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At least 1,297 records · Page 72Linked to original sources
USGS2022

New projections of 21st century climate and hydrology for Alaska and Hawaiʻi

In the United States, high-resolution, century-long, hydroclimate projection datasets have been developed for water resources planning, focusing on the contiguous United States (CONUS) domain. However, there are few statewide hydroclimate projection datasets available for Alaska and Hawaiʻi. The limited information on hydroclimatic change motivates developing hydrologic scenarios from 1950 to 2099 using climate-hydrology impact modeling chains consisting of multiple statistically downscaled climate projections as input to hydrologic model simulations for both states. We adopt an approach similar to the previous CONUS hydrologic assessments where: 1) we select the outputs from ten global climate models (GCM) from the Coupled Model Intercomparison Project Phase 5 with Representative Concentration Pathways 4.5 and 8.5; 2) we perform statistical downscaling to generate climate input data for hydrologic models (12-km grid-spacing for Alaska and 1-km for Hawaiʻi); and 3) we perform process-based hydrologic model simulations. For Alaska, we have advanced the hydrologic model configuration from CONUS by using the full water-energy balance computation, frozen soils and a simple glacier model. The simulations show that robust warming and increases in precipitation produce runoff increases for most of Alaska, with runoff reductions in the currently glacierized areas in Southeast Alaska. For Hawaiʻi, we produce the projections at high resolution (1 km) which highlight high spatial variability of climate variables across the state, and a large spread of runoff across the GCMs is driven by a large precipitation spread across the GCMs. Our new ensemble datasets assist with state-wide climate adaptation and other water planning.

Alaska, Hawaii↗
USGS2016

Cross-seasonal effects on waterfowl productivity: Implications under climate change

Previous efforts to relate winter-ground precipitation to subsequent reproductive success as measured by the ratio of juveniles to adults in the autumn failed to account for increased vulnerability of juvenile ducks to hunting and uncertainty in the estimated age ratio. Neglecting increased juvenile vulnerability will positively bias the mean productivity estimate, and neglecting increased vulnerability and estimation uncertainty will positively bias the year-to-year variance in productivity because raw age ratios are the product of sampling variation, the year-specific vulnerability, and year-specific reproductive success. Therefore, we estimated the effects of cumulative winter precipitation in the California Central Valley and the Mississippi Alluvial Valley on pintail ( Anas acuta ) and mallard ( Anas platyrhnchos ) reproduction, respectively, using hierarchical Bayesian methods to correct for sampling bias in productivity estimates and observation error in covariates. We applied the model to a hunter-collected parts survey implemented by the United States Fish and Wildlife Service and band recoveries reported to the United States Geological Survey Bird Banding Laboratory using data from 1961 to 2013. We compared our results to previous estimates that used simple linear regression on uncorrected age ratios from a smaller subset of years in pintail (1961–1985). Like previous analyses, we found large and consistent effects of population size and wetland conditions in prairie Canada on mallard productivity, and large effects of population size and mean latitude of the observed breeding population on pintail productivity. Unlike previous analyses, we report a large amount of uncertainty in the estimated effects of wintering-ground precipitation on pintail and mallard productivity, with considerable uncertainty in the sign of the estimated main effect, although the posterior medians of precipitation effects were consistent with past studies. We found more consistent estimates in the sign of an interaction effect between population size and precipitation, suggesting that wintering-ground precipitation has a larger effect in years of high population size, especially for pintail. When we used the estimated effects in a population model to derive a sustainable harvest and population size projection (i.e., a yield curve), there was considerable uncertainty in the effect of increased or decreased wintering-ground precipitation on sustainable harvest potential and population size. These results suggest that the mechanism of cross-seasonal effects between winter habitat and reproduction in ducks occurs through a reduction in the strength of density dependence in years of above-average wintering-ground precipitation. We suggest additional investigation of the underlying mechanisms and that habitat managers and decision-makers consider the level of uncertainty in these estimates when attempting to integrate habitat management and harvest management decisions. Collection of annual data on the status of wintering-ground habitat in a rigorous sampling framework would likely be the most direct way to improve understanding of mechanisms and inform management.

Journal of Wildlife Management↗
USGS2021

Optimization of salt marsh management at the Edwin B. Forsythe National Wildlife Refuge, New Jersey, through use of structured decision making

Structured decision making is a systematic, transparent process for improving the quality of complex decisions by identifying measurable management objectives and feasible management actions; predicting the potential consequences of management actions relative to the stated objectives; and selecting a course of action that maximizes the total benefit achieved and balances tradeoffs among objectives. The U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service, applied an existing, regional framework for structured decision making to develop a prototype tool for optimizing tidal marsh management decisions at the Edwin B. Forsythe National Wildlife Refuge in New Jersey. Refuge biologists, refuge managers, and research scientists identified multiple potential management actions to improve the ecological integrity of 23 marsh management units within the refuge and estimated the outcomes of each action in terms of performance metrics associated with each management objective. Value functions previously developed at the regional level were used to transform metric scores to a common utility scale, and utilities were summed to produce a single score representing the total management benefit that could be accrued from each potential management action. Constrained optimization was used to identify the set of management actions, one per marsh management unit, that could maximize total management benefits at different cost constraints at the refuge scale. Results indicated that, for the objectives and actions considered here, total management benefits may increase consistently up to about \$980,000, but that further expenditures may yield diminishing return on investment. Potential management actions in optimal portfolios at total costs less than \$980,000 included applying sediment to the marsh surface to increase elevation in five marsh management units, digging runnels on the marsh surface to improve drainage in five marsh management units, and breaching roads and berms to improve tidal flow in five marsh management units. The potential management benefits were derived from expected reduction in the duration of surface flooding, improved capacity for marsh elevation to keep pace with sea-level rise and increases in numbers of spiders (as an indicator of trophic health), tidal marsh obligate birds, and wintering American black ducks. The prototype presented here does not resolve management decisions; rather, it provides a framework for decision making at the Edwin B. Forsythe National Wildlife Refuge that can be updated as new data and information become available. Insights from this process may also be useful to inform future habitat management planning at the refuges.

