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This dataset consists of the current distribution (2000s) of mangrove forests in the southeastern U.S. This dataset was created from the current best available mangrove data on a state specific basis. Florida mangrove data was extracted from Florida Landuse Land Cover Classification System (FLUCCS). For Louisiana, we used observations of mangrove stands from aerial surveys by Michot et al. (2010). Mangrove presence in Texas came from maps produced by Sherrod & McMillan (1981) and the NOAA Benthic Habitat Atlas of Coastal Texas (Finkbeiner et al. 2009). Please note that this map depicts the distribution of mangrove forests and not mangrove individuals. More detailed information on this dataset is available in Osland...
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Coastal vegetation of South Florida typically comprises salinity-tolerant mangroves bordering salinity-intolerant hardwood hammocks and fresh water marshes. Two primary ecological factors appear to influence the maintenance of mangrove/hammock ecotones against changes that might occur due to disturbances. One of these is a gradient in one or more environmental factors. The other is the action of positive feedback mechanisms, in which each vegetation community influences its local environment to favor itself, reinforcing the boundary between communities. The relative contributions of these two factors, however, can be hard to discern. A spatially explicit individual-based model of vegetation, coupled with a model...
Categories: Publication; Types: Citation; Tags: Landscape Ecology
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Free water is considered important to wildlife in arid regions. In the western United States, thousands of water developments have been built to benefit wildlife in arid landscapes. Agencies and researchers have yet to clearly demonstrate their effectiveness. We combined a spatial analysis of summer chukar (Alectoris chukar) covey locations with dietary composition analysis in western Utah. Our specific objectives were to determine if chukars showed a spatial pattern that suggested association with free water in four study areas and to document summer dietary moisture content in relation to average distance from water. The observed data for the Cedar Mountains study area fell within the middle of the random mean...
Categories: Publication; Types: Citation; Tags: Landscape Ecology
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This service definition contains landscape factors representing human disturbances summarized to local and network catchments of river reaches for the Ohio River Basin Fish Habitat Partnership. This dataset is the result of clipping the feature class 'NFHAP 2010 HCI Scores and Human Disturbance Data for the Conterminous United States linked to NHDPLUSV1.gdb' to the boundary of the Ohio River Basin Fish Habitat Partnership. Landscape factors include land uses, population density, roads, dams, mines, and point-source pollution sites. The source datasets that were compiled and attributed to catchments were identified as being: (1) meaningful for assessing fish habitat; (2) consistent across the entire study area in...
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This service definition contains landscape factors representing human disturbances summarized to local and network catchments of river reaches for the state of Montana. This dataset is the result of clipping the feature class 'NFHAP 2010 HCI Scores and Human Disturbance Data for the Conterminous United States linked to NHDPLUSV1.gdb' to the state boundary of Montana. Landscape factors include land uses, population density, roads, dams, mines, and point-source pollution sites. The source datasets that were compiled and attributed to catchments were identified as being: (1) meaningful for assessing fish habitat; (2) consistent across the entire study area in the way that they were assembled; (3) representative of...
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This service definition contains landscape factors representing human disturbances summarized to local and network catchments of river reaches for the state of New York. This dataset is the result of clipping the feature class 'NFHAP 2010 HCI Scores and Human Disturbance Data for the Conterminous United States linked to NHDPLUSV1.gdb' to the state boundary of New York. Landscape factors include land uses, population density, roads, dams, mines, and point-source pollution sites. The source datasets that were compiled and attributed to catchments were identified as being: (1) meaningful for assessing fish habitat; (2) consistent across the entire study area in the way that they were assembled; (3) representative of...
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This service definition contains landscape factors representing human disturbances summarized to local and network catchments of river reaches for the state of Ohio. This dataset is the result of clipping the feature class 'NFHAP 2010 HCI Scores and Human Disturbance Data for the Conterminous United States linked to NHDPLUSV1.gdb' to the state boundary of Ohio. Landscape factors include land uses, population density, roads, dams, mines, and point-source pollution sites. The source datasets that were compiled and attributed to catchments were identified as being: (1) meaningful for assessing fish habitat; (2) consistent across the entire study area in the way that they were assembled; (3) representative of conditions...
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This service definition contains landscape factors representing human disturbances summarized to local and network catchments of river reaches for the state of Tennessee. This dataset is the result of clipping the feature class 'NFHAP 2010 HCI Scores and Human Disturbance Data for the Conterminous United States linked to NHDPLUSV1.gdb' to the state boundary of Tennessee. Landscape factors include land uses, population density, roads, dams, mines, and point-source pollution sites. The source datasets that were compiled and attributed to catchments were identified as being: (1) meaningful for assessing fish habitat; (2) consistent across the entire study area in the way that they were assembled; (3) representative...
