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The cumulative effects problem in natural resource management and land use planning stems from the difficulty of demonstrating that while each single land use change results in a negligible impact, the accumulation of these individual changes over time and within a landscape or region may constitute a major impact. This paper details a general approach to estimate the cumulative effects of land use change on wildlife habitat using Summit County, CO, USA as a case study. Our approach is based on a functional relationship between effect on habitat and distance from development. Within this building-effect distance, habitat is assumed to be degraded, producing a disturbance zone. We sum the total area within the disturbance...
Predicted probability of marten year-round occurrence derived from future (2046-2065) 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,...
Predicted probability of marten year-round occurrence derived from future (2046-2065) 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,...
The PFLCC has recently completed a set of comprehensive conservation planning scenarios for the state of Florida. This represents the first statewide effort to assess likely alternative futures for conservation considering an array of financial, biological, climatological and urbanistic conditions. These spatially explicit and temporal scenarios simulate both urban growth and climate change and identify the most suitable areas for conservation given the resulting land use pattern. Conservation allocations are based on both fee-title and conservation easements.The conservation priorities and mechanisms expressed in these scenarios are based on a wide set of contributing factors, and simulated conservation is purposefully...
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: 2014,
Conservation Planning,
Datasets/Database,
Impact Assessment,
LCC,
File-based data for download:https://www.sciencebase.gov/catalog/item/6329f0f4d34e71c6d67b8f82Related report with figures: https://doi.org/10.3133/ofr20221081Location and extent of the invasive annual grass threat across the sagebrush biome in the United States for 2020. Blue areas (dark and light, representing core sagebrush areas [CSAs] and growth opportunity areas [GOAs], respectively) are locations of high sagebrush ecological integrity and could serve as anchor points in an overall biome-wide strategy. A separate, high-resolution portable document format (PDF) version of this map is available at https://doi.org/10.3133/ofr20221081 so stakeholders can zoom in and see the results at much smaller scales. By zooming...
This coverage augments the 2002 Multi-Source Land Cover dataset produced by the California Department of Forestry and Fire Protection to include categories for agricultural land cover types as well as urban boundaries complete to 2006. The agricultural categories are classified to the types in the California Wildlife Habitat Relationships system. The agricultural information is derived from the Department of Water Resources land cover mapping as well crop information from pesticide use reports produced by the Department of Pesticide Regulation. Urban land use changes since the 2002 map were identified by combining the urban boundaries indicated in the Department of Conservation Farmland Mapping Program and urban...
Predicted probability of marten year-round occurrence created with Maxent (Phillips et al. 2006) using marten detections (N = 302, spanning 1990 – 2011) and nine predictor variables: mean annual precipitation, mean summer (July – September) precipitation, mean summer temperature amplitude, mean annual temperature maximum, mean fraction of vegetation carbon burned, mean understory index, mean vegetation carbon (g C m2), modal vegetation class, and average maximum tree LAI. 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 marten distribution model has a 10-fold cross-validated...
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 = 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...
Predicted probability of marten winter occurrence created with Maxent (Phillips et al. 2006) using marten detections (N = 162, December – April, spanning 1990 – 2011) and nine predictor variables: mean winter (January – March) precipitation, mean amount of snow on the ground in March, mean fraction of vegetation carbon burned, mean fraction of total forest carbon in coarse wood carbon, mean forest carbon (g C m2), mean fraction of vegetation carbon in forest, mean understory index (fraction of grass vegetation carbon in forest), average maximum tree LAI, and modal vegetation class. Predictor variables had a grid cell size of 4 km by 4 km, vegetation variables were simulated with MC1 dynamic global vegetation model...
Predicted probability of marten summer occurrence created with Maxent (Phillips et al. 2006) using marten detections (N = 197, May – November, spanning 1990 – 2011) and nine predictor variables: mean potential evapotranspiration, mean annual precipitation, mean summer temperature amplitude, 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. Predictor variables had a grid cell size of 4 km by 4 km, vegetation variables were simulated MC1 dynamic global vegetation model (Bachelet et al. 2001) and historical climate variables were...
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...
Future (2076-2095) predicted probability of marten year-round occurrence projected under the A1fi emissions scenario with the Hadley CM3 GCM model (Gordon et al. 2000, Pope et al. 2000). Projected marten distribution was created with Maxent (Phillips et al. 2006) using marten detections (N = 302, spanning 1990 – 2011) and eight predictor variables: mean annual precipitation, mean summer (July – September) precipitation, mean summer temperature amplitude, mean annual temperature maximum, mean fraction of vegetation carbon burned, mean understory index, mean vegetation carbon (g C m-2), and modal vegetation class. Predictor variables had a grid cell size of 10 km, vegetation variables were simulated with MC1 (Hayhoe...
The PFLCC has recently completed a set of comprehensive conservation planning scenarios for the state of Florida. This represents the first statewide effort to assess likely alternative futures for conservation considering an array of financial, biological, climatological and urbanistic conditions. These spatially explicit and temporal scenarios simulate both urban growth and climate change and identify the most suitable areas for conservation given the resulting land use pattern. Conservation allocations are based on both fee-title and conservation easements.The conservation priorities and mechanisms expressed in these scenarios are based on a wide set of contributing factors, and simulated conservation is purposefully...
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: 2014,
Conservation Planning,
Data,
Datasets/Database,
Impact Assessment,
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