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USGS1982

Results of a modeling workshop concerning economic and environmental trends and concomitant resource management issues in the Mobile Bay area

During the past decade, the southern regions of the U.S. have experienced rapid change which is expected to continue into the foreseeable future. Growth in population, industry, and resource development has been attributed to a variety of advantages such as an abundant and inexpensive labor force, a mild climate, and the availability of energy, water, land, and other natural resources. While this growth has many benefits for the region, it also creates the potential for increased air, water, and solid waste pollution, and modification of natural habitats. A workshop was convened to consider the Mobile Bay area as a site-specific case of growth and its environmental consequences in the southern region. The objectives of the modeling workshop were to: (1) identify major factors of economic development as they relate to growth in the area over the immediate and longer term; (2) identify major environmental and resource management issues associated with this expected growth; and (3) identify and characterize the complex interrelationships among economic and environmental factors. This report summarizes the activities and results of a modeling workshop concerning economic growth and concomitant resource management issues in the Mobile Bay area. The workshop was organized around construction of a simulation model representing the relationships between a series of actions and indicators identified by participants. The workshop model had five major components. An Industry Submodel generated scenarios of growth in several industrial and transportation sectors. A Human Population/Economy Submodel calculated human population and economic variables in response to employment opportunities. A Land Use/Air Quality Submodel tabulated changes in land use, shoreline use, and air quality. A Water Submodel calculated indicators of water quality and quantity for fresh surface water, ground water, and Mobile Bay based on discharge information provided by the Industry and Human Population/Economy Submodels. Finally, a Fish Submodel calculated indicators of habitat quality for finfish and shellfish, utilizing information on water quality and wetlands acreage. The workshop was successful in identifying many of the critical interrelations between components of the Mobile area system. Not all of those interactions, such as the feedback of air quality as a limitation on development, could be incorporated into the workshop model because of the model's broad spatial scale and because of uncertainties or data gaps. Thus, the value of the modeling workshop was in the areas outlines below, rather than in the predictive power of the initial model developed at the workshop. First, participants developed a holistic perspective on the interactions which will determine future economic and environmental trends within the Mobile Bay area. Potential environmental consequences and limitations to grown identified at the workshop included: shoreline and water access; water quality of Mobile Bay; finfish and shellfish habitat quality with respect to dissolved oxygen and coliforms; air quality; and acreage of critical wetland habitat. Second, the model's requirements for specific, quantitative information stimulated supporting analyses, such as economic input-output calculations, which provide additional insight into the Mobile Bay area system. Third, the perspective of the Mobile area as an interacting system was developed in an open, cooperative forum which my provide a foundation for conflict resolution based on common understanding. Finally, the identification of model limitations and uncertainties should be useful in guiding the efficient allocation of future research effort.

Alabama↗

USGS2004

Selenium loading through the Blackfoot River watershed--linking sources to ecosystem

