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This indicator is a continuous index of dolphin and whale density based on monthly density predictions for ten species of cetaceans and yearly density predictions for three rarer cetacean species. Note: This indicator is at a 200 m resolution, which is coarser than other indicators used in the 2020 Blueprint.Reason for SelectionMarine mammals help identify key areas of ocean productivity and overall ocean health, are regularly monitored, and resonate with a variety of audiences. Marine mammals are often used as ocean health indicators due to their long life spans, feeding at a high trophic levels, and large blubber stores that can serve as repositories for anthropogenic chemicals and toxins (Bossart 2011).Input...
Categories: Data; Types: ArcGIS REST Map Service, ArcGIS Service Definition, Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: ANTHROPOGENIC/HUMAN INFLUENCED ECOSYSTEMS, ANTHROPOGENIC/HUMAN INFLUENCED ECOSYSTEMS, ANTHROPOGENIC/HUMAN INFLUENCED ECOSYSTEMS, BIOSPHERE, BIOSPHERE, All tags...
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Agreement in predicted fisher year-round distribution derived from future (2046-2065) climate projections and vegetation simulations using 2 GCMs: Hadley CM3 (Johns et al. 2003) and MIROC (Hasumi and Emori 2004) under the A2 emissions scenario (Naki?enovi? et al. 2000). Projected fisher distribution was created with Maxent (Phillips et al. 2006) using fisher detections (N = 102, spanning 1993 – 2011) and nine predictor variables: mean winter (January – March) precipitation, mean summer (July – September) precipitation, mean summer temperature amplitude, mean daily low temperature for the month of the year with the warmest mean daily low temperature, average number of months with mean temperature < 0°C, mean...
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Agreement in predicted marten year-round distribution derived from future (2076-2095) climate projections and vegetation simulations using 2 GCMs (Hadley CM3 (Johns et al. 2003) and MIROC (Hasumi and Emori 2004)) under the A2 emissions scenario (Naki?enovi? et al. 2000). Projected marten distribution was created with Maxent (Phillips et al. 2006) using marten detections (N = 302, spanning 1990 – 2011) and nine predictor variables: mean winter (January – March) precipitation, mean amount of snow on the ground in March, mean understory index (fraction of grass vegetation carbon in forest), mean fraction of total forest carbon in coarse wood carbon, average maximum tree LAI, mean fraction of vegetation carbon burned,...
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Predicted probability of fisher year-round occurrence derived from future (2076-2095) climate projections and vegetation simulations. Projected fisher distribution was created with Maxent (Phillips et al. 2006) using fisher detections (N = 302, spanning 1990 – 2011) and five predictor variables: mean annual precipitation, mean summer (July – September) precipitation, mean understory index (fraction of grass vegetation carbon in forest), mean forest carbon (g C m2), and mean fraction of vegetation carbon in forest. Future climate drivers were generated using statistical downscaling (simple delta method) of general circulation model projections, in this case CSIRO Mk3 (Gordon 2002) under the A2 emission scenario...
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Predicted probability of fisher year-round occurrence derived from future (2046-2065) climate projections and vegetation simulations. Projected fisher distribution was created with Maxent (Phillips et al. 2006) using fisher detections (N = 102, spanning 1993 – 2011) and nine predictor variables: mean winter (January – March) precipitation, mean summer (July – September) precipitation, mean summer temperature amplitude, mean daily low temperature for the month of the year with the warmest mean daily low temperature, average number of months with mean temperature < 0°C, mean understory index (fraction of grass vegetation carbon in forest), mean fraction of total forest carbon in coarse wood carbon, mean forest carbon...
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Future (2076-2095) predicted probability of fisher year-round occurrence projected under the A2 emissions scenario with the PCM1 GCM (Washington et al. 2000; Meehl et al. 2003). The projected fisher distribution was created with Maxent (Phillips et al. 2006) using fisher detections (N = 102, spanning 1993 – 2011) and seven predictor variables: mean winter (January – March) precipitation, mean summer (July – September) precipitation, mean summer temperature amplitude, mean daily low temperature for the month of the year with the warmest mean daily low temperature, mean fraction of vegetation carbon burned, mean vegetation carbon (g C m2), and modal vegetation class. Predictor variables had a grid cell size of 10...
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Future (2046-2065) predicted probability of fisher year-round occurrence projected under the A2 emissions scenario with the PCM1 GCM (Washington et al. 2000; Meehl et al. 2003). The projected fisher distribution was created with Maxent (Phillips et al. 2006) using fisher detections (N = 102, spanning 1993 – 2011) and seven predictor variables: mean winter (January – March) precipitation, mean summer (July – September) precipitation, mean summer temperature amplitude, mean daily low temperature for the month of the year with the warmest mean daily low temperature, mean fraction of vegetation carbon burned, mean vegetation carbon (g C m2), and modal vegetation class. Predictor variables had a grid cell size of 10...