New Jersey↗
USGS2022

Optimization of salt marsh management at the Petit Manan National Wildlife Refuge of the Maine Coastal Islands National Wildlife Refuge Complex, Maine, through use of structured decision making

Structured decision making is a systematic, transparent process for improving the quality of complex decisions by identifying measurable management objectives and feasible management actions; predicting the potential consequences of management actions relative to the stated objectives; and selecting a course of action that maximizes the total benefit achieved and balances tradeoffs among objectives. The U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service, applied an existing, regional framework for structured decision making to develop a prototype tool for optimizing tidal marsh management decisions at the Petit Manan National Wildlife Refuge of the Maine Coastal Islands National Wildlife Refuge Complex in Maine. Refuge biologists, refuge managers, and research scientists identified multiple potential management actions to improve the ecological integrity of two marsh management units within the refuge complex, totaling about 47 hectares, and estimated the outcomes of each action in terms of performance metrics associated with each management objective. Value functions previously developed at the regional level were used to transform metric scores to a common utility scale, and utilities were summed to produce a single score representing the total management benefit that could be accrued from each potential management action. Constrained optimization was used to identify the set of management actions, one per marsh management unit, that could maximize total management benefits at different cost constraints at the refuge scale. Results indicated that, for the objectives and actions considered here, total management benefits may increase consistently up to $ 9,545, and may continue to increase at a lower rate with further expenditures. Potential management actions in optimal portfolios at total costs less than or equal to $ 9,545 included removing dikes to restore tidal flow in the Gouldsboro Bay management unit and installing runnels to improve surface-water drainage in the Sawyers Marsh management unit. The potential management benefits were derived from expected increases in the numbers of tidal marsh obligate breeding birds and density of spiders (as an indicator of trophic health), reduced duration of flooding, and increased capacity of marsh elevation to keep pace with sea-level rise. The prototype presented here does not resolve management decisions; rather, it provides a framework for decision making at the Maine Coastal Islands National Wildlife Refuge Complex that can be updated for implementation as new data and information become available. Insights from this process may also be useful to inform future habitat management planning at the refuge complex.

Maine↗
USGS2006

Geologic map of the Wrangell-Saint Elias National Park and Preserve, Alaska

Wrangell-Saint Elias National Park and Preserve, the largest national park within the U.S. National Park Service system, extends from the northern Pacific Ocean to beyond the eastern Alaska Range into interior Alaska. It features impressively spectacular scenery such as high and craggy mountains, active and ancient volcanoes, expansive ice fields, immense tidewater glaciers, and a myriad of alpine glaciers. The park also includes the famous Kennecott Mine, a world-class copper deposit that was mined from 1911 to 1938, and remnant ghost town, which is now a National Historic Landmark. Geologic investigations encompassing Wrangell-Saint Elias National Park and Preserve began in 1796, with Dmitriv Tarkhanov, a Russian mining engineer, who unsuccessfully ventured up the Copper River in search of rumored copper. Lieutenant H.T. Allen (1897) of the U.S. Army made a successful epic summer journey with a limited military crew up the Copper River in 1885, across the Alaska Range, and down the Tanana and Yukon Rivers. Allen?s crew was supported by a prospector named John Bremner and local Eyak and Ahtna native guides whose tribes controlled access into the Copper River basin. Allen witnessed the Ahtnas? many uses of the native copper. His stories about the copper prompted prospectors to return to this area in search of the rich copper ore in the years following his journey. The region boasts a rich mining and exploration history prior to becoming a park in 1980. Several U.S. Geological Survey geologists have conducted reconnaissance surveys in the area since Allen?s explorations. This map is the result of their work and is enhanced by more detailed investigations, which began in the late 1950s and are still continuing. For a better understanding of the processes that have shaped the geology of the park and a history of the geologic investigations in the area, we recommend U.S. Geological Survey Professional Paper 1616, ?A Geologic Guide to Wrangell-Saint Elias National Park and Preserve, Alaska,? an exceptionally well illustrated and informative book by Gary R. Winkler, 2000. Geologically, the park consists of a collage of seven tectonostratigraphic terranes that formed south in the equatorial Pacific Ocean and rafted northward on oceanic plates, eventually accreting to Alaska and the North American continent. Each terrane features a distinct stratigraphy and is separated from neighboring terranes by major strike-slip or thrust faults.

Alaska↗
USGS2016

Forecasting tidal marsh elevation and habitat change through fusion of Earth observations and a process model

Reducing uncertainty in data inputs at relevant spatial scales can improve tidal marsh forecasting models, and their usefulness in coastal climate change adaptation decisions. The Marsh Equilibrium Model (MEM), a one-dimensional mechanistic elevation model, incorporates feedbacks of organic and inorganic inputs to project elevations under sea-level rise scenarios. We tested the feasibility of deriving two key MEM inputs—average annual suspended sediment concentration (SSC) and aboveground peak biomass—from remote sensing data in order to apply MEM across a broader geographic region. We analyzed the precision and representativeness (spatial distribution) of these remote sensing inputs to improve understanding of our study region, a brackish tidal marsh in San Francisco Bay, and to test the applicable spatial extent for coastal modeling. We compared biomass and SSC models derived from Landsat 8, DigitalGlobe WorldView-2, and hyperspectral airborne imagery. Landsat 8-derived inputs were evaluated in a MEM sensitivity analysis. Biomass models were comparable although peak biomass from Landsat 8 best matched field-measured values. The Portable Remote Imaging Spectrometer SSC model was most accurate, although a Landsat 8 time series provided annual average SSC estimates. Landsat 8-measured peak biomass values were randomly distributed, and annual average SSC (30 mg/L) was well represented in the main channels (IQR: 29–32 mg/L), illustrating the suitability of these inputs across the model domain. Trend response surface analysis identified significant diversion between field and remote sensing-based model runs at 60 yr due to model sensitivity at the marsh edge (80–140 cm NAVD88), although at 100 yr, elevation forecasts differed less than 10 cm across 97% of the marsh surface (150–200 cm NAVD88). Results demonstrate the utility of Landsat 8 for landscape-scale tidal marsh elevation projections due to its comparable performance with the other sensors, temporal frequency, and cost. Integration of remote sensing data with MEM should advance regional projections of marsh vegetation change by better parameterizing MEM inputs spatially. Improving information for coastal modeling will support planning for ecosystem services, including habitat, carbon storage, and flood protection.