The upper Blackfoot River watershed in southeast Idaho receives drainage from 11 of 16 phosphate mines that have extracted ore from the Phosphoria Formation, three of which are presently active. Toxic effects from selenium (Se), including death of livestock and deformity in aquatic birds, were documented locally in areas where phosphatic shales are exposed ( Piper et al., 2000 ; Presser et al., Chapter 11). Current drainage conditions are leading to Se bioaccumulation at concentrations that pose a risk to fish in the Blackfoot River and its tributaries (Hamilton et al., Chapter 18). A gaging station on the Blackfoot River was re-activated in April 2001 to assess hydrologic conditions and concentration, load, and speciation for Se discharges on a watershed scale. The gaging-station data are considered to represent regional drainage conditions in the upper Blackfoot River water- shed because of its location near the outlet of the watershed and directly upstream of the Blackfoot Reservoir. Watershed discharges for 2001 and 2002 were below minimum hydrologic conditions for the gage as documented by the historical record. Drought emergencies were declared in the area in both 2001 and 2002. Unmonitored diversions for irrigation that routinely take place during the snowmelt season also affected conditions downstream. Annual cycles in Se concentration, load, and selenate (Se 6+ ) reached maxima in the spring during the period of maximum flow at the gaging station. Thirty-seven to 44% of annual flow occurred dur- ing the three-month high-flow season (April through June) in 2001 and 56% of annual flow occurred during that time period in 2002. Extrapolation from historical hydrographs for average and wet years and a limited data set of regional Se concentrations for 2001 and 2002 indicated potential for a 3.6- to 7.4-fold increase in Se loading because of increased seasonal flows in the Blackfoot River watershed. Supplementation data indicate that: (a) the difference between total Se and dissolved Se, as a measure of the contribution of particulate Se, was < 10% except at the peak of con- centration when total Se was 18% more than dissolved Se; (b) selenite (Se 4+ ) represented less than 10% of the dissolved species during all months of 2001; and (c) dissolved Se was approximately a 50:50 mixture of selenate and organic selenide (operationally defined Se 2- ) during summer 2001 (June through August). Ecological risk based on regional Se drainage occurred during both the high- and low-flow seasons. Seventy to 83% of the Se load occurred during the high-flow season. During early May of both years, dissolved-Se concentrations exceeded the criterion for the protection of aquatic life and the ecological threshold of 5 gL 1 Se at which sub- stantive risk occurs. During the majority of the three-month high-flow season, dissolved- Se concentrations exceeded the 2 gL 1 Se concern level for aquatic biota. The Se concentration in suspended material during high flow in 2002 was within the range of marginal risk to aquatic life (2-4 gg 1 Se, dry weight). Selenate was the major species during peak flows, with both selenate and organic selenide being major species during relatively low-flow periods in summer. A change in speciation to reduced Se may indicate elevated biotic productivity during summer months and could result in enhanced Se uptake in food webs. In addition to the magnitude of regional Se release in the Blackfoot River watershed, Se concentrations in individual source drains and waste-rock seeps, and those predicted by experimental column leaching of proposed mining overburden materials, also indicate that drainage options that currently meet existing demands for phosphate mining cause eco- logical risk thresholds to be exceeded. At times, the drinking-water Se standard (50 g L 1 Se) and the criterion for hazardous Se waste (1000 L -1 Se) ( US Department of the Interior, 1998 ; US Environmental Protection Agency, 1987 ) are also exceeded. For water-years 2001 and 2002, seasonal increased input of water in the mining area resulted in increased Se transport, suggesting a mechanism of contamination that involves a significant Se reservoir. Hence, recognition and monitoring of Se loading to the envi- ronment on a mass balance basis (i.e. inputs, fluxes and storage within environmental media, and outputs) are essential to evaluating how to control Se concentrations within environmentally protective ranges ( Presser and Piper, 1998 ). In areas where release of Se to aquatic systems is anticipated as a product of future expansion of phosphate mining, continuous monitoring of flow and development of seasonal Se loading patterns would help to model watersheds in terms of sources, flow periods, and environmental-Se con- centrations that most influence bioavailability. These data, in turn, could be linked to Se- bioaccumulation models specific to food webs and vulnerable species of the impacted areas to accurately project ecological effects. Gaging at this site on the Blackfoot River is planned to continue in order to establish a long-term (>10 year) record of hydrologic conditions.

Idaho↗

USGS2024

Transfer learning with convolutional neural networks for hydrological streamline delineation

Hydrological streamline delineation is critical for effective environmental management, influencing agriculture sustainability, river dynamics, watershed planning, and more. This study develops a novel approach to combining transfer learning with convolutional neural networks that capitalize on image-based pre-trained models to improve the accuracy and transferability of streamline delineation. We evaluate the performance of eleven image-based pre-trained models and a baseline model using datasets from Rowan County, North Carolina, and Covington River, Virginia in the USA. Our results demonstrate that when models are adapted to a new area, the fine-tuned ImageNet pre-trained model exhibits superior predictive accuracy, markedly higher than the models trained from scratch or those only fine-tuned on the same area. Moreover, the pre-trained model achieves better smoothness and connectivity between classified streamline channels. These findings underline the effectiveness of transfer learning in enhancing the delineation of hydrological streamlines across varied geographies, offering a scalable solution for accurate and efficient environmental modelling.

