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At least 109 records · Page 6Linked to original sources

USGS2000

Predicting red wolf release success in the southeastern United States

Although the red wolf ( Canis rufus ) was once found throughout the southeastern United States, indiscriminate killing and habitat destruction reduced its range to a small section of coastal Texas and Louisiana. Wolves trapped from 1973 to 1980 were taken to establish a captive breeding program that was used to repatriate 2 mainland and 3 island red wolf populations. We collected data from 320 red wolf releases in these areas and classified each as a success or failure based on survival and reproductive criteria, and whether recaptures were necessary to resolve conflicts with humans. We evaluated the relations between release success and conditions at the release sites, characteristics of released wolves, and release procedures. Although <44% of the variation in release success was explained, model performance based on jackknife tests indicated a 72-80% correct prediction rate for the 4 operational models we developed. The models indicated that success was associated with human influences on the landscape and the level of wolf habituation to humans prior to release. We applied the models to 31 prospective areas for wolf repatriation and calculated an index of release success for each area. Decision-makers can use these models to objectively rank prospective release areas and compare strengths and weaknesses of each.

Journal of Wildlife Management↗

USGS2023

Evaluating baits with lufenuron and nitenpyram for flea control on prairie dogs (Cynomys spp.) to mitigate plague

Plague, caused by Yersinia pestis , is a widespread threat to endangered black-footed ferrets ( Mustela nigripes ) and their primary prey, prairie dogs ( Cynomys spp.). Wildlife biologists most commonly manage plague using insecticides to control fleas, the primary vectors of Y. pestis . We tested edible baits containing the insecticides lufenuron and/or nitenpyram in prairie dogs. During a laboratory study, we treated 26 white-tailed prairie dogs ( Cynomys leucurus ) with lufenuron at 300 mg/kg body mass. All animals remained clinically healthy over the 9 wk monitoring period. Although serum lufenuron concentrations were >130 ppb in two treatment groups at week 1, concentrations declined to ≤60 ppb after 3 wk in non-torpid prairie dogs and after 7 wk in torpid prairie dogs. In a field experiment, we tested baits containing a combination of 75 mg lufenuron and 6 mg nitenpyram, respectively, in black-tailed prairie dogs ( Cynomys ludovicianus ). We uniformly distributed baits at 125 baits/ha on two plots (treated once) and 250 baits/ha on two plots (each treated twice 4.4 wk apart). Following treatments, flea abundance increased on prairie dogs and remained stable in burrows. Our findings indicate that baits containing lufenuron and nitenpyram, at the reported treatment rates, are ineffective tools for flea control on prairie dogs. Future experiments might evaluate efficacy of higher doses of lufenuron and nitenpyram, and repetitive treatments at differing intervals over time to evaluate potentially therapeutic treatments.

Journal of Wildlife Diseases↗

USGS2008

Variational analysis of drifter positions and model outputs for the reconstruction of surface currents in the central Adriatic during fall 2002

In this paper we present an application of a variational method for the reconstruction of the velocity field in a coastal flow in the central Adriatic Sea, using in situ data from surface drifters and outputs from the ROMS circulation model. The variational approach, previously developed and tested for mesoscale open ocean flows, has been improved and adapted to account for inhomogeneities on boundary current dynamics over complex bathymetry and coastline and for weak Lagrangian persistence in coastal flows. The velocity reconstruction is performed using nine drifter trajectories over 45 d, and a hierarchy of indirect tests is introduced to evaluate the results as the real ocean state is not known. For internal consistency and impact of the analysis, three diagnostics characterizing the particle prediction and transport, in terms of residence times in various zones and export rates from the boundary current toward the interior, show that the reconstruction is quite effective. A qualitative comparison with sea color data from the MODIS satellite images shows that the reconstruction significantly improves the description of the boundary current with respect to the ROMS model first guess, capturing its main features and its exchanges with the interior when sampled by the drifters. Copyright 2008 by the American Geophysical Union.