California↗
USGS2020

Predicting barrier island habitats and oyster and seagrass habitat suitability for various restoration measures and future conditions for Dauphin Island, Alabama

Barrier islands, such as Dauphin Island, Alabama, provide numerous invaluable ecosystem services including storm damage reduction and erosion control to the mainland, habitat for fish and wildlife, carbon sequestration in marshes, water catchment and purification, recreation, and tourism. These islands are dynamic environments that are gradually shaped by currents, waves, and tides under quiescent conditions yet can evolve in the time scale of hours to days during hurricanes and other extreme storms. The ecosystems associated with these islands also face numerous other hazards, including accelerated sea-level rise, oil spills, and anthropogenic stressors. Hurricane Katrina in 2005 and the Deepwater Horizon oil spill in 2010 are two major events that have affected habitats and natural resources on Dauphin Island, Ala. The latter event prompted a cooperative effort between the U.S. Geological Survey and the U.S. Army Corps of Engineers to investigate viable, sustainable restoration measures that reduce degradation and enhance the natural resources of Dauphin Island, Ala. In collaboration with the State of Alabama and the National Fish and Wildlife Foundation, the overarching goal of the Alabama Barrier Island Restoration Feasibility Assessment project was to document baseline conditions and forecast potential conditions under varying sea-level change and storm scenarios for a no-action alternative along with a variety of restoration measures including beach and dune restoration, marsh and back-barrier restoration, and placement of sand in the littoral zone. The modeling component of this project used decadal hydrodynamic geomorphic, water quality, and habitat modeling to better understand how the various restoration measures may influence the habitat composition, sustainability, and resiliency of Dauphin Island under potential future conditions, benchmarked against the no-action case. The report covers the habitat modeling efforts associated with the Alabama Barrier Island Restoration Feasibility Assessment project. For various potential future island configurations for Dauphin Island, we predicted coverage of habitat types (for example, beach, dune, intertidal marsh, and woody vegetation) using a spatially explicit habitat model based on landscape-position information (for example, elevation and distance from shore) extracted from the hydrodynamic geomorphic outputs. Similarly, we forecasted habitat suitability for oysters and seagrass using habitat suitability index models. Another component of the Alabama Barrier Island Restoration Feasibility Assessment project, presented separately, integrates these habitat model results into a structured decision-making framework that accounts for competing objectives. Collectively, this information provides insights to natural resource managers and planners on how a restoration measure may maintain or impede natural coastal processes and provide information critical for making future-focused decisions regarding barrier island restoration.

Alabama↗
USGS2021

Optimization of salt marsh management at the Eastern Shore of Virginia and Fisherman Island National Wildlife Refuges, Virginia, through use of structured decision making

Structured decision making is a systematic, transparent process for improving the quality of complex decisions by identifying measurable management objectives and feasible management actions; predicting the potential consequences of management actions relative to the stated objectives; and selecting a course of action that maximizes the total benefit achieved and balances tradeoffs among objectives. The U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service, applied an existing, regional framework for structured decision making to develop a prototype tool for optimizing tidal marsh management decisions at the Eastern Shore of Virginia and Fisherman Island National Wildlife Refuges in Virginia. Refuge biologists, refuge managers, and research scientists identified multiple potential management actions to improve the ecological integrity of six marsh management units within the refuges, totaling about 575 hectares, and estimated the outcomes of each action in terms of performance metrics associated with each management objective. Value functions previously developed at the regional level were used to transform metric scores to a common utility scale, and utilities were summed to produce a single score representing the total management benefit that could be accrued from each potential management action. Constrained optimization was used to identify the set of management actions, one per marsh management unit, that could maximize total management benefits at different cost constraints at the refuge scale. Results indicated that, for the objectives and actions considered here, total management benefits may increase consistently up to approximately $ 143,000, but that further expenditures may yield diminishing return on investment. Potential management actions in optimal portfolios at total costs less than $ 143,000 included digging runnels by hand to improve drainage from the marsh surface, breaching a road to restore natural hydrology, trapping predators to enhance nest success of tidal marsh birds, and reducing the abundance of Odocoileus virginianus (white-tailed deer) to minimize their effects on marsh vegetation. The potential management benefits were derived from expected increases in number of tidal marsh obligate breeding birds, species richness of nekton, and density of spiders (as an indicator of trophic health); and an expected decrease in duration of surface flooding. The prototype presented here does not resolve management decisions; rather, it provides a framework for decision making at the Eastern Shore of Virginia and Fisherman Island National Wildlife Refuges that can be updated as new data and information become available. Insights from this process may also be useful to inform future habitat management planning at the refuges.

