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At least 919 records · Page 51Linked to original sources
USGS2022

Climate and land change impacts on future managed wetland habitat: A case study from California’s Central Valley

Concept California’s Central Valley provides critical habitat for migratory waterbirds, yet only 10% of naturally occurring wetlands remain. Competition for limited water supplies and climate change will impact the long-term viability of these intensively managed habitats. Objectives Forecast the distribution, abundance, and connectivity of surface water and managed wetland habitats, using 5 spatially explicit (270 m 2 ) climate/land use/water prioritization scenarios. Mapping potential future dynamic flooded habitat used by waterbirds and other wetland-dependent wildlife to inform management decisions. Methods We integrated a climate-driven hydrologic water use model with a spatially explicit land change model, to examine stakeholder-driven scenarios of future land change, climate, and water use and their impacts on future habitat availability. Results Declining water availability is the dominant driver of habitat loss across scenarios. The hot/dry scenarios showed the greatest declines in January flooded area by 2101—an important month for overwintering waterbirds. In contrast, higher water supplies in wet climates drive perennial cropland conversion and loss of potential habitat. Potential flooded cropland declined (25 and 33%) under warmer/wetter climate conditions due to this conversion to perennial crops, exposing habitat vulnerability. Conclusion Climate-driven loss of water availability had a greater impact on flooded habitat availability than land-use change. When combined, climate change and the conversion of potentially flooded cropland to perennial cropland will threaten future waterbird habitat particularly in January, the peak of the migratory bird season, even when habitat restoration goals are met. Stakeholder-informed scenario analysis can identify target areas for potential habitat change, vulnerability, and conservation.

California↗
USGS1999

Reference intervals and physiologic alterations in hematologic and biochemical values of free-ranging desert tortoises in the Mojave Desert

Desert tortoise ( Gopherus agassizii ) populations have experienced precipitous declines resulting from the cumulative impact of habitat loss, and human and disease-related mortality. Evaluation of hematologic and biochemical responses of desert tortoises to physiologic and environmental factors can facilitate the assessment of stress and disease in tortoises and contribute to management decisions and population recovery. The goal of this study was to obtain and analyze clinical laboratory data from free-ranging desert tortoises at three sites in the Mojave Desert (California, USA) between October 1990 and October 1995, to establish reference intervals, and to develop guidelines for the interpretation of laboratory data under a variety of environmental and physiologic conditions. Body weight, carapace length, and venous blood samples for a complete blood count and clinical chemistry profile were obtained from 98 clinically healthy adult desert tortoises of both sexes at the Desert Tortoise Research Natural area (western Mojave), Goffs (eastern Mojave) and Ivanpah Valley (northeastern Mojave). Samples were obtained four times per year, in winter (February/March), spring (May/June), summer (July/August), and fall (October). Years of near-, above- and below-average rainfall were represented in the 5 yr period. Minimum, maximum and median values, and central 95 percentiles were used as reference intervals and measures of central tendency for tortoises at each site and/or season. Data were analyzed using repeated measures analysis of variance for significant ( P < 0.01) variation on the basis of sex, site, season, and interactions between these variables. Significant sex differences were observed for packed cell volume, hemoglobin concentration, aspartate transaminase activity, and cholesterol, triglyceride, calcium, and phosphorus concentrations. Marked seasonal variation was observed in most parameters in conjunction with reproductive cycle, hibernation, or seasonal rainfall. Year-to-year differences and long-term alterations primarily reflected winter rainfall amounts. Site differences were minimal, and largely reflected geographic differences in precipitation patterns, such that results from these studies can be applied to other tortoise populations in environments with known rainfall and forage availability patterns.

