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At least 937 records · Page 52Linked to original sources

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↗

USGS2006

Surface-Water Quantity and Quality of the Upper Milwaukee River, Cedar Creek, and Root River Basins, Wisconsin, 2004

The U.S. Geological Survey, in cooperation with the Southeastern Wisconsin Regional Planning Commission (SEWRPC), collected discharge and water-quality data at nine sites in previously monitored areas of the upper Milwaukee River, Cedar Creek, and Root River Basins, in Wisconsin from May 1 through November 15, 2004. The data were collected for calibration of hydrological models that will be used to simulate how various management strategies will affect the water quality of streams. The data also will support SEWRPC and Milwaukee Metropolitan Sewerage District (MMSD) managers in development of the SEWRPC Regional Water Quality Management Plan and the MMSD 2020 Facilities Plan. These management plans will provide a scientific basis for future management decisions regarding development and maintenance of public and private waste-disposal systems. In May 2004, parts of the study area received over 13 inches of precipitation (3.06 inches is normal). In June 2004, most of the study area received between 7 and 11 inches of rainfall (3.56 inches is normal). This excessive rainfall caused flooding throughout the study area and resultant high discharges were measured at all nine monitoring sites. For example, the mean daily discharge recorded at the Cedar Creek site on May 27, 2004, was 2,120 cubic feet per second. This discharge ranked ninth of the largest 10 mean daily discharges in the 75-year record, and was the highest discharge recorded since March 30, 1960. Discharge records from continuous monitoring on the Root River Canal near Franklin since October 1, 1963, indicated that the discharge recorded on May 23, 2004, ranked second highest on record, and was the highest discharge recorded since March 4, 1974. Water-quality samples were taken during two base-flow events and six storm events at each of the nine sites. Analysis of water-quality data indicated that most concentrations of dissolved oxygen, biological oxygen demand, fecal coliform bacteria, chloride, suspended solids, nitrate plus nitrite nitrogen, ammonia nitrogen, Kjeldahl nitrogen, total phosphorus, dissolved orthophosphorus, total copper, particulate mercury, dissolved mercury, particulate methylmercury, dissolved methylmercury, and total zinc were below U.S. Environmental Protection Agency (USEPA) and State of Wisconsin water-quality standards at all sites, with the exception of dissolved oxygen at the Kewaskum, Farmington, Root River Canal, Root River Racine, and Root River Mouth sites. Each of these sites had from several days to several weeks of daily average dissolved oxygen concentrations below the 5 milligrams per liter State of Wisconsin standard for aquatic life. The lowest dissolved oxygen concentrations were measured at the heavily urbanized Root River Mouth site in downtown Racine, Wisconsin, where elevated concentrations of ammonia may have contributed to oxygen consumption during oxidation of ammonia to nitrate. Additionally, the maximum concentrations of copper in several Root River samples exceeded draft USEPA Ambient Water-Quality Criteria (U.S. Environmental Protection Agency, 2003) for acute toxicity to several species of aquatic organisms. Substantial water-quality changes were not correlated with hydrologic changes at any of the nine sites. Base-flow water-quality was generally indistinguishable from that sampled during storm events. The sparsely developed upper Milwaukee River and Cedar Creek Basins had relatively low ranges of contamination for all laboratory-reported parameters. For all nine sites, the highest reported concentrations of chloride (216 mg/L), total phosphorus (0.627 mg/L), ortho-phosphorus (0.136 mg/L), nitrate plus nitrate (9.32 mg/L), and copper (38 ?g/L) were reported for samples collected at the Root River Canal site. The highest concentrations of fecal coliforms (3,600 colonies per 100 mL) and Escherichia coli (2,300 colonies per 100 mL) were reported in samples collected at Kewaskum. The highest concentrations of s

Open-File Report↗

USGS2020

Investigating the effects of land use and land cover on the relationship between moisture and reflectance using Landsat Time Series

