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USGS2013

LANDFIRE 2010 - updated data to support wildfire and ecological management

Wildfire is a global phenomenon that affects human populations and ecosystems. Wildfire effects occur at local to global scales impacting many people in different ways (Figure 1). Ecological concerns due to land use, fragmentation, and climate change impact natural resource use, allocation, and conservation. Access to consistent and current environmental data is a constant challenge, yet necessary for understanding the complexities of wildfire and ecological management. Data products and tools from the LANDFIRE Program help decision-makers to clarify problems and identify possible solutions when managing fires and natural resources. LANDFIRE supports the reduction of risk from wildfire to human lives and property, monitoring of fire danger, prediction of fire behavior on active incidents, and assessment of fire severity and impacts on natural systems [1] [2] [3]. LANDFIRE products are unique in that they are nationally consistent and provide the only complete geospatial dataset describing vegetation and wildland fuel information for the entire U.S. As such, LANDFIRE data are useful for many ecological applications [3]. For example, LANDFIRE data were recently integrated into a decision-support system for resource management and conservation decision-making along the Appalachian Trail. LANDFIRE is a joint effort between the U.S. Department of the Interior Office of Wildland Fire, U.S. Department of Agriculture Forest Service Fire & Aviation Management, and The Nature Conservancy. To date, seven versions of LANDFIRE data have been released, with each successive version improving the quality of the data, adding additional features, and/or updating the time period represented by the data. The latest version, LANDFIRE 2010 (LF 2010), released mid-2013, represents circa 2010 landscape conditions and succeeds LANDFIRE 2008 (LF 2008), which represented circa 2008 landscape conditions. LF 2010 used many of the same processes developed for the LF 2008 effort [3]. Ongoing refinement of the LANDFIRE vegetation and fuel data is necessary to improve the quality and usability of the data and to capture landscape disturbance. LANDFIRE relies on Landsat multi-spectral imagery to produce and update vegetation and fuel data. The deep Landsat archive provides data needed for vegetation classification, change analysis, and historical disturbance characterization, for which LANDFIRE has used more than 24,000 image scenes since the program’s inception. In addition, LF 2010 used airborne and spaceborne lidar, and spaceborne synthetic aperture radar (SAR) to map vegetation structure in areas where ground-based field information was lacking, including Alaska and U.S.-affiliated islands in the Caribbean and the Pacific. The mapping of insular areas is new for the 2010 data release; previous versions of LANDFIRE were limited to the conterminous U.S., Alaska, and Hawaii.

Earthzine↗

USGS2022

Adaptive problem maps (APM): Connecting data dots to build increasingly informed and defensible environmental conservation decisions

Connecting individual datasets from different projects to each other and to decisions can help manager-researcher-administrator teams build on what is known and adapt their environmental decision-making process as new information becomes available. Throughout their careers, environmental professionals often collect data on many individual projects that address similar sets of natural resource conservation problems. Consequently, the institutions, agencies, and organizations that employ these environmental professionals accumulate a large reservoir of project-specific information. However, bigger-picture opportunities to advance broader natural resource conservation goals are lost if individual projects and datasets are not integrated. Here we illustrate how our adaptive problem mapping (APM) process provides a framing and internal structure that charts relationships among pertinent information types, germane data sets, applicable concepts, and relevant decisions. In the APM process, appropriately defined problem statements and coordinated bridging questions connect data and concepts to build a network of increasingly informed and defensible decisions. Although our APM process can be applied to many environmental problems, here we focus on examples from aquatic systems in which fish are conservation priorities. Prioritizing an initial evaluation and regular modification of the relationships among datasets and decisions using the APM process helps manager-research-administrator teams envision, track, and update what is known, unknown, learned, and needed. The resulting broader point of view advances strategic planning, evaluations of progress, assessments of opportunity costs, identification of options, and justifications of decision-related actions.

Journal of Environmental Management↗

USGS1984

Map showing selected surface-water data for the Nephi 30 x 60-minute quadrangle, Utah

This is one of a series of maps that describe the geology and related natural resources of the Nephi 30 x 60 minute quadrangle, Utah. Streamflow records used to compile this map were collected by the U.S. Geological Survey in cooperation with the Utah Department of Natural Resources, Division of Water Rights, and the Utah Department of Transportation. The principal runoff-producing areas shown on the map were delineated from a work map (scale 1:250,000) compiled to estimate water yields in Utah (Bagley and others, 1964). Sources of information about recorded floods resulting from cloudbursts included Woolley (1946) and Butler and Marsell (1972); sources of information about the chemical quality of streamflow included Hahl and Cabell (1965) Mundorff (1972 and 1974), and Waddell and others (1982).

