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At least 919 records · Page 51Linked to original sources

Archive of digitized analog boomer and minisparker seismic reflection data collected from the Alabama-Mississippi-Louisiana Shelf during cruises onboard the R/V Carancahua and R/V Gyre, April and July, 1981

In April and July of 1981, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the shallow geologic framework of the Alabama-Mississippi-Louisiana Shelf in the northern Gulf of Mexico. Work was conducted onboard the Texas A&M University R/V Carancahua and the R/V Gyre to develop a geologic understanding of the study area and to locate potential hazards related to offshore oil and gas production. While the R/V Carancahua only collected boomer data, the R/V Gyre used a 400-Joule minisparker, 3.5-kilohertz (kHz) subbottom profiler, 12-kHz precision depth recorder, and two air guns. The authors selected the minisparker data set because, unlike with the boomer data, it provided the most complete record. This report is part of a series to digitally archive the legacy analog data collected from the Mississippi-Alabama SHelf (MASH). The MASH data rescue project is a cooperative effort by the USGS and the Minerals Management Service (MMS). This report serves as an archive of high-resolution scanned Tagged Image File Format (TIFF) and Graphics Interchange Format (GIF) images of the original boomer and minisparker paper records, navigation files, trackline maps, Geographic Information System (GIS) files, cruise logs, and formal Federal Geographic Data Committee (FGDC) metadata.

Alabama, Louisiana, Mississippi↗

NOGA Online: a USGS resource for energy GIS data and services

The PowerPoint presentation in this report was given at the BLM Resource Management Tools Conference in Phoenix, Arizona, April, 2003. Some diagrams that appeared in the original presentation have been updated in this report. It informs that the U.S. Geological Survey (USGS) Central Energy Resources Team (CERT) in Denver, Colorado, is providing National Oil and Gas Assessment (NOGA) results online at http://energy.cr.usgs.gov/oilgas/noga/. Available at this site are recently completed assessments of the potential for undiscovered oil and natural gas resources of five priority provinces (Montana Thrust Belt, Powder River Basin, San Juan Basin, Southwestern Wyoming, Uinta-Piceance) to meet the requirements of the Energy Policy and Conservation Act of 2000 (EPCA 2000). High demand for current assessment results and for the entirely digital, 1995 NOGA results for other provinces, prompted CERT to develop an internet map application using ArcIMS to deliver geologic data to the public. CERT continues to work on assessing oil and natural gas resources of priority basins in the United States; assessment results and GIS layers are made available at this site on an ongoing basis.

Open-File Report↗

Flood-inundation maps for the South Platte River at Fort Morgan, Colorado, 2018

In 2017, the U.S. Geological Survey (USGS), in cooperation with the Colorado Water Conservation Board (CWCB), studied floods in the historic record to produce a library of flood-inundation maps for the South Platte River at Fort Morgan, Colorado. Digital flood-inundation maps for a 4.5-mile (7.2-kilometers) reach of the South Platte River at Fort Morgan from Morgan County Road 16 to Morgan County Road 20.5, were created. The flood-inundation maps depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the U.S. Geological Survey streamgage on the South Platte River at Fort Morgan (streamgage number 06759500). Water-surface profiles were computed for the stream reach by means of a one-dimensional, step-backwater model. The September 15, 2013, and May 20, 2017, floods were used to calibrate the model, and the June 15, 2015, and May 29, 2017, floods were used to independently validate the model. Nine pressure transducers were deployed to record the stage at nine different locations along the reach and to document the floods of May 20 and 29, 2017, at the South Platte River at Fort Morgan streamgage. The hydraulic model was then used to compute 16 water-surface profiles for flood stages at 1-foot (ft; 0.3-meter [m]) intervals referenced to the streamgage datum and ranging from 12 ft (3.66 m) or below bankfull to 27 ft (8.23 m), which is 1 ft (0.3 m) greater than the highest recorded water level (25.73 ft [7.84 m] on September 15, 2013) at the South Platte River at Fort Morgan streamgage during its period of record; the 2013 flood exceeds the major flood stage of 21.5 ft (6.55 m) by more than 4 ft (1.2 m), as defined by the National Weather Service. The simulated water-surface profiles were then combined with a geographic information system digital elevation model (derived from light detection and ranging data having a 0.37-ft [0.11-m] vertical accuracy and 3.28-ft [1.00-m] horizontal resolution) to delineate the area flooded for stages ranging from 12 to 27 ft (3.66 to 8.23 m). These flood-inundation maps, in conjunction with the real-time stage data from the USGS streamgage on the South Platte River at Fort Morgan, are intended to help guide the general public in taking individual safety precautions and provide emergency management personnel with a tool to efficiently manage emergency flood operations and post flood recovery efforts.