Journal of Wildlife Diseases↗
USGS2019

Analysis of groundwater response to tidal fluctuations, Operable Unit 1, Naval Base Kitsap, Keyport, Washington

Chlorinated volatile organic compounds have affected groundwater beneath a former 9-acre landfill at Operable Unit 1 (OU 1) of Naval Base Kitsap (NBK) Keyport, in Keyport, Washington. The landfill was the primary disposal area for domestic and industrial waste generated by NBK Keyport from the 1930s through 1973. Naval Facilities Engineering Command Northwest, in conjunction with the Environmental Protection Agency, Washington State Department of Ecology, and the Suquamish Tribe, is charged with collecting necessary data to monitor the contamination left in place and to ensure that the site does not pose a risk to human health or the environment. To support these efforts, refined information was collected on how groundwater levels throughout OU 1 respond to tidal fluctuations at this nearshore site adjacent to Liberty Bay, an inlet of Puget Sound. The information was analyzed to determine the optimal times during the semidiurnal and the neap-spring tidal cycles to sample groundwater for contaminants associated with fresh groundwater originating from OU 1. The optimal times for sampling are presumed to be when fresh groundwater flowing seaward is least impeded by elevated tides, and those times are related to predicted tide levels by tidal lags, the durations between low tides, and corresponding low groundwater levels. Discrete groundwater-specific conductance data also were collected to determine if a seawater/freshwater interface was present at any of the monitoring wells, and to inform decisions on the depth at which groundwater should be sampled in existing wells. Groundwater and surface-water levels were monitored at 19 monitoring wells and five adjacent surface-water sites. Specific conductance was monitored in each surface-water site. All time-series data parameters were collected every 15 minutes during a 4-week duration to measure how nearshore groundwater responds to tidal forcing. Time-series data were collected from July 12, 2018, to August 8, 2018, a period that included neap and spring tides. Vertical water-quality profiles were measured once in the screened interval of nine selected monitoring wells. The profiles included measurements at the top, middle, and bottom of each saturated screen interval. Tidal lag times were determined relative to tidal levels in Liberty Bay (rather than in the more nearby Tide Flats) because the predicted tides for the Poulsbo, Washington Station (National Oceanic and Atmospheric Administration [NOAA] Station 9445719) that are used to schedule groundwater sampling represent open-water conditions in the area; a sill that separates Dogfish Bay from the Tide Flats clearly affects the timing and magnitude of low-low tides in the Tide Flats. Calculated tidal lag times were divided into three general groups: (1) wells where groundwater responded to tidal level changes immediately, (2) wells where groundwater responded to tidal level changes within about 2–5 hours, and (3) wells where groundwater had minimal response to tidal level changes. Groundwater levels in the middle group of wells primarily responded in concert with tidal level changes in the Tide Flats rather than tidal level changes in Liberty Bay. An intended sampling depth refinement based on an assessment of transient seawater intrusion was not completed because of a failure to collect specific-conductance time-series data in select wells. Instead, discrete specific-conductance data from this and prior studies were evaluated to determine that the midpoint of well screens in OU 1 wells can be assumed to be a reasonably representative of undiluted groundwater. When sampling during spring (rather than neap) tides (as has generally been the standard practice at OU 1), the optimal time to sample the monitoring wells influenced by tides would be to add the tidal lags presented in this report to the time of the predicted low-low tide for Liberty Bay as measured at NOAA Station 9445719 at Poulsbo, Washington. Sampling schedules for the six wells where groundwater levels were only minimally influenced by tide changes should not be constrained by tidal conditions.

Washington↗
USGS2026

GT-Seq panel development for species identification and parentage analysis of closely related hybridising Scaphirhynchus sturgeons

Hatchery supplementation is vital for conserving dwindling fish populations. Effective augmentation requires distinguishing hatchery-origin from wild individuals and accurately identifying species, particularly in systems where closely related species coexist. Genetic monitoring is key to quantifying genetic differences, but conventional markers do not distinguish hybrids, especially backcrosses. Misidentifying hybrids in hatchery programs compromises wild gene pools because hatchery broodstock contributes to numerous offspring being released into the wild. Here, we present a workflow for developing and evaluating the Genotyping-in-Thousands by sequencing (GT-seq) single nucleotide polymorphism (SNP) panel for North American river sturgeons ( Scaphirhynchus spp.). This panel is designed to detect complex hybrid classes and to determine parent-offspring relationships. Our species identification panel (S-loci) contains 155 SNPs selected for high genetic differentiation (F ST ) between Pallid Sturgeon ( S. albus ) and Shovelnose Sturgeon ( S. platorynchus ), and the parentage assignment panel (P-loci) includes 112 SNPs with high heterozygosity within Pallid Sturgeon. Simulation analyses demonstrated that our GT-seq S-loci panel reliably classifies pure species, F1, F2 and backcross hybrids, even with up to 70% missing data. The P-loci panel achieves high-confidence parentage assignment with ≥ 80% typed loci, with performance influenced by the proportion of sampled parents. Overall, the novel Scaphirhynchus GT-seq panel developed in this study represents a robust and efficient tool for detecting hybridisation, assigning parentage and providing critical information for management decisions in ongoing Pallid Sturgeon conservation.