Virginia↗
USGS2007

Pygmy rabbit surveys on state lands in Oregon

The pygmy rabbit (Brachylagus idahoensis) is classified by the federal government as a species of concern (i.e., under review by the U.S. Fish and Wildlife Service for consideration as a candidate for listing as threatened or endangered under the Endangered Species Act) because of its specialized habitat requirements and evidence of declining populations. The Oregon Department of Fish and Wildlife (ODFW) lists pygmy rabbits as “sensitive-vulnerable,” meaning that protective measures are needed if sustainable populations are to be maintained over time (Oregon Natural Heritage Program, 2001). The Oregon Natural Heritage Program considers this species to be threatened with extirpation from Oregon. Pygmy rabbits also are a species of concern in all the other states where they occur (NatureServe, 2004). The Washington population, known as the Columbia Basin pygmy rabbit, was listed as endangered by the federal government in 2003. Historically, pygmy rabbits have been collected from Deschutes, Klamath, Crook, Lake, Grant, Harney, Baker, and Malheur Counties in Oregon. However, the geographic range of pygmy rabbit in Oregon may have decreased in historic times (Verts and Carraway, 1998), and boundaries of the current distribution are not known. Not all potentially suitable sites appear to be occupied, and populations are susceptible to rapid declines and local extirpation (Weiss and Verts, 1984). In order to protect and manage remaining populations on State of Oregon lands, Oregon Department of Fish and Wildlife needs to identify areas currently occupied by pygmy rabbits, as well as suitable habitats. The main objective of this survey was document to presence or absence of pygmy rabbits on state lands in Malheur, Harney, Lake, and Deschutes counties. Knowledge of the location and extent of pygmy rabbit populations can provide a foundation for the conservation and management of this species in Oregon. The pygmy rabbit is just one of a suite of species of concern associated with sagebrush habitats in the Great Basin. Because information on habitat and distribution of many species is scarce, a secondary goal of the rabbit surveys was to list all other vertebrate species encountered on surveyed sites. This information may be useful in directing future studies aimed at specific taxa.

Open-File Report↗
USGS1987

Results of a workshop concerning assessment of the functions of bottomland hardwoods

The U.S. Environmental Protection Agency (EPA) is authorized under Section 404 of the Clean Water Act (33 U.S.C. 1344) to participate in the regulation of the discharge of dredged or fill material into waters of the United States. This regulatory authority is exercised in partnership with the U.S. Army Corps of Engineers, which has responsibility for permit issuance, and in consultation with the U.S. Fish and Wildlife Service and the National Marine Fisheries Service. Through amendments to the original statute, a series of legal actions and court decisions, and the development of operating guidance among the responsible agencies, Section 404 has evolved into the primary mechanism afforded Federal authorities for the protection of wetlands. EPA recognizes the importance of wetlands in achieving the goals of the Clean Water Act, which are to protect and maintain the chemical, physical, and biological integrity of the Nation’s waters. EPA Administrator Lee Thomas has identified wetlands protection as among the highest of Agency priorities. EPA recognizes that bottomland hardwood (BLH) wetlands have vital and unique attributes that, if lost, would severely impact the physical, chemical, and biological integrity of the Nation's waters. As part of a broad program to better protect the Nation's wetlands, EPA has therefore identified bottomland hardwood wetlands as a priority resource requiring special attention on a national basis. Recognizing the importance of implementing an effective, nationally consistent, and scientifically defensible regulatory program, EPA, in October 1984, issued Interim Operating Guidance to its field personnel for implementing the Section 404 regulatory program in bottomland hardwood wetlands. With the goal of improving and finalizing that guidance, EPA is sponsoring a series of workshops designed to answer key questions concerning BLH wetlands, based on the best scientific and technical information currently available. The first two workshops were directed toward summarizing existing scientific and technical knowledge concerning the functions of BLH ecosystems, the characteristics that are important to each function, and the impact of various development activities on those characteristics. The first workshop, which was held in St. Francisville, Louisiana, in December, 1984, examined a wetland zonation concept as a framework for gaining a greater understanding of BLH structure and function. The workshop set out to determine whether characterization of BLH resources as a series of relatively distinct zones, defined by concomitant variation in hydrologic regime, soils, and vegetation, might provide the basis for a useful and scientifically sound regulatory framework. For examp1e, if certain zones are of particular importance to one or more wetland functions that the Clean Water Act was intended to protect, then the zonation concept might be useful from the perspective of how various activities should be regulated. Discussions during the first workshop, however, indicated that the zonation concept provides, at best, only an incomplete picture of the structure and function of BLH ecosystems. In many cases, BLH functions are not limited to or closely correlated with particular zones and, furthermore, many factors other than zone are important determinants of BLH functions. With these responses in mind, the second workshop, held at Lake Lanier, Georgia, in July, 1985, was designed to elicit information on two questions. First, if zones are not an adequate framework for understanding the functions of BLH systems, what characteristics (predictors) can be used to assess the extent to which a particular site performs these functions? And second, what are the impacts of various development activities that often occur in BLH ecosystems on those characteristics and thus on the functions themselves? At the second workshop, individual workgroups dealing with particular subject areas (e.g., hydrology, water quality, fisheries, wildlife, ecosystem processes, and cultural/recreational/economic resources) were able to identify site characteristics that are important determinants of the performance of various functions. For example, the Hydrology Workgroup identified flood storage as one of three major hydrologic functions that BLH ecosystems perform. The workgroup then identified the most important characteristic (e.g., surface area of the site, soil saturation, and others) that determine flood storage and the likely impact of several common activities (e.g., conversion to soybean production and levee construction) on these characteristics. Some of the workgroups also provided estimates of the aggregate impact of activities, acting through all of the characteristics, on certain functions. The workgroups also identified key characteristics that could be used to identify high-value wetlands for various functions. In addition, the workgroups pointed out a number of topics needing further examination and discussion. First, all of the workgroups identified the need to develop the technical basis and information sources to address the problem of cumulative impacts in the regulatory process. Second, most of the workgroups noted the important of contextual variables in assessing the function of a particular site. For example, the location of a BLH site in relationship to other tracts of habitat is an important variable for many wildlife species. Similarly, the extent to which a site retains or transforms contaminants is depended not only on the characteristics of the site, but also on its position in a watershed relative to contaminant inputs. And finally, several of the workgroups pointed out that assessing the impact of an activity on a function is not as simple as "adding up" the impact on individual characteristics, but may depend instead on complex interactions among characteristics. Addressing these questions, as summarized in the objectives and discussions that follow, was the focus of the third workshop, the results of which are described in this report.

