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Climate Change Exposure Temperature - Anomalies, Deltas, Trends. These data are provided by Bureau of Land Management (BLM) "as is" and may contain errors or omissions. The User assumes the entire risk associated with its use of these data and bears all responsibility in determining whether these data are fit for the User's intended use. These data may not have the accuracy, resolution, completeness, timeliness, or other characteristics appropriate for applications that potential users of the data may contemplate. The User is encouraged to carefully consider the content of the metadata file associated with these data. The BLM should be cited as the data source in any products derived from these data.
This part of DS 781 presents data for the acoustic-backscatter map of Offshore of Santa Cruz map area, California. Backscatter data are provided as a raster file included in "Backscatter_Swath_OffshoreSantaCruz.zip," which is accessible from https://doi.org/10.5066/F7TM785G. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Erdey, M.D., Golden, N.E., Greene, H.G., Dieter, B.E., Hartwell, S.R., Ritchie, A.C., Finlayson, D.P., Endris, C.A., Watt, J.T., Davenport, C.W., Sliter, R.W., Maier, K.L., and Krigsman, L.M. (G.R. Cochrane and S.A. Cochran, eds.), 2016, California State Waters Map Series—Offshore of Santa Cruz, California: U.S. Geological Survey Open-File Report...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Acoustic Reflectivity,
Backscatter,
Bathymetry,
CMHRP,
Coastal and Marine Hazards and Resources Program,
This part of DS 781 presents data for the habitat map of the seafloor of the Offshore of Santa Cruz map area, California. The vector data file is included in "Habitat_OffshoreSantaCruz.zip," which is accessible from https://doi.org/10.5066/F7TM785G. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Erdey, M.D., Golden, N.E., Greene, H.G., Dieter, B.E., Hartwell, S.R., Ritchie, A.C., Finlayson, D.P., Endris, C.A., Watt, J.T., Davenport, C.W., Sliter, R.W., Maier, K.L., and Krigsman, L.M. (G.R. Cochrane and S.A. Cochran, eds.), 2016, California State Waters Map Series—Offshore of Santa Cruz, California: U.S. Geological Survey Open-File Report 2016-1024, pamphlet 40 p.,...
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: CMHRP,
Coastal and Marine Hazards and Resources Program,
Continental/Island Shelf,
Fisheries,
Marine Nearshore Subtidal,
This part of DS 781 presents data for the acoustic-backscatter map of Offshore of Scott Creek map area, California. Backscatter data are provided as three separate grids depending on mapping system. The raster data files are included in "BackscatterA_8101_OffshoreScottCreek.zip," which is accessible from https://doi.org/10.5066/F7CJ8BJW. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Watt, J.T., Krigsman, L.M., Ritchie, A.C., Sliter, R.W., Finlayson, D.P., and Maier, K.L. (G.R. Cochrane and S.A. Cochran, eds.), 2015, California State Waters Map Series--Offshore...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Acoustic Reflectivity,
Backscatter,
CMHRP,
Coastal and Marine Hazards and Resources Program,
Continental/Island Shelf,
This is the collection of raw data was collected during MBM-AK TLSA annual molting goose surveys. Partial quality control has been completed for these data: following each survey, the observer listened to their survey recording that documented counts along transects and then transcribed these findings into these raw datasets (‘raw_data’). The observer listened to their recording a second time in order to confirm that their transcriptions were correct. Further quality control and tidying was completed for these raw data using R scripts noted by the file extension ‘.Rmd’ located in the ‘GitHub_Annual_Report_Code’ folder. Ultimately, these scripts produced final datasets (‘final_data’) containing data used in annual...
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: ALPINE/TUNDRA,
ANIMALS/VERTEBRATES,
ARCTIC TUNDRA,
BIOLOGICAL CLASSIFICATION,
BIOLOGICAL RECORDS,
Standing dead trees, or snags, are an important habitat element in any forested system, and provide diurnal or seasonal shelter for many LCC priority species. The ISA landscape endpoint for snag density in upland hardwood woodland and forest systems targets one large (≥16” dbh) snag for every five acres of forest (or approximately ~0.2 large snags/acre), reflected by cavity-roosting habitat needs of the silver-haired bat (Lasionycteris noctivagans) and ample other avian, and mammalian species that require cavities in snags to carry out their life history. We used USFS imputed density of large (>16” dbh) snags data (USDA Forest Service Remote Sensing Applications Center, personal communication) extracted through...
