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At least 829 records · Page 46Linked to original sources
USGS2013

The environmental-data automated track annotation (Env-DATA) system: linking animal tracks with environmental data

The movement of animals is strongly influenced by external factors in their surrounding environment such as weather, habitat types, and human land use. With advances in positioning and sensor technologies, it is now possible to capture animal locations at high spatial and temporal granularities. Likewise, scientists have an increasing access to large volumes of environmental data. Environmental data are heterogeneous in source and format, and are usually obtained at different spatiotemporal scales than movement data. Indeed, there remain scientific and technical challenges in developing linkages between the growing collections of animal movement data and the large repositories of heterogeneous remote sensing observations, as well as in the developments of new statistical and computational methods for the analysis of movement in its environmental context. These challenges include retrieval, indexing, efficient storage, data integration, and analytical techniques.

Movement Ecology↗
USGS2020

Population and habitat analyses for greater sage-grouse (Centrocercus urophasianus) in the bi-state distinct population segment—2018 update

Executive Summary The Bi-State Distinct Population Segment (Bi-State DPS) of greater sage-grouse ( Centrocercus urophasianus , hereinafter “sage-grouse”) represents a genetically distinct and geographically isolated population that straddles the border between Nevada and California. The primary threat to these sage-grouse populations is the expansion of single-leaf pinyon ( Pinus monophylla ) and Utah juniper ( Juniperus osteosperma ) into sagebrush ecosystems, which fragments and reduces population connectivity and survival. Other important threats include low water availability during brood-rearing, particularly during drought, and increased predation by common ravens ( Corvus corax ), a generalist predator often associated with anthropogenic resource subsidies. Although the Bi-State DPS occurs at high elevations relative to sage-grouse range-wide, changes in historical wildfire cycles and the conversion of native shrubs to invasive annual grasslands still threaten these populations. The Bi-State DPS has undergone multiple federal status assessments and associated litigation. For example, in October of 2013, the Bi-State DPS was proposed for listing as threatened under the Endangered Species Act of 1973 by the U.S. Fish and Wildlife Service (USFWS), then withdrawn in April 2015. The withdrawal decision was challenged, and in May 2018, a Federal district court ordered the withdrawal decision to be vacated, and USFWS was required to re-open the October 2013 listing evaluation. In response, the U.S. Geological Survey (USGS), with State and Federal collaborators, embarked on a multipronged analysis to provide current and best available science regarding population status of sage-grouse within the Bi-State DPS. Using data from a long-term monitoring program, we carried out four analytical study objectives, and here, we provide preliminary results of these analyses. First, we used integrated population modeling (IPM) to predict annual population abundance and annual finite rate of population change for the Bi-State DPS, as a whole, and for each subpopulation between 1995 and 2018. Because sage-grouse exhibit population cycles (periodic increases and decreases in abundance across approximately 6- to 10-year wavelengths), we estimated trends across three nested temporal scales that represent one (11 years), two (18 years), and three (24 years) complete population cycles. These estimates of relatively long-term averaged population change account for temporal (that is, interannual) variation. Our model predicted population abundance for the Bi-State DPS during 2018 at 3,305 individuals (2,247–4,683), with the majority occupying Bodie Hills and Long Valley. The model also predicted cyclic dynamics in abundance through time with evidence of 24-year population growth and slight trends of decline over the past 18 years. Specifically, across the Bi-State DPS as a whole, we estimated annual average at 0.99, 0.99, and 1.02 over the one, two, and three population cycles, which equated to a 10.5 percent, 16.6 percent decrease, and 60.0 percent increase in abundance over the 11-, 18-, and 24-year cycles. Estimated abundance in 2018 had not reached numbers lower than those predicted during 1995. However, we found spatial variation in population trends across the three cycles. Bodie Hills subpopulation comprised the greatest (1,521) and exhibited average annual greater than 1.0 across all periods resulting in average annual increases of 7 percent. This relatively large subpopulation has grown 5 times larger than what was predicted in 1995 while experiencing cyclical dynamics within that period. Conversely, other smaller subpopulations within the Bi-State DPS exhibited average annual equal to or less than 1.0 resulting in estimated 10-year risks of extirpation ranging from 2.0 to 76.1 percent. In general, evidence of decline among smaller subpopulations was greatest for the most recent period (2008–18) compared to a period that encompassed three full population cycles (24-year). This difference coincides with an intense period of drought that began in 2012. For comparative purposes as part of this first objective, we conducted a similar analysis for populations of sage-grouse within Nevada and California but outside the Bi-State DPS. We developed a region-wide and distance-weighted IPM using lek count from Nevada Department of