Colorado↗

The Integrated Landscape Modeling partnership - Current status and future directions

The Integrated Landscape Modeling (ILM) partnership is an effort by the U.S. Geological Survey (USGS) and U.S. Department of Agriculture (USDA) to identify, evaluate, and develop models to quantify services derived from ecosystems, with a focus on wetland ecosystems and conservation effects. The ILM partnership uses the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) modeling platform to facilitate regional quantifications of ecosystem services under various scenarios of land-cover change that are representative of differing conservation program and practice implementation scenarios. To date, the ILM InVEST partnership has resulted in capabilities to quantify carbon stores, amphibian habitat, plant-community diversity, and pollination services. Work to include waterfowl and grassland bird habitat quality is in progress. Initial InVEST modeling has been focused on the Prairie Pothole Region (PPR) of the United States; future efforts might encompass other regions as data availability and knowledge increase as to how functions affecting ecosystem services differ among regions. The ILM partnership is also developing the capability for field-scale process-based modeling of depressional wetland ecosystems using the Agricultural Policy/Environmental Extender (APEX) model. Progress was made towards the development of techniques to use the APEX model for closed-basin depressional wetlands of the PPR, in addition to the open systems that the model was originally designed to simulate. The ILM partnership has matured to the stage where effects of conservation programs and practices on multiple ecosystem services can now be simulated in selected areas. Future work might include the continued development of modeling capabilities, as well as development and evaluation of differing conservation program and practice scenarios of interest to partner agencies including the USDA’s Farm Service Agency (FSA) and Natural Resources Conservation Service (NRCS). When combined, the ecosystem services modeling capabilities of InVEST and the process-based abilities of the APEX model should provide complementary information needed to meet USDA and the Department of the Interior information needs.

Iowa, Minnesota, Nebraska, North Dakota, South Dak↗

Method for Estimating Water Withdrawals for Livestock in the United States, 2005

Livestock water use includes ground water and surface water associated with livestock watering, feedlots, dairy operations, and other on-farm needs. The water may be used for drinking, cooling, sanitation, waste disposal, and other needs related to the animals. Estimates of water withdrawals for livestock are needed for water planning and management. This report documents a method used to estimate withdrawals of fresh ground water and surface water for livestock in 2005 for each county and county equivalent in the United States, Puerto Rico, and the U.S. Virgin Islands. Categories of livestock included dairy cattle, beef and other cattle, hogs and pigs, laying hens, broilers and other chickens, turkeys, sheep and lambs, all goats, and horses (including ponies, mules, burros, and donkeys). Use of the method described in this report could result in more consistent water-withdrawal estimates for livestock that can be used by water managers and planners to determine water needs and trends across the United States. Water withdrawals for livestock in 2005 were estimated by using water-use coefficients, in gallons per head per day for each animal type, and livestock-population data. Coefficients for various livestock for most States were obtained from U.S. Geological Survey water-use program personnel or U.S. Geological Survey water-use publications. When no coefficient was available for an animal type in a State, the median value of reported coefficients for that animal was used. Livestock-population data were provided by the National Agricultural Statistics Service. County estimates were further divided into ground-water and surface-water withdrawals for each county and county equivalent. County totals from 2005 were compared to county totals from 1995 and 2000. Large deviations from 1995 or 2000 livestock withdrawal estimates were investigated and generally were due to comparison with reported withdrawals, differences in estimation techniques, differences in livestock coefficients, or use of livestock-population data from different sources. The results of this study were distributed to U.S. Geological Survey water-use program personnel in each State during 2007. Water-use program personnel are required to submit estimated withdrawals for all categories of use in their States to the National Water-Use Information Program for inclusion in a national report describing water use in the United States during 2005. Water-use program personnel had the option of submitting these estimates, a modified version of these estimates, or their own set of estimates or reported data. Estimated withdrawals resulting from the method described in this report are not presented herein to avoid potential inconsistencies with estimated withdrawals for livestock that will be presented in the national report, as different methods used by water-use personnel may result in different withdrawal estimates. Estimated withdrawals also are not presented to avoid potential disclosure of data for individual livestock operations.