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This shapefile contains landscape factors representing human disturbances summarized to local and network catchments of river reaches for the state of South Dakota. This dataset is the result of clipping the feature class 'NFHAP 2010 HCI Scores and Human Disturbance Data for the Conterminous United States linked to NHDPLUSV1.gdb' to the state boundary of South Dakota. Landscape factors include land uses, population density, roads, dams, mines, and point-source pollution sites. The source datasets that were compiled and attributed to catchments were identified as being: (1) meaningful for assessing fish habitat; (2) consistent across the entire study area in the way that they were assembled; (3) representative of...
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These data consist of species relative cover, percent cover of dead plant material, percent cover of soil and rock, and a variety of broad - and local- scale environmental variables. These data relate to sample sites along the Colorado River through Grand Canyon between Lees Ferry and river mile 245. The plant and ground cover data included here were originally collected as a part of annual vegetation monitoring by Grand Canyon Monitoring and Research Center. Environmental variables were either recorded in the field or obtained through other data sources. Species and ground cover data were collected in August and September 2014 at 96 randomly selected sample sites that were approximately evenly distributed along...
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These raster datasets represent historical stand age. The last four digits of the file name specifies the year represented by the raster. For example a file named Age_years_historical_1990.tif represents the year 1990. Cell values represent the age of vegetation in years since last fire, with zero (0) indicating burned area in that year. Files from years 1860-2006 use a variety of historical datasets for Boreal ALFRESCO model spin up and calibration to most closely match historical wildfire dynamics.
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This shapefile contains landscape factors representing human disturbances summarized to local and network catchments of river reaches for the state of Georgia. This dataset is the result of clipping the feature class 'NFHAP 2010 HCI Scores and Human Disturbance Data for the Conterminous United States linked to NHDPLUSV1.gdb' to the state boundary of Georgia. Landscape factors include land uses, population density, roads, dams, mines, and point-source pollution sites. The source datasets that were compiled and attributed to catchments were identified as being: (1) meaningful for assessing fish habitat; (2) consistent across the entire study area in the way that they were assembled; (3) representative of conditions...
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This shapefile contains landscape factors representing human disturbances summarized to local and network catchments of river reaches for the state of Louisiana. This dataset is the result of clipping the feature class 'NFHAP 2010 HCI Scores and Human Disturbance Data for the Conterminous United States linked to NHDPLUSV1.gdb' to the state boundary of Louisiana. Landscape factors include land uses, population density, roads, dams, mines, and point-source pollution sites. The source datasets that were compiled and attributed to catchments were identified as being: (1) meaningful for assessing fish habitat; (2) consistent across the entire study area in the way that they were assembled; (3) representative of conditions...
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These raster datasets represent historical stand age. The last four digits of the file name specifies the year represented by the raster. For example a file named Age_years_historical_1990.tif represents the year 1990. Cell values represent the age of vegetation in years since last fire, with zero (0) indicating burned area in that year. Files from years 1860-2006 use a variety of historical datasets for Boreal ALFRESCO model spin up and calibration to most closely match historical wildfire dynamics.
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Over the past 50 years, the number and size of high-latitude lakes have decreased throughout many regions; however, individual lake trends have been variable in direction and magnitude. This spatial heterogeneity in lake change makes statistical detection of temporal trends challenging, particularly in small analysis areas where weak trends are difficult to separate from inter- and intra-annual variability. Factors affecting trend detection include inherent variability, trend magnitude, and sample size. In this paper, we investigated how the statistical power to detect average linear trends in lake size of 0.5, 1.0 and 2.0 %/year was affected by the size of the analysis area and the number of years of monitoring...
Categories: Publication; Types: Citation; Tags: Landscape Ecology
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This shapefile contains landscape factors representing human disturbances summarized to local and network catchments of river reaches for the Desert Fish Habitat Partnership. This dataset is the result of clipping the feature class 'NFHAP 2010 HCI Scores and Human Disturbance Data for the Conterminous United States linked to NHDPLUSV1.gdb' to the boundary of the Desert Fish Habitat Partnership. Landscape factors include land uses, population density, roads, dams, mines, and point-source pollution sites. The source datasets that were compiled and attributed to catchments were identified as being: (1) meaningful for assessing fish habitat; (2) consistent across the entire study area in the way that they were assembled;...
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This shapefile contains sub-indices comprised of various anthropogenic land use/covers respresentative of the risk of potential habitat degradation to streams within the state of Hawaii. This file is an updated version of 'nfhap_hci_hawaii.shp' and incorporates the suggestion from the Hawaii Fish Habitat Partnership of removing trails and paths from the road network to help better represent amounts of disturbance in remote areas such as the Na Pali coast. Subindices are summarized for local and network catchments specific to perennial stream reaches throughout the state. The local and network catchments were developed using a modified version of the 1:24,000 scale National Hydrography Dataset (NHD) as a baselayer....