Utah↗

USGS2006

Bathymetric contour maps of lakes surveyed in Iowa in 2004

The U.S. Geological Survey, in cooperation with the Iowa Department of Natural Resources, conducted bathymetric surveys on six lakes in Iowa during 2004 (Lake Darling, Littlefield Lake, Lake Minnewashta, Nine Eagles Lake, Prairie Rose Lake, and Upper Gar Lake). The surveys were conducted to provide the Iowa Department of Natural Resources with information for the development of total maximum daily load limits, particularly for estimating sediment load and deposition rates. The bathymetric surveys can provide a baseline for future work on sediment loads and deposition rates for these lakes. Two of the lakes surveyed in 2004, Lake Minnewashta and Upper Gar Lake, are natural lakes. The other four lakes are manmade lakes with fixed spillways. Bathymetric data were collected using a boat-mounted, differential global positioning system, echo depth-sounding equipment, and computer software. Data were processed with commercial hydrographic software and exported into a geographic information system for mapping and calculating area and volume. Lake volume estimates ranged from 83,924,000 cubic feet (1,930 acre-feet) at Lake Darling to 5,967,000 cubic feet (140 acre-feet) at Upper Gar Lake. Surface area estimates ranged from 10,660,000 square feet (240 acres) at Lake Darling to 1,557,000 square feet (36 acres) at Upper Gar Lake.

Iowa↗

USGS2011

Floods of September 2010 in Southern Minnesota

During September 22-24, 2010, heavy rainfall ranging from 3 inches to more than 10 inches caused severe flooding across southern Minnesota. The floods were exacerbated by wet antecedent conditions, where summer rainfall totals were as high as 20 inches, exceeding the historical average by more than 4 inches. Widespread flooding that occurred as a result of the heavy rainfall caused evacuations of hundreds of residents, and damages in excess of 64 million dollars to residences, businesses, and infrastructure. In all, 21 counties in southern Minnesota were declared Federal disaster areas. Peak-of-record streamflows were recorded at nine U.S. Geological Survey and three Minnesota Department of Natural Resources streamgages as a result of the heavy rainfall. Flood-peak gage heights, peak streamflows, and annual exceedance probabilities were tabulated for 27 U.S. Geological Survey and 5 Minnesota Department of Natural Resources streamgages and 5 ungaged sites. Flood-peak streamflows in 2010 had annual exceedance probabilities estimated to be less than 0.2 percent (recurrence interval greater than 500 years) at 7 streamgages and less than 1 percent (recurrence interval greater than 100 years) at 5 streamgages and 4 ungaged sites. High-water marks were identified and tabulated for the most severely affected communities of Faribault along the Cannon and Straight Rivers, Owatonna along the Straight River and Maple Creek, Pine Island along the North Branch and Middle Fork Zumbro River, and Zumbro Falls along the Zumbro River. The nearby communities of Hammond, Henderson, Millville, Oronoco, Pipestone, and Rapidan also received extensive flooding and damage but were not surveyed for high-water marks. Flood-peak inundation maps and water-surface profiles for the four most severely affected communities were constructed in a geographic information system by combining high-water-mark data with the highest resolution digital elevation model data available. The flood maps and profiles show the extent and height of flooding through the communities and can be used for flood response and recovery efforts by local, county, State, and Federal agencies.

Minnesota↗

USGS2005

Upper Auglaize watershed AGNPS modeling project

The Upper Auglaize Watershed agricultural non-point source modeling project was an interagency effort to use a Geographic Information System (GIS)-based modeling approach for assessing and reducing pollution from agricultural runoff and other non-point sources. This project applied the U.S. Department of Agriculture (USDA), Agricultural Research Service’s AGricultural Non-Point Source (AGNPS) suite of models to the Upper Auglaize River Watershed, a major watershed within the Maumee River Basin. This modeling project was conducted by an interagency team consisting of a partnership between the: (1) USDA, Agricultural Research Service (ARS); (2) USDA, Natural Resources Conservation Service (NRCS); (3) U.S. Army Corps of Engineers (USACE); (4) U.S. Geological Survey (USGS); (5) Ohio State University; (6) University of Toledo (UT); (7) Heidelberg College; (8) Ohio Department of Natural Resources (ODNR), Division of Soil and Water Conservation; (9) Ohio Environmental Protection Agency (OEPA); and (10) Allen, Auglaize, Van Wert, and Putnam Soil and Water Conservation Districts. The partnership was the first step in a process to eventually apply the model in a portioned subset of watersheds for the Maumee Basin, and then to link them to form a comprehensive basin-wide model This work was performed under the authority of Section 516(e) of the Water Resources Development Act (WRDA) of 1996, as amended, for the purpose of assisting State and local watershed managers with their evaluation, prioritization and implementation of alternatives for soil conservation, sediment trapping and non-point source pollution prevention in the Upper Auglaize River watershed. The project team, working in a cooperative effort, used the models to determine sediment sources, contributing locations, and the effect of application of best management practices (BMPs) on rates of sediment delivery to the mouth of the watershed. The results will be used to guide conservation incentive and land treatment programs. The team relied heavily on Geographic Information System (GIS)-based applications to expedite the application of the model. The results of the analysis demonstrated that the application of BMPs would have a positive effect on reducing the loadings of sediment leaving the mouth of the Upper Auglaize Watershed. An application of 17 percent new no-till acres and eight percent new grassland acres, when randomly applied to the watershed, reduced loadings at the mouth to 82 percent of the simulated existing condition loadings. No-till, conversion of cropland to grassland, other uses including grass buffers, and reforestation of parts of the watershed, were all shown by the model to have a measurable effect on reducing sediment loads. Conversion of all of the cropland in the watershed to no-till would reduce the average unit load (tons of sediment per acre) leaving the mouth of the watershed to a level that is 42 percent of the simulated existing condition load. Ephemeral gullies were found to be the primary source of erosion (72 percent), sediment yield (73 percent), and sediment loading (73 percent). Controlling sediment load means controlling gully erosion and possibly trapping sediment yield before it reaches the stream system. Most BMPs (e.g., no-till, conversion of cropland, etc.) that reduce sheet and rill erosion and its sediment yield will also reduce gully erosion and its sediment yield. However, grassed waterways, which have no effect on sheet and rill erosion, are frequently an effective BMP to prevent ephemeral gullies. And, of course, riparian vegetation and sediment traps would reduce the delivery ratios of all types of landscape erosion. New techniques were developed by the team to quantify the ephemeral gully erosion within the model. When calibrated to available stream gage data the model suggests that more (73% in the existing condition simulation) of the sediment load originates from ephemeral gully erosion than from traditional sheet and rill erosion. The model quantified the value of tile drainage in reducing the sediment load from the watershed. Loadings under drained conditions were always less than loadings under undrained conditions for otherwise identical land uses. The average sediment load of all alternatives for drained loadings was 89.2 percent of the load for the corresponding undrained loadings. The model established that while many conservation incentive programs treat tile drainage as a production practice, significant erosion and sediment control benefits are provided by the practice in comparison to cultivation in an undrained state.