North Carolina, Virginia↗

USGS2024

An introduction to Criteria for Reporting and Evaluating Exposure Datasets (CREED) for use in environmental assessments

Risks posed by environmental exposure to chemicals are routinely assessed to inform activities ranging from environmental status reporting to authorization and registration of chemicals for commercial uses. Environmental risk assessment generally relies on two key values generated from exposure data and ecotoxicity data. Data sets of measured concentrations of chemicals in environmental matrices, referred to here as exposure data, are widely used to support environmental risk management, decision-making, and reporting, such as for chemical screening, ecological or human health risk assessments, and establishment of guidelines. Practitioners have developed schemes to determine the suitability of ecotoxicity data for specific purposes, focused on evaluating reliability and relevance, but analogous schemes are not available for exposure data. Moreover, regulatory guidance arguably provides less resolution on reporting and evaluating exposure data sets compared to ecotoxicity data. The evaluation of exposure data sets is subject to limitations from variable or unreported data quality objectives and/or from differences in expert judgments, potentially introducing bias and leading to decisions based on flawed and/or inconsistent information. Exposure data sets should be evaluated for reliability and relevance prior to use in environmental assessments. This paper is the first of a four-paper series detailing the outcomes of a Society of Environmental Toxicology and Chemistry technical workshop that has developed Criteria for Reporting and Evaluating Exposure Datasets (CREED). The workshop participants developed practical, systematic criteria for consistent and transparent evaluation of the reliability (quality) and relevance (fitness for purpose) of exposure data. This guidance should apply to many different (unspecified) purposes of assessment. CREED can be used to evaluate existing data sets, but can also inform data generators interested in improving their data collection and reporting to maximize data utility to other users. This first paper details existing frameworks for the evaluation of exposure data sets and demonstrates the need for CREED, drawing from different regulatory assessments, and describes the technical workshop.

Integrated Environmental Assessment and Management↗

USGS2018

The Connecticut Streamflow and Sustainable Water Use Estimator—A decision-support tool to estimate water availability at ungaged stream locations in Connecticut

Freshwater streams in Connecticut are subject to many competing demands, including public water supply; agricultural, commercial, and industrial water use; and ecosystem and habitat needs. In recent years, drought has further stressed Connecticut’s water resources. To sustainably allocate and manage water resources among these competing uses, Federal, State, and local water-resource managers require data and modeling tools to estimate the water availability at a variety of temporal and spatial scales for planning purposes. The Connecticut Streamflow and Sustainable Water Use Estimator (CT SSWUE), developed by the U.S. Geological Survey in cooperation with the Connecticut Department of Energy and Environmental Protection, is a decision-support tool for estimating daily unaltered streamflow and sustainable water use at ungaged sites in Connecticut. The CT SSWUE estimates unaltered daily mean streamflow and water-use-adjusted streamflow for the period from October 1, 1960, to September 30, 2015, and the monthly sustainable net withdrawal at ungaged sites in Connecticut. Unaltered streamflow is the estimated daily mean streamflow in a drainage basin in the absence of any water withdrawals or wastewater discharges and with minimal human development. Sustainable net withdrawal is the maximum net withdrawal (withdrawal minus wastewater discharges) that can be drawn from a basin without critically depleting the water available through natural streamflow patterns. Sustainable net withdrawal is defined for this study as the difference between the unaltered daily mean streamflow and a user-defined target minimum streamflow. Weighted least squares and Tobit regression techniques were used to develop equations for estimating streamflow at ungaged sites at 19 streamflow quantiles with exceedance probabilities ranging from 0.005 to 99.995 percent. Regressions were based on streamflow quantiles and basin characteristics from 36 reference streamgages in and around Connecticut. Four basin characteristics—drainage area, mean of the soil permeability, mean of the average annual precipitation, and ratio of the length of streams that overlay sand and gravel deposits to the total length of streams in the basin—are used as explanatory variables in the equations. At an ungaged site, interpolation between the streamflow quantiles estimated from the regression equations produces a continuous flow-duration curve. A time series of daily mean streamflow at an ungaged site is then estimated by assuming that for each day, the streamflow quantile occurs on the same date at both a reference streamgage and the ungaged site. In a remove-one cross validation, estimated unaltered daily mean streamflow agreed well with observed values at reference streamgages, with a few exceptions. Nash Sutcliffe efficiency ranged from −0.43 to 0.97 with a median value of 0.88. The normalized root-mean-square error ranged from 16.6 to 120.4 percent with a median value of 34.5 percent. An empirical method for estimating 95-percent prediction intervals for unaltered daily and monthly mean streamflow was developed and tested by using the cross-validation data. Prediction intervals for unaltered daily mean streamflow at the cross-validation reference streamgages performed well in most cases. Gaged streamflow values from the cross-validation data fell within the prediction intervals a median 96.6 percent of the time for daily mean time series and 93.9 percent of the time for monthly mean time series. The CT SSWUE computes water-use-adjusted streamflow using spatially referenced water-use information provided by the Connecticut Department of Energy and Environmental Protection. Available water-use information included permitted and registered water withdrawals and permitted wastewater discharges during 1998 to 2015 for the Thames River Basin and central coastal drainage basins. Water-use information was incorporated into the U.S. Geological Survey StreamStats web application for Connecticut and can be used for computing water-use-adjusted streamflow and sustainable net withdrawal at selected points of interest. Altered daily streamflow is computed by applying average daily withdrawals and wastewater discharges to the water balance equation. Average daily surface water withdrawals and wastewater discharges are applied directly to the daily water balance equation. Time-lagged alterations on streamflow from groundwater withdrawals or wastewater discharges are estimated by using a response-coefficient method developed from results of previously published, calibrated groundwater models.