Journal of Geophysical Research C: Oceans↗

USGS2021

Mixed evidence for biotic homogenization of southern Appalachian fish communities

Anthropogenic impacts on the landscape can drive biotic homogenization, whereby distinct biological communities become more similar to one another over time. Land-use change in the Southern Appalachian region is expected to result in homogenization of the highly diverse freshwater fish communities as in-stream habitat alterations favor widespread cosmopolitan species at the expense of more narrowly distributed highland endemic species. We compiled four datasets spanning 25 years to (1) evaluate the effects of environmental factors on relative abundance and richness of highland endemic vs. cosmopolitan species in this region and (2) test for taxonomic homogenization, measured as a change in beta diversity over time. We found that several environmental factors differentially affected highland endemic and cosmopolitan species, with the proportion of forested land cover in a watershed most strongly predicting higher relative abundance and richness of highland endemic species. Our analysis of beta diversity change, however, shows mixed evidence of taxonomic homogenization, depending on how common species are weighted. Shifts in community composition, with or without homogenization, may warrant attention in biodiversity conservation planning.

Georgia, North Carolina↗

USGS2006

The influence of hazard models on GIS-based regional risk assessments and mitigation policies

Geographic information systems (GIS) are important tools for understanding and communicating the spatial distribution of risks associated with natural hazards in regional economies. We present a GIS-based decision support system (DSS) for assessing community vulnerability to natural hazards and evaluating potential mitigation policy outcomes. The Land Use Portfolio Modeler (LUPM) integrates earth science and socioeconomic information to predict the economic impacts of loss-reduction strategies. However, the potential use of such systems in decision making may be limited when multiple but conflicting interpretations of the hazard are available. To explore this problem, we conduct a policy comparison using the LUPM to test the sensitivity of three available assessments of earthquake-induced lateral-spread ground failure susceptibility in a coastal California community. We find that the uncertainty regarding the interpretation of the science inputs can influence the development and implementation of natural hazard management policies. Copyright ?? 2006 Inderscience Enterprises Ltd.

International Journal of Risk Assessment and Manag↗

USGS2015

The effects of numerical-model complexity and observation type on estimated porosity values

The relative merits of model complexity and types of observations employed in model calibration are compared. An existing groundwater flow model coupled with an advective transport simulation of the Salt Lake Valley, Utah (USA), is adapted for advective transport, and effective porosity is adjusted until simulated tritium concentrations match concentrations in samples from wells. Two calibration approaches are used: a “complex” highly parameterized porosity field and a “simple” parsimonious model of porosity distribution. The use of an atmospheric tracer (tritium in this case) and apparent ages (from tritium/helium) in model calibration also are discussed. Of the models tested, the complex model (with tritium concentrations and tritium/helium apparent ages) performs best. Although tritium breakthrough curves simulated by complex and simple models are very generally similar, and there is value in the simple model, the complex model is supported by a more realistic porosity distribution and a greater number of estimable parameters. Culling the best quality data did not lead to better calibration, possibly because of processes and aquifer characteristics that are not simulated. Despite many factors that contribute to shortcomings of both the models and the data, useful information is obtained from all the models evaluated. Although any particular prediction of tritium breakthrough may have large errors, overall, the models mimic observed trends.

Utah↗

USGS2015

Surveillance potential of non-native Hawaiian birds for detection of West Nile Virus

West Nile virus (WNV) was first detected in North America in 1999. Alaska and Hawaii (HI) remain the only U.S. states in which transmission of WNV has not been detected. Dead bird surveillance has played an important role in the detection of the virus geographically, as well as temporally. In North America, corvids have played a major role in WNV surveillance; however, the only corvid in HI is the endangered Hawaiian crow that exists only in captivity, thus precluding the use of this species for WNV surveillance in HI. To evaluate the suitability of alternate avian species for WNV surveillance, we experimentally challenged seven abundant non-native bird species present in HI with WNV and compared mortality, viremia, oral shedding of virus, and seroconversion. For detection of WNV in oral swabs, we compared viral culture, reverse-transcriptase polymerase chain reaction, and the RAMP ® test. For detection of antibodies to WNV, we compared an indirect and a competitive enzyme-linked immunoassay. We found four species (house sparrow, house finch, Japanese white-eye, and Java sparrow) that may be useful in dead bird surveillance for WNV; while common myna, zebra dove, and spotted dove survived infection and may be useful in serosurveillance.