Scientific Investigations Report↗

Learning and adaptation in the management of waterfowl harvests

A formal framework for the adaptive management of waterfowl harvests was adopted by the U.S. Fish and Wildlife Service in 1995. The process admits competing models of waterfowl population dynamics and harvest impacts, and relies on model averaging to compute optimal strategies for regulating harvest. Model weights, reflecting the relative ability of the alternative models to predict changes in population size, are used in the model averaging and are updated each year based on a comparison of model predictions and observations of population size. Since its inception the adaptive harvest program has focused principally on mallards ( Anas platyrhynchos ), which constitute a large portion of the U.S. waterfowl harvest. Four competing models, derived from a combination of two survival and two reproductive hypotheses, were originally assigned equal weights. In the last year of available information (2007), model weights favored the weakly density-dependent reproductive hypothesis over the strongly density-dependent one, and the additive mortality hypothesis over the compensatory one. The change in model weights led to a more conservative harvesting policy than what was in effect in the early years of the program. Adaptive harvest management has been successful in many ways, but nonetheless has exposed the difficulties in defining management objectives, in predicting and regulating harvests, and in coping with the tradeoffs inherent in managing multiple waterfowl stocks exposed to a common harvest. The key challenge now facing managers is whether adaptive harvest management as an institution can be sufficiently adaptive, and whether the knowledge and experience gained from the process can be reflected in higher-level policy decisions.

Journal of Environmental Management↗

National Geospatial Program

The National Geospatial Program (NGP; http://www.usgs.gov/ngpo/ ) satisfies the needs of customers by providing geospatial products and services that customers incorporate into their decisionmaking and operational activities. These products and services provide geospatial data that are organized and maintained in cost-effective ways and developed by working with partners and organizations whose activities align with those of the program. To accomplish its mission, the NGP— organizes, maintains, publishes, and disseminates the geospatial baseline of the Nation's topography, natural landscape, and manmade environment through The National Map fosters a general understanding of broad geographic patterns, trends, and conditions through The National Atlas of the United States of America increases the efficiency of the Nation's geospatial community by improving communications about geospatial data, products, services, projects, needs, standards, and best practices. The NGP comprises seven major components (described below), that are managed as a unified set. For example, The National Map establishes data standards and identifies geographic areas where specific types of geospatial data need to be incorporated into The National Map . Partnership Network Liaisons work with Federal, State, local, and tribal partners to help acquire the data. Geospatial technical operations ensure the quality control, integration, and availability to the public of the data acquired. The Emergency Operations Office provides the requirements to The National Map and, during emergencies and natural disasters, provides rapid dissemination of information and data targeted to the needs of emergency responders. The National Atlas uses data from The National Map and other sources to make small-scale maps and multimedia articles about the maps.

Fact Sheet↗

Gillnet sampling methods for monitoring status and trends of Clear Lake Hitch in Clear Lake, Lake County, California