Wildlife (NDOW) and California Department of Fish and Wildlife (CDFW) databases and with telemetry data collected by USGS across 12 sage-grouse subpopulations. Our models predicted similar patterns in population cycling outside the Bi-State DPS but with much stronger evidence of long-term declines across 24 years. Specifically, median averaged across each year of the 11-, 18-, and 24-year periods resulted in average annual values of 0.94, 0.97, and 0.99, respectively. These values equate to 41.0 percent, 38.5 percent, and 21.3 percent declines over the corresponding periods. Second, we used lek count data in a state-space modeling framework to compare trends in population abundance across different spatial scales (that is, leks versus Bi-State DPS). This hierarchical framework allowed us to disentangle declines associated with climate conditions as opposed to other local level factors that might signal the need for management intervention. Specifically, we identified 7 leks that were both declining and recently decoupled from larger spatial scale trends, typically governed by climatic conditions (referred to as soft or hard signals). The goal of this analysis was to provide an early warning system that might have implications for conservation actions at local scales. Third, we developed phenological (spring, summer–fall, and winter) and reproductive life stage (nesting, early brood-rearing, and late-brood rearing) based resource selection functions using various environmental covariates. We report rankings of variable importance for each season and life stage, developed maps of habitat selection indices (HSI), binned categories representing low, moderate, and high classes of quality (where any category greater than or equal to low indicated selected habitat) for each phenological season and life stage, and produced composite maps by selected phenological and reproductive stage to estimate annual habitat. Fourth, we used for each lek within the Bi-State DPS to carry out a spatial analysis that quantified substantial changes in the distribution of occupied habitat across long- (24-year) and short- (11-year) term periods. Owing to differences among available datasets, the long-term analysis primarily reflected spatial shifts among subpopulations comprising the majority of the Bi-State DPS (that is, Bodie Hills and Long Valley) while the short-term analysis also quantified changes among subpopulations along the periphery. Over long and short-term periods, the overall distribution of occupied habitat (as measured by 99 percent utilization distributions intersecting any quantified habitat) was reduced by 20,573 ha and 55,492 ha, respectively. Occupied core areas (as measured by 50 percent utilization distributions intersecting any quantified habitat) over long-term periods were solely located in Bodie Hills and Long Valley. Although nearly all subpopulations experienced contractions in occupied overall and core distribution, Bodie Hills experienced spatial expansion that occurred with concomitant spatial contraction at Long Valley over both periods. Subpopulations at the northern (Pine Nuts), central (Sagehen) and southern (White-Mountains) extents of the Bi-State DPS also experienced spatial contraction over the short-term period. These findings, coupled with those of population trends, indicate long-term patterns in redistribution of sage-grouse from Long Valley and peripheral subpopulations to Bodie Hills. That is, sage-grouse subpopulations at the periphery are declining while the largest population at the core is increasing, which could have meaningful impacts on overall metapopulation persistence. We provide evidence for loss of occupied habitat (reduced distribution) given local extirpation of subpopulations. Fifth, we calculated percentages of selected phenological, life stage, and annual habitat that each subpopulation contributed to the Bi-State DPS. We then intersected these maps with a composite estimate of occupied habitat from the fourth objective and calculated percentages of selected habitat likely occupied by sage-grouse that each subpopulation contributed to the Bi-State DPS. These values provide evidence for loss of occupied habitat and subsequent reductions in spatial distribution given reductions in abundance and, in some cases, extirpation of leks within subpopulations. Lastly, we carried out an initial in-depth analysis of selection for irrigated pastures and wet meadows during the brood-rearing stage for the Long Valley subpopulation. We chose this subpopulation because it represents a population core, representing 26.5 percent of total sage-grouse within the Bi-State DPS, and has exhibited long-term declines in abundance and distribution. This subpopulation is highly sensitive to precipitation and other factors that influence water availability. Models predicted higher use of the interior portions of irrigated pastures and wet meadows during late brood-rearing period, which represented a potentially risky use of habitat that was exacerbated during periods of low moisture (for example, drought, reduced water delivery, or both). Sage-grouse typically used edges of riparian areas and pastures, largely because the interior of these mesic areas consisted of considerably less overhead concealment cover (for example, shrubs) that likely resulted in a higher risk of mortality. We found that a lack of water delivery to pastures in the form of overwinter precipitation or diversion ditches increased the movements of sage-grouse to the interior of pastures. Although further investigation of water delivery impacts on chick survival are warrented, our initial findings regarding resource selection may explain recent declines in population growth at Long Valley.