Ohio↗

USGS1996

Comparison of estimated and observed stormwater runoff for fifteen watersheds in west-central Florida, using five common design techniques

Hydrologists use several traditional techniques for estimating peak discharges and runoff volumes from ungaged watersheds. However, applying these techniques to watersheds in west-central Florida requires that empirical relationships be extrapolated beyond tested ranges. As a result there is some uncertainty as to their accuracy. Sixty-six storms in 15 west-central Florida watersheds were modeled using (1) the rational method, (2) the U.S. Geological Survey regional regression equations, (3) the Natural Resources Conservation Service (formerly the Soil Conservation Service) TR-20 model, (4) the Army Corps of Engineers HEC-1 model, and (5) the Environmental Protection Agency SWMM model. The watersheds ranged between fully developed urban and undeveloped natural watersheds. Peak discharges and runoff volumes were estimated using standard or recommended methods for determining input parameters. All model runs were uncalibrated and the selection of input parameters was not influenced by observed data. The rational method, only used to calculate peak discharges, overestimated 45 storms, underestimated 20 storms and estimated the same discharge for 1 storm. The mean estimation error for all storms indicates the method overestimates the peak discharges. Estimation errors were generally smaller in the urban watersheds and larger in the natural watersheds. The U.S. Geological Survey regression equations provide peak discharges for storms of specific recurrence intervals. Therefore, direct comparison with observed data was limited to sixteen observed storms that had precipitation equivalent to specific recurrence intervals. The mean estimation error for all storms indicates the method over estimates both peak discharges and runoff volumes. Estimation errors were smallest for the larger natural watersheds in Sarasota County, and largest for the small watersheds located in the eastern part of the study area. The Natural Resources Conservation Service TR-20 model, overestimated peak discharges for 45 storms and underestimated 21 storms, and overestimated runoff volumes for 44 storms and underestimated 22 storms. The mean estimation error for all storms modeled indicates that the model overestimates peak discharges and runoff volumes. The smaller estimation errors in both peak discharges and runoff volumes were for storms occurring in the urban watersheds, and the larger errors were for storms occurring in the natural watersheds. The HEC-1 model overestimated peak discharge rates for 55 storms and underestimated 11 storms. Runoff volumes were overestimated for 44 storms and underestimated for 22 storms using the Army Corps of Engineers HEC-1 model. The mean estimation error for all the storms modeled indicates that the model overestimates peak discharge rates and runoff volumes. Generally, the smaller estimation errors in peak discharges were for storms occurring in the urban watersheds, and the larger errors were for storms occurring in the natural watersheds. Estimation errors in runoff volumes; however, were smallest for the 3 natural watersheds located in the southernmost part of Sarasota County. The Environmental Protection Agency Storm Water Management model produced similar peak discharges and runoff volumes when using both the Green-Ampt and Horton infiltration methods. Estimated peak discharge and runoff volume data calculated with the Horton method was only slightly higher than those calculated with the Green-Ampt method. The mean estimation error for all the storms modeled indicates the model using the Green-Ampt infiltration method overestimates peak discharges and slightly underestimates runoff volumes. Using the Horton infiltration method, the model overestimates both peak discharges and runoff volumes. The smaller estimation errors in both peak discharges and runoff volumes were for storms occurring in the five natural watersheds in Sarasota County with the least amount of impervious cover and the lowest slopes. The largest errors were for storms occurring in the three small natural watersheds in the eastern part of the study area. The mean estimation errors for peak discharge ranged from an underestimation of 63 percent to an overestimation of 224 percent. For runoff volume, the mean estimation errors range from an underestimation of 63.3 percent to an overestimation of 267 percent.