The Clear Lake Hitch ( Lavinia exilicauda chi ) is a minnow endemic to Clear Lake, Lake County, California. This species is listed as a threatened species under the California Endangered Species Act and has been petitioned for listing under the United States Endangered Species Act. In 2017, the U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service, initiated a Clear Lake Hitch monitoring program to generate information annually on relative abundance and size structure. The monitoring program was organized around a conceptual life cycle diagram, focused on life stages approximately ≥1 year of age, and incorporated a probabilistic study design involving approximately 10 days of short-duration (approximately 40 minutes) gillnet sampling undertaken during daytime. This report documents monitoring program activities from 2017 to 2023 and presents the results of an evaluation of the monitoring program. The evaluation was done after the 2023 sampling event, following 6 years of implementation, which is the approximate generation cycle of Clear Lake Hitch. The results of the evaluation indicated the following: (1) gillnets used in the monitoring program were effective at capturing Clear Lake Hitch aged 1 year or more; (2) the study design was effective at generating the information needed to characterize Clear Lake Hitch relative abundance and size structure, and meaningful operational efficiencies can be obtained by implementing simple changes; and (3) future sampling can be scaled to approximately 4–7 days of effort and maintain at least 80-percent confidence in detecting at least a 25-percent change in abundance, assuming past work productivity is maintained and future data are typical of previous data.

California↗

Yellowstone grizzly bear investigations: Annual report of the Interagency Grizzly Bear Study Team, 2004

The contents of this Annual Report summarize results of monitoring and research from the 2004 field season. The report also contains a summary of nuisance grizzly bear ( Ursus arctos horribilis ) management actions. The study team continues to work on issues associated with counts of unduplicated females with cubs-of-the-year (COY). These counts are used to establish a minimum population size, which is then used to establish mortality thresholds for the Recovery Plan (U.S. Fish and Wildlife Service [USFWS] 1993). A computer program that defines the rule set used by Knight et al. (1995) to differentiate unique family groups was completed in spring 2005. We will use an improved version of this model to verify the accuracy of the rules using known bears and their telemetry locations in test runs. We hope to have this work complete by the end of 2005. The grizzly bear recovery plan (USFWS 1993) established mortality quotas at 4% of the minimum population estimate derived from female with COY data and no more than 30% of the 4% (1.2%) could be female bears. Simulation modeling (Harris 1984) established sustainable mortality at around 6% of the population. We used the latest information on reproduction and survival to estimate population trajectory in the same simulation model originally used by Harris. A Wildlife Monograph has been accepted for publication and should be available by summer 2005. Our project addressing the potential application of stable isotopes and trace elements to quantify consumption rates of whitebark pine ( Pinus albicaulis ) and cutthroat trout ( Oncorhynchus clarki ) by grizzly bears was completed. Our manuscript on consumption rates of whitebark pine has been published (Canadian Journal of Zoology 81:763-770). The manuscript on fish consumption rates was also accepted and is published in the Canadian Journal of Zoology 82:493-501. Both can be found on the Interagency Grizzly Bear Study Team (IGBST) website http://www.nrmsc.usgs.gov/research/igbst-home.htm. We began a new study in Grand Teton National Park evaluating habitat use both temporally and spatially between grizzly and black ( Ursus americanus ) bears. We will employ a new form of Global Positioning System (GPS) technology that incorporates a spread spectrum communication system. Spread spectrum allows for transfer of stored GPS locations from the collar to a remote receiving station. Results of our first yea r’s field season are summarized in this report. Whitebark pine (WBP) has been identified as one of the import ant fall foods of the Yellowstone grizzly bear. Previous efforts to map the distribution of WBP were for the Cumulative Effects Model. Consequently the only coverage of WBP distribution was for the grizzly bear Recovery Zone. We were successful in getting financial support through the U.S. Geological Survey Land Remote Sensing Program and Interdisciplinary Science Support Activities Project to create an ecosystem-wide map of the distribution of WBP. The results of that project are reported in Appendix A. The study team annually estimates WBP cone production on a series of transects. That information is reported annually in our reports. Concern over the long-term health of WBP prompted us to investigate the usefulness of cone counts as an indirect index of WBP health. Results of this analysis (Appendix B) indicated that cone production is too variable to serve this purpose. Consequently, we partnered with several 2 other agencies and embarked on a program to develop a long-term monitoring program directed specifically at WBP health in the Greater Yellowstone Ecosystem (GYE). Our team (Greater Yellowstone Whitebark Pine Monitoring Working Group) was successful in obtaining funds to develop and implement a WBP health monitoring program. Results of our first years work are presented in Appendix C. We also successfully competed for funds in 2005 and will continue to collect information on WBP health. Army cutworm moths ( Euxoa auxiliaris ) are also a very important food for a segment of the GYE grizzly bear population. Hillary Robison, graduate student at University of Nevada, Reno, is nearing completion of her program. In this report, we post her annual work summary, and abstracts of her most recently submitted publications. These include one on the levels of pesticides in cutworm moths and their potential affect on grizzly bears (Appendix D), a spatial analysis to identify army cutworm moth habitat (Appendix E), and the results of a preliminary analysis of pollen grains on the mouth parts of moths (Appendix F) to help identify which plant species are commonly fed upon. Other study team members have also been working on various aspects of grizzly bear science. Study team member Kerry Gunther hosted a workshop on habituated grizzly bears in North America. A copy of the abstract of that report can be found in Appendix G. Additionally, Kerry Gunther and Doug Smith, wolf researcher in Yellowstone National Park (YNP), reported on the interactions between gray wolves ( Canis lupus ) and female grizzly bears with young. They report that of 15 interactions between these 2 carnivores, 8 involve d females with COY. They observed 2 incidents where cubs were killed by wolves at ungulate carcasses (Appendix H). The annual reports of the IGBST summarize annual data collection. Because additional information can be obtained after publication, data summaries are subject to change. For that reason, data analyses and summaries presented in this report supersede all previously published data. The study area and sampling techniques are reported by Blanchard (1985), Mattson et al. (1991 a ), and Haroldson et al. (1998).