Connecticut↗

USGS2013

An automated digital imaging system for environmental monitoring applications

Recent improvements in the affordability and availability of high-resolution digital cameras, data loggers, embedded computers, and radio/cellular modems have advanced the development of sophisticated automated systems for remote imaging. Researchers have successfully placed and operated automated digital cameras in remote locations and in extremes of temperature and humidity, ranging from the islands of the South Pacific to the Mojave Desert and the Grand Canyon. With the integration of environmental sensors, these automated systems are able to respond to local conditions and modify their imaging regimes as needed. In this report we describe in detail the design of one type of automated imaging system developed by our group. It is easily replicated, low-cost, highly robust, and is a stand-alone automated camera designed to be placed in remote locations, without wireless connectivity.

Open-File Report↗

USGS2013

Analyzing the water budget and hydrological characteristics and responses to land use in a monsoonal climate river basin in South China

Hydrological models have been increasingly used by hydrologists and water resource managers to understand natural processes and human activities that affect watersheds. In this study, we use the physically based model, Soil and Water Assessment Tool (SWAT), to investigate the hydrological processes in the East River Basin in South China, a coastal area dominated by monsoonal climate. The SWAT model was calibrated using 8-year (1973–1980) record of the daily streamflow at the basin outlet (Boluo station), and then validated using data collected during the subsequent 8 years (1981–1988). Statistical evaluation shows that SWAT can consistently simulate the streamflow of the East River with monthly Nash–Sutcliffe efficiencies of 0.93 for calibration and 0.90 for validation at the Boluo station. We analyzed the model simulations with calibrated parameters, presented the spatiotemporal distribution of the key hydrological components, and quantified their responses to different land uses. Watershed managers can use the results of this study to understand hydrological features and evaluate water resources of the East River in terms of sustainable development and effective management.

Environmental Management↗

USGS2015

Integrating gene transcription-based biomarkers to understand desert tortoise and ecosystem health

Tortoises are susceptible to a wide variety of environmental stressors, and the influence of human disturbances on health and survival of tortoises is difficult to detect. As an addition to current diagnostic methods for desert tortoises, we have developed the first leukocyte gene transcription biomarker panel for the desert tortoise ( Gopherus agassizii ), enhancing the ability to identify specific environmental conditions potentially linked to declining animal health. Blood leukocyte transcript profiles have the potential to identify physiologically stressed animals in lieu of clinical signs. For desert tortoises, the gene transcript profile included a combination of immune or detoxification response genes with the potential to be modified by biological or physical injury and consequently provide information on the type and magnitude of stressors present in the animal’s habitat. Blood from 64 wild adult tortoises at three sites in Clark County, NV, and San Bernardino, CA, and from 19 captive tortoises in Clark County, NV, was collected and evaluated for genes indicative of physiological status. Statistical analysis using a priori groupings indicated significant differences among groups for several genes, while multidimensional scaling and cluster analyses of transcription C T values indicated strong differentiation of a large cluster and multiple outlying individual tortoises or small clusters in multidimensional space. These analyses highlight the effectiveness of the gene panel at detecting environmental perturbations as well as providing guidance in determining the health of the desert tortoise.