Report↗
USGS2016

Archive of bathymetry and backscatter data collected in 2014 nearshore Breton and Gosier Islands, Breton National Wildlife Refuge, Louisiana

As part of the Barrier Island Monitoring Project, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted nearshore geophysical surveys off Breton and Gosier Islands, Louisiana, in July and August of 2014. To assist the United States Fish and Wildlife Service (USFWS) with restoration planning efforts, the USGS was tasked with answering fundamental questions about the physical environment of the southern Chandeleur Islands, including the geology, morphology, and oceanography. Baseline data needed to answer these questions were either insufficient or missing. The USGS conducted a comprehensive geologic investigation in the summer of 2014, collecting geophysical and sedimentological data. Breton Island, located at the southern end of the Chandeleur Island chain in southeastern Louisiana, was recognized as a natural, globally significant nesting sanctuary for several bird species and was established as the Breton National Wildlife Refuge (NWR) in 1904. The areal extent of Breton Island has diminished 90 percent since 1920. Land loss is attributed to ongoing relative sea-level rise, diminished sediment supply, and storm impacts. The bird population on Breton Island has also declined over the years, most notably after Hurricane George in 1998 and after Hurricane Katrina in 2015; the latter completely submerged the island. Despite decreasing habitable acreage, migratory seabirds continue to return and nest on Breton Island. To prevent the island from being submerged in the future, and to protect, stabilize, and provide more nesting and foraging areas for the bird population, the USFWS proposed a restoration effort to rebuild Breton Island to its pre-Katrina footprint. This data series serves as an archive of processed interferometric swath and single-beam bathymetry data, and side-scan sonar data, collected in the nearshore of Breton and Gosier Islands, NWR, Louisiana. The data were collected during two USGS cruises (USGS Field Activity Numbers 2014-314-FA and 2014-317-FA) in July and August 2014. Geographic information system data products include a 100-meter-cell-size interpolated bathymetry grid, trackline maps, and point data files. Additional files include error analysis maps, Field Activity Collection System logs, and formal Federal Geographic Data Committee metadata. NOTE: These data are scientific in nature and are not to be used for navigation. Any use of trade names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

Louisiana↗
USGS2022

Ungulate migration in a changing climate—An initial assessment of climate impacts, management priorities, and science needs

Executive Summary Migratory behavior among ungulates in the Western United States occurs in response to changing forage quality and quantity, weather patterns, and predation risk. As snow melts and vegetation green-up begins in late spring and early summer, many migratory ungulates leave their winter range and move to higher elevation summer ranges to access high-quality forage and areas with vegetative cover for protection during fawning. Ungulates remain on these ranges until the fall when increasing snowfall and decreasing temperatures trigger them to migrate back to their lower elevation winter ranges. While researchers have begun to assess the effects of physical barriers such as roads and energy infrastructure on migration, less attention has been paid to understanding how changing climate conditions might affect ungulate movements and range habitats. Does earlier spring green-up make ungulates leave their winter ranges sooner? Do persistent drought conditions reduce the carrying capacity of seasonal range habitats or lead to shifts in migration pathways? These and other questions remain largely unanswered but could have cascading effects on ungulate population dynamics and migratory behavior. In February 2018, the Secretary of the Interior signed Department of the Interior Secretarial Order 3362 (SO3362), “Improving Habitat Quality in Western Big-Game Winter Range and Migration Corridors.” The order, which focuses on elk, mule deer, and pronghorn in 11 Western States, directs the Bureau of Land Management (BLM), the U.S. Fish and Wildlife Service (FWS), the National Park Service (NPS), and the U.S. Geological Survey (USGS) to partner with State wildlife agencies on their priorities and objectives for identifying and conserving ungulate migration corridors and winter-range habitat. The USGS Climate Adaptation Science Centers (CASCs) were established to help managers of the Nation’s fish, wildlife, waters, and lands understand the effects of climate change and adapt to changing conditions. To support the recent Department of the Interior (DOI) emphasis on ungulate migration corridors and winter-range habitat, this report assesses current information on how climate change could affect elk, mule deer, and pronghorn migration. The report synthesizes the drivers of migration, outlines what is known about how climate change might affect these drivers, and summarizes management priorities and science needs related to ungulate migration corridors and range habitat. A review of the literature on ungulate migration shows that the core drivers of spring migration are the timing of spring green-up and snowmelt, and the core driver of fall migration is winter severity. After exploring what is known about how these drivers affect or could be affected by climate change, several pathways through which ungulate migration could be altered were identified: (1) ungulates alter migration timing to better track plant phenology or in response to changes in winter conditions; (2) ungulates change their migration route or distance traveled during migration to accommodate changes in environmental conditions; and (3) ungulate populations that are currently migratory may begin to demonstrate interannual variability in whether they migrate, depending on environmental conditions and density-dependence, and may remain resident for sets of consecutive years. Through discussions with managers, physical barriers to movement such as roads and fences were identified as a core concern. In addition, the primary research needs of States are the acquisition and analysis of data on ungulate movements, to refine delineation of winter range, summer range, and corridors, and to support a better understanding of how ungulates use these habitats. When it comes to understanding climate effects, managers were more concerned with understanding the vulnerability of winter- and summer-range habitats than the vulnerability of migration corridors because of the influence of summer and winter forage on ungulate condition and reproductive success. Managers were also concerned about how forage quality and quantity might change because of stressors such as drought, wildfire, and invasive species and how they might need to alter habitat-treatment strategies as a result. More baseline data are needed before effective projections of ungulate migration, at a West-wide scale under climate change, can be made. These data needs include (1) more clearly defined corridors and seasonal range habitats; (2) a comprehensive understanding of the ecological drivers of migration across ungulate species and populations; and (3) the identification of environmental thresholds for key variables that influence migration, above which ungulates alter migratory behavior. The CASCs have several opportunities to play a role in addressing these needs. The CASCs could initiate projects to identify past and potential future changes and trends in key variables known to affect ungulate migration, such as plant phenology, forage quality, or winter severity. However, it would be difficult to use this information to determine what those trends mean for ungulate migration due to the lack of knowledge about environmental thresholds for ungulates. Additional projects would be required to compare multiple years of movement data with key variables to define thresholds. Once available, information on environmental thresholds could be integrated with projections of key variables to forecast the likelihood that the migration routes or the distance traveled could change—another area in which the CASCs could contribute. A more immediate role for the CASCs would be to carry out synthesis projects. One such project could summarize the “state of the science” on the drivers of ungulate migration. Although there are dozens of population- and location-specific studies on this topic, collating this information could help highlight trends in migration drivers that span species and geographies: a necessary first step toward determining the extent to which migration drivers could be affected by climate change. A second project could focus on what is known about how climate variability and change affect ungulate life-histories, population dynamics, and migration in the Western United States. The goal of this effort could be to identify knowledge clusters and information gaps that require further investigation. Together, these synthesized products could focus future scientific activities on the most pressing issues of ungulate migration and climate change in the Western United States.