California, Nevada↗
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↗
USGS2005

Simulated water sources and effects of pumping on surface and ground water, Sagamore and Monomoy flow lenses, Cape Cod, Massachusetts

The sandy sediments underlying Cape Cod, Massachusetts, compose an important aquifer that is the sole source of water for a region undergoing rapid development. Population increases and urbanization on Cape Cod lead to two primary environmental effects that relate directly to water supply: (1) adverse effects of land use on the quality of water in the aquifer and (2) increases in pumping that can adversely affect environmentally sensitive surface waters, such as ponds and streams. These considerations are particularly important on the Sagamore and Monomoy flow lenses, which underlie the largest and most populous areas on Cape Cod. Numerical models of the two flow lenses were developed to simulate ground-water-flow conditions in the aquifer and to (1) delineate areas at the water table contributing water to wells and (2) estimate the effects of pumping and natural changes in recharge on surface waters. About 350 million gallons per day (Mgal/d) of water recharges the aquifer at the water table in this area; most water (about 65 percent) discharges at the coast and most of the remaining water (about 28 percent) discharges into streams. A total of about 24.9 Mgal/d, or about 7 percent, of water in the aquifer is withdrawn for water supply; most pumped water is returned to the hydrologic system as return flow creating a state of near mass balance in the aquifer. Areas at the water table that contribute water directly to production wells total about 17 square miles; some water (about 10 percent) pumped from the wells flows through ponds prior to reaching the wells. Current (2003) steady-state pumping reduces simulated ground-water levels in some areas by more than 4 feet; projected (2020) pumping may reduce water levels by an additional 3 feet or more in these same areas. Current (2003) and future (2020) pumping reduces total streamflow by about 4 and 9 cubic feet per second (ft3/s), corresponding to about 5 percent and 9 percent, respectively, of total streamflow. Natural recharge varies with time, over both monthly and multiyear time scales. Monthly changes in recharge cause pond levels to vary between 1 and 2 feet in an average year; annual changes in recharge, which can be much larger than monthly variations, can cause pond levels to vary by more than 10 feet in some areas over a period of years. Streamflow, which also changes in response to changes in recharge, varies by a factor of two over an average year and can vary more over multiyear periods. On average, monthly pumping ranges from 15.8 Mgal/d in March to 45.3 Mgal/d in August. Pumping and the distribution of return flow can seasonally affect the hydrologic system by lowering ground-water and pond levels and by depleting streamflows, particularly in the summer months. Maximum drawdowns in March and August exceed 3 feet and 6 feet, respectively, for current (2003) pumping. Simulated drawdowns from projected (2020) pumping, relative to water levels representing 2003 pumping conditions, exceed 2 feet in March and 5 feet in August. Current (2003) and future (2020) pumping can decrease pond levels in some areas by more than 3 feet; drawdown generally is largest during the month of August of an average year. Over multiyear periods, seasonal pumping can lower pond levels in some areas by more than 4 feet; the effects of seasonal pumping are largest during periods of reduced recharge. Monthly streamflow depletion varies in individual streams but can exceed 2 ft3/s in some streams. The combined effects of seasonal pumping and drought can reduce pond levels by more than 10 feet below average levels. Water levels in Mary Dunn Pond, which is in an area of large current and projected pumping, are predicted (2020) to decline during drought conditions by about 10.6 feet: about 6.9 feet from lower recharge, about 2.3 feet from current (2003) pumping, and about 1.4 feet from additional future (2020) pumping. The results indicate that pumping generally does not cause substantial streamflow depletion and that the primary effect of pumping is on water levels in ponds. Natural changes in recharge account for most of the variation in pond levels; however, pumping can cause substantial declines in the levels of ponds near pumping wells. Also, the effects of pumping and recharge can combine to cause drawdowns of more than 10 feet in some areas.