Idaho, Montana, Wyoming↗

Catalogue of polar bear (Ursus maritimus) maternal den locations in the Beaufort and Chukchi Seas and nearby areas, 1910–2018

This report presents data on the approximate locations and methods of discovery of 530 polar bear ( Ursus maritimus ) maternal dens observed in the Beaufort and Chukchi Seas and neighboring areas from 1910 to 2018, and archived partly by the U.S. Geological Survey, Alaska Science Center, and partly by the U.S. Fish and Wildlife Service, Marine Mammals Management, in Anchorage, Alaska. A description of data collection methods and their associated biases, primary data collection time periods, and estimated position uncertainty are provided. Polar bears in the Beaufort and Chukchi Seas den on sea ice and land. Standardized very high frequency (VHF) aircraft surveys and satellite radio telemetry data provide a general understanding of where polar bears have denned in this region over the past 3 decades. Den observations made during other research activities and anecdotal reports from other government agencies, coastal residents, and industry personnel also are reported. These data on past polar bear maternal den locations are provided to inform decision making by natural resource agencies and for public use.

Alaska↗

New Jersey Tide Telemetry System

Each summer the population of the barrier-island communities of New Jersey increases by tens of thousands. When a coastal storm threatens these communities, the limited number of bridges and causeways that connect the islands with the mainland become overcrowded, making evacuations from the barrier islands to the mainland difficult. Timely evacuation depends on well-defined emergency evacuation plans used in conjunction with accurate flood forecasting and up to the minute (real-time) tide-level information. The 'Great Nor'easter' storm that struck the coastal areas of New Jersey on December 11, 1992, caused about $270 million in insured damages to public and private property (Dorr and others, 1995). Most of the damage was due to tidal flooding and storm surge, which were especially severe along the back bay areas. Comprehensive and reliable tide-level and meteorological data for the back bays was needed to make accurate flood forecasts. Collection of tidal data for the ocean and large bays was adequately covered by the National Oceanic and Atmospheric Administration's National Ocean Service (NOAA's NOS), but in New Jersey little to no data are available for the back-bay areas. The back bays behave quite differently than the ocean as a result of the complex interaction between the winds and the geometry of the inlets and bays. A slow moving Nor'easter can keep tide levels in back bays several feet higher than the ocean tide by not allowing tides to recede, resulting in flooding of bridges and causeways that link the barrier islands to the mainland. The U.S. Geological Survey (USGS), in cooperation with the New Jersey Department of Transportation (NJDOT), designed and installed the New Jersey Tide Telemetry System (NJTTS) with assistance from NOAA's NOS in 1997. This system is part of a statewide network of tide gages, weather stations, and stream gages that collect data in real time. The NJTTS supplies comprehensive, reliable real-time tide-level and meteorological data for flood-prone areas along the New Jersey shore and back bays. These data are transmitted to computer base stations located at offices of the National Weather Service, New Jersey State Police (NJSP), NJDOT, county emergency management agencies, other critical decision-making centers, and the World Wide Web (WWW). This fact sheet describes the NJTTS and identifies its benefits.