American Journal of Tropical Medicine and Hygiene↗

USGS2021

Evaluating management options to reduce Lake Erie algal blooms using an ensemble of watershed models

Reducing harmful algal blooms in Lake Erie, situated between the United States and Canada, requires implementing best management practices to decrease nutrient loading from upstream sources. Bi-national water quality targets have been set for total and dissolved phosphorus loads, with the ultimate goal of reaching these targets in 9-out-of-10 years. Row crop agriculture dominates the land use in the Western Lake Erie Basin thus requiring efforts to mitigate nutrient loads from agricultural systems. To determine the types and extent of agricultural management practices needed to reach the water quality goals, we used five independently developed Soil and Water Assessment Tool models to evaluate the effects of 18 management scenarios over a 10-year period on nutrient export. Guidance from a stakeholder group was provided throughout the project, and resulted in improved data, development of realistic scenarios, and expanded outreach. Subsurface placement of phosphorus fertilizers, cover crops, riparian buffers, and wetlands were among the most effective management options. But, only in one realistic scenario did a majority (3/5) of the models predict that the total phosphorus loading target would be met in 9-out-of-10 years. Further, the dissolved phosphorus loading target was predicted to meet the 9-out-of-10-year goal by only one model and only in three scenarios. In all scenarios evaluated, the 9-out-of-10-year goal was not met based on the average of model predictions. Ensemble modeling revealed general agreement about the effects of several practices although some scenarios resulted in a wide range of uncertainty. Overall, our results demonstrate that there are multiple pathways to approach the established water quality goals, but greater adoption rates of practices than those tested here will likely be needed to attain the management targets.

Michigan↗

USGS2021

Performance of bedload sediment transport formulas applied to the Lower Minnesota River

Despite limitations in reproducing complex bedload sediment transport processes in rivers, formulas have been preferred over collection and analysis of field data due to the high cost and time-consuming nature of bedload discharge measurements. However, the performance of such formulas depends on the hydraulic and sedimentological conditions they attempt to describe. The availability of field measurements provides a unique opportunity to test bedload transport formulas to better guide formula selection. Hydraulic parameters and bedload discharge data from the Lower Minnesota River and two of its tributaries were used to evaluate nine bedload transport formulas using three different indices. The bedload data for the different sites were collected by the United States Geological Survey (USGS) from 2011 through 2014, with bed material varying from very coarse to medium sand. The formulas calculated higher bedload rates than were measured due to a combination of site-specific physical characteristics, including the presence of bed forms (dunes), and sampling uncertainties. Because of the lack of reproducibility of the tested formulas, five power functions, based on the relation between the specific unit power (independent hydraulic variable) and the USGS measured data (dependent variable), were derived as provisional equations to estimate the bedload discharge on the Lower Minnesota River and tributaries.

Minnesota↗

USGS2013

Behaviors of southwestern native fishes in response to introduced catfish predators

Native fishes reared in hatcheries typically suffer high predation mortality when stocked into natural environments. We evaluated the behavior of juvenile bonytail Gila elegans, roundtail chub Gila robusta, razorback sucker Xyrauchen texanus, and Sonora sucker Catostomus insignis in response to introduced channel catfish Ictalurus punctatus and flathead catfish Pylodictis olivaris. Our laboratory tests indicate these species did not inherently recognize catfish as a threat, but they can quickly (within 12 h) change their behavior in response to a novel predator paired with the sight and scent of a dead conspecific. Chubs appear to avoid predation by swimming away from the threat, whereas suckers reduced movement. Effects of antipredator conditioning on survival of fish reared in hatcheries is unknown; however, our results suggest some native fish can be conditioned to recognize introduced predators, which could increase poststocking survival.