lower Mississippi River, Missouri River↗
USGS2023

Climate-induced shifts in grassland bird nesting phenology have implications for grassland management

Grasslands are among the most impacted ecosystems globally. In the midcontinent of North America, a > 80% loss of grasslands has made their conservation a major priority for resource managers. Grassland ecosystems evolved under periodic disturbances; consequently, grassland management often involves regular actions such as grazing, haying, or burning to maintain ecosystem integrity. The timing of such practices has direct implications on grassland ecology, agricultural economics, and survival and fecundity of grassland nesting birds (hereafter grassland birds). We conducted a meta-analysis on the nesting phenology of grassland birds throughout North America, focusing on nest-survival literature. We constructed a well-fitting model to predict median date of expected nest departure (hereafter fledge date) for grassland birds across the midcontinent. Predictions from our model demonstrate considerable spatial variation in median nesting phenology that is predictable using a spatially explicit spring phenology index. Median fledge dates were 8 or 13 days earlier in years of extreme weather conditions (dry or wet, respectively) than in years of average conditions. Species that generally nest in taller vegetation tended to have later median nest phenologies than those using shorter vegetation. Our results incorporate the most rigorous information available in the literature on nesting phenology of 36 grassland bird species and improve information available to managers about nesting phenology of grassland birds in the midcontinent of North America. Our predictions approximate the day when one-half of the nesting efforts would be complete for a given area within the midcontinent grasslands and can inform management and conservation decisions about the timing of management actions in grassland ecosystems.

Global Ecology and Conservation↗
USGS2015

Machine learning for predicting soil classes in three semi-arid landscapes

Mapping the spatial distribution of soil taxonomic classes is important for informing soil use and management decisions. Digital soil mapping (DSM) can quantitatively predict the spatial distribution of soil taxonomic classes. Key components of DSM are the method and the set of environmental covariates used to predict soil classes. Machine learning is a general term for a broad set of statistical modeling techniques. Many different machine learning models have been applied in the literature and there are different approaches for selecting covariates for DSM. However, there is little guidance as to which, if any, machine learning model and covariate set might be optimal for predicting soil classes across different landscapes. Our objective was to compare multiple machine learning models and covariate sets for predicting soil taxonomic classes at three geographically distinct areas in the semi-arid western United States of America (southern New Mexico, southwestern Utah, and northeastern Wyoming). All three areas were the focus of digital soil mapping studies. Sampling sites at each study area were selected using conditioned Latin hypercube sampling (cLHS). We compared models that had been used in other DSM studies, including clustering algorithms, discriminant analysis, multinomial logistic regression, neural networks, tree based methods, and support vector machine classifiers. Tested machine learning models were divided into three groups based on model complexity: simple, moderate, and complex. We also compared environmental covariates derived from digital elevation models and Landsat imagery that were divided into three different sets: 1) covariates selected a priori by soil scientists familiar with each area and used as input into cLHS, 2) the covariates in set 1 plus 113 additional covariates, and 3) covariates selected using recursive feature elimination. Overall, complex models were consistently more accurate than simple or moderately complex models. Random forests (RF) using covariates selected via recursive feature elimination was consistently the most accurate, or was among the most accurate, classifiers between study areas and between covariate sets within each study area. We recommend that for soil taxonomic class prediction, complex models and covariates selected by recursive feature elimination be used. Overall classification accuracy in each study area was largely dependent upon the number of soil taxonomic classes and the frequency distribution of pedon observations between taxonomic classes. Individual subgroup class accuracy was generally dependent upon the number of soil pedon observations in each taxonomic class. The number of soil classes is related to the inherent variability of a given area. The imbalance of soil pedon observations between classes is likely related to cLHS. Imbalanced frequency distributions of soil pedon observations between classes must be addressed to improve model accuracy. Solutions include increasing the number of soil pedon observations in classes with few observations or decreasing the number of classes. Spatial predictions using the most accurate models generally agree with expected soil–landscape relationships. Spatial prediction uncertainty was lowest in areas of relatively low relief for each study area.