Florida↗

USGS2017

Forecasting stream habitat and Brook Trout responses to climate change in Catoctin Mountain Park

Anticipating and mitigating the effects of climate change is a fundamental challenge for natural resource conservation. In this report, we respond to research needs identified by Catoctin Mountain Park (CATO) for native Brook Trout (Salvelinus fontinalis) conservation and management as part of the US Geological Survey (USGS) Natural Resources Preservation Program in FY15-16. We addressed three overarching research questions: (1) How will anticipated changes in air temperature affect stream habitats? (2) How will changes to stream habitat affect the distribution of Brook Trout? (3) Which stream segments are most and least vulnerable to the effects of climate change? First, we surveyed Brook Trout abundance and fish community composition using electrofishing techniques within three watersheds: Owens Creek, upper Big Hunting Creek, and Blue Blazes Creek (a tributary to Big Hunting Creek). Second, we deployed a network of stream temperature gages to assess spatial variation in stream temperature and groundwater (GW) influence. Third, we used modeling techniques to forecast future stream temperatures that account for GW influences and air temperature scenarios. Fish sampling detected 13 species and 15,345 individual fish, the majority of which were Blacknose Dace (60%), Blue Ridge Sculpin (26%), and Brook Trout (6%). Brook Trout were not observed in Blue Blazes Creek and exhibited higher densities in Owens Creek than upper Big Hunting Creek (average densities = 19 fish/100 m and 4 fish/100 m, respectively). In contrast, Brown Trout were present in Blue Blazes Creek and exhibited greater density in Blue Blazes Creek than either Owens Creek or upper Big Hunting Creek (average densities = 3.0 fish/100 m, 0.3 fish/100 m, and 1.7 fish/100 m, respectively). Brown Trout occurred in sympatry with Brook Trout in Owens Creek and upper Big Hunting Creek, but appeared to have replaced Brook Trout in Blue Blazes Creek. Our fish surveys also revealed important locations for Brook Trout reproduction and young-of-year (YOY) dispersal within the Owens Creek watershed. Our study also revealed surprising differences in the distribution of Blue Ridge Sculpin among CATO streams. This species was abundant in Owens Creek (average density = 83 fish/100 m) but was less common in Blue Blazes Creek (average density = 12 fish/100 m) and was not detected in upper Big Hunting Creek. Histological examination of several specimens from Blue Blazes Creek by V. Blazer at the USGS Leetown Science Center revealed the presence of a novel parasite (Dermosystidium sp.) which has been linked to fish population declines elsewhere (Blazer et al. 2016). The parasite was not detected in Blue Ridge Sculpin samples from Owens Creek, and all trout appeared to be uninfected. Our survey results suggest that Blue Ridge Sculpin have been extirpated from upper Big Hunting Creek and have not recolonized from downstream source populations due to the fish passage barrier of Cunningham Falls. We recommend additional research to (1) evaluate the feasibility of reintroducing Blue Ridge Sculpin into upper Big Hunting Creek and (2) continue monitoring the distribution and potential spread of Dermocystidium in downstream waters. Stream temperatures ranged from 9.6 – 27.6 ºC during baseflow conditions in 2015 and 2016. Sites within upper Big Hunting Creek were consistently warmer than in Owens Creek or Blue Blazes Creek, suggesting an effect of headwater ponds outside CATO on upper Big Hunting Creek temperatures. For instance, in 2016 the maximum observed temperature in upper Big Hunting Creek was 27.6 ºC whereas Owens Creek reached a maximum of 23.7 ºC that year. Stream temperature data also revealed that 2016 was warmer than 2015 throughout the study area but did not exceed thermal tolerance limits for Brook Trout in either year. We estimated the influence of GW on stream temperatures using a statistical modeling approach based on the relationship between daily mean air temperature and stream temperature over time. Results indicated that effects of GW were generally stronger in the Owens Creek watershed than in Blue Blazes or upper Big Hunting Creek. However, we detected substantial spatial variation in GW influence among Owens Creek sites, with stream temperatures at some locations showing relatively little GW influence and others showing very strong influences (and correspondingly small influence of daily mean air temperatures). Although incoming lateral seeps were detected in upper Big Hunting Creek (D. Ferrier, Hood College, personal communication), the strongest effects of GW in the study area were due to GW upwelling within portions of the Owens Creek watershed (i.e., Tributary C in Figure 4) where we also observed high numbers of Brook Trout juveniles. Our results therefore identified potential high-priority areas for Brook Trout conservation in CATO. Finally, we modeled future stream temperatures based on scenarios characterizing GW sensitivity to air temperature and future air temperature increases. Stream temperature forecasts revealed important differences in habitat suitability for Brook Trout within and among watersheds. Big Hunting Creek sites were generally more sensitive to air temperature increases than sites in Owens Creek or Blue Blazes Creek. For instance, an increase in mean annual air temperature of 1.5 ºC (lowest level evaluated) exceeded thermal thresholds for Brook Trout in the majority of sites within that watershed, regardless of GW influence levels. In contrast, an air temperature increase of 1.5 ºC did not exceed thermal thresholds for Brook Trout in Owens Creek. However, modeled air temperature increases of 5 ºC resulted in a loss of Brook Trout thermal suitability throughout the study area. Model results revealed spatially patchy responses to air temperature increases that could provide an early-warning system for trout monitoring designs in CATO.