Fact Sheet↗

Map showing locations and statistical parameters of beach and offshore sand samples, Tutuila Island, American Samoa

In April 1985, sand samples were collected from many of the beaches on Tutuila Island, American Samoa, and in July 1985, three bays were surveyed using side-scan sonar and shallow seismic profiling. During that second trip, scuba divers collected sand samples from the surveyed areas. Dingler and others (1986) describes the study; this report presents the grain-size and composition data for the onshore and offshore sand samples. Locations of the onshore samples are plotted on the map of the island, which is reproduced from Normark and others (1985); locations of most of the offshore samples and side-scan sonar interpretations made during the study are plotted on enlargements (A and B, respectively) of Fagaitua and Nua-seetaga Bays. Lam Yuen (1981), U.S. Army Corps of Engineers (1980), and Sea Engineering Services Inc. (1980) provide additional information pertaining to the island's beaches.

Tutuila Island↗

Geologic map database of the El Mirage Lake area, San Bernardino and Los Angeles Counties, California

This geologic map database for the El Mirage Lake area describes geologic materials for the dry lake, parts of the adjacent Shadow Mountains and Adobe Mountain, and much of the piedmont extending south from the lake upward toward the San Gabriel Mountains. This area lies within the western Mojave Desert of San Bernardino and Los Angeles Counties, southeastern California. The area is traversed by a few paved highways that service the community of El Mirage, and by numerous dirt roads that lead to outlying properties. An off-highway vehicle area established by the Bureau of Land Management encompasses the dry lake and much of the land north and east of the lake. The physiography of the area consists of the dry lake, flanking mud and sand flats and alluvial piedmonts, and a few sharp craggy mountains. This digital geologic map database, intended for use at 1:24,000-scale, describes and portrays the rock units and surficial deposits of the El Mirage Lake area. The map database was prepared to aid in a water-resource assessment of the area by providing surface geologic information with which deepergroundwater-bearing units may be understood. The area mapped covers the Shadow Mountains SE and parts of the Shadow Mountains, Adobe Mountain, and El Mirage 7.5-minute quadrangles. The map includes detailed geology of surface and bedrock deposits, which represent a significant update from previous bedrock geologic maps by Dibblee (1960) and Troxel and Gunderson (1970), and the surficial geologic map of Ponti and Burke (1980); it incorporates a fringe of the detailed bedrock mapping in the Shadow Mountains by Martin (1992). The map data were assembled as a digital database using ARC/INFO to enable wider applications than traditional paper-product geologic maps and to provide for efficient meshing with other digital data bases prepared by the U.S. Geological Survey's Southern California Areal Mapping Project.

California↗

Flood tracking chart for the Illinois River basin

This Flood Tracking Chart for the Illinois River Basin in Illinois can be used to record and compare the predicted or current flood-crest stage to past flood-crest information. This information can then be used by residents and emergency-response personnel to make informed decisions concerning the threat of flooding to life and property. The chart shows a map of the Illinois River Basin (see below), the location of real-time streamflow-gaging stations in the basin, graphs of selected historical recorded flood-crest stages at each of the stations, and sea-level conversion (SLC) factors that allow conversion of the current or predicted flood-crest stage to elevation above sea level. Each graph represents a streamflow-gaging station and has a space to record the most current river stage reported for that station by the U.S. Geological Survey (USGS). The National Weather Service (NWS) predicts flood crests for many of the stations shown on this chart.