Massachusetts↗
USGS1977

Shelled benthic fauna of the eastern Chukchi Sea

The purposes of this study were to identify the benthic shelled infauna and epifauna of the eastern Chukchi Sea, compile species lists and distribution maps, determine recurrent groups of species (communities), and examine the environmental parameters that may control the distribution of the faunal groups. The study was partly supported by the Bureau of Land Management through an interagency agreement with the National Oceanic and Atmospheric Administration, under which a multi-year program responding to the needs of petroleum development of the Alaskan continental shelf is managed by the Outer Continental Shelf Environmental Assessment Program (OCSEAP) Office. The objective of this study is to provide an assessment of the biological patterns of the region as related to petroleum development. Future offshore oil leases proposed by the State of Alaska and the Federal Government require a biological data base from which impact statements can be derived. Samples used in this report were collected by the U.S. Geological Survey in August 1974 from the U.S. Coast Guard Cutter Burton Island under the direction of Arthur Grantz. Sampling was conducted using van Veen grabs, gravity cores, dart cores, and bottom dredges. Only the van Veen grabs contained material useful for this study. At present 103 samples containing 90 species have been examined.

Alaska↗
USGS2019

Evaluating environmental change and behavioral decision-making for sustainability policy using an agent-based model: A case study for the Smoky Hill River Watershed, Kansas

Sustainability has been at the forefront of the environmental research agenda of the integrated anthroposphere, hydrosphere, and biosphere since the last century and will continue to be critically important for future environmental science. However, linking humans and the environment through effective policy remains a major challenge for sustainability research and practice. Here we address this gap using an agent-based model (ABM) for a coupled natural and human systems in the Smoky Hill River Watershed (SHRW), Kansas, USA. For this freshwater-dependent agricultural watershed with a highly variable flow regime influenced by human-induced land-use and climate change, we tested the support for an environmental policy designed to conserve and protect fish biodiversity in the SHRW. We develop a proof of concept interdisciplinary ABM that integrates field data on hydrology, ecology (fish richness), social-psychology (value-belief-norm) and economics, to simulate human agents' decisions to support environmental policy. The mechanism to link human behaviors to environmental changes is the social-psychological sequence identified by the value-belief-norm framework and is informed by hydrological and fish ecology models. Our results indicate that (1) cultural factors influence the decision to support the policy; (2) a mechanism modifying social-psychological factors can influence the decision-making process; (3) there is resistance to environmental policy in the SHRW, even under potentially extreme climate conditions; and (4) the best opportunities for policy acceptance were found immediately after extreme environmental events. The modeling approach presented herein explicitly links biophysical and social science has broad generality for sustainability problems.

Kansas↗
USGS2009

Responses of benthic macroinvertebrates to urbanization in nine metropolitan areas of the conterminous United States

The effects of urbanization on benthic macroinvertebrates were investigated in nine metropolitan areas (Boston, MA; Raleigh, NC; Atlanta, GA; Birmingham, AL; Milwaukee–Green Bay, WI; Denver, CO; Dallas–Fort Worth, TX; Salt Lake City, UT; and Portland, OR) as a part of the U.S. Geological Survey National Water Quality Assessment Program. Several invertebrate metrics showed strong, linear responses to urbanization when forest or shrublands were developed. Responses were difficult to discern in areas where urbanization was occurring on agricultural lands because invertebrate assemblages were already severely degraded. There was no evidence that assemblages showed any initial resistance to urbanization. Ordination scores, EPT taxa richness, and the average tolerance of organisms were the best indicators of changes in assemblage condition at a site. Richness metrics were better indicators than abundance metrics, and qualitative samples were as good as quantitative samples. A common set of landscape variables (population density, housing density, developed landcover, impervious surface, and roads) were strongly correlated with urbanization and invertebrate responses in all non-agricultural areas. The instream environmental variables (hydrology, water chemistry, habitat, and temperature) that were strongly correlated with urbanization and invertebrate responses were influenced by environmental setting (e.g., dominant ecoregion) and varied widely among metropolitan areas. Multilevel hierarchical regression models were developed that predicted invertebrate responses using only two landcover variables—basinscale landcover (percentage of basin area in developed land) and regional-scale landcover (antecedent agricultural land).