New Mexico, Utah, Wyoming↗
USGS2015

Surrogate Analysis and Index Developer (SAID) tool

The use of acoustic and other parameters as surrogates for suspended-sediment concentrations (SSC) in rivers has been successful in multiple applications across the Nation. Tools to process and evaluate the data are critical to advancing the operational use of surrogates along with the subsequent development of regression models from which real-time sediment concentrations can be made available to the public. Recent developments in both areas are having an immediate impact on surrogate research and on surrogate monitoring sites currently (2015) in operation. The Surrogate Analysis and Index Developer (SAID) standalone tool, under development by the U.S. Geological Survey (USGS), assists in the creation of linear regression models that relate constituent and surrogate parameters by providing visual and quantitative diagnostics to the user. SAID also processes acoustic parameters to be used as explanatory variables for SSC. The sediment acoustic method utilizes acoustic parameters from fixed-mount stationary equipment. The theory and method used by the SAID tool have been described in recent publications. The tool also serves to support sediment-acoustic-index methods and other surrogate guidelines such as turbidity and SSC (Rasmussen and others, 2009). The regression models created in SAID can be used in utilities that have been developed to work with the USGS National Water Information System (NWIS) and for the USGS National Real-Time Water Quality (NRTWQ) Web site. The real-time dissemination of predicted SSC and prediction intervals for each time step has substantial potential to improve understanding of sediment-related water quality and associated engineering and ecological management decisions.

Open-File Report↗
USGS2013

Climate change and watershed mercury export: a multiple projection and model analysis

Future shifts in climatic conditions may impact watershed mercury (Hg) dynamics and transport. An ensemble of watershed models was applied in the present study to simulate and evaluate the responses of hydrological and total Hg (THg) fluxes from the landscape to the watershed outlet and in-stream THg concentrations to contrasting climate change projections for a watershed in the southeastern coastal plain of the United States. Simulations were conducted under stationary atmospheric deposition and land cover conditions to explicitly evaluate the effect of projected precipitation and temperature on watershed Hg export (i.e., the flux of Hg at the watershed outlet). Based on downscaled inputs from 2 global circulation models that capture extremes of projected wet (Community Climate System Model, Ver 3 [CCSM3]) and dry (ECHAM4/HOPE-G [ECHO]) conditions for this region, watershed model simulation results suggest a decrease of approximately 19% in ensemble-averaged mean annual watershed THg fluxes using the ECHO climate-change model and an increase of approximately 5% in THg fluxes with the CCSM3 model. Ensemble-averaged mean annual ECHO in-stream THg concentrations increased 20%, while those of CCSM3 decreased by 9% between the baseline and projected simulation periods. Watershed model simulation results using both climate change models suggest that monthly watershed THg fluxes increase during the summer, when projected flow is higher than baseline conditions. The present study's multiple watershed model approach underscores the uncertainty associated with climate change response projections and their use in climate change management decisions. Thus, single-model predictions can be misleading, particularly in developmental stages of watershed Hg modeling.

South Carolina↗
USGS2020

Characterizing spatiotemporal patterns of crop phenology across North America during 2000–2016 using satellite imagery and agricultural survey data

Crop phenology represents an integrative indicator of climate change and plays a vital role in terrestrial carbon dynamics and sustainable agricultural development. However, spatiotemporal variations of crop phenology remain unclear at large scales. This knowledge gap has hindered our ability to realistically quantify the biogeochemical dynamics in agroecosystems, predict future climate, and make informed decisions for climate change mitigation and adaptation. In this study, we improved an EVI-curve-based approach and used it to detect spatiotemporal patterns in cropping intensity and five major phenological stages over North America during 2000–2016 using vegetation index in combination with agricultural survey data and other ancillary maps. Our predicted crop phenological stages showed strong linear relationships with the survey-based datasets, with R 2 , RMSEs, and MAEs in the ranges of 0.35 –0.99, three to ten days, and two to eight days, respectively. During the study period, the planting dates were advanced by 0.60 days/year ( p < 0.01), and harvesting dates were delayed by 0.78 days/year ( p < 0.01) over North America. A minimum temperature increase by 1 °C caused a 4.26-day planting advance (r = −0.50, p < 0. 01) or a 0.66-day harvest delay (r = 0.10, p < 0.01). While, a higher maximum temperature resulted in a planting advance by 4.48 days/°C (r = −0.62, p < 0.01) or a harvest advance by 2.22 days/°C (r = −0.40, p < 0.01). Our analysis illustrated evident spatiotemporal variations in crop phenology in response to climate change and management practices. The derived crop phenological datasets and cropping intensity maps can be used in regional climate assessments and in developing adaptation strategies.