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These raster datasets represent historical stand age. The last four digits of the file name specifies the year represented by the raster. For example a file named Age_years_historical_1990.tif represents the year 1990. Cell values represent the age of vegetation in years since last fire, with zero (0) indicating burned area in that year. Files from years 1860-2006 use a variety of historical datasets for Boreal ALFRESCO model spin up and calibration to most closely match historical wildfire dynamics.
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This pilot project has initiated a long-term integrated modeling project that aims todevelop a dynamically linked model framework focused on climate driven changes tovegetation, disturbance, hydrology, and permafrost, and their interactions and feedbacks.This pilot phase has developed a conceptual framework for linking current state-of-thesciencemodels of ecosystem processes in Alaska – ALFRESCO, TEM, GIPL-1 – and theprimary processes of vegetation, disturbance, hydrology, and permafrost that theysimulate. A framework that dynamically links these models has been defined and primaryinput datasets required by the models have been developed.


map background search result map search result map National Fish Habitat Action Plan (NFHAP) 2010 HCI Scores and Human Disturbance Data (linked to NHDPLUSV1) for Desert Fish Habitat Partnership South Dakota: NFHAP 2010 HCI Scores and Disturbances Georgia: NFHAP 2010 HCI Scores and Disturbances Louisiana: NFHAP 2010 HCI Scores and Disturbances National Fish Habitat Partnership (NFHP) 2010 HCI Scores and Human Disturbance Data for Hawaii Linked to NFHAP Catchments (developed using the 1:24,000 scale National Hydrography Dataset) VERSION 2.0 Spatial heterogeneity in statistical power to detect changes in lake area in Alaskan National Wildlife Refuges National Fish Habitat Action Plan (NFHAP) 2010 HCI Scores and Human Disturbance Data (linked to NHDPLUSV1) for Montana: ESRI Service Definition National Fish Habitat Action Plan (NFHAP) 2010 HCI Scores and Human Disturbance Data (linked to NHDPLUSV1) for New York: ESRI Service Definition National Fish Habitat Action Plan (NFHAP) 2010 HCI Scores and Human Disturbance Data (linked to NHDPLUSV1) for Ohio: ESRI Service Definition National Fish Habitat Action Plan (NFHAP) 2010 HCI Scores and Human Disturbance Data (linked to NHDPLUSV1) for Tennessee: ESRI Service Definition National Fish Habitat Action Plan (NFHAP) 2010 HCI Scores and Human Disturbance Data (linked to NHDPLUSV1) for Ohio River Basin Fish Habitat Partnership: ESRI Service Definition Riparian Vegetation and Environmental Variables, Colorado River, 2014—Data Alaska Integrated Ecosystem Model Pilot Year Final Report Historical Stand Age 1870-1879 Historical Stand Age 1900-1909 Historical Stand Age 1910-1919 Riparian Vegetation and Environmental Variables, Colorado River, 2014—Data National Fish Habitat Action Plan (NFHAP) 2010 HCI Scores and Human Disturbance Data (linked to NHDPLUSV1) for Tennessee: ESRI Service Definition National Fish Habitat Action Plan (NFHAP) 2010 HCI Scores and Human Disturbance Data (linked to NHDPLUSV1) for Ohio: ESRI Service Definition National Fish Habitat Partnership (NFHP) 2010 HCI Scores and Human Disturbance Data for Hawaii Linked to NFHAP Catchments (developed using the 1:24,000 scale National Hydrography Dataset) VERSION 2.0 Louisiana: NFHAP 2010 HCI Scores and Disturbances Georgia: NFHAP 2010 HCI Scores and Disturbances South Dakota: NFHAP 2010 HCI Scores and Disturbances National Fish Habitat Action Plan (NFHAP) 2010 HCI Scores and Human Disturbance Data (linked to NHDPLUSV1) for New York: ESRI Service Definition National Fish Habitat Action Plan (NFHAP) 2010 HCI Scores and Human Disturbance Data (linked to NHDPLUSV1) for Montana: ESRI Service Definition National Fish Habitat Action Plan (NFHAP) 2010 HCI Scores and Human Disturbance Data (linked to NHDPLUSV1) for Ohio River Basin Fish Habitat Partnership: ESRI Service Definition National Fish Habitat Action Plan (NFHAP) 2010 HCI Scores and Human Disturbance Data (linked to NHDPLUSV1) for Desert Fish Habitat Partnership Alaska Integrated Ecosystem Model Pilot Year Final Report Historical Stand Age 1870-1879 Historical Stand Age 1900-1909 Historical Stand Age 1910-1919 Spatial heterogeneity in statistical power to detect changes in lake area in Alaskan National Wildlife Refuges