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: BIOSPHERE,
BIOSPHERE,
Conservation planning,
Data,
EARTH SCIENCE,
The Gulf Coastal Plains and Ozarks (GCPO) region is, to a large extent, defined by its mainstem big rivers, with eight of the largest ten rivers (by discharge) in the lower U.S. terminating here. Those rivers are the Mississippi, Ohio, Missouri, Tennessee, Mobile, Atchafalaya, Red, and Arkansas. Whilethis assessment focuses on rivers of the MAV, the analysis has also been extended to big rivers throughout the GCPO.People have historically altered large river systems through the construction of levees and floodways, channelization, and dredging to support agriculture, navigation, commerce, and to provide greater stability and protection from flooding. Many large rivers in the GCPO are, in fact, part of theinland...
R code that takes in the nest capture history data (chdata.csv), reformats it for model fitting in Program Mark via the R package RMark. A series of models of increasing complexity are fit and compared using AIC. Output is written to text files for each model but is generally not used or saved. Code can be run to generate model results and R workspaces/ object to inspect parameter estimates. The primary purpose of this code is to explore model structures for predicting detection and as an attempt to reproduce historically used parameter estimates in past nest plot reports (e.g., Fischer et al. 2017 and earlier). Results from ‘Model 7’ are most similar to detection estimates used in the past.
Categories: Data,
Software;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: ANIMALS/VERTEBRATES,
ANIMALS/VERTEBRATES,
ANIMALS/VERTEBRATES,
BIOLOGICAL CLASSIFICATION,
BIOLOGICAL CLASSIFICATION,
These are the observer names, observer initials, year, and unique observer number for all observe that collected data on the YKD nest plot project from 1985 to 2019. This data is used with the nest card data to in various ways, but primarily to calculate cumulative observer experience for nest detection rates. This file is also used for quality control and reconciling non-unique observer initials across years.
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: ANIMALS/VERTEBRATES,
ANIMALS/VERTEBRATES,
ANIMALS/VERTEBRATES,
ANIMALS/VERTEBRATES,
ANIMALS/VERTEBRATES,
This R code (YKDsalinity_QC.R) is used to process the raw legacy salinity data for fixed and random plots (2006 - 2019) and produce the quality controlled legacy salinity data for analysis and sharing (YKDsalinity_QC.csv). Basic operations include transforming missing value to a common code, transforming other variables to match the data dictionary, and cleaning spatial location issues. Of special note is that this QC process discover significant error in location data due to a variety of reasons so the random plot centers are added to the data table and should be used for analysis. The code requires the raw data (“Official_YKD.SALINITY.DATA.MASTER.2020.csv”), a definition of the nest plot study area (“NestPlotStudyAreaBoundary.geojson”),...
Categories: Data,
Software;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: BIOSPHERE,
BIOSPHERE,
BIOSPHERE,
DATA INTEROPERABILITY,
DATA INTEROPERABILITY,
This is the YKD egg observation data reformatted from the nest card data (‘Nest_Cards_1985_2019_QC.csv’). The file eggs.R is used to produce this data set, and then this is further summarized into yearly stats on mean initiation and hatch dates to produce the file yearstats.csv.
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: ANIMALS/VERTEBRATES,
ANIMALS/VERTEBRATES,
ANIMALS/VERTEBRATES,
ANIMALS/VERTEBRATES,
ANIMALS/VERTEBRATES,
From 1995 to 1999, a subset of nest plots were searched twice by field crews to estimate nest detection probability by mark-recapture methods. Over the five years, 30 plots were searched twice and over 2700 unique nests were found. From these data, nest detection probability is estimated using a Huggins-type mark recapture model where individual-level covariate effects of nest and observer attributes were estimated. These estimates are then used to predict nest detection rates in other years based on covariates of nests and observers. Nest detection rates are then applied to annual plot search to estimate nest populations for each species in the sampled area.