ISPRS Journal of Photogrammetry and Remote Sensing↗
USGS2023

Quantifying ecosystem states and state transitions of the Upper Mississippi River System using topological data analysis

Aquatic systems worldwide can exist in multiple ecosystem states (i.e., a recurring collection of biological and chemical attributes), and effectively characterizing multidimensionality will aid protection of desirable states and guide rehabilitation. The Upper Mississippi River System is composed of a large floodplain river system spanning 2200 km and multiple federal, state, tribal and local governmental units. Multiple ecosystem states may occur within the system, and characterization of the variables that define these ecosystem states could guide river rehabilitation. We coupled a long-term (30-year) highly dimensional water quality monitoring dataset with multiple topological data analysis (TDA) techniques to classify ecosystem states, identify state variables, and detect state transitions over 30 years in the river to guide conservation. Across the entire system, TDA identified five ecosystem states. State 1 was characterized by exceptionally clear, clean, and cold-water conditions typical of winter (i.e., a clear-water state); State 2 had the greatest range of environmental conditions and contained most the data (i.e., a status-quo state); and States 3, 4, and 5 had extremely high concentrations of suspended solids (i.e., turbid states, with State 5 as the most turbid). The TDA mapped clear patterns of the ecosystem states across several riverine navigation reaches and seasons that furthered ecological understanding. State variables were identified as suspended solids, chlorophyll a , and total phosphorus, which are also state variables of shallow lakes worldwide. The TDA change detection function showed short-term state transitions based on seasonality and episodic events, and provided evidence of gradual, long-term changes due to water quality improvements over three decades. These results can inform decision making and guide actions for regulatory and restoration agencies by assessing the status and trends of this important river and provide quantitative targets for state variables. The TDA change detection function may serve as a new tool for predicting the vulnerability to undesirable state transitions in this system and other ecosystems with sufficient data. Coupling ecosystem state concepts and TDA tools can be transferred to any ecosystem with large data to help classify states and understand their vulnerability to state transitions.

PLOS Computational Biology↗
USGS1989

Use of experimental ecosystems in regulatory decision making

Tiered testing for the effects of chemicals on aquatic ecosystems has begun to include tests at the ecosystem level as a component in pesticide regristration. Because such tests are expensive, regulators and industry need to know what additional information they can gain from such tests relative to the costs of the simpler single-species toxicity bioassays. Requirements for ecosystem-level testing have developed because resource managers have not fully understood the implications of potential damage to resources without having evaluations of the predicted impacts under field conditions. We review approaches taken in the use of experimental ecosystems, discuss benefits and limitations of small- and large-scale ecosystem tests, and point to correlative approaches between laboratory and field toxicity testing. Laboratory experimental ecosystems (microcosms) have been successfully used to measure contaminant bioavailability, to determine routes of uptake in moderately complex aquatic systems, and to isolate factors modifying contaminant uptake into the biota. Such factors cannot be as readily studied in outdoor experimental ecosystems because direct cause-and-effect relations are often confounded and difficult to isolate. However, laboratory tests can be designed to quantify the relations among three variables: known concentrations of Stressors; specific sublethal behavioral, biochemical, and physiological effects displayed by organisms; and responses that have been observed in ecosystem-level analyses. For regulatory purposes, the specificity of test results determines how widely they can be applied. Ecotoxicological research should be directed at attempts to identify instances where single-species testing would be the appropriate level of analysis for identifying critical ecological endpoints and for clarifying relationships between ecosystem structure and function, and where it would be inadequate for a given level of analysis.