Conference Paper↗
USGS2021

Method development for a short-term 7-day toxicity test with unionid mussels

The US Environmental Protection Agency's short-term freshwater effluent test methods include a fish ( Pimephales promelas ), a cladoceran ( Ceriodaphnia dubia ), and a green alga ( Raphidocelis subcapitata ). There is a recognized need for additional taxa to accompany the three standard species for effluent testing. An appropriate additional taxon is unionid mussels because mussels are widely distributed, live burrowed in sediment and filter particles from the water column for food, and exhibit high sensitivity to a variety of contaminants. Multiple studies were conducted to develop a relevant and robust short-term test method for mussels. We first evaluated the comparative sensitivity of two mussel species ( Villosa constricta and Lampsilis siliquoidea ) and two standard species ( P. promelas and C. dubia ) using two mock effluents prepared by mixing ammonia and five metals (cadmium, copper, nickel, lead, and zinc) or a field-collected effluent in 7-day exposures. Both mussel species were equally or more sensitive (more than two-fold) to effluents compared with the standard species. Next, we refined the mussel test method by first determining the best feeding rate of a commercial algal mixture for three age groups (1, 2, and 3 weeks old) of L. siliquoidea in a 7-day feeding experiment, and then used the derived optimal feeding rates to assess the sensitivity of the three ages of juveniles in a 7-day reference toxicant (sodium chloride [NaCl]) test. Juvenile mussels grew substantially (30%–52% length increase) when the 1- or 2-week-old mussels were fed 2 ml twice daily and the 3-week-old mussels were fed 3 ml twice daily. The 25% inhibition concentrations (IC25s) for NaCl were similar (314–520 mg Cl/L) among the three age groups, indicating that an age range of 1- to 3-week-old mussels can be used for a 7-day test. Finally, using the refined test method, we conducted an interlaboratory study among 13 laboratories to evaluate the performance of a 7-day NaCl test with L. siliquoidea . Eleven laboratories successfully completed the test, with more than 80% control survival and reliable growth data. The IC25s ranged from 296 to 1076 mg Cl/L, with a low (34%) coefficient of variation, indicating that the proposed method for L. siliquoidea has acceptable precision. Environ Toxicol Chem 2021;40:3392–3409. © 2021 SETAC

Environmental Toxicology and Chemistry↗
USGS2022

Stage-specific environmental correlates of reproductive success in Boreal Toads (Anaxyrus boreas boreas)

Compensatory recruitment can facilitate the persistence of populations experiencing high adult mortality. Because early life-stages of many taxa, including amphibians, are difficult to mark and recapture, sources of variation in survival at these stages often are unknown, which creates barriers to improving in situ recruitment rates. We leveraged count data and open N-mixture models to examine the environmental factors associated with the hatching of egg clutches, tadpole survival, and probability of metamorphosis in Boreal Toads ( Anaxyrus boreas boreas ) that inhabit pastures leased for cattle grazing in western Wyoming, USA. We conducted weekly surveys and measured a suite of environmental variables at 20 breeding ponds during May–September 2018. The hatching of egg clutches was most strongly related to pond surface area, as clutches often desiccated at smaller ponds. Weekly tadpole survival was lowest in ponds with high abundance of aquatic predators. Predation did not preclude metamorphosis, which was more strongly associated with higher dissolved oxygen and vegetation cover. Cattle grazing reduced vegetation cover in and around breeding ponds, which resulted in lower levels of dissolved oxygen. Grazing-induced habitat changes are therefore likely to negatively influence tadpole metamorphosis both via indirect effects on dissolved oxygen, and direct effects on vegetation cover, which also serves as feeding sites and escape cover from predators. We demonstrate the success of three critical phases in early life-stage development (egg hatching, tadpole survival, metamorphosis) was associated with different environmental factors. The inclusion of stage-specific responses in demographic analyses is therefore critical for a thorough understanding of what limits populations.

Journal of Herpetology↗
USGS2019

Phosphorus and nitrogen transport in the binational Great Lakes Basin estimated using SPARROW watershed models

Eutrophication problems in the Great Lakes are caused by excessive nutrient inputs (primarily phosphorus, P, and nitrogen, N) from various sources throughout its basin. In developing protection and restoration plans, it is important to know where and from what sources the nutrients originate. As part of a binational effort, Midcontinent SPARROW (SPAtially Referenced Regression On Watershed attributes) models were developed and used to estimate P and N loading from throughout the entire basin based on nutrient inputs similar to 2002; previous SPARROW models only estimated U.S. contributions. The new models have a higher resolution (~2‐km 2 catchments) enabling improved descriptions of where nutrients originate and the sources at various spatial scales. The models were developed using harmonized geospatial datasets describing the stream network, nutrient sources, and environmental characteristics affecting P and N delivery. The models were calibrated using loads from sites estimated with ratio estimator and regression techniques and additional statistical approaches to reduce spatial correlation in the residuals and have all monitoring sites equally influence model development. SPARROW results, along with interlake transfers and direct atmospheric inputs, were used to quantify the entire P and N input to each lake and describe the importance of each nutrient source. Model results can be used to compare loading and yields from various tributaries and jurisdictions.