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Description: Predicted probability of fisher year-round occurrence created with Maxent (Phillips et al. 2006) using fisher detections (N = 102, spanning 1993 – 2011) and seven predictor variables: mean winter (January – March) precipitation, mean summer (July – September) precipitation, mean summer temperature amplitude, mean daily low temperature for the month of the year with the warmest mean daily low temperature, mean fraction of vegetation carbon burned, mean vegetation carbon (g C m2), and modal vegetation class. Predictor variables had a grid cell size of 10 km, vegetation variables were simulated with MC1 (Lenihan et al. 2008) and climate variables were provided by the PRISM GROUP (Daly et al. 1994). This...
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In addition to current distribution of each mammal species, this map shows their current and near-term status within the ecoregion. Current, long-term, and summary bioclimate data is also include for several of these mammal species. The input datasets used in the distribution model are also included. 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...
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This dataset consists of polygon range maps for terrestrial vertebrate species in Alaska. The maps are shapefiles between 0 and 12 MB in size to be used in OpenGIS or ArcGIS on a PC. Individual species range maps were developed using the best available known range of the species (derived from a variety of available point data sources), overlaid with watershed-scale units (8-digit HUCs; standard map for U.S. GAP project) for the state of Alaska in the Alaska Albers NAD83 projection. These maps present the data in the form that they were created in, are subject to change, and are freely available from the the Alaska GAP project.
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Some of the SNK rasters intentionally do not align or have the same extent. These rasters were not snapped to a common raster per the authors' discretion. Please review selected rasters prior to use. These varying alignments are a result of the use of differing source data sets and all products derived from them. We recommend that users snap or align rasters as best suits their own projects. - This dataset consists of raster distribution maps for terrestrial vertebrate species in Alaska. Individual species distribution maps were developed using the best available known occurrence points for each species and modeled using MaxEnt software and a series of environmental predictor variables. Output maps were clipped...
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Some of the SNK rasters intentionally do not align or have the same extent. These rasters were not snapped to a common raster per the authors' discretion. Please review selected rasters prior to use. These varying alignments are a result of the use of differing source data sets and all products derived from them. We recommend that users snap or align rasters as best suits their own projects. - This dataset consists of raster distribution maps for terrestrial vertebrate species in Alaska. Individual species distribution maps were developed using the best available known occurrence points for each species and modeled using MaxEnt software and a series of environmental predictor variables. Output maps were clipped...
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In addition to current distribution of each mammal species, this map shows their current and near-term status within the ecoregion. Current, long-term, and summary bioclimate data is also include for several of these mammal species. The input datasets used in the distribution model are also included. 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...
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Solar development has the potential to have widespread impacts on the California desert. Thus, it is important to have as much information as possible regarding the impacts of facilities and related infrastructure on the natural ecosystem and surrounding desert communities, how current policies are influencing development, and how the federal process is working on evaluating solar development applications. This research is detailed in this website. "Renewable Energy in the California Desert: Mechanisms for Evaluating Solar Development on Public Lands" is the result of sixteen months of research conducted by ten graduate students from the University of Michigan School of Natural Resources and Environmen t through...
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Chihuahuan Desert landscapes exemplify the ecological conditions, vulnerability, and management challenges in arid and semi-arid regions around the world. The goal of the Jornada Basin Long Term Ecological Research program (JRN LTER) established in 1982 is to understand and quantify the key factors and processes controlling ecosystem dynamics and patterns in Chihuahuan Desert landscapes. In collaboration with the Jornada Experimental Range (USDA ARS), studies initiated in 1915 have been incorporated into the JRN LTER program. Previous research focused on desertification, a state change from perennial grasslands to woody plant dominance that occurs globally. Based on findings from growing long-term databases, the...
Types: Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: CMQ3, Chihuahuan Desert, DLCC, Desert LCC, English, All tags...
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The Central Arizona Grassland Conservation Strategy (CAGCS) was signed (2010) by three signatory agencies to the charter with complementary roles and responsibilities in managing historic grassland ecosystems and/or the wildlife species that inhabit them. The Bureau of Land Management (BLM) management emphasis within the Agua Fria National Monument (AFNM) is to conserve and restore diverse habitats, vegetative communities and corridors of connectivity to sustain a wide range of native species. The Arizona Game and Fish Department (AGFD) hold the public trust responsibility of managing the wildlife that inhabits these ecosystems. This includes but is not limited to gathering and managing wildlife data, and providing...
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Sky Island grasslands of central and southern Arizona, southern New Mexico and northern Mexico form the “grassland seas” that surround small forested mountain ranges in the borderlands. Their unique biogeographical setting and the ecological gradients associated with “Sky Island mountains” add tremendous floral and faunal diversity to these grasslands and the region as a whole. Sky Island grasslands have undergone dramatic vegetation changes over the last 130 years including encroachment by shrubs, loss of perennial grass cover and spread of non-native species. Changes in grassland composition and structure have not occurred uniformly across the region and they are dynamic and ongoing. In 2009, The National Fish...