Environmental Management↗
USGS2023

Landowner and biologist perceptions of game bird predators and management

Nest survival has been identified as one of the most influential vital rates causing population change in game birds, and depredation, often influenced by habitat loss and fragmentation, is the primary cause of nest failure of upland game birds. We were interested in quantifying and comparing the perspectives of landowners and biologists in South Dakota regarding complex predator-prey interactions to improve communication and management efficacy. We developed a questionnaire regarding the following: 1) general attitude statements about game bird species; 2) perceived impacts of 9 factors (e.g., development, pollution, predators) and 13 potential predators on game bird abundances; and 3) attitude statements regarding use of lethal predator control and nesting habitat management practices. A cluster analysis using landowner attitude statements about predator management identified 3 landowner segments that had strong (most supportive; 37%), moderate (moderately supportive; 35%), or weak (least supportive; 28%) attitude statements about lethal predator control. Landowner segments most supportive and moderately supportive of predator control rated predators as the primary negative factor impacting game bird abundances and agreed that predators were the primary cause of game bird abundance declines, whereas the landowner segment least supportive of predator control rated habitat loss as the top factor and disagreed that predators were the primary cause of game bird declines. Biologists rated habitat loss as the top factor negatively impacting game bird abundances and disagreed that predators were the primary cause of game bird abundance declines. Thus, when considering the effectiveness of strategies to reduce nest depredation, most landowners focused on the direct cause of nest failures (predators), whereas biologists focused on an indirect cause (habitat loss). Perception differences among these groups emphasizes the need for better communication on proximate and ultimate factors affecting game bird populations and how these differences may impact management decisions.

South Dakota↗
USGS2012

Dealing with uncertainty when assessing fish passage through culvert road crossings

Assessing the passage of aquatic organisms through culvert road crossings has become increasingly common in efforts to restore stream habitat. Several federal and state agencies and local stakeholders have adopted assessment approaches based on literature-derived criteria for culvert impassability. However, criteria differ and are typically specific to larger-bodied fishes. In an analysis to prioritize culverts for remediation to benefit imperiled, small-bodied fishes in the Upper Coosa River system in the southeastern United States, we assessed the sensitivity of prioritization to the use of differing but plausible criteria for culvert impassability. Using measurements at 256 road crossings, we assessed culvert impassability using four alternative criteria sets represented in Bayesian belief networks. Two criteria sets scored culverts as either passable or impassable based on alternative thresholds of culvert characteristics (outlet elevation, baseflow water velocity). Two additional criteria sets incorporated uncertainty concerning ability of small-bodied fishes to pass through culverts and estimated a probability of culvert impassability. To prioritize culverts for remediation, we combined estimated culvert impassability with culvert position in the stream network relative to other barriers to compute prospective gain in connected stream habitat for the target fish species. Although four culverts ranked highly for remediation regardless of which criteria were used to assess impassability, other culverts differed widely in priority depending on criteria. Our results emphasize the value of explicitly incorporating uncertainty into criteria underlying remediation decisions. Comparing outcomes among alternative, plausible criteria may also help to identify research most needed to narrow management uncertainty.

Environmental Management↗
USGS2012

Compartment-based hydrodynamics and water quality modeling of a northern Everglades wetland, Florida, USA

The last remaining large remnant of softwater wetlands in the US Florida Everglades lies within the Arthur R. Marshall Loxahatchee National Wildlife Refuge. However, Refuge water quality today is impacted by pumped stormwater inflows to the eutrophic and mineral-enriched 100-km canal, which circumscribes the wetland. Optimal management is a challenge and requires scientifically based predictive tools to assess and forecast the impacts of water management on Refuge water quality. In this research, we developed a compartment-based numerical model of hydrodynamics and water quality for the Refuge. Using the numerical model, we examined the dynamics in stage, water depth, discharge from hydraulic structures along the canal, and exchange flow among canal and marsh compartments. We also investigated the transport of chloride, sulfate and total phosphorus from the canal to the marsh interior driven by hydraulic gradients as well as biological removal of sulfate and total phosphorus. The model was calibrated and validated using long-term stage and water quality data (1995-2007). Statistical analysis indicates that the model is capable of capturing the spatial (from canal to interior marsh) gradients of constituents across the Refuge. Simulations demonstrate that flow from the eutrophic and mineral-enriched canal impacts chloride and sulfate in the interior marsh. In contrast, total phosphorus in the interior marsh shows low sensitivity to intrusion and dispersive transport. We conducted a rainfall-driven scenario test in which the pumped inflow concentrations of chloride, sulfate and total phosphorus were equal to rainfall concentrations (wet deposition). This test shows that pumped inflow is the dominant factor responsible for the substantially increased chloride and sulfate concentrations in the interior marsh. Therefore, the present day Refuge should not be classified as solely a rainfall-driven or ombrotrophic wetland. The model provides an effective screening tool for studying the impacts of various water management alternatives on water quality across the Refuge, and demonstrates the practicality of similarly modeling other wetland systems. As a general rule, modeling provides one component of a multi-faceted effort to provide technical support for ecosystem management decisions.