Categories: Data,
Project;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: ANIMALS/VERTEBRATES,
ANIMALS/VERTEBRATES,
ANIMALS/VERTEBRATES,
ANIMALS/VERTEBRATES,
ANIMALS/VERTEBRATES,
The World Terrestrial Ecosystems datalayer is a global raster dataset at a 250 m spatial resolution where 431 ecosystem types are identified and mapped. Each ecosystem type is a unique combination of vegetation/land cover, climate region, and landform. The data is available as attached file "USGSEsriTNCWorldTerrestrialEcosystems2020.mpkx" at https://doi.org/10.5066/P9DO61LP. The data are distributed in Esri map package format (USGSEsriTNCWorldTerrestrialEcosystems2020.mpkx) and can be used by any software that can process this format, sometimes requiring minor format adjustments. NOTE: This global dataset replaces the Terrestrial Ecosystems of the Conterminous United States, NGDAID4, https://data.usgs.gov/datacatalog/data/USGS:94fd91d2-5197-4950-b14a-2381c0f66ff1
Nitrogen deposition is altering forest dynamics, terrestrial carbon storage, and biodiversity. However, our ability to forecast how different tree species will respond to N deposition, especially key response thresholds, is limited by a lack of synthesis across spatial scales and research approaches. To develop our best understanding of N deposition impact on tree growth and survival, we will integrate plot-‐ level studies describing plant growth and survival responses to N inputs and plant-‐ available soil nutrients with a continental scale analysis across a N deposition gradient. Our primary outcome will be estimates of tree response to N deposition with explicit representation of uncertainty and the identification...
Sea-level rise and storms cause major changes on coastal landscapes, including shifts in elevation, ecosystem type (for example, dunes and tidal wetlands), soils, and plant communities. Because these changes can have impacts on human communities, the local economy, and ecosystems, understanding how, when, and why these changes occur can be important for informing policy and natural resource management decisions. However, much is still unknown in our understanding of and ability to forecast coastal landscape change, and many current modeling approaches do not include important feedbacks between the physical landscape and the species inhabiting it. Examples of these types of feedbacks include the rapid development...
Wind energy is poised for rapid growth over the next 2-3 decades yet fatalities to birds and bats is a leading concern that may constrain wind energy development in the US. This working group will integrate wind energy forecasting models with bat ecological models and management policy considerations to transform our ability to understand and manage renewable energy development while minimizing unintended consequences to wildlife and habitat. The key activities include: 1. Simulate tiered wind energy deployment constraints representing impact mitigation to assess effects to both species’ habitat and wind energy development; 2. integrate wind energy forecast simulations and bat demographic models to elucidate the...
Despite the proven efficacy of geothermal energy as a city-scale heating and cooling resource, the relative newness of most city-scale applications using diverse technologies has resulted in limited widespread adoption. We aim to develop authoritative information suitable for city-managers and other decision-makers. Geothermal resources are ubiquitous and diverse, with technologies available both for harvesting ambient heat or for storing thermal energy. These local low-carbon, baseload energy sources provide resilience, security, and jobs. The project team proposes to accelerate understanding and possibly energy-solution adoption by developing an international systematic nomenclature to describe the range of...
These data represent habitat selection of greater sage-grouse at the 50 day mark of their brood rearing process. Sage-grouse and their broods were monitored on their own individual time lines, so one group's 50th day may not necessarily be the same as any other bird's 50th day.
The Gulf Coast Vulnerability Assessment (GCVA) used an expert opinion approach to qualitatively assess the vulnerability of four ecosystems: mangrove, oyster reef, tidal emergent marsh, and barrier islands, and a suite of wildlife species that depend on them. More than 50 individuals participated in the completion of the GCVA, facilitated via Ecosystem and Species Expert Teams. The GCVA made use of the Standardized Index of Vulnerability and Value Assessment (SIVVA) (Reece and Noss 2014) to provide an objective framework for evaluating vulnerability by guiding assessors through a series of questions related to the changes an ecosystem or species might experience due to climate change and other threats. Assessors...
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Alabama,
BARRIER ISLANDS,
BIOSPHERE,
BIOSPHERE,
Barrier Islands,
This dataset was developed as part of the Designing Sustainble Landscapes project led by Professor Kevin McGarigal of UMass Amherst and sponsored by the North Atlantic Landscape Conservation Cooperative (https://www.fws.gov/science/catalog); for more information about the entire project see: http://www.umass.edu/landeco/research/dsl/dsl.htmlThis dataset was last updated 02/2017. The revised version incorporates the addition of a simplified version of The Nature Conservancy's Northeast lakes and ponds classification, visit https://www.conservationgateway.org/ConservationByGeography/NorthAmerica/UnitedStates/edc/reportsdata/freshwater/Pages/Northeast-Lakes.aspx for more details.This dataset represents terrestrial...
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Citation,
Downloadable,
Map Service;
Tags: 2010,
2010,
DSL,
DSL,
Data,
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