Great Lakes↗
USGS2013

Developing and implementing the use of predictive models for estimating water quality at Great Lakes beaches

Predictive models have been used at beaches to improve the timeliness and accuracy of recreational water-quality assessments over the most common current approach to water-quality monitoring, which relies on culturing fecal-indicator bacteria such as Escherichia coli (E. coli.) . Beach-specific predictive models use environmental and water-quality variables that are easily and quickly measured as surrogates to estimate concentrations of fecal-indicator bacteria or to provide the probability that a State recreational water-quality standard will be exceeded. When predictive models are used for beach closure or advisory decisions, they are referred to as “nowcasts.” During the recreational seasons of 2010-12, the U.S. Geological Survey (USGS), in cooperation with 23 local and State agencies, worked to improve existing nowcasts at 4 beaches, validate predictive models at another 38 beaches, and collect data for predictive-model development at 7 beaches throughout the Great Lakes. This report summarizes efforts to collect data and develop predictive models by multiple agencies and to compile existing information on the beaches and beach-monitoring programs into one comprehensive report. Local agencies measured E. coli concentrations and variables expected to affect E. coli concentrations such as wave height, turbidity, water temperature, and numbers of birds at the time of sampling. In addition to these field measurements, equipment was installed by the USGS or local agencies at or near several beaches to collect water-quality and metrological measurements in near real time, including nearshore buoys, weather stations, and tributary staff gages and monitors. The USGS worked with local agencies to retrieve data from existing sources either manually or by use of tools designed specifically to compile and process data for predictive-model development. Predictive models were developed by use of linear regression and (or) partial least squares techniques for 42 beaches that had at least 2 years of data (2010-11 and sometimes earlier) and for 1 beach that had 1 year of data. For most models, software designed for model development by the U.S. Environmental Protection Agency (Virtual Beach) was used. The selected model for each beach was based on a combination of explanatory variables including, most commonly, turbidity, day of the year, change in lake level over 24 hours, wave height, wind direction and speed, and antecedent rainfall for various time periods. Forty-two predictive models were validated against data collected during an independent year (2012) and compared to the current method for assessing recreational water quality-using the previous day’s E. coli concentration (persistence model). Goals for good predictive-model performance were responses that were at least 5 percent greater than the persistence model and overall correct responses greater than or equal to 80 percent, sensitivities (percentage of exceedances of the bathing-water standard that were correctly predicted by the model) greater than or equal to 50 percent, and specificities (percentage of nonexceedances correctly predicted by the model) greater than or equal to 85 percent. Out of 42 predictive models, 24 models yielded over-all correct responses that were at least 5 percent greater than the use of the persistence model. Predictive-model responses met the performance goals more often than the persistence-model responses in terms of overall correctness (28 versus 17 models, respectively), sensitivity (17 versus 4 models), and specificity (34 versus 25 models). Gaining knowledge of each beach and the factors that affect E. coli concentrations is important for developing good predictive models. Collection of additional years of data with a wide range of environmental conditions may also help to improve future model performance. The USGS will continue to work with local agencies in 2013 and beyond to develop and validate predictive models at beaches and improve existing nowcasts, restructuring monitoring activities to accommodate future uncertainties in funding and resources.

Great Lakes↗
USGS2010

USGS Toxic Substances Hydrology Program, 2010

The U.S. Geological Survey (USGS) Toxic Substances Hydrology Program adapts research priorities to address the most important contamination issues facing the Nation and to identify new threats to environmental health. The Program investigates two major types of contamination problems: * Subsurface Point-Source Contamination, and * Watershed and Regional Contamination. Research objectives include developing remediation methods that use natural processes, characterizing and remediating contaminant plumes in fractured-rock aquifers, identifying new environmental contaminants, characterizing new and understudied pesticides in common pesticide-use settings, explaining mercury methylation and bioaccumulation, and developing approaches for remediating watersheds affected by active and historic mining.