California, Nevada↗

USGS2012

A stakeholder project to model water temperature under future climate scenarios in the Satus and Toppenish watersheds of the Yakima River Basinin Washington, USA

The goal of this study was to support an assessment of the potential effects of climate change on select natural, social, and economic resources in the Yakima River Basin. A workshop with local stakeholders highlighted the usefulness of projecting climate change impacts on anadromous steelhead ( Oncorhynchus mykiss) , a fish species of importance to local tribes, fisherman, and conservationists. Stream temperature is an important environmental variable for the freshwater stages of steelhead. For this study, we developed water temperature models for the Satus and Toppenish watersheds, two of the key stronghold areas for steelhead in the Yakima River Basin. We constructed the models with the Stream Network Temperature Model (SNTEMP), a mechanistic approach to simulate water temperature in a stream network. The models were calibrated over the April 15, 2008 to September 30, 2008 period and validated over the April 15, 2009 to September 30, 2009 period using historic measurements of stream temperature and discharge provided by the Yakama Nation Fisheries Resource Management Program. Once validated, the models were run to simulate conditions during the spring and summer seasons over a baseline period (1981–2005) and two future climate scenarios with increased air temperature of 1°C and 2°C. The models simulated daily mean and maximum water temperatures at sites throughout the two watersheds under the baseline and future climate scenarios.

Washington↗

USGS2016

Number of genera as a potential screening tool for assessing quality of bryophyte communities in Ohio wetlands

Bryophytes (mosses, liverworts, and hornworts) have numerous advantages as indicators of environmental quality. A quality assessment index for bryophyte species assemblages (BQAI) was developed for the State of Ohio, USA. Reliable identification of bryophytes to species often requires considerable training, practice, and time. In contrast, reliable identification to genera for most bryophytes in Ohio requires much less training. We identified 110 bryophyte species (14 liverworts and 96 mosses) belonging to 69 genera (13 liverwort and 56 moss) in 45 wetlands (27 emergent, 13 forested, and 5 shrub) in Ohio. As expected, there were more genera and higher BQAI scores in forested than in emergent wetlands. Number of genera was highly correlated ( r  ≥ 0.9) with BQAI in emergent and forested wetlands and for the combined set of wetlands. Number of genera and BQAI responded almost identically to an index of wetland disturbance. The results suggest that number of genera has potential as a screening tool for assessing bryophyte community quality in wetlands in some regions.

Wetlands↗

USGS2014

Uncertainty, robustness, and the value of information in managing an expanding Arctic goose population