To better understand the Earth system, it is important to investigate the interactions between precipitation, land use/land cover (LULC), and the land surface, especially vegetation. An improved understanding of these land-atmosphere interactions can aid understanding of the climate system and modeling of time series satellite data. Here, we investigate the effect of precipitation and LULC on the reflectance of the land surface in the northern U.S. Great Plains. We utilize time series satellite data from the 45 year Landsat archive. The length of the Landsat record allows for analysis of multiple periods of drought and wet conditions (reflecting climate, as well as weather), such that the precipitation-reflectance relationship can be investigated robustly for every individual pixel in the study area. The high spatial resolution of Landsat (30 m) allows for investigation of spatial patterns in weather (i.e., precipitation extremes) interactions with land surface reflectance at the scale of individual fields. Weather history is represented by a drought index that describes effective moisture availability, the Standardized Precipitation and Evaporation Index (SPEI). We find that effective moisture has a robust and consistent effect on reflectance over many types of land cover, with ∼90% of all pixels having significantly ( p < 0.01 "> p < 0.01 ) higher visible reflectance during dry periods than during wet, occurring in nearly all regional, temporal, and LULC categories investigated. In grassland, the relationship is especially strong; there is an average reflectance increase of more than a third between very wet and very dry conditions (red band), and ∼99% of pixels have a significant relationship. In cropland, the effective moisture-reflectance relationship is more variable, suggesting that management decisions are an important factor in cropland-reflectance relationships.

North Dakota, South Dakota↗

USGS2023

Modeling the spatial distribution of carcasses of eagles killed by wind turbines

Currently, the US Fish and Wildlife Service makes eagle permitting and management decisions nationwide based on a limited understanding of the impacts of wind power generation on eagles, and the factors that influence risk at a given facility. Accurate estimates of eagle mortality at wind power facilities form the basis for comparing the magnitudes of mortality rates in different areas and for measuring the benefits of proposed methods of minimizing the collision-caused impacts to eagle populations. Simple counts of observed eagle carcasses at wind facilities are almost certainly underestimates of the true mortality because fatalities can be removed by scavengers, be missed by searchers, or fall outside searched areas. For the latter, models of relative carcass density as a function of distance from the turbine can be fit to observed carcass locations and used to estimate the proportion of carcasses expected to land within an area of any configuration beneath a turbine. In the USA, however, it has been difficult to estimate these models for large birds such as Bald Eagles ( Haliaeetus leucocephalus ) and Golden Eagles ( Aquila chrysaetos ) due to inadequate numbers of dead eagles found at any single facility. In this case, analysis of a surrogate species might be useful to inform carcass distributions. We chose to model the carcass distribution of White-tailed Eagles ( Haliaeetus albicilla ) in Norway as an informative surrogate for Bald Eagles and Golden Eagles in the USA. Our three best-fitting parametric models were very consistent in estimating that 50% (95% CI: 40–60%) of White-tailed Eagle carcasses land within approximately 42 m of the turbines that had 70-m hubs and approximately 40-m blades. Although our models were fit to data from White-tailed Eagles and not Bald or Golden Eagles, applying these models when calculating mortality impacts of wind developments on both eagle species will likely improve the accuracy of post-construction mortality estimates, particularly at sites where substantial areas may be unsearchable. Accurate post-construction mortality estimates can inform pre-construction fatality prediction models. Resource managers can determine whether their conditions are sufficiently similar to those we modeled to warrant the use of these models for Bald and Golden Eagle carcass distributions.

Journal of Raptor Research↗

USGS2021

SMaRT: A science-based tiered framework for common ravens

Large-scale increases and expansion of common raven ( Corvus corax ; raven) populations are occurring across much of North America, leading to increased negative consequences for livestock and agriculture, human health and safety, and sensitive species conservation. We describe a science-based adaptive management framework that incorporates recent quantitative analyses and mapping products for addressing areas with elevated raven numbers and minimizing potential adverse impacts to sensitive species, agricultural damage, and human safety. The framework comprises 5 steps: (1) desktop analysis; (2) field assessments; (3) comparison of raven density estimates to an ecological threshold (in terms of either density or density plus distance to nearest active or previous nest); (4) prescribing management options using a 3-tiered process (i.e., habitat improvements, subsidy reductions, and direct actions using StallPOPd.V4 software); and (5) post-management monitoring. The framework is integrated within the Science-based Management of Ravens Tool (SMaRT), a web-based application outfitted with a user-friendly interface that guides managers through each step to develop a fully customized adaptive plan for raven management. In the SMaRT interface, users can: (1) interact with pre-loaded maps of raven occurrence and density and define their own areas of interest within the Great Basin to delineate proposed survey or treatment sites; (2) enter site-level density estimates from distance sampling methods or perform estimation of raven densities using the rapid assessment protocol that we provide; (3) compare site-level density estimates to an identified ecological threshold; and (4) produce a list of potential management options for their consideration. The SMaRT supports decision-making by operationalizing scientific products for raven management and facilitates realization of diverse management goals including sensitive species conservation, protection of livestock and agriculture, safeguarding human health, and addressing raven overabundance and expansion. We illustrate the use of the framework through SMaRT using an example of greater sage-grouse ( Centrocercus urophasianus ) conservation efforts within the Great Basin, USA.