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How well are we protecting common plants and animals? Gap Analysis is the science of answering this question. Developing the data and tools to support that science is the mission of the USGS Gap Analysis Program (GAP). GAP works to ensure that common species – those that are not officially endangered – remain common by identifying those species and plant communities that are not adequately represented in existing conservation lands. Learn more about Gap Analysis >> We work with a wide range of government, academic, non-profit and private partners, providing them with essential data and analyses that they can use to protect the habitats on which the survival of common species depends.
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Predicted probability of marten year-round occurrence derived from future (2076-2095) climate projections and vegetation simulations. Projected marten distribution was created with Maxent (Phillips et al. 2006) using marten detections (N = 102, spanning 1993 – 2011) and eight predictor variables: mean potential evapotranspiration, mean annual precipitation, mean fraction of vegetation carbon burned, mean forest carbon (g C m2), mean fraction of vegetation carbon in forest, understory index (fraction of grass vegetation carbon in forest), average maximum tree LAI, and modal vegetation class. Future climate drivers were generated using statistical downscaling (simple delta method) of general circulation model projections,...
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Predicted probability of fisher year-round occurrence derived from future (2076-2095) climate projections and vegetation simulations. Projected fisher distribution was created with Maxent (Phillips et al. 2006) using fisher detections (N = 302, spanning 1990 – 2011) and five predictor variables: mean annual precipitation, mean summer (July – September) precipitation, mean understory index (fraction of grass vegetation carbon in forest), mean forest carbon (g C m2), and mean fraction of vegetation carbon in forest. Future climate drivers were generated using statistical downscaling (simple delta method) of general circulation model projections, in this case MIROC 3.2 medres (Hasumi and Emori 2004) under the A2 emission...


map background search result map search result map Overlay of projected marten distributions, 2076-2095, 4 km resolution Overlay of projected fisher distributions, 2046-2065, 4 km resolution Predicted probability of marten year-round occurrence, 2076-2095, MIROC A2, 800 m resolution Predicted probability of fisher year-round occurrence, 2076-2095, MIROC A2, 800 m resolution Predicted probability of fisher year-round occurrence, 2076-2095, CSIRO Mk3 A2, 800 m resolution Predicted probability of fisher year-round occurrence, 2046-2065, Hadley CM3 A2, 4 km resolution Predicted probability of fisher year-round occurrence, 2076-2095, PCM1 A2, 10 km resolution Predicted probability of fisher year-round occurrence, 2046-2065, PCM1 A2, 10 km resolution Predicted probability of fisher year-round occurrence, 1986-2005, PCM1 A2, 10 km resolution Jornada Bibliography Renewable Energy in the California Desert Indicator: Marine Mammals Central Arizona Grassland Conservation Strategy National Gap Analysis Program (GAP) Sky Island Grassland Assessment BLM REA SNK 2010 Alaska Gap Analysis Project: Year Round Distribution Map for Alces americanus BLM REA SNK 2010 Alaska Gap Analysis Project: Seasonal range maps for Caribou BLM REA SNK 2010 Alaska Gap Analysis Project: Breeding Season Distribution Map for Plectrophenax hyperboreus BLM REA MBR 2010 Terrestrial Species Mammals Status - Bighorn Sheep BLM REA CBR 2010 Terrestrial Species Mammals Status - Big Brown Bat Jornada Bibliography Central Arizona Grassland Conservation Strategy Sky Island Grassland Assessment Renewable Energy in the California Desert BLM REA MBR 2010 Terrestrial Species Mammals Status - Bighorn Sheep BLM REA SNK 2010 Alaska Gap Analysis Project: Seasonal range maps for Caribou BLM REA SNK 2010 Alaska Gap Analysis Project: Breeding Season Distribution Map for Plectrophenax hyperboreus BLM REA SNK 2010 Alaska Gap Analysis Project: Year Round Distribution Map for Alces americanus Predicted probability of marten year-round occurrence, 2076-2095, MIROC A2, 800 m resolution Predicted probability of fisher year-round occurrence, 2076-2095, MIROC A2, 800 m resolution Predicted probability of fisher year-round occurrence, 2076-2095, CSIRO Mk3 A2, 800 m resolution Overlay of projected marten distributions, 2076-2095, 4 km resolution Overlay of projected fisher distributions, 2046-2065, 4 km resolution Predicted probability of fisher year-round occurrence, 2046-2065, Hadley CM3 A2, 4 km resolution Indicator: Marine Mammals Predicted probability of fisher year-round occurrence, 2076-2095, PCM1 A2, 10 km resolution Predicted probability of fisher year-round occurrence, 2046-2065, PCM1 A2, 10 km resolution Predicted probability of fisher year-round occurrence, 1986-2005, PCM1 A2, 10 km resolution BLM REA CBR 2010 Terrestrial Species Mammals Status - Big Brown Bat National Gap Analysis Program (GAP)