We explored the application of dynamic-optimization methods to the problem of pink-footed goose (Anser brachyrhynchus) management in western Europe. We were especially concerned with the extent to which uncertainty in population dynamics influenced an optimal management strategy, the gain in management performance that could be expected if uncertainty could be eliminated or reduced, and whether an adaptive or robust management strategy might be most appropriate in the face of uncertainty. We combined three alternative survival models with three alternative reproductive models to form a set of nine annual-cycle models for pink-footed geese. These models represent a wide range of possibilities concerning the extent to which demographic rates are density dependent or independent, and the extent to which they are influenced by spring temperatures. We calculated state-dependent harvest strategies for these models using stochastic dynamic programming and an objective function that maximized sustainable harvest, subject to a constraint on desired population size. As expected, attaining the largest mean objective value (i.e., the relative measure of management performance) depended on the ability to match a model-dependent optimal strategy with its generating model of population dynamics. The nine models suggested widely varying objective values regardless of the harvest strategy, with the density-independent models generally producing higher objective values than models with density-dependent survival. In the face of uncertainty as to which of the nine models is most appropriate, the optimal strategy assuming that both survival and reproduction were a function of goose abundance and spring temperatures maximized the expected minimum objective value (i.e., maxi–min). In contrast, the optimal strategy assuming equal model weights minimized the expected maximum loss in objective value. The expected value of eliminating model uncertainty was an increase in objective value of only 3.0%. This value represents the difference between the best that could be expected if the most appropriate model were known and the best that could be expected in the face of model uncertainty. The value of eliminating uncertainty about the survival process was substantially higher than that associated with the reproductive process, which is consistent with evidence that variation in survival is more important than variation in reproduction in relatively long-lived avian species. Comparing the expected objective value if the most appropriate model were known with that of the maxi–min robust strategy, we found the value of eliminating uncertainty to be an expected increase of 6.2% in objective value. This result underscores the conservatism of the maxi–min rule and suggests that risk-neutral managers would prefer the optimal strategy that maximizes expected value, which is also the strategy that is expected to minimize the maximum loss (i.e., a strategy based on equal model weights). The low value of information calculated for pink-footed geese suggests that a robust strategy (i.e., one in which no learning is anticipated) could be as nearly effective as an adaptive one (i.e., a strategy in which the relative credibility of models is assessed through time). Of course, an alternative explanation for the low value of information is that the set of population models we considered was too narrow to represent key uncertainties in population dynamics. Yet we know that questions about the presence of density dependence must be central to the development of a sustainable harvest strategy. And while there are potentially many environmental covariates that could help explain variation in survival or reproduction, our admission of models in which vital rates are drawn randomly from reasonable distributions represents a worst-case scenario for management. We suspect that much of the value of the various harvest strategies we calculated is derived from the fact that they are state dependent, such that appropriate harvest rates depend on population abundance and weather conditions, as well as our focus on an infinite time horizon for sustainability.

Ecological Modelling↗

USGS2021

Piloting urban ecosystem accounting for the United States

In this study, we develop urban ecosystem accounts in the U.S., using the System of Environmental-Economic Accounting Experimental Ecosystem Accounting (SEEA EEA) framework. Most ecosystem accounts focus on regional and national scales, which are appropriate for many ecosystem services. However, ecosystems provide substantial services in cities, improving quality of life and contributing to resiliency for substantial parts of the population. Our models estimate energy savings for indoor cooling resulting from heat mitigated by trees and rainfall intercepted by trees. Both models cover major cities in the contiguous U.S. and report the results through physical supply and use tables for multiple accounting periods (2011 and 2016). Using conservative assumptions, urban trees provide substantial heat mitigation (4,098 and 4,229 GWh, valued at $523 and $539 million in 2011 and 2016, respectively) and rainfall interception (2,422 and 2,627 million m 3 , valued at $434 and $425 million for 2011 and 2016, respectively). Interannual differences largely reflect variations in weather patterns. Our work shows how Earth observation data can support urban ecosystem accounting. We provide model code within a public repository to facilitate model runs elsewhere, enabling the SEEA EEA and Earth observation user communities to reuse our models and provide feedback for improvement.

Ecosystem Services↗

USGS2017

Incorporating population viability models into species status assessment and listing decisions under the U.S. Endangered Species Act

Assessment of a species' status is a key part of management decision making for endangered and threatened species under the U.S. Endangered Species Act. Predicting the future state of the species is an essential part of species status assessment, and projection models can play an important role in developing predictions. We built a stochastic simulation model that incorporated parametric and environmental uncertainty to predict the probable future status of the Sonoran desert tortoise in the southwestern United States and North Central Mexico. Sonoran desert tortoise was a Candidate species for listing under the Endangered Species Act, and decision makers wanted to use model predictions in their decision making process. The model accounted for future habitat loss and possible effects of climate change induced droughts to predict future population growth rates, abundances, and quasi-extinction probabilities. Our model predicts that the population will likely decline over the next few decades, but there is very low probability of quasi-extinction less than 75 years into the future. Increases in drought frequency and intensity may increase extinction risk for the species. Our model helped decision makers predict and characterize uncertainty about the future status of the species in their listing decision. We incorporated complex ecological processes (e.g., climate change effects on tortoises) in transparent and explicit ways tailored to support decision making processes related to endangered species.