Fact Sheet↗
USGS2020

Changes in physiology and microbial diversity in larval ornate chorus frogs are associated with habitat quality

Environmental change associated with anthropogenic disturbance can lower habitat quality, especially for sensitive species such as many amphibians. Variation in environmental quality may affect an organism’s physiological health and, ultimately, survival and fitness. Using multiple health measures can aid in identifying populations at increased risk of declines. Our objective was to measure environmental variables at multiple spatial scales and their effect on three indicators of health in ornate chorus frog ( Pseudacris ornata ) tadpoles to identify potential correlates of population declines. To accomplish this, we measured a glucocorticoid hormone (corticosterone; CORT) profile associated with the stress response, as well as the skin mucosal immune function (combined function of skin secretions and skin bacterial community) and bacterial communities of tadpoles from multiple ponds. We found that water quality characteristics associated with environmental variation, including higher water temperature, conductivity and total dissolved solids, as well as percent developed land nearby, were associated with elevated CORT release rates. However, mucosal immune function, although highly variable, was not significantly associated with water quality or environmental factors. Finally, we examined skin bacterial diversity as it aids in immunity and is affected by environmental variation. We found that skin bacterial diversity differed between ponds and was affected by land cover type, canopy cover and pond proximity. Our results indicate that both local water quality and land cover characteristics are important determinants of population health for ornate chorus frogs. Moreover, using these proactive measures of health over time may aid in early identification of at-risk populations that could prevent further declines and aid in management decisions.

Conservation Physiology↗
USGSDate not supplied

Development of stochastic modeling systems using deterministic models and GIS: Principles and a case study in the Atlantic Zone of Costa Rica

The most important requirements for large-area environmental modeling are a tight integration between models and data, and a close match of the spatial scale at which the model is developed with the scale at which the model is to be applied. To better match the scale of data with that of the model, we propose a set of principles for the development of stochastic modeling systems based on linkage of deterministic models with GIS data. For modeling purposes, a region is usually rasterized into cells and the environmental conditions of those cells are specified by ranges or classes using GIS data layers. It is not necessary to simulate each and every GIS cell in the study area because many cells may have similar environmental conditions and can be grouped together to form cohorts. We define a cohort as the assembly of the cells sharing a unique combination of environmental conditions within the study region. Multiple model simulations can be performed for any given cohort. For each simulation, some of the parameter values can be randomly generated within the specified environmental conditions of the cohort according to a certain statistical distribution which, in turn, can be specified by GIS data layers. By this method the variance and covariance of environmental variables in space and time are integrated into the simulation processes with these modeling systems to make full use of the available data and to assess the uncertainties of the simulated results. An integrated simulation system between CENTURY model and GIS was developed to demonstrate the value of the concepts imbedded in stochastic simulation systems for large area studies.

Conference Paper↗
USGS2003

Some implications of changing patterns of mineral consumption

DeYoung and Menzie (1999) examined the relations among population, Gross Domestic Product, and mineral consumption (aluminum, cement, copper, and salt) for Japan, Korea, and the United States between 1965 and 1995. They noted the extremely rapid growth of consumption in Korea between 1975 and 1995. Concomitantly, Korea's population growth rate declined. This paper extends that earlier work by examining patterns of consumption of these same commodities in the twenty most populous countries for the period 1970 through 1995. Developed countries, such as France, Germany, Japan, the United Kingdom, and the United States, show patterns of consumption that are stable (cement, copper, and salt) or grow slowly (aluminum). Some developing countries, including China, Thailand, and Turkey, show more rapid growth of consumption, especially of cement, copper, and aluminum. These changing patterns of mineral consumption in developing countries have important implications -- if they continue, there could be major increases in world mineral consumption and major increases in environmental residuals from mineral production and use. If China reaches the level of consumption of copper of developed countries, world consumption could reach levels more than twice that of 1995 (10.5 million tons).

Open-File Report↗
USGS2021

Ontogenetic trait shifts: Seedlings display high trait variability during early stages of development

Characterizing variation in plant functional traits is often key to understanding community-level processes and predicting ecosystem responses to environmental change. Trait-based ecology has focused on interspecific trait variation, but sources and consequences of within-species ontogenetic trait variation, particularly during early stages of development, remain understudied. Using a manipulative greenhouse experiment, we investigated trait variation during early stages of seedling development in seven dominant perennial plant species in the western United States. We examined variability in key trait values (i.e. SLA, root:shoot ratio (RSR), specific root length (SRL) and root dry matter content (RDMC)) of 20- to 62-day-old seedlings grown under low and high levels of water availability. We also compared these to compiled trait databases to assess how representative these readily available data sources are of seedling trait values. Early seedling trait values shifted greatly during early stages of development and generally differed from average plant trait database values. Trait shifts were greatest in forbs versus grasses. Overall, observed trait shifts suggested a transition from fast-growing resource acquisitional strategies towards more slow-growing conservative strategies over time. For example, seedling SLA decreased while RSR and RDMC increased over time. That seedling trait values aconsistently differed from trait database values indicates that plant trait database values may be poor predictors of seedling trait values. Such mismatches in species trait information could result in inaccurate predictions of community assembly outcomes or incongruities between seedling traits and environmental filters experienced by seedlings during early stages of recruitment in applied settings. We suggest that additional work is needed to characterize intraspecific trait variation across plant ontogeny, and that this information should be incorporated into studies ranging from understanding early plant growth and survival to evaluating the outcomes of ecological restoration.