Florida↗
USGS2007

USGS Tampa Bay Pilot Study

Many of the nation's estuaries have been environmentally stressed since the turn of the 20th century and will continue to be impacted in the future. Tampa Bay, one the Gulf of Mexico's largest estuaries, exemplifies the threats that our estuaries face (EPA Report 2001, Tampa Bay Estuary Program-Comprehensive Conservation and Management Plan (TBEP-CCMP)). More than 2 million people live in the Tampa Bay watershed, and the population constitutes to grow. Demand for freshwater resources, conversion of undeveloped areas to resident and industrial uses, increases in storm-water runoff, and increased air pollution from urban and industrial sources are some of the known human activities that impact Tampa Bay. Beginning on 2001, additional anthropogenic modifications began in Tampa Bat including construction of an underwater gas pipeline and a desalinization plant, expansion of existing ports, and increased freshwater withdrawal from three major tributaries to the bay. In January of 2001, the Tampa Bay Estuary Program (TBEP) and its partners identifies a critical need for participation from the U.S. Geological Survey (USGS) in providing multidisciplinary expertise and a regional-scale, integrated science approach to address complex scientific research issue and critical scientific information gaps that are necessary for continued restoration and preservation of Tampa Bay. Tampa Bay stakeholders identified several critical science gaps for which USGS expertise was needed (Yates et al. 2001). These critical science gaps fall under four topical categories (or system components): 1) water and sediment quality, 2) hydrodynamics, 3) geology and geomorphology, and 4) ecosystem structure and function. Scientists and resource managers participating in Tampa Bay studies recognize that it is no longer sufficient to simply examine each of these estuarine system components individually, Rather, the interrelation among system components must be understood to develop conceptual and predictive modeling tools for effective ecosystem adaptive management. As a multidisciplinary organization, the USGS possesses the capability of developing and coordinating an integrated science strategy for estuarine research founded on partnerships and collaborative efforts, multidisciplinary teams of scientists, and integrated field work, data analysis and interpretation, and product development. The primary role of the USGS in Tamps Bay research was defined with our partners based upon this capability to address estuarine issues using an integrated science approach with a regional perspective and within a national context to complement the numerous ongoing scien efforts by state and local agencies that address local issues within Tamp Bay. Six primary components of the USGS Tamp Bay Study address critical gaps within each of the the four estuarine system components and focus on: 1.) Examining how natural and man-made physical changes affect ecosystem health through mapping and modeling. 2.) Identifying sources and quality of groundwater, surface water, and sediment, 3.) Identifying sources and quality of groundwater, surface water, and sediment, 4.) Assessing the natural and man-made changes affecting wetland health and restoration, 5.) Identifying and measuring the impact of urbanization on seafloor habitats, Providing a web-based digital information management system of information for scientists and the public, including a system that supports the work of those officials who must make decisions that affect the state of the bay. The Tampa Bay Study is in its sixth year and will continue through September 2007. This paper presents a non-inclusive summary of key findings associated with the six primary project components listed above. Component 4 (above) is described in detail in the following chapter 13. More information on the Tampa Bay Study is available from our on-line digital information system for the Tampa Bay Study at http://gulfsci.usgs.gov.