Sonoran Desert↗

USGS2018

Identifying management-relevant research priorities for responding to disease-associated amphibian declines

A research priority can be defined as a knowledge gap that, if resolved, identifies the optimal course of conservation action. We (a group of geographically distributed and multidisciplinary research scientists) used tools from nominal group theory and decision analysis to collaboratively identify and prioritize information needs within the context of disease-associated amphibian decline , in order to develop a strategy that would support US management agency needs. We developed iterated influence diagrams to create and assess a unified research strategy. We illustrated a transparent process for identifying specific knowledge gaps in amphibian disease ecology relevant to environmental management, and then constructed a research plan to address these uncertainties. The resulting priorities include a need to: (1) understand the drivers of the community-disease relationship, (2) determine the mechanisms by which exposure to contaminants influence disease outcomes, (3) identify elements of terrestrial and aquatic habitats that stabilize host-pathogen dynamics, (4) discuss how metapopulations may be managed to reduce the speed and intensity of disease outbreaks, and (5) define the relationship between habitat management and the environmental and host microbiomes. Along with identifying research priorities for disease management, we present the details of the process used to develop a consensus plan for addressing disease-related declines in amphibians on federally managed lands of the United States.

Global Ecology and Conservation↗

USGS2024

The EnMAP spaceborne imaging spectroscopy mission: Initial scientific results two years after launch

Imaging spectroscopy has been a recognized and established remote sensing technology since the 1980s, mainly using airborne and field-based platforms to identify and quantify key bio- and geo-chemical surface and atmospheric compounds, based on characteristic spectral reflectance features in the visible-near infrared (VNIR) and short-wave infrared (SWIR). Spaceborne missions, a leap in technology, were sparse, starting with the CHRIS/PROBA and EO1/Hyperion missions in the early 2000s, and providing spectroscopy data with limited spectral coverage and/or low data quality in the SWIR. Since 2019, several countries and agencies have successfully launched a number of spaceborne imaging spectroscopy systems into orbit or deployed them on the International Space Station (ISS) such as DESIS, PRISMA, HISUI, GF-5, EnMAP and EMIT. Among these recent missions, the German Environmental Mapping and Analysis Program (EnMAP) stands for its long-term development, sophisticated design with on-board calibration, high data quality requirements, and extensive accompanying science program. EnMAP was launched in April 2022 and, following a successful commissioning phase, started its operational activities in November 2022. The EnMAP mission encompasses global coverage from 80° N to 80° S through on-demand data acquisitions. Data are free and open access with 30 m spatial resolution, a high spectral resolution with a spectral sampling distance of 6.5 nm and 10 nm in the VNIR and SWIR regions respectively, and a high signal-to-noise ratio. In this paper, we aim to present the mission's current status, coverage, science capabilities and performance two years after launch. We show the potential of EnMAP for space-based imaging spectroscopy to operate in various environments, including high and low light levels, dense forests, Antarctic glaciers, and arid agricultural areas. EnMAP enables various applications in fields such as agriculture and forestry, soil compositional, raw materials, and methane mapping, as well as water quality assessment, and snow and ice properties. The results show that EnMAP's performance exceeds the mission requirements, and highlights the significant potential for contribution to scientific exploitation in various geo- and biochemical sciences. EnMAP is also expected to serve as a key tool for the development and testing of data processing algorithms for upcoming global operational missions.

Remote Sensing of Environment↗

USGS2011

Evaluating impacts of subdivision density on shallow groundwater in Southeastern Wisconsin, USA

Using simple numerical groundwater flow models, we tested the impacts of suburban developments on groundwater levels and discharge to streams. We used lot sizes of 1, 3 and 5 acres (4000, 12,000 and 20,000 m 2 ) with one domestic well per lot that pumped water from shallow aquifers. Our modelling showed that pumping had little impact on water levels and groundwater discharge to streams if the developed area is of a moderate size. However, domestic wells had the potential to impact local groundwater levels and baseflows in large developments. In township-wide development scenarios of 1-acre (4000 m 2 ) lots, simulated drawdowns beneath developed areas ranged from 1 to 18 ft (0.3 to 5.5 m), and baseflow reductions ranged from 20 to 40%. Impacts generally were inversely proportional to lot size, recharge rate and hydraulic conductivity of the aquifer materials. Developments using individual domestic wells have the potential to impact local groundwater levels and surface water features. The impacts can range from negligible to severe, depending on local hydrogeologic conditions and on whether wastewater is recharged onsite or is removed from the basin. An assessment of groundwater impacts should be a part of the planning process for all suburban developments.