Functional Ecology↗
USGS2025

Properties of solid bitumen formed during hydrous, anhydrous, and brine pyrolysis of oil shale: Implications for solid bitumen reflectance in source-rock reservoirs

Solid bitumen reflectance (BR o in %) is widely used as a thermal maturity proxy in source-rock reservoirs, yet solid bitumen texture and physical attributes may be affected by varying environmental constraints during its formation, e.g., water saturation, mineral catalysis, or salinity. Herein we investigated the development of solid bitumen properties during artificial maturation using three diverse (lacustrine to marine) oil shale samples containing abundant amorphous H-rich sedimentary organic matter (bituminite). The oil shales were treated via pyrolysis (320 °C, 72 h) using hydrous, anhydrous, and brine conditions, causing the development of a newly formed solid bitumen in the experiment residues from the thermal conversion of bituminite. The properties of the newly formed solid bitumen then were evaluated via geochemical screening tests, optical and electron microscopy, and infrared spectroscopy. Experimental residues also were treated via solvent extraction, allowing characterization of the effects of extraction on solid bitumen. Results showed that bituminite with higher resin and asphaltene components evolved to a solid bitumen with higher reflectance (as a percentage of the original value) when exposed to the same heat treatment, relative to bituminite with higher saturate and aromatic components. Aromatization of solid bitumen also was generally more pronounced in the presence of deionized water relative to anhydrous conditions, supporting prior observations. These results suggest the compositions of primary sedimentary organic matter, and the local concentration of water, affect the development of solid bitumen during thermal advance, potentially explaining the origin of multiple solid bitumen populations with varying reflectance in source-rock reservoir samples or in a single microscope field. Experiments using brine were inconclusive regarding enhanced/decreased aromatization, which could be attributed to the salinities of the brines used in the tests. Extraction of residues caused a consistent increase in BR o values, suggesting that migrating or expelled oils could cause an increase in BR o via natural solvation and absent an increase in temperature. This work provides insights into the development and evolution of BR o in source-rock reservoirs as a function of the composition of the original bituminite and changing environmental conditions, with potentially broad application for petroleum prospecting and resource estimation.

Colorado↗
USGS2005

Acute toxicity value extrapolation with fish and aquatic invertebrates

Assessment of risk posed by an environmental contaminant to an aquatic community requires estimation of both its magnitude of occurrence ( exposure ) and its ability to cause harm ( effects ). Our ability to estimate effects is often hindered by limited toxicological information. As a result, resource managers and environmental regulators are often faced with the need to extrapolate across taxonomic groups in order to protect the more sensitive members of the aquatic community. The goals of this effort were to 1) compile and organize an extensive body of acute toxicity data, 2) characterize the distribution of toxicant sensitivity across taxa and species, and 3) evaluate the utility of toxicity extrapolation methods based upon sensitivity relations among species and chemicals. Although the analysis encompassed a wide range of toxicants and species, pesticides and freshwater fish and invertebrates were emphasized as a reflection of available data. Although it is obviously desirable to have high-quality acute toxicity values for as many species as possible, the results of this effort allow for better use of available information for predicting the sensitivity of untested species to environmental contaminants. A software program entitled “Ecological Risk Analysis” (ERA) was developed that predicts toxicity values for sensitive members of the aquatic community using species sensitivity distributions. Of several methods evaluated, the ERA program used with minimum data sets comprising acute toxicity values for rainbow trout, bluegill, daphnia, and mysids provided the most satisfactory predictions with the least amount of data. However, if predictions must be made using data for a single species, the most satisfactory results were obtained with extrapolation factors developed for rainbow trout (0.412), bluegill (0.331), or scud (0.041). Although many specific exceptions occur, our results also support the conventional wisdom that invertebrates are generally more sensitive to contaminants than fish are.

Archives of Environmental Contamination and Toxico↗