifically targeting connectivity and O&G structures, although other studies provide important related information. Evidence for O&G structures facilitating vertical and horizontal seascape connectivity exists for larvae and mobile adult invertebrates, fish and megafauna; including threatened and commercially important species. The degree to which these structures represent a beneficial or detrimental net impact remains unclear, is complex and ultimately needs more research to determine the extent to which natural connectivity networks are conserved, enhanced or disrupted. We discuss the potential impacts of different decommissioning approaches on seascape connectivity and identify, through expert elicitation, critical knowledge gaps that, if addressed, may further inform decision making for the life cycle of O&G infrastructure, with relevance for other industries (e.g. renewables). The most highly ranked critical knowledge gap was a need to understand how O&G structures modify and influence the movement patterns of mobile species and dispersal stages of sessile marine species. Understanding how different decommissioning options affect species survival and movement was also highly ranked, as was understanding the extent to which O&G structures contribute to extending species distributions by providing rest stops, foraging habitat, and stepping stones. These questions could be addressed with further dedicated studies of animal movement in relation to structures using telemetry, molecular techniques and movement models. Our review and these priority questions provide a roadmap for advancing research needed to support evidence-based decision making for decommissioning O&G infrastructure.

Global Change Biology↗
USGS2010

Modeling the human invader in the United States

Modern biogeographers recognize that humans are seen as constituents of ecosystems, drivers of significant change, and perhaps, the most invasive species on earth. We found it instructive to model humans as invasive organisms with the same environmental factors. We present a preliminary model of the spread of modern humans in the conterminous United States between 1992 and 2001 based on a subset of National Land Cover Data (NLCD), a time series LANDSAT product. We relied on the commonly used Maxent model, a species-environmental matching model, to map urbanization. Results: Urban areas represented 5.1% of the lower 48 states in 2001, an increase of 7.5% (18,112 km 2 ) in the nine year period. At this rate, an area the size of Massachusetts is converted to urban land use every ten years. We used accepted models commonly used for mapping plant and animal distributions and found that climatic and environmental factors can strongly predict our spread (i.e., the conversion of forests, shrub/grass, and wetland areas into urban areas), with a 92.5% success rate (Area Under the Curve). Adding a roads layer in the model improved predictions to a 95.5% success rate. 8.8% of the 1-km 2 > cells in the conterminous U.S. now have a major road in them. In 2001, 0.8% of 1-km 2 > cells in the U.S. had an urbanness value of > 800, (>89% of a 1-km 2 > cell is urban), while we predict that 24.5% of 1-km 2 > cells in the conterminous U.S. will be > 800 eventually. Main conclusion: Humans have a highly predictable pattern of urbanization based on climatic and topographic variables. Conservation strategies may benefit from that predictability.

Journal of Applied Remote Sensing↗
USGS2006

Educating veterinarians for careers in free-ranging wildlife medicine and ecosystem health

In the last 10 years, the field of zoological medicine has seen an expansive broadening into the arenas of free-ranging wildlife, conservation medicine, and ecosystem health. During the spring/summer of 2005, we prepared and disseminated a survey designed to identify training and educational needs for individuals entering the wildlife medicine and ecosystem health fields. Our data revealed that few wildlife veterinarians believe that the training they received in veterinary school adequately prepared them to acquire and succeed in their field. Wildlife veterinarians and their employers ranked mentorship with an experienced wildlife veterinarian, training in leadership and communication, courses and externships in wildlife health, and additional formal training beyond the veterinary degree as important in preparation for success. Employers, wildlife veterinarians, and job seekers alike reported that understanding and maintaining ecosystem health is a key component of the wildlife veterinarian's job description, as it is critical to protecting animal health, including human health. Today's wildlife veterinarians are a new type of transdisciplinary professional; they practice medicine in their communities and hold titles in every level of government and academia. It is time that we integrate ecosystem health into our curricula to nurture and enhance an expansive way of looking at veterinary medicine and to ensure that veterinary graduates are prepared to excel in this new and complex world, in which the health of wildlife, domestic animals, and people are interdependent.

Journal of Veterinary Medical Education↗
USGS2018

Marine threats overlap key foraging habitat for two imperiled sea turtle species in the Gulf of Mexico

Effective management of human activities affecting listed species requires understanding both threats and animal habitat-use patterns. However, the extent of spatial overlap between high-use foraging areas (where multiple marine species congregate) and anthropogenic threats is not well known. Our modeling approach incorporates data on sea turtle spatial ecology and a suite of threats in the Gulf of Mexico to identify and map “hot spots” of threats to two imperiled turtle species. Of all 820 “high” threats grid cells, our tracked turtles foraged at least one day in 77% of them. Although threat data were not available outside the U.S. Exclusive Economic Zone, our map of turtle and threat “hotspots” can be incorporated in future more comprehensive threat analyses for the region. Knowledge of these shared foraging- and threat-areas can assist managers charged with designing effective conservation and population recovery strategies, in future habitat modeling efforts, and in designations of Gulf of Mexico habitat with high conservation value.

Frontiers in Marine Science↗
USGS2018

Biological connectivity of seasonally ponded wetlands across spatial and temporal scales

Many species that inhabit seasonally ponded wetlands also rely on surrounding upland habitats and nearby aquatic ecosystems for resources to support life stages and to maintain viable populations. Understanding biological connectivity among these habitats is critical to ensure that landscapes are protected at appropriate scales to conserve species and ecosystem function. Biological connectivity occurs across a range of spatial and temporal scales. For example, at annual time scales many organisms move between seasonal wetlands and adjacent terrestrial habitats as they undergo life‐stage transitions; at generational time scales, individuals may disperse among nearby wetlands; and at multigenerational scales, there can be gene flow across large portions of a species’ range. The scale of biological connectivity may also vary among species. Larger bodied or more vagile species can connect a matrix of seasonally ponded wetlands, streams, lakes, and surrounding terrestrial habitats on a seasonal or annual basis. Measuring biological connectivity at different spatial and temporal scales remains a challenge. Here we review environmental and biological factors that drive biological connectivity, discuss implications of biological connectivity for animal populations and ecosystem processes, and provide examples illustrating the range of spatial and temporal scales across which biological connectivity occurs in seasonal wetlands.

Journal of the American Water Resources Associatio↗