Arizona, California, Colorado, Idaho, Montana, New↗
USGS2012

Development of a flood-warning system and flood-inundation mapping in Licking County, Ohio

Digital flood-inundation maps for selected reaches of South Fork Licking River, Raccoon Creek, North Fork Licking River, and the Licking River in Licking County, Ohio, were created by the U.S. Geological Survey (USGS), in cooperation with the Ohio Department of Transportation; U.S. Department of Transportation, Federal Highway Administration; Muskingum Watershed Conservancy District; U.S. Department of Agriculture, Natural Resources Conservation Service; and the City of Newark and Village of Granville, Ohio. The inundation maps depict estimates of the areal extent of flooding corresponding to water levels (stages) at the following USGS streamgages: South Fork Licking River at Heath, Ohio (03145173); Raccoon Creek below Wilson Street at Newark, Ohio (03145534); North Fork Licking River at East Main Street at Newark, Ohio (03146402); and Licking River near Newark, Ohio (03146500). The maps were provided to the National Weather Service (NWS) for incorporation into a Web-based flood-warning system that can be used in conjunction with NWS flood-forecast data to show areas of predicted flood inundation associated with forecasted flood-peak stages. As part of the flood-warning streamflow network, the USGS re-installed one streamgage on North Fork Licking River, and added three new streamgages, one each on North Fork Licking River, South Fork Licking River, and Raccoon Creek. Additionally, the USGS upgraded a lake-level gage on Buckeye Lake. Data from the streamgages and lake-level gage can be used by emergency-management personnel, in conjunction with the flood-inundation maps, to help determine a course of action when flooding is imminent. Flood profiles for selected reaches were prepared by calibrating steady-state step-backwater models to selected, established streamgage rating curves. The step-backwater models then were used to determine water-surface-elevation profiles for up to 10 flood stages at a streamgage with corresponding streamflows ranging from approximately the 50 to 0.2-percent chance annual-exceedance probabilities for each of the 4 streamgages that correspond to the flood-inundation maps. The computed flood profiles were used in combination with digital elevation data to delineate flood-inundation areas. Maps of Licking County showing flood-inundation areas overlain on digital orthophotographs are presented for the selected floods. The USGS also developed an unsteady-flow model for a reach of South Fork Licking River for use by the NWS to enhance their ability to provide advanced flood warning in the region north of Buckeye Lake, Ohio. The unsteady-flow model was calibrated based on data from four flooding events that occurred from June 2008 to December 2011. Model calibration was approximate due to the fact that there were unmeasured inflows to the river that were not able to be considered during the calibration. Information on unmeasured inflow derived from NWS hydrologic models and additional flood-event data could enable the NWS to further refine the unsteady-flow model.

Ohio↗
USGS2024

Spaceborne imaging spectroscopy enables carbon trait estimation in cover crop and cash crop residues

Purpose Cover crops and reduced tillage are two key climate smart agricultural practices that can provide agroecosystem services including improved soil health, increased soil carbon sequestration, and reduced fertilizer needs. Crop residue carbon traits (i.e., lignin, holocellulose, non-structural carbohydrates) and nitrogen concentrations largely mediate decomposition rates and amount of plant-available nitrogen accessible to cash crops and determine soil carbon residence time. Non-destructive approaches to quantify these important traits are possible using spectroscopy. Methods The objective of this study was to quantify cash and cover crop residue nitrogen and carbon traits using partial least squares regression models and a combination of 1) the band equivalent reflectance (BER) of the PRecursore IperSpettrale della Missione Applicativa (PRISMA) imaging spectroscopy sensor derived from laboratory collected ASD spectra (n = 296) of 11 cover crop species and three cash crop species, and 2) spaceborne PRISMA imagery that coincided with destructive crop residue collections in the spring of 2022 (n = 65). Spectral range was constrained to 1200 to 2400nm to reduce the likelihood of confounding relationships in wavelengths sensitive to plant pigments or those related to canopy structure for both analytical approaches. Results Models using laboratory BER of PRISMA all demonstrated high accuracies and low errors for estimation of nitrogen and carbon traits (adj. R2 = 0.86 – 0.98; RMSE = 0.24 – 4.25%) and results suggest that a single model may be used for a given trait across all species. Models using spaceborne imaging spectroscopy demonstrated that crop residue carbon traits can be successfully estimated using PRISMA imagery (adj. R2 = 0.65 – 0.75; RMSE = 2.71 – 4.16%). We found moderate relationships between nitrogen concentration and PRISMA imagery (adj. R2 = 0.52; RMSE = 0.25%), which is partly related to the range of nitrogen in these senesced crop residues (0.38 – 1.85%). PRISMA imagery models were also impacted by atmospheric absorption, variability in surface moisture content, and some presence of green vegetation. Conclusion As spaceborne imaging spectroscopy data become more widely available from upcoming missions, crop residue trait estimates could be regularly generated and integrated into decision support tools to calculate decomposition rates and associated nitrogen credits to inform precision field management, as well as to enable measurement, monitoring, reporting, and verification of net carbon benefits from climate smart agricultural practice adoption in an emerging carbon marketplace.