Illinois↗

National Park Service Vegetation Mapping Inventory Program: Appalachian National Scenic Trail vegetation mapping project

The National Park Service (NPS) Vegetation Mapping Inventory (VMI) Program classifies, describes, and maps existing vegetation of national park units for the NPS Natural Resource Inventory and Monitoring (I&M) Program. The NPS VMI Program is managed by the NPS I&M Division and provides baseline vegetation information to the NPS Natural Resource I&M Program. The U.S. Geological Survey Upper Midwest Environmental Sciences Center, NatureServe, NPS Northeast Temperate Network, and NPS Appalachian National Scenic Trail (APPA) have completed vegetation classification and mapping of APPA for the NPS VMI Program. Mappers, ecologists, and botanists collaborated to affirm vegetation types within the U.S. National Vegetation Classification (USNVC) of APPA and to determine how best to map the vegetation types by using aerial imagery. Analyses of data from 1,618 vegetation plots were used to describe USNVC associations of APPA. Data from 289 verification sites were collected to test the field key to vegetation associations and the application of vegetation associations to a sample set of map polygons. Data from 269 validation sites were collected to assess vegetation mapping prior to submitting the vegetation map for accuracy assessment (AA). Data from 3,265 AA sites were collected, of which 3,204 were used to test accuracy of the vegetation map layer. The collective of these datasets affirmed 280 USNVC associations for the APPA vegetation mapping project. To map the vegetation and land cover of APPA, 169 map classes were developed. The 169 map classes consist of 150 that represent natural (including ruderal) vegetation types in the USNVC, 11 that represent cultural (agricultural and developed) vegetation types in the USNVC, 5 that represent natural landscapes with catastrophic disturbance or some other modification to natural vegetation preventing accurate classification in the USNVC, and 3 that represent nonvegetated water (non-USNVC). Features were interpreted from viewing 4-band digital aerial imagery using digital onscreen three-dimensional stereoscopic workflow systems in geographic information systems (GIS). (Digital aerial imagery was collected each fall during 2009–11 to capture leaf-phenology change of hardwood trees across the latitudinal range of APPA.) The interpreted data were digitally and spatially referenced, thus making the spatial-database layers usable in GIS. Polygon units were mapped to either a 0.5-hectare (ha) or 0.25-ha minimum mapping unit, depending on vegetation type or scenario; however, polygon units were mapped to 0.1 ha for alpine vegetation. A geodatabase containing various feature-class layers and tables provide locations and support data to USNVC vegetation types (vegetation map layer), vegetation plots, verification sites, validation sites, AA sites, project boundary extent and zones, and aerial image centers and flight lines. The feature-class layer and related tables of the vegetation map layer provide 30,395 polygons of detailed attribute data covering 110,919.7 ha, with an average polygon size of 3.6 ha; the vegetation map coincides closely with the administrative boundary for APPA. Summary reports generated from the vegetation map layer of the map classes representing USNVC natural (including ruderal) vegetation types apply to 28,242 polygons (92.9% of polygons) and cover 106,413.0 ha (95.9%) of the map extent for APPA. The map layer indicates APPA to be 92.4% forest and woodland (102,480.8 ha), 1.7% shrubland (1866.3 ha), and 1.8% herbaceous cover (2,065.9 ha). Map classes representing park-special vegetation (undefined in the USNVC) apply to 58 polygons (0.2% of polygons) and cover 404.3 ha (0.4%) of the map extent. Map classes representing USNVC cultural types apply to 1,777 polygons (5.8% of polygons) and cover 2,516.3 ha (2.3%) of the map extent. Map classes representing nonvegetated water (non-USNVC) apply to 332 polygons (1.1% of polygons) and cover 1,586.2 ha (1.4%) of the map extent.

