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1) Raw parcel-level habitat data for the South Carolina Lowcountry surrounding Cape Romain NWR and Francis Marion NF, from current current conditions and for three projected sea-level rise futures based on SLAMM model outputs, NLCD land cover and the projected distribution of sea levels for 2050. 2) a table of parcel identification numbers (without georeference) with parcel size (Ha) and sub-group identity. 3) Optimization-model derived reserve design portfolios that define the Pareto-optimal frontier for each sub-group and for four budget scenarios along axes of reserve design benefits and risk.
This capacity-building activity supported three tribal college and university (TCU) mini-­grants to initiate student phenological and meteorological observation projects in support of climate change research, to document impacts of climate change and development of indigenous geography curriculum. Students made observations of culturally and/or traditionally significant plants to generate data sets for use in climate change impact assessment of these plants and plant communities. The activity contributed to the larger national efforts of the Smithsonian National Museum of the American Indian’s “Indigenous Geography” curricula, by engaging with students at tribal colleges to explore the linkage between the “seasonality”...
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This landcover raster was generated through a Random Forest predictive model developed in R using a combination of image-derived and ancillary variables, and field-derived training points grouped into 18 classes. Overall accuracy, generated internally through bootstrapping, was 75.5%. A series of post-modeling steps brought the final number of land cover classes to 28.
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Training points collected in the field between 2012 and 2013 were grouped into 18 classes: Forested Burn (66), Foothill Woodland Steppe Transition (73), Greasewood Flat (73), Greasewood Steppe (239), Greasewood Sage Steppe (277), Great Plains Badlands (166), Great Plains Riparian (255), Low Density Sage Steppe (776), Medium Density Sage Steppe (783), Mixed Grass Prairie (555), Mixed Grass Prairie Burned (278), Ponderosa Pine Woodland and Shrubland (512), Riparian Floodplain (223), Semi-Desert Grassland (103), Sparsely Vegetated Mixed Shrub (252), Silver Sage Flat (70) , Silver Sage Steppe (64), and Water (246). When insufficient field data were available for a class, we augmented it through photointerpretation of...
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These datasets contain time series of anomalies, relative to 1950-1999 period, in the annual and seasonal soil moisture (%) and runoff (%) in the Pinyon-Juniper ecosystem of Southwest Colorado for the three future climate scenarios considered in the Social Ecological and Climate Resiliency (SECR) project.
(1) This written report summarizes and synthesizes results of literature review, interviews, and workshops, providing the scientific basis for and extension strategies for the management recommendations provided in the "green website" [Data Input New Collection]. The report includes an addendum regarding reference bibliographies and a references list with citations. (2) Selected, unusual references that are not readily available online or through standard academic sources were collected by the project. (3) Selected photographs are retained by the project in electronic form.
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Publicly accessible open spaces provide valuable opportunities for people to exercise, play, socialize, and build community. People are more likely to use public open spaces that are close (ideally within walking distance) to their homes, and larger open spaces often provide more amenities. To assess the potential benefit of creating new open space in the southeast US, we identified areas without access to open space within a certain distance category (in this case, 0.5 miles). Then, for each 30-meter pixel in the study area, we then totaled the number of people within 0.5 miles who do not currently have access to open space within that distance. This represents the number of people who would benefit from new open...
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Publicly accessible open spaces provide valuable opportunities for people to exercise, play, socialize, and build community. People are more likely to use public open spaces that are close (ideally within walking distance) to their homes. To assess the spatial distribution of access to open space for recreation in the southeastern United States, we constructed an index of open space access based on the size of the largest publicly accessible open space within 10 miles of each point on the landscape, using three distance categories to represent whether people can reach the open spaces by walking (within 0.5 mile), via a short drive (within 3 miles), or via a longer drive (within 10 miles). Using the open space access...
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Wild insect pollination has significant positive effects on pollinator-dependent crop production. To assess the spatial distribution of demand for wild insect pollination, we mapped pollinator-dependent crops based on the 2011Cropland Data Layer.
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UW_Olallie_photo_metadata & image files: These are the raw timelapse photographs. The date/time stamp is inaccurate for the camera deployed in the open (at the SNOTEL) due to a programming error. This timestamp is one day early (i.e., subtract 1 day from the timestamp when using these data). Also available is metadata for two timelapse cameras and their associated snow depth poles (two visible in each camera's field of view) deployed at Olallie Meadows SNOTEL during water year 2015. One camera was deployed in the open area that is the Olallie Meadows SNOTEL station (the snow pillow is in the field of view). The other camera was deployed in the adjacent forest, approximately 60 m to the southeast of the SNOTEL....
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Data points intensively sampling 46 North American biomes were used to predict the geographic distribution of biomes from climate variables using the Random Forests classification tree. Techniques were incorporated to accommodate a large number of classes and to predict the future occurrence of climates beyond the contemporary climatic range of the biomes. Errors of prediction from the statistical model averaged 3.7%, but for individual biomes, ranged from 0% to 21.5%. In validating the ability of the model to identify climates without analogs, 78% of 1528 locations outside North America and 81% of land area of the Caribbean Islands were predicted to have no analogs among the 46 biomes. Biome climates were projected...