Maryland↗
USGS2021

Nearshore water quality and coral health indicators along the west coast of the Island of Hawaiʻi, 2010–2014

Coral reefs worldwide are experiencing rapid degradation in response to climate and land-use change, namely effects of warming sea-surface temperatures, contaminant runoff, and overfishing. Extensive coral bleaching caused by the steady rise of sea-surface temperatures is projected to increase, but our understanding and ability to predict where corals may be most resilient to this effect is limited owing to a lack of knowledge of nearshore habitat conditions and the role of compromised coral health in preconditioning bleaching vulnerability. On high islands and most atolls, fresh to brackish groundwater discharges to the coast through the beach face and seafloor, where it mixes with marine waters and commonly creates cool estuarine nearshore waters that are important to wildlife and ecosystem services that benefit people. Here, we summarize results of a study to evaluate the ecosystem services and effects of groundwater on coral reef health and the potential role of groundwater to maintain cold-water refugia that can buffer corals from thermal stress during temperature maxima. Across 75 kilometers of the west coastline of the Island of Hawaiʻi, paired time-series and discrete measurements of water quality, coral-community and colony size structures, and coral health indicators, including bleaching, at 33 stations grouped into 12 study areas were made from July 2010 to December 2013. The results show that nearshore water temperatures are depressed by groundwater across extensive areas of the nearshore. Persistent cold-water refugia ranging from 1 to 5 degrees Celsius below surrounding marine water temperatures are shown to be associated with identified groundwater inputs. Significant correlations were found between metrics of coral health and water temperature. Because areas of temperature refugia were notable along the west coast of the Island of Hawaiʻi and are identified by ecologists as increasingly important to valued wildlife, improved understanding of groundwater flux to the long-term resilience of coral reefs is likely important. In particular, evaluating the extent that the magnitude and timing of groundwater discharge across the nearshore mitigate thermal bleaching stress may help inform the fate of coral reefs projected to experience rising sea-surface temperatures worldwide.

Hawaii↗
USGS2023

Improving the Midwest Climate Change Vulnerability Assessment Tool to support regional climate adaptation

An online climate vulnerability assessment dashboard was developed in 2021 through collaboration between U.S. Geological Survey (USGS) and U.S. Fish and Wildlife Service (FWS) to support regional climate adaptation efforts. The dashboard included 15 climate change impact metrics (five each from three categories: hydrology, precipitation, and temperature) and five metrics representing each watershed's capacity to adapt to changing conditions. Users could then adjust relative weights of each metric to generate vulnerability scores. The metrics included in the dashboard were identified by FWS for their programs but have broad relevance, making the dashboard useful to a wide range of stakeholders. For this project we had two primary goals: (1) update the online dashboard to better communicate the variability that is inherent in climate change projections, and (2) develop a use case example using the dashboard to collaboratively assess vulnerability of a resource of concern at a workshop with resource managers. For objective 2, we selected prairie-obligate butterflies (POBs), which are dependent on, and often restricted to, native prairie habitat. The extent of native prairie has been greatly reduced over the last two centuries resulting in a patchwork of isolated and often small tracts of land. For many POBs, declines and extirpations have been observed in recent decades. Although the causes are not always known, hypotheses include overuse of management tools (e.g., too frequent burning or overgrazing), lack of dispersal opportunities, or extreme weather events. With more extreme weather events anticipated in the future along with other changes in climate, it is important to better understand the vulnerability of POBs to design effective adaptation strategies. While research on extreme weather, climate change, and adaptation is ongoing for some prairie-obligate species, this workshop sought to take a broad perspective using POBs as the focal taxonomic group across eight U.S. States in the Midwest During the workshop we discussed weather and climate-related influences on butterfly communities and assessed climate change vulnerability using the Watershed-based Midwest Climate Change Vulnerability Assessment Tool (https://www.usgs.gov/apps/CC_Vulnerability/). We produced maps that quantify the regional vulnerability of POBs across 360 watersheds for two future emissions scenarios. The information developed during the workshop could help in regional planning for climate change adaptation and to identify avenues for research and collaboration for POBs in the Midwest.