Florida↗
USGS2019

Evaluating community-level response to management actions across a diverse Hawaiian forest bird community

Although species‐specific approaches are necessary to understand the dynamics of individual species composing a community, they do not offer a framework for making optimal management decisions at the community level. Here, we present a simple framework for comparing the response of entire communities to multiple management scenarios. Our approach uses a weighted average of standardized species‐specific responses to produce a single integrative measure of the community response and employs mixed‐effect linear models to quantify the increase in the community response due to each management action, or combination of actions. We demonstrate our approach with a simulation study assessing the potential benefits of multiple management actions on the avian community of Hakalau Forest National Wildlife Refuge, Hawaiʻi, which is composed of eight native species with conservation status varying from endangered to least concern. Management actions considered included a reduction of avian malaria transmission risk, reducing rat predation, and increasing forest habitat. We used three different prioritization (weighting) schemes to assess whether the response to management actions differed along a conservation gradient (from endangered to least concern). We also investigated whether future changes in disease distribution as a result of climate change will alter the relationship between management practices and community response. Our community‐level analysis produced three important insights, highlighting the need to consider the response from multiple species to changing threats and management actions. First, increasing the amount of habitat always had the greatest positive impact on the avian community, regardless of the weighting scheme. Second, the community response to management was different under current vs. future conditions, with increased benefit in the future when disease risks were higher. Third, the response to management varied along the conservation gradient. Reducing malaria transmission risk in 2100 had the greatest benefit to endangered species, while increasing forest habitat had the greatest benefit to “least concern” species. However, reducing rat predation appeared to benefit a subset of species based on ecological factors unrelated to rarity, such as nest accessibility. Our approach is widely applicable using experimental, observational, or simulation‐based data, allowing managers to consider the response of all species while weighting their priority levels.

Hawaii↗
USGS2011

A GIS application for assessing, mapping, and quantifying the social values of ecosystem services

As human pressures on ecosystems continue to increase, research involving the effective incorporation of social values information into the context of comprehensive ecosystem services assessments is becoming more important. Including quantified, spatially explicit social value metrics in such assessments will improve the analysis of relative tradeoffs among ecosystem services. This paper describes a GIS application, So cia l V alues for E cosystem S ervices (SolVES), developed to assess, map, and quantify the perceived social values of ecosystem services by deriving a non-monetary Value Index from responses to a public attitude and preference survey. SolVES calculates and maps the Value Index for social values held by various survey subgroups, as distinguished by their attitudes regarding ecosystem use. Index values can be compared within and among survey subgroups to explore the effect of social contexts on the valuation of ecosystem services. Index values can also be correlated and regressed against landscape metrics SolVES calculates from various environmental data layers. Coefficients derived through these analyses were applied to their corresponding data layers to generate a predicted social value map. This map compared favorably with other SolVES output and led to the addition of a predictive mapping function to SolVES for value transfer to areas where survey data are unavailable. A more robust application is being developed as a public domain tool for decision makers and researchers to map social values of ecosystem services and to facilitate discussions among diverse stakeholders involving relative tradeoffs among different ecosystem services in a variety of physical and social contexts.

Applied Geography↗
USGS2024

Social vulnerability and water insecurity in the western US: A systematic review of framings, indicators, and uncertainty

Water insecurity poses a complex challenge for the western United States. Large populations are exposed and susceptible to physical and social factors that can leave them with precarious access to sufficient water supplies. Consideration of social issues by water managers can help ensure equitable supply. However, how social factors affect water insecurity conditions remains unclear. This paper reviews literature on how social vulnerability influences water insecurity in the western United States. Through a meta-analysis, indicators measuring how dimensions of social vulnerability influence water insecurity were classified and hierarchical clustering was used to characterize the relationships among these vulnerability dimensions for the largest water-users—the agricultural and municipal sectors. The study then assessed uncertainty associated with social vulnerability dimensions and their indicators. There is greatest evidence for the influence of demographic characteristics, socioeconomic status, and exposure. Indicators of these determinants were mainly significant and exacerbated conditions of water insecurity. Evidence for indicators of social dependence and special needs populations was limited, although studies assessing these factors showed significant agreement on their influence on water insecurity. Conceptual framings of social vulnerability and water security determined which indicators were measured, whereas studies of the water-use sectors focused on differing associations of social vulnerability. These findings indicate the importance of recognizing the different contexts posed by water-use sectors and diverse conceptual framings. Further, some determinants such as living conditions remain important but underexplored drivers of a community's experience of water insecurity. Understanding the uncertainty associated with these measures has implications to equitable decision making.

Water Resources Research↗