Maryland↗

USGS2019

Scientific Framework for resilience research on the Upper Mississippi River System

The goal of this research framework is to outline research that would continue to improve our understanding of ecological resilience of the Upper Mississippi River System (UMRS) and inform management of the system for health and resilience. We provide a broad overview of recently completed and ongoing work that has been funded as a part of the UMRS Ecological Resilience Assessment and related efforts to provide context for how proposed research questions build upon our current knowledge and may inform restoration planning and design. We describe two primary objectives within this research framework - the first objective is to investigate hypothesized drivers and feedbacks related to specified resilience, and the second is to expand our utility of general resilience indicators through further development and evaluation. The intended audience for this framework is the Upper Mississippi River Restoration Program (UMRR). The UMRR partnership is made up of natural resource agencies from five states (Illinois, Iowa, Minnesota, Missouri and Wisconsin) and five federal agencies (U.S. Army Corps of Engineers, U.S. Environmental Protection Agency, U.S. Fish and Wildlife Service, U.S. Geological Survey, and USDA Natural Resources Conservation Service).

Illinois, Iowa, Minnesota, Missouri, Wisconsin↗

USGS2013

Identification of metrics to monitor salt marsh integrity on National Wildlife Refuges in relation to conservation and management objectives

Executive Summary Most salt marshes in the US have been degraded by human activities, and threats from physical alterations, surrounding land-use, species invasions, and global climate change persist. Salt marshes are unique and highly productive ecosystems with high intrinsic value to wildlife, and many National Wildlife Refuges (NWRs) have been established in coastal areas to protect large tracts of salt marsh and wetland-dependent species. Various management practices are employed routinely on coastal NWRs to restore and enhance marsh integrity and ensure ecosystem sustainability. Prioritizing NWR salt marshes for application of management actions and choosing among multiple management options requires scientifically-based methods for assessing marsh condition. Monitoring is integral to structured decision-making (SDM), a formal process for decomposing a decision into its essential elements. Within a natural resource context, SDM involves identifying management objectives, alternative management actions, and expected management outcomes. The core of SDM is a set of criteria for measuring system performance and evaluating management responses. Therefore, use of SDM to frame natural resource decisions leads to logical selection of monitoring attributes that are linked explicitly to management needs. We used SDM to guide selection of variables for monitoring the ecological integrity of salt marshes within the National Wildlife Refuge System (NWRS). Our objectives were to identify indicators of salt marsh integrity that are effective across large geographic regions, responsive to a wide range of threats, and feasible to implement within funding and staffing constraints of the NWRS. In April, 2008, we engaged interdisciplinary experts in a week-long rapid prototyping SDM workshop to define the essential elements of salt marsh management decisions on refuges throughout the northeastern, southwestern, and northwestern US, corresponding to respective Regions 5, 2, and 1 of the US Fish and Wildlife Service (FWS). Through this process we identified measurable attributes for monitoring salt marsh ecosystems that are integrated into conservation practice and target management objectives. The following salt marsh attributes were identified through the SDM process either for describing state condition to determine management needs or for evaluating the achievement of management objectives: historical condition and geomorphic setting; ditch density; surrounding land use; ratio of open water area to vegetation area; rate of pesticide application; environmental contaminant concentration; change in marsh surface elevation relative to sea level rise; tidal range and groundwater level; surface topography; salinity; and species composition and abundance of vegetation, invasive species, invertebrates, nekton, and breeding and wintering birds. The identified attributes were too broadly defined to serve as operational monitoring variables. Therefore, we tested specific metrics for quantifying most of these attributes in summers of 2008 and 2009. The first four attributes in the above list can be characterized by office-based analysis of existing GIS data layers. The remaining attributes require field-based methods for assessment. We were forced to exclude a small number of attributes from field tests due to inconsistent data (pesticide application rate, environmental contaminant concentrations) or requirements that exceeded the scope of this project (change in marsh surface elevation; surface topography; benthic invertebrates; wintering birds). We evaluated potential metrics for evaluating all remaining field attributes. In partnership with NWRS biologists, we tested rapid versus intensive metrics for monitoring field attributes (tidal range and groundwater level; marsh surface elevation; salinity; and species composition and abundance of vegetation, invasive species, nekton, and breeding birds) at coastal refuges throughout FWS Region 5. Seven refuges participated in metric testing in 2008: Rachel Carson (ME), Parker River (MA), Wertheim (NY), E. B. Forsythe (NJ), Bombay Hook (DE), Prime Hook (DE), and Eastern Shore of Virginia Complex (VA). These seven and two additional refuges participated in metric testing in 2009: Rhode Island Complex (RI) and Stewart B. McKinney (CT). We based all field metrics on existing protocols for salt marsh assessment. Sampling locations were determined randomly within delineated marsh study units (MSUs) at each refuge. Detailed field methods are provided in appendices to this report. Measurements for individual metrics