Journal of Fish and Wildlife Management↗

USGS2021

Landscape features fail to explain spatial genetic structure in white-tailed deer across Ohio, USA

Landscape features influence wildlife movements across spatial scales and have the potential to influence the spread of disease. Chronic wasting disease (CWD) is a fatal prion disease affecting members of the family Cervidae, particularly white-tailed deer ( Odocoileus virginianus ), and the first positive CWD case in a wild deer in Ohio, USA, was recorded in 2020. Landscape genetics approaches are increasingly used to better understand potential pathways for CWD spread in white-tailed deer, but little is known about genetic structure of white-tailed deer in Ohio. The objectives of our study were to evaluate spatial genetic structure in white-tailed deer across Ohio and compare the support for isolation by distance (IBD) and isolation by landscape resistance (IBR) models in explaining this structure. We collected genetic data from 619 individual deer from 24 counties across Ohio during 2007–2009. We used microsatellite genotypes from 619 individuals genotyped at 11 loci and haplotypes from a 547-base pair fragment of the mitochondrial DNA control region. We used spatial and non-spatial genetic clustering tests to evaluate genetic structure in both types of genetic data and empirically optimized landscape resistance surfaces to compare IBD and IBR using microsatellite data. Non-spatial genetic clustering tests failed to detect spatial genetic structure, whereas spatial genetic clustering tests indicated subtle spatial genetic structure. The IBD model consistently outperformed IBR models that included land cover, traffic volume, and streams. Our results indicated widespread genetic connectivity of white-tailed deer across Ohio and negligible effects of landscape features. These patterns likely reflect some combination of minimal resistive effects of landscape features on white-tail deer movement in Ohio and the effects of regional recolonization or translocation. We encourage continued CWD surveillance in Ohio, particularly in the proximity of confirmed cases.

Ohio↗

USGS2020

Fish out of water: Insights from a case study of a highly social animal that failed the mirror self-recognition test

Mirror self-recognition (MSR) tests have been conducted with a variety of species with the aim of examining whether subject animals have the capacity for self-awareness. To date, the majority of animals that have convincingly passed are highly social mammals whose wild counterparts live in complex societies, though there is much debate concerning what constitutes passing and what passing means in terms of self-awareness. Amid recent reports that a fish (cleaner wrasse, Labroides dimidiatus ) passed, it is intriguing that a mammal as highly social, tolerant, attentive, and cooperative as the grey wolf ( Canis lupus ) reportedly failed the test. Given the many possible reasons for failure, we aimed to elucidate the wolves’ responses at various stages of the MSR test to pinpoint potential problem areas where species-appropriate modifications to the test may be needed. Thus, we evaluated 6 socialized, captive grey wolves as a case study of failed MSR in socially complex canids. At a minimum, wolves did not respond to their reflection as an unfamiliar conspecific. Unfortunately, the wolves rapidly lost interest in the mirror and were uninterested in the applied marks. We note limitations of the MSR test for this species, recommend changes for future MSR tests of wolves, discuss other emerging self-cognizance methods for socially complex canids, and highlight the need for a suite of ecologically relevant, potentially scalable self-cognizance methods. Our findings and recommendations may aid in understanding self-cognizance in other untested highly social, cooperatively-hunting, coursing, terrestrial carnivores such as African wild dogs ( Lycaon pictus ), spotted hyenas ( Crocuta crocuta ), and African lions ( Panthera leo ).

International Journal of Comparative Psychology↗

USGS2016

Antemortem detection of chronic wasting disease prions in nasal brush collections and rectal biopsies from white-tailed deer by real time quaking-induced conversion