Illinois, Indiana, Iowa, Michigan, Minnesota, Miss↗
USGS2026

Analyses of meteorological and hydrological records support Tribal members’ accounts of changing climate on the Fort Apache Reservation, east–central Arizona

The Fort Apache Reservation in east–central Arizona, home to the White Mountain Apache Tribe of the Fort Apache Reservation, Arizona, contains several climate zones because of the large variation in surface elevation within the reservation. This study was carried out in cooperation with the White Mountain Apache Tribe of the Fort Apache Reservation, Arizona, to raise awareness of how the changing climate affects the Fort Apache Reservation. This report documents the evaluation of existing multidecadal meteorological and hydrological datasets for the Fort Apache Reservation, used to evaluate the effects of a changing climate on the reservation. In this evaluation, near-surface air temperature, snow depth, snow water equivalent, precipitation, and streamflow datasets were analyzed for monotonic trends indicative of changing climatic conditions during specified periods of time. The results of these trend analyses were then compared with the Tribal community's memories of the changing climate. Trend analysis of near-surface air temperatures from a U.S. Historical Climatological Network station on the Fort Apache Reservation at Whiteriver, Arizona, indicated that mean annual air temperatures have increased by an average of 2.48 degrees Fahrenheit from 1980 to 2023. Records from the same station also indicated that average monthly maximum temperatures recorded for March increased by 5.39 degrees Fahrenheit for the same time period. Annual precipitation at the five precipitation stations used in this study decreased greatly from the 1980s to 2023. The largest total decrease was 10.07 inches, or 34.7 percent. However, only one of the two precipitation stations with longer term data available prior to 1980 had a significant negative trend when data from the entire period of record, from 1901 to 2023, were analyzed. Trend analyses show a decrease in the annual maximum snow water equivalent and an earlier disappearance of the snowpack at two Natural Resources Conservation Service snow telemetry stations in the mountainous region just east of the Fort Apache Reservation from 1981 to 2023. Based on the trend analyses, the average annual maximum snow water equivalent has decreased by more than 40 percent at both stations, and the average date when the snowpack was fully melted at the stations in the spring has moved earlier in time from late April to early April or late March. However, a statistically significant trend was not determined for the early April snow water equivalent measured at a nearby Natural Resources Conservation Service snow course across its period of record, indicating that the history of mountain snowpack in this area is not fully understood. Analysis of snowfall data from a National Oceanic and Atmospheric Administration Cooperative Observer Program network station on the Fort Apache Reservation at McNary 2N, AZ (station 025412) indicated that, on average, the measured total annual snowfall at the station decreased 42.4 percent from 1935 to 2023. Streamflow data from six U.S. Geological Survey streamgages on the Fort Apache Reservation were analyzed for trends. For most streamflow gages, statistically significant trends were not determined for tested parameters when the entire streamflow period of record was used for stations with records going back to at least the 1960s. However, when the data from 1980 to 2023 was tested, most of the streamflow parameters had statistically significant negative trends. All six streamgages showed a decrease in average annual runoff of at least 50 percent from 1980 to 2023; one streamgage showed an 81.8 percent decrease. A similar statistical finding was observed in the analysis of the annual spring snowmelt peak from one of the six streamgages used in the study and located in an area receiving measurable amounts of snowmelt runoff. When data from the entire period of record (1958–2023) was used, no trend in streamflow was determined; however, a significant negative trend was determined from 1980 to 2023, indicating a decrease in average annual springtime runoff of 62.6 percent. Statistical analysis on the timing of the annual spring snowmelt peak at the same streamgage indicated the snowmelt peak is happening on average about 12 days earlier now (2023) than it did in the past. The trend results for the timing of the annual spring snowmelt peak were the same and statistically significant for both periods tested (1958–2023 and 1980–2023). Two of the streamflow records from the Fort Apache Reservation were compared to the Palmer Hydrological Drought Index computed for Arizona Climate Division 4 (East Central) by the National Centers for Environmental Information. The comparison showed that the streamflow records generally tracked the Palmer Hydrological Drought Index. In interviews, Tribal community members living on the Fort Apache Reservation described the changes in climate that they observed during their lifetimes. Common themes reported were that air temperatures have become warmer, and the weather is less predictable with changes in seasonal patterns. Drier conditions, lower snowfall, shorter winters, and lower river levels were also reported. These community member observations align with the results of this study.

Arizona↗
USGS2010

Development of monitoring protocols to detect change in rocky intertidal communities of Glacier Bay National Park and Preserve

Glacier Bay National Park and Preserve in southeastern Alaska includes extensive coastlines representing a major proportion of all coastlines held by the National Park Service. The marine plants and invertebrates that occupy intertidal shores form highly productive communities that are ecologically important to a number of vertebrate and invertebrate consumers and that are vulnerable to human disturbances. To better understand these communities and their sensitivity, it is important to obtain information on species abundances over space and time. During field studies from 1997 to 2001, I investigated probability-based rocky intertidal monitoring designs that allow inference of results to similar habitat within the bay and that reduce bias. Aerial surveys of a subset of intertidal habitat indicated that the original target habitat of bedrock-dominated sites with slope less than or equal to 30 degrees was rare. This finding illustrated the value of probability-based surveys and led to a shift in the target habitat type to more mixed rocky habitat with steeper slopes. Subsequently, I investigated different sampling methods and strategies for their relative power to detect changes in the abundances of the predominant sessile intertidal taxa: barnacles -Balanomorpha, the mussel Mytilus trossulus and the rockweed Fucus distichus subsp. evanescens. I found that lower-intensity sampling of 25 randomly selected sites (= coarse-grained sampling) provided a greater ability to detect changes in the abundances of these taxa than did more intensive sampling of 6 sites (= fine-grained sampling). Because of its greater power, the coarse-grained sampling scheme was adopted in subsequent years. This report provides detailed analyses of the 4 years of data and evaluates the relative effect of different sampling attributes and management-set parameters on the ability of the sampling to detect changes in the abundances of these taxa. The intent was to provide managers with information to guide design choices for intertidal monitoring. I found that the coarse-grained surveys, as conducted from 1998 to 2001, had power ranging from 0.68 to 1.0 to detect 10 percent annual changes in the abundances of these predominant sessile species. The information gained through intertidal monitoring would be useful in assessing changes due to climate (including ocean acidification), invasive species, trampling effects, and oil spills.

Open-File Report↗