were averaged across samples within MSUs during each year of sampling. Each year, correlation or regression analysis was conducted on average measurements across MSUs within each attribute set to identify redundant metrics. Statistical redundancy between a pair of metrics within an attribute set (i.e., correlation or regression slopes with p-values < 0.05) was considered justification for eliminating one of the pair from the regional set of monitoring metrics. Decisions regarding metric elimination versus retention were based on feasibility of monitoring, considering such factors as sampling time, resources required, and potential for regional standardization in implementation. The result of these tests is a reduced suite of monitoring metrics that targets NWRS management decisions and is practicable for implementing on a regional scale. Based on these tests, we recommend the following list of metrics for monitoring integrity of NWRS salt marshes (marsh attribute category is in parentheses): (historical condition and geomorphic setting) position of marsh in the landscape, marsh shape, degree of fill and/or fragmentation, degree of tidal flushing, amount of aquatic edge; (ditch density) ranking of ditch density from none to severe; (surrounding land use) relative proportion of agricultural land in a 150-m buffer around the marsh, relative proportion of natural land in a 150-m buffer around the marsh, relative proportion of natural land in a 1-km buffer around the marsh; (ratio of open water area to vegetation area) ratio of open water to emergent herbaceous wetlands within the marsh; (marsh surface elevation) elevation referenced to NAVD88 in a representative area of the marsh; (tidal range and groundwater level) percent of time the marsh surface is flooded during deployment of a continuous water-level monitor at a representative marsh location, mean depth of surface flooding as measured by a continuous water-level monitor at a representative location; (salinity) salinity measured in surface water; (vegetation community) vegetation species richness using the point-intercept method in 100-m diameter survey plots, percent cover of various marsh community types within 100-m diameter survey plots; (invasive species abundance) percent cover of invasive plant species measured using the point-intercept method in 100-m diameter survey plots; (nekton community) nekton density, nekton species richness, length of Fundulus heteroclitus ; (breeding bird community) abundance of Willets counted per point during standard call-broadcast surveys, summed abundance of tidal marsh obligate species (Clapper Rail, Willet, Saltmarsh Sparrow, Seaside Sparrow) counted per point during standard call-broadcast surveys. Metrics describing the historical condition, geomorphic setting, and broad landscape features can be assessed using existing GIS databases. Our results support use of rapid methods to assess the majority of field metrics; only those used to describe the nekton community must be measured using intensive methods (throw traps or ditch nets, dependant on habitat configuration). Implementation of these metrics for quantitative assessment of NWRS salt marsh integrity in FWS Region 5 requires developing sampling designs for each refuge. Additionally, it is important to determine how the monitoring information will be used within a management context. SDM should be used to complete the analysis of salt marsh management decisions. The next steps would involve 1) prioritizing and weighting the management objectives; 2) predicting responses to individual management actions in terms of objectives and metrics; 3) using multiattribute utility theory to convert all measurable attributes to a common utility scale; 4) determining the total management benefit of each action by summing utilities across objectives; and 5) maximizing the total management benefits within cost constraints for each refuge. This process would allow the optimum management decisions for NWRS salt marshes to be selected and implemented based directly on monitoring data and current understanding of marsh responses to management actions. Monitoring the outcome of management actions would then allow new monitoring data to be incorporated into subsequent decisions.

Connecticut, Delaware, Maine, Massachusetts, New J↗

USGS2011

Flow studies for recycling metal commodities in the United States

As world population increases and the world economy expands, so does the demand for natural resources. An accurate assessment of the Nation's mineral resources must include not only the resources available in the ground but also those that become available through recycling. Supplying this information to decisionmakers is an essential part of the USGS commitment to providing the science that society needs to meet natural resource and environmental challenges. The U.S. Geological Survey is authorized by Congress to collect, analyze, and disseminate data on the domestic and international supply of and demand for minerals essential to the U.S. economy and national security. This information on mineral occurrence, production, use, and recycling helps policymakers manage resources wisely. USGS Circular 1196, "Flow Studies for Recycling Metal Commodities in the United States," presents the results of flow studies for recycling 26 metal commodities, from aluminum to zinc. These metals are a key component of the U.S. economy. Overall, recycling accounts for more than 40 percent of the U.S. metal supply. Marcia K. McNutt Director

Circular↗

USGS1982

Map showing selected surface-water data for the Alton-Kolob coal-fields area, Utah

This is one of a series of maps that describe the geology and related natural resources of the Alton-Kolob coal-fields area, Utah. Streamflow records used to compile the map and the following table were collected by the U.S. Geological Survey in cooperation with the Utah Department of Natural Resources, Division of Water Rights, and the Utah Department of Transportation. The principal runoff-producing areas were delineated form a work map (scale 1:250,000) compiled to estimate water yields in Utah (Bagley and others, 1964).