Chronic wasting disease (CWD), a transmissible spongiform encephalopathy of cervids, was first documented nearly 50 years ago in Colorado and Wyoming and has since spread to cervids in 23 states, two Canadian provinces, and the Republic of Korea. The expansion of this disease makes the development of sensitive diagnostic assays and antemortem sampling techniques crucial for the mitigation of its spread; this is especially true in cases of relocation/reintroduction of farmed or free-ranging deer and elk or surveillance studies of private or protected herds, where depopulation is contraindicated. This study sought to evaluate the sensitivity of the real-time quaking-induced conversion (RT-QuIC) assay by using recto-anal mucosa-associated lymphoid tissue (RAMALT) biopsy specimens and nasal brush samples collected antemortem from farmed white-tailed deer ( n = 409). Antemortem findings were then compared to results from ante- and postmortem samples (RAMALT, brainstem, and medial retropharyngeal lymph nodes) evaluated by using the current gold standard in vitro assay, immunohistochemistry (IHC) analysis. We hypothesized that the sensitivity of RT-QuIC would be comparable to IHC analysis in antemortem tissues and would correlate with both the genotype and the stage of clinical disease. Our results showed that RAMALT testing by RT-QuIC assay had the highest sensitivity (69.8%) compared to that of postmortem testing, with a specificity of >93.9%. These data suggest that RT-QuIC, like IHC analysis, is an effective assay for detection of PrP CWD in rectal biopsy specimens and other antemortem samples and, with further research to identify more sensitive tissues, bodily fluids, or experimental conditions, has potential for large-scale and rapid automated testing for CWD diagnosis.

Journal of Clinical Microbiology↗

USGS2018

Effects of antecedent streamflow and sample timing on trend assessments of fish, invertebrate, and diatom communities

Detecting trends in biological attributes is central to many stream monitoring programs; however, understanding how natural variability in environmental factors affects trend results is not well understood. We evaluated the influence of antecedent streamflow and sample timing (covariates) on trend estimates for fish, invertebrate, and diatom taxa richness and biological condition from 2002 to 2012 at 51 sites distributed across the conterminous United States. A combination of linear regression and Kendall‐tau test for trends were used to evaluate covariate influence on trend estimates. Adjusting for covariates changed the magnitude of trend estimates in two‐thirds of cases on average by 21%, most often reducing the estimated magnitude of the trend. Additionally, covariates influenced the interpretation of over one‐third of trend estimates by either strengthening or weakening trends after adjustment. Our findings clearly indicate that antecedent streamflow and sample timing influences trend estimates and subsequent interpretation. Accounting for covariates during trend analysis will enhance stream monitoring programs by providing a better understanding and interpretation of estimated changes in biological endpoints at monitored sites. Failure to account for antecedent streamflow and sample timing may lead to mischaracterization of a trend and/or misunderstanding of potential causes.

Journal of the American Water Resources Associatio↗

USGS2022

Assessing spatial transferability of a random forest metamodel for predicting drainage fraction

Fully distributed hydrological models are widely used in groundwater management, but model speed and data requirements impede their use for decision support purposes. Metamodels provide a simpler and faster model which emulates the underlying complex model using machine learning techniques. However, metamodel predictions beyond the ranges, in space and/or time, of training data are highly uncertain, and thus it is important to assess the predictive model performance to ranges outside the training data, i.e., model transferability . We present a novel methodology for evaluating model transferability to areas not contained in the training data set, based on various metrics that quantify the differences in covariate distributions between training and testing data. The transferability method can be employed as a screening tool to assess the suitability of a metamodel for spatial prediction beyond its training domain. We evaluated this transferability approach on a Random Forest metamodel of a 1000 km 2 fully distributed coupled groundwater model for predicting drainage fraction, the partitioning of infiltrating water between drains and groundwater. We conducted spatial cross-validation on 9 holdout sub-basins to assess metamodel transferability beyond sampling locations and compared this estimate with a random split-sample validation test. Using mappable covariates only, the metamodel showed high performance (R 2 = 0.79) tested on a 20% randomly sampled holdout. Conversely, metamodel performance significantly decreased for the 9 spatial holdouts (R 2 ranging from 0.13 to 0.61). We document that the proposed transferability metric correlates with metamodel predictive performance, and demonstrate its use to assess model transferability to datasets outside the training data spatial domain.