Appalachian National Scenic Trail↗

Informing adaptive management to reduce ungulate aggregations: A case study involving winter feeding of elk

In the United States, wildlife managers are entrusted with preserving culturally and economically important ungulate populations in the face of the ongoing spread of chronic wasting disease (CWD). The U.S. Fish and Wildlife Service established an adaptive management plan to reduce the reliance of elk ( Cervus canadensis ) on supplemental winter feeding on the National Elk Refuge. The end goal of reducing the unnaturally high aggregation of elk during the winter is to mitigate the threat of disease outbreaks and to meet the objectives of sustainable populations of elk on the refuge. In this case study, we evaluated 6 years (2017–2022) of data from GPS-collared elk to determine the efficacy of shortening the length of the annual feeding period on the refuge to reduce elk aggregation. We measured aggregation using proximity rates, based on pairwise interactions over time, in both raw form as an index as well as predicted proximity as a function of other abiotic influences. We created a new R package, wildagg , to help with the process of computing the metrics from our study and to increase reproducibility in the future. Aggregation declined in years with less feeding on the refuge according to raw aggregation metrics when examined in isolation and dependent on the baseline feeding year used for comparison. However, accounting for abiotic factors while modeling proximity rates suggested in some years the decision to shorten the feeding period had less influence on aggregation than predicted. Our results underscore the complexity of measuring management outcomes and the usefulness of multiple approaches to evaluation.

Wyoming↗

An application of Social Values for Ecosystem Services (SolVES) to three national forests in Colorado and Wyoming

Despite widespread recognition that social-value information is needed to inform stakeholders and decision makers regarding trade-offs in environmental management, it too often remains absent from ecosystem service assessments. Although quantitative indicators of social values need to be explicitly accounted for in the decision-making process, they need not be monetary. Ongoing efforts to map such values demonstrate how they can also be made spatially explicit and relatable to underlying ecological information. We originally developed Social Values for Ecosystem Services (SolVES) as a tool to assess, map, and quantify nonmarket values perceived by various groups of ecosystem stakeholders. With SolVES 2.0 we have extended the functionality by integrating SolVES with Maxent maximum entropy modeling software to generate more complete social-value maps from available value and preference survey data and to produce more robust models describing the relationship between social values and ecosystems. The current study has two objectives: (1) evaluate how effectively the value index, a quantitative, nonmonetary social-value indicator calculated by SolVES, reproduces results from more common statistical methods of social-survey data analysis and (2) examine how the spatial results produced by SolVES provide additional information that could be used by managers and stakeholders to better understand more complex relationships among stakeholder values, attitudes, and preferences. To achieve these objectives, we applied SolVES to value and preference survey data collected for three national forests, the Pike and San Isabel in Colorado and the Bridger–Teton and the Shoshone in Wyoming. Value index results were generally consistent with results found through more common statistical analyses of the survey data such as frequency, discriminant function, and correlation analyses. In addition, spatial analysis of the social-value maps produced by SolVES provided information that was useful for explaining relationships between stakeholder values and forest uses. Our results suggest that SolVES can effectively reproduce information derived from traditional statistical analyses while adding spatially explicit, social-value information that can contribute to integrated resource assessment, planning, and management of forests and other ecosystems.

Colorado;Wyoming↗

Interoperability for ecosystem service assessments: Why, how, who, and for whom?

Despite continued, rapid growth in the literature, the fragmentation of information is a major barrier to more timely and credible ecosystem services (ES) assessments. A major reason for this fragmentation is the currently limited state of interoperability of ES data, models, and software. The FAIR Principles, a recent reformulation of long-standing open science goals, highlight the importance of making scientific knowledge Findable, Accessible, Interoperable, and Reusable . Critically, FAIR aims to make science more transparent and transferable by both people and computers . However, it is easier to make data and models findable and accessible through data and code repositories than to achieve interoperability and reusability. Achieving interoperability will require more consistent adherence to current technical best practices and, more critically, to build consensus about and consistently use semantics that can represent ES-relevant phenomena. Building on recent examples from major international initiatives for ES (IPBES, SEEA, GEO BON), we illustrate strategies to address interoperability, discuss their importance, and describe potential gains for individual researchers and practitioners and the field of ES. Although interoperability comes with many challenges, including greater scientific coordination than today’s status quo, it is technically achievable and offers potentially transformative advantages to ES assessments needed to mainstream their use by decision makers. Individuals and organizations active in ES research and practice can play critical roles in creating widespread interoperability and reusability of ES science. A representative community of practice targeting interoperability for ES would help advance these goals.

Ecosystem Services↗