California, Idaho, Nevada, Oregon, Utah↗

USGS2021

Rigorously valuing the impact of Hurricanes Irma and Maria on coastal hazard risks in Florida and Puerto Rico

The degradation of coastal habitats, particularly coral reefs, raises risks by increasing the exposure of coastal communities to flooding hazards. In the United States, the physical protective services provided by coral reefs were recently assessed in social and economic terms, with the annual protection provided by U.S. coral reefs off the coasts of the State of Florida and the Commonwealth of Puerto Rico estimated to be more than 9,800 people and $859 million (2010 U.S. dollars). Hurricanes Irma and Maria in 2017 caused widespread damage to coral reefs in the State of Florida and the Commonwealth of Puerto Rico. These damages were measured in post-storm surveys of reefs and assessed in terms of their impact on reef condition and height, which are critical parameters for evaluating the coastal defense benefits of reefs. We combined engineering, ecologic, geospatial, social, and economic data and tools to value the increased risks in Florida and Puerto Rico from hurricane-induced damages to their adjacent coral reefs. We followed risk-based valuation approaches to map flooding at 10-square-meter resolution along all 980 kilometers of Florida and Puerto Rico’s reef-lined shorelines considering reef condition before (undamaged) and after (damaged) the 2017 hurricanes. We quantified the coastal flood risk increase caused by the hurricane-induced damage to the coral reefs using the latest information from the U.S. Census Bureau, Federal Emergency Management Agency, and Bureau of Economic Analysis for return-interval storm events. Using the damages associated with each storm probability, we also calculated the change in annual expected damages, a measure of the annual protection lost because of the reef damage caused by the 2017 hurricanes. We found that the damages to the coral reefs off Florida and Puerto Rico from Hurricanes Irma and Maria increased future risks significantly. In particular, we estimated the protection lost by Florida and Puerto Rico’s coral reefs from the 2017 hurricanes to result in: Increased flooding to more than 10.72 square kilometers (4.14 square miles) of land annually; Increased flooding affecting more than 4,300 people annually; Increased direct damages of more than $57.2 million to more than 1,800 buildings annually; and Increased indirect damages to more $124.3 million in economic activity owing to housing and business damage annually. Thus, the annual value of increased flood risk caused by the damage to Florida and Puerto Rico’s coral reefs from hurricanes in 2017 is more than 4,300 people and $181.5 mil-lion (2010 U.S. dollars) in economic impacts. These data provide stakeholders and decision makers with a spatially explicit, rigorous valuation of how, where, and when the damage from the 2017 hurricanes decreased critical coastal storm flood reduction benefits to Florida and Puerto Rico’s coral reefs. These results help identify areas where reef management, recovery, and restoration could potentially help reduce the risk to, and increase the resiliency of, Florida and Puerto Rico’s coastal communities.

Florida↗

USGS2024

An integrated analysis for estimation of survival, growth, and movement of unmarked juvenile anadromous fish

Managers invest substantial resources to promote recovery of declining anadromous fish stocks. Recovery strategies are manifold and often include management actions intended to stimulate somatic growth, increase in-river survival, and motivate juvenile outmigration during favorable environmental conditions. Evaluating the efficacy of these management actions is difficult, however, because monitoring data that explicitly track individuals from egg deposition to juvenile outmigration are typically lacking. We developed an integrated population model that links two different and often collected types of anadromous fish monitoring data: spawning ground surveys and rotary screw trap juvenile catch data. The integrated model accounts for incomplete detection and uses the two sources of data to estimate juvenile demographic parameters in a multistate framework. We evaluated the model's performance using simulated data under a range of conditions typically encountered in similar surveys. Simulation results indicated that the model estimated juvenile survival, growth, and movement with no-to-minimal bias (i.e., ≥ 50 % of simulations ± 0–0.05). As an example case study, we fit the model to empirical fall-run Chinook Salmon ( Oncorhynchus tshawytscha ) monitoring data collected in California's Central Valley, U.S.A. In doing so, we evaluated the influence of environmental conditions (e.g., discharge, water temperature) and habitat availability on juvenile demographic rates. We demonstrated that through our integrated approach we could estimate state transition probabilities that are typically inestimable for naturally produced, unmarked juvenile fish when using traditional statistical approaches to analyze these types of monitoring data. Furthermore, the structure of our model can serve as a useful foundation for decision-support models within adaptive management programs by directly linking management actions, decision-support-model predictions, and monitoring.

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