This dataset is a continuous parameter grid (CPG) of normal (average) annual precipitation data for the years 1981 through 2010 in the Pacific Northwest. Source precipitation data was produced by the PRISM Climate Group at Oregon State University.
These datasets are continuous parameter grids (CPG) of permeability (and impermeability) of surface geology in the Pacific Northwest. Source data come from work by Chris Konrad, U.S. Geological Survey (USGS), and geologic map databases produced by USGS scientists.
We mosaicked twelve LandSat-8 OLI satellite images taken during the summer of 2014, which were used in an object based image analysis (OBIA) to classify the landscape. We mapped seventeen of the most dominant geomorphic land cover classes on the Alaskan Coastal Plain (ACP): **value** | **class name** 1 | Coastal saline waters 2 | Large lakes 3 | Medium lakes 4 | Small lakes 5 | Ponds 6 | Rivers 7 | Nonpatterned Drained Thaw Lake Basins 8 | Coalescent low-center polygons 9 | Low-center polygons 10 | Flat-center polygons 11 | High-center polygons 12 | Drained slope 13 | Sandy barrens 14 | Sand dunes 15 | Riparian corridors 16 | Ice 17 | Urban (i.e. towns and roads)
The aim of this project is to facilitate expansion of current data management protocols to accommodate social science data for the USGS National Climate Change and Wildlife Science Center (NCCWSC) and its regional Climate Science Centers (CSCs). To address this expansion, we (1) identified the best practices and approaches from practitioners/experts through interviews with current curators of social science data, (2) explored the approaches of existing tools and services to determine if they are capable of meeting the needs of the NCCWSC, and (3) conducted a survey of the specific user community, with a focus on social science researchers funded by the NCCWSC and managers of the data within the program. The dataset...
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Information about these images can be found in the Final Report for Sea-level Rise Response Modeling for San Francisco Bay Estuary Tidal Marshes. Site-specific data are available by request. Contact: Dr. John Y. Takekawa, USGS Western Ecological Research Center, San Francisco Bay Estuary Field Station, 505 Azuar Dr. Vallejo, Calif. 94592, 707-562-2000
Projected suitable habitat models were constructed in randomForest (R package, version 4.6-10) using a set of presence points for the species derived from element occurrence and herbarium records, together with temperature, precipitation, and soil variables. The current distribution used modeled historic period (1970-2000) climate variables from the appropriate matching GCM model run. These model parameters were then used with projected climate data to get future (2020-2050) modeled suitable habitat for each scenario. Modeled past suitable habitat and modeled future suitable habitat are combined to show areas of change, using various thresholds to distinguish change categories, as well as current mapped pinyon occupied...
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The purpose of this study was to understand how the U.S. Department of Interior’s federal land and resource managers and their stakeholders (i.e., NPS, BLM, FWS, BOR, BIA and tribes, among others) are experiencing and dealing with drought in their landscapes. The database is part of the Drought Risk and Adaptation in the Interior project. We conducted in-depth interviews (n=41) with DOI and tribal land managers in three case sites across the north central United States (northwest Colorado, southwest South Dakota, and Wind River Reservation), the goal of which was to develop a better understanding of drought vulnerabilities, risks, and responses in high-risk, multi-jurisdictional landscapes across the Missouri River...
map background search result map search result map Timelapse photos at SNOTEL station, locations, and associated metadata, Ollalie Meadows, Wash., 2015 North American vegetation model data for land-use planning in a changing climate: Charles M. Russell National Wildlife Refuge Spot Landcover Classification in Relation to Greater Sage Grouse Training Points Water Balance and Habitat Suitability Data for Pinus Albicaulis in Greater Yellowstone Ecosystem Drought Risk and Adaptation in the Interior (DRAI) Database of Interviews with DOI/Tribal land managers in northwest Colorado, southwest South Dakota, and Wind River Reservation in Wyoming, 2013-2016 Time Series of the Anomalies in Soil Moisture and Runoff Between 1950-2099 for the Pinyon-Juniper Ecosystem of Southwest Colorado Under Three Future Climate Scenarios Streamflow Permanence Probability rasters, 2004-2011, Version 2.0 (PROSPER) Pollinator-Dependent Crops in the Southeast United States (2011) Conservation Priorities for Open Space Recreation Access in the Southeast United States, by Census Block Group (2018) Timelapse photos at SNOTEL station, locations, and associated metadata, Ollalie Meadows, Wash., 2015 Time Series of the Anomalies in Soil Moisture and Runoff Between 1950-2099 for the Pinyon-Juniper Ecosystem of Southwest Colorado Under Three Future Climate Scenarios Training Points Charles M. Russell National Wildlife Refuge Spot Landcover Classification in Relation to Greater Sage Grouse Water Balance and Habitat Suitability Data for Pinus Albicaulis in Greater Yellowstone Ecosystem North American vegetation model data for land-use planning in a changing climate: Streamflow Permanence Probability rasters, 2004-2011, Version 2.0 (PROSPER) Drought Risk and Adaptation in the Interior (DRAI) Database of Interviews with DOI/Tribal land managers in northwest Colorado, southwest South Dakota, and Wind River Reservation in Wyoming, 2013-2016 Pollinator-Dependent Crops in the Southeast United States (2011) Conservation Priorities for Open Space Recreation Access in the Southeast United States, by Census Block Group (2018)