Utah↗

USGS2012

Mapping outdoor recreationists' perceived social values for ecosystem services at Hinchinbrook Island National Park, Australia

Coastal ecosystems are increasingly faced with human impacts. To better understand these changing conditions, biophysical and economic values of nature have been used to prioritize spatial planning efforts and ecosystem-based management of human activities. Less is known, however, about how to characterize and represent non-material values in decision-making. We collected on-site and mailback survey data ( n = 209), and analyzed these data using the Social Values for Ecosystem Services (SolVES) GIS application to incorporate measures of social value and natural resource conditions on Hinchinbrook Island National Park, Australia. Our objectives in this paper are to: 1) determine the spatial distribution and point density of social values for ecosystem services; 2) examine the relationship between social values and natural resource conditions; and 3) compare social value allocations between two subgroups of outdoor recreationists. Results suggest that high priority areas exist on Hinchinbrook's land and seascapes according to the multiple values assigned to places by outdoor recreationists engaged in consumptive (e.g., fishing) and non-consumptive (e.g., hiking) activities. We examine statistically significant spatial clustering across two subgroups of the survey population for three value types that reflect Recreation, Biological Diversity, and Aesthetic qualities. The relationship between the relative importance of social values for ecosystem services and spatially-defined ecological data is explored to guide management decision-making in the context of an island national park setting.

Hinchinbrook Island National Park↗

USGS2024

Climate-smart invasive species management for 21st century global change challenges

Addressing the global challenges of climate change and biotic invasions requires understanding their interactions and implications for natural resource management. To facilitate and support invasive species management in a changing climate, we review how climate change and invasions interact to impact the planning, action, and outcomes of invasive species management. Climate change is affecting which species natural resource managers need to assess, monitor, and target by facilitating the introduction of new potential invasive species and altering pathways of introduction and spread. Climate-driven shifts in seasonal conditions and phenological events disrupt and require more flexible management timelines. Climate change may reduce the efficacy and feasibility of current treatment methods and create a need to shift management goals as native ecosystems become more vulnerable to disturbance. Additionally, extreme climate events can compound the spread and impacts of biological invasions, making invasive species management a necessary part of extreme event preparation and response planning. As a solution to these challenges, we propose climate-smart invasive species management, which we define as the approaches that managers and decision-makers can take to address the interactive effects of climate change and invasions. Climate-smart invasive species management includes considering shifts in species ranges, abundance, and impacts to inform monitoring, treatment, and regulation of potential and new invaders at multiple scales. Managers can also adjust the timing of and approach to treatment as efficacy and feasibility change, promote resilient ecosystems through climate-smart restoration, and consider the effects of climate change when setting management goals. Furthermore, climate adaptation funds could expand avenues of funding and support for invasive species management. Explicitly considering the interactions of climate change and biological invasions within organizational decision-making and policy will lead to more effective management and can promote more resilient landscapes.

Global Change Biology↗

USGS2002

Identifying and assessing ecotourism visitor impacts at selected protected areas in Costa Rica and Belize

Protected area visitation is an important component of ecotourism, and as such, must be sustainable. However, protected area visitation may degrade natural resources, particularly in areas of concentrated visitor activities like trails and recreation sites. This is an important concern in ecotourism destinations such as Belize and Costa Rica, because they actively promote ecotourism and emphasize the pristine qualities of their natural resources. Research on visitor impacts to protected areas has many potential applications in protected area management, though it has not been widely applied in Central and South America. This study targeted this deficiency through manager interviews and evaluations of alternative impact assessment procedures at eight protected areas in Belize and Costa Rica. Impact assessment procedures included qualitative condition class systems, ratings systems, and measurement-based systems applied to trails and recreation sites. The resulting data characterize manager perceptions of impact problems, document trail and recreation site impacts, and provide examples of inexpensive, efficient and effective rapid impact assessment procedures. Interview subjects reported a variety of impacts affecting trails, recreation sites, wildlife, water, attraction features and other resources. Standardized assessment procedures were developed and applied to record trail and recreation site impacts. Impacts affecting the study areas included trail proliferation, erosion and widening, muddiness on trails, vegetation cover loss, soil and root exposure, and tree damage on recreation sites. The findings also illustrate the types of assessment data yielded by several alternative methods and demonstrate their utility to protected area managers. The need for additional rapid assessment procedures for wildlife, water, attraction feature and other resource impacts was also identified.