Journal of Hydrology↗

USGS2012

Crop classification modelling using remote sensing and environmental data in the Greater Platte River Basin, USA

With an ever expanding population, potential climate variability and an increasing demand for agriculture-based alternative fuels, accurate agricultural land-cover classification for specific crops and their spatial distributions are becoming critical to researchers, policymakers, land managers and farmers. It is important to ensure the sustainability of these and other land uses and to quantify the net impacts that certain management practices have on the environment. Although other quality crop classification products are often available, temporal and spatial coverage gaps can create complications for certain regional or time-specific applications. Our goal was to develop a model capable of classifying major crops in the Greater Platte River Basin (GPRB) for the post-2000 era to supplement existing crop classification products. This study identifies annual spatial distributions and area totals of corn, soybeans, wheat and other crops across the GPRB from 2000 to 2009. We developed a regression tree classification model based on 2.5 million training data points derived from the National Agricultural Statistics Service (NASS) Cropland Data Layer (CDL) in relation to a variety of other relevant input environmental variables. The primary input variables included the weekly 250 m US Geological Survey Earth Observing System Moderate Resolution Imaging Spectroradiometer normalized differential vegetation index, average long-term growing season temperature, average long-term growing season precipitation and yearly start of growing season. An overall model accuracy rating of 78% was achieved for a test sample of roughly 215 000 independent points that were withheld from model training. Ten 250 m resolution annual crop classification maps were produced and evaluated for the GPRB region, one for each year from 2000 to 2009. In addition to the model accuracy assessment, our validation focused on spatial distribution and county-level crop area totals in comparison with the NASS CDL and county statistics from the US Department of Agriculture (USDA) Census of Agriculture. The results showed that our model produced crop classification maps that closely resembled the spatial distribution trends observed in the NASS CDL and exhibited a close linear agreement with county-by-county crop area totals from USDA census data ( R 2 = 0.90).

Greater Platte River Basin↗

USGS2009

Postmortem evaluation of reintroduced migratory Whooping Cranes in eastern North America

Reintroduction of endangered Whooping Cranes ( Grus americana ) in eastern North America has successfully established a migratory population between Wisconsin and Florida. Eighty birds (47 males, 33 females) were released between 2001 and 2006, and all birds were tracked following release with satellite and/or VHF monitoring devices. By the end of 2006, 17 deaths (12 males, five females) were recorded from this population. Postmortem findings and field data were evaluated for each bird to determine the cause of death. Causes included predation ( n =8, 47%), trauma ( n =2, 12%), and degenerative disease ( n =1, 6%); the cause of death was undetermined for 35% ( n =6) of the birds. Based on physical evidence, the primary predator of the birds was the bobcat ( Lynx rufus ). Limited roosting habitat availability or bird behavior were likely prime factors in the occurrence of predation. Traumatic injuries and mortality were caused by gunshot, electrical utility lines, and an unknown source. The lone case of degenerative disease was due to chronic exertional myopathy associated with translocation. Available postmortem testing did not indicate the presence of infectious disease in this limited sample.

Alabama, Florida, Indiana, Michigan, South Carolin↗

USGS1994

Classification of vegetation communities in which geese rear broods on the Yukon-Kuskokwim Delta, Alaska

Plant communities are described from an area on the Yukon – Kuskokwim (Y-K) delta of Alaska that is used extensively for brood rearing by three species of geese. Earlier studies identified plant species important as food for young geese, but few studies describe or quantify plant communities. We classified species presence or absence information from over 700 quadrats using a two-way indicator species analysis ( TWINSPAN ) and then tested for agreement of signatures on colour infrared air photos with the identified communities. Sedges were found to dominate all but the wettest and driest communities. Most of the brood-rearing area was covered by Carex ramenskii and Carex rariflora meadows, ponds, Carex mackenziei -dominated pond margins, and C . ramenskii and grass levee meadows. Our interpretation of airphotos accurately predicted vegetation community classes, which will facilitate future studies of habitat selection by geese during the time they are rearing young. The TWINSPAN classification was comparable to classifications of studies conducted elsewhere on the Y-K delta. The interpretation of air photos will enable the identification and evaluation of wetland vegetation complexes and potential goose brood-rearing areas away from our study site.

Alaska↗