Wisconsin↗

USGS2015

Life-stage-specific physiology defines invasion extent of a riverine fish

Many ecologists have called for mechanism-based investigations to identify the underlying controls on species distributions. Understanding these controls can be especially useful to construct robust predictions of how a species range may change in response to climate change or the extent to which a non-native species may spread in novel environments. Here, we link spatially intensive observations with mechanistic models to illustrate how physiology determines the upstream extent of the aquatic ectotherm smallmouth bass ( Micropterus dolomieu ) in two headwater rivers. Our results demonstrate that as temperatures become increasingly cold across a downstream to upstream gradient, food consumption in age 0 bass becomes increasingly constrained, and as a result, these fish become growth limited. Sufficient first summer growth of age 0 bass is essential for overwinter survival because young bass must persist from energy reserves accumulated during the summer, and those reserves are determined by body size. Our field data reveal the upstream extent of adult bass reproduction corresponds to a point in the downstream/upstream gradient where cold temperatures impair growth opportunities in young bass. This pattern was repeated in both study streams and explained why bass positioned nests twice as far upstream in the warm compared to the cold stream in the same basin. Placement of spawning nests by adult bass is likely subject to strong evolutionary selection in temperate systems: if bass spawn too far upstream, their young are unlikely to grow large enough to survive the winter. Consumption and growth in older bass (age 3–4) was far less sensitive to temperature. Based on these data, we suggest that temperature-sensitive age 0 bass constrain the upstream distribution limits of bass within temperate streams. In this study, we investigated how temperature-dependent physiology changed through the life history of a species and, in doing so, identified a climate-sensitive life-history stage that likely sets the distributional limits of all other life-history stages. We anticipate the framework developed here could be employed to identify how similar stage-specific environmental sensitivity determines distribution in many other ectothermic species.

Oregon↗

USGS2021

Sarcoptic mange: An emerging panzootic in wildlife

Sarcoptic mange, a skin infestation caused by the mite Sarcoptes scabiei , is an emerging disease for some species of wildlife, potentially jeopardizing their welfare and conservation. Sarcoptes scabiei has a near-global distribution facilitated by its forms of transmission and use of a large diversity of host species (many of those with broad geographic distribution). In this review, we synthesize the current knowledge concerning the geographic and host taxonomic distribution of mange in wildlife, the epidemiological connections between species, and the potential threat of sarcoptic mange for wildlife conservation. Recent sarcoptic mange outbreaks in wildlife appear to demonstrate ongoing geographic spread, increase in the number of hosts and increased virulence. Sarcoptic mange has been reported in at least 12 orders, 39 families and 148 species of domestic and wild mammals, making it one of the most generalist ectoparasites of mammals. Taxonomically, the orders with most species found infested so far include Perissodactyla (67% species from the entire order), Artiodactyla (47%), and Diprotodontia (67% from this order). This suggests that new species from these mammal orders are likely to suffer cross-species transmission and be reported positive to sarcoptic mange as surveillance improves. We propose a new agenda for the study of sarcoptic mange in wildlife, including the study of the global phylogeography of S. scabiei , linkages between ecological host traits and sarcoptic mange susceptibility, immunology of individuals and species, development of control strategies in wildlife outbreaks and the effects of global environmental change in the sarcoptic mange system. The ongoing transmission globally and sustained spread among areas and wildlife species make sarcoptic mange an emerging panzootic in wildlife. A better understanding of sarcoptic mange could illuminate the aspects of ecological and evolutionary drivers in cross-species transmission for many emerging diseases.

Transboundary and Emerging Diseases↗