Environmental Conservation↗

USGS1995

United States Geological Survey, programs in Nevada

The U.S. Geological Survey (USGS) has been collecting and interpreting natural-resources data in Nevada for more than 100 years. This long-term commitment enables planners to manage better the resources of a State noted for paradoxes. Although Nevada is one of the most sparsely populated States in the Nation, it has the fastest growing population (fig. 1). Although 90 percent of the land is rural, it is the fourth most urban State. Nevada is the most arid State and relies heavily on water resources. Historically, mining and agriculture have formed the basis of the economy; now tourism and urban development also have become important. The USGS works with more than 40 local, State, and other Federal agencies in Nevada to provide natural-resources information for immediate and long-term decisions. Subjects included in this fact sheet: Low-Level Radioactive-Waste Disposal Mining and Water in the Humboldt Basin Aquifer Systems in the Great Basin Water Allocation in Truckee and Carson Basins National Water-Quality Assessment Program Minerals Assessment for Land Management Irrigation Drainage Ground-Water Movement at Nevada Test Site Oil and Gas Resources National Mapping Program Digital Mapping and Aerial Photography Collection of Hydrologlc Data Geologic Mapping Earthquake Hazards Assessing Mineral Resources of the Subsurface Earth Observation Data Cooperative Programs

Nevada↗

USGS2008

Bathymetric contour maps of lakes surveyed in Iowa in 2005

The U.S. Geological Survey, in cooperation with the Iowa Department of Natural Resources, conducted bathymetric surveys on seven lakes in Iowa during 2005 (Arrowhead Pond, Central Park Lake, Lake Keomah, Manteno Park Pond, Lake Miami, Springbrook Lake, and Yellow Smoke Lake). The surveys were conducted to provide the Iowa Department of Natural Resources with information for the development of total maximum daily load limits, particularly for estimating sediment load and deposition rates. The bathymetric surveys provide a baseline for future work on sediment loads and deposition rates for these lakes. All of the lakes surveyed in 2005 are man-made lakes with fixed spillways. Bathymetric data were collected using boat-mounted, differential global positioning system, echo depth-sounding equipment, and computer software. Data were processed with commercial hydrographic software and exported into a geographic information system for mapping and calculating area and volume. Lake volume estimates ranged from 47,784,000 cubic feet (1,100 acre-feet) at Lake Miami to 2,595,000 cubic feet (60 acre-feet) at Manteno Park Pond. Surface area estimates ranged from 5,454,000 square feet (125 acres) at Lake Miami to 558,000 square feet (13 acres) at Springbrook Lake.

Iowa↗

USGS2013

U.S. Geological Survey climate and land use change science strategy—A framework for understanding and responding to global change

Executive Summary The U.S. Geological Survey (USGS), a nonregulatory Federal science agency with national scope and responsibilities, is uniquely positioned to serve the Nation’s needs in understanding and responding to global change, including changes in climate, water availability, sea level, land use and land cover, ecosystems, and global biogeochemical cycles. Global change is among the most challenging and formidable issues confronting our Nation and society. Scientists agree that global environmental changes during this century will have far-reaching societal implications (Intergovernmental Panel on Climate Change, 2007; U.S. Global Change Research Program, 2009). In the face of these challenges, the Nation can benefit greatly by using natural science information in decisionmaking. Since the passage of the U.S. Global Change Research Act of 1990, the USGS has made substantial scientific contributions to understanding the interactive living and nonliving components of the Earth system. USGS natural science activities have led to fundamental advances in observing and understanding climate and land-cover change and the effects these changes have on ecosystems, natural-resource availability, and societal sustainability. Most of these major advances were pursued in partnership with other organizations within and outside the Department of the Interior. The inherent value of partnerships with other U.S. Global Change Research Program agencies and natural-resource managers is emphasized in all aspects of the planning and implementation of this Science Strategy for the coming decade. Over the next 10 years, the USGS will make substantial contributions to understanding how Earth systems interact, respond to, and cause global change. The USGS will work with science partners, decisionmakers, and resource managers at local to international levels (including Native American tribes) to improve understanding of past and present change; develop relevant forecasts; and identify those lands, resources, and communities most vulnerable to global change processes. Science will play an essential role in helping communities and land and resource managers understand local to global implications, anticipate effects, prepare for changes, and reduce the risks associated with decisionmaking in a changing environment. USGS partners and stakeholders will benefit from the data, predictive models, and decision-support products and services resulting from the implementation of this strategy. This Science Strategy recognizes core USGS strengths that are applied to key societal problems. It establishes seven goals for USGS global change science and strategic actions that may be implemented in the short term (1–5 years) and the longer term (5–10 years) to improve our understanding of the following areas of inquiry: Rates, causes, and impacts of past global changes; The global carbon cycle; Biogeochemical cycles and their coupled interactions; Land-use and land-cover change rates, causes, and consequences; Droughts, floods, and water availability under changing land-use and climatic conditions; Coastal response to sea-level rise, climatic change, and human development; and Biological responses to global change. In addition to the seven thematic goals, we address the central role of monitoring in accordance with the USGS Science Strategy recommendation that global change research should rely on existing “…decades of observational data and long-term records to interpret consequences of climate variability and change to the Nation’s biological populations, ecosystems, and land and water resources” (U.S. Geological Survey, 2007, p. 19). We also briefly describe specific needs and opportunities for coordinating USGS global change science among USGS Mission Areas and address the need for a comprehensive and sustained communications strategy.

Circular↗