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Exposure (vulnerability) index for the future time period (2061-2080) representing projected climate conditions from the Meteorological Research Institute's Coupled Atmosphere-Ocean General Circulation Model, version 3, and the rcp85 emissions scenario. The exposure model uses LANDFIRE vegetation data and Worldclim climate data .The raster values represent exposure scores for the corresponding vegetation type. The modeled vegetation types can be spatially associated with the exposure values by overlaying them with the "landfire_veg_sw_300m.tif" raster.Exposure values represent where the location falls in climate space relative to its recent historical distribution:5 (core 5% of historical climate space); 10 (5 -...
This survey was used in a study on the use of scientific information in public natural resource management planning and decision-making. This survey was intended to help staff at the Southwest Climate Science Center (SWCSC), and others in the research community, gain a more specific understanding of the kinds of decisions made by public natural resource officials and to identify how scientific information, and in particular climate information, is obtained and applied in National Environmental Policy Act (NEPA) natural resource decision-making processes. Aside from questions and associated information, the survey document contains page logic describing actions taken in a web-based environment.
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We are seeking to better understand networks among resource managers with respect to developing plans for climate change adaptation. We are pursuing this through a network analysis based on a survey of federal resource management staff and scientists in the southwestern and Midwestern U.S. Originally planned, this study was conceived to cover the Southwest and North Central Climate Science Centers, as defined by the USGS. In practice, surveys are most easily distributed within regions as defined by the federal resource agencies. Unfortunately, there is no uniform set of regions. We have tried to be comprehensive in our survey and cover at least the North Central and Southwestern Region.
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California - one of the nation's most populous states - hosts extensive public lands, crown-jewel national parks, and diverse natural resources. Resource managers in federal, state, tribal, and local agencies face challenges due to environmental changes and extreme events such as severe droughts, heat waves, flood events, massive wildfires, and forest dieback. However, state-of-the-art research that could aid in the management of natural resources facing these challenges is typically slow to be applied, owing to limited time and capacity on the part of both researchers and managers. This project aims to accelerate the application of science to resource management by facilitating the translation and synthesis of...
Exposure (vulnerability) index for the future time period (2041-2060) representing projected climate conditions from the Model for Interdisciplinary Research on Climate, Earth System Model, Chemistry Coupled (MIROC-ESM-CHEM) and the rcp85 emissions scenario. The exposure model uses LANDFIRE vegetation data and Worldclim climate data .The raster values represent exposure scores for the corresponding vegetation type. The modeled vegetation types can be spatially associated with the exposure values by overlaying them with the "landfire_veg_sw_300m.tif" raster.Exposure values represent where the location falls in climate space relative to its recent historical distribution:5 (core 5% of historical climate space); 10...
Exposure (vulnerability) index for the future time period (2061-2080) representing projected climate conditions from the MRI-CGCM3 GCM and the rcp45 emissions scenario. The exposure model uses LANDFIRE vegetation data and Worldclim climate data .The raster values represent exposure scores for the corresponding vegetation type. The modeled vegetation types can be spatially associated with the exposure values by overlaying them with the "landfire_veg_sw_300m.tif" raster.Exposure values represent where the location falls in climate space relative to its recent historical distribution:5 (core 5% of historical climate space); 10 (5 - 10%; still very good); ... ; 95 (90 - 95%; within the historical distribution, but getting...
Exposure (vulnerability) index for the future time period (2041-2060) representing projected climate conditions from the Meterological Research Institute's Coupled Atmosphere-Ocean General Circulation Model (MRI-CGCM3) and the rcp45 emissions scenario. The exposure model uses LANDFIRE vegetation data and Worldclim climate data .The raster values represent exposure scores for the corresponding vegetation type. The modeled vegetation types can be spatially associated with the exposure values by overlaying them with the "landfire_veg_sw_300m.tif" raster.Exposure values represent where the location falls in climate space relative to its recent historical distribution:5 (core 5% of historical climate space); 10 (5 -...
Abstract (from http://onlinelibrary.wiley.com/doi/10.1111/ddi.12257/abstract): Aim Ecological niche modelling is one of the main tools that allows for the incorporation of climate change effects into conservation planning. For example, ecological niche model predictions can be used to rank species by degree of predicted future habitat loss. While many studies have considered how different modelling decisions contribute to uncertainty in niche model outputs, here we evaluate how metrics used to rank species by conservation risk respond to the choice of global climate models, greenhouse gas emission scenarios, suitable versus unsuitable threshold values, and the degree of model complexity. Location California,...
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The goal of this project was to: (a) archive the relevant AR5 model output data for the southwest region; (b) downscale daily temperature and precipitation to 12 X 12 km cell spatial resolution over the Southwest; (c) assess the precision (degree of agreement) of the simulated models; (d) assess the direction and magnitude of change in projections between AR4 and AR5, as well as assess projections of key extreme climatic events (i.e., extreme drought, extreme seasonal precipitation, extreme high and low temperature events); and (e) assess critical ecosystem impacts (i.e., climate water deficit and fire; hydrological condition of major river systems; impacts on highly valued species).
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Derived from the LANDFIRE Existing Vegetation data (http://www.landfire.gov/vegetation.php). This dataset has been resampled from the 30 m resolution of the source data to 300 m. The resampling was done using a majority filter so that cells in the new raster represent the most common type from the original raster. The main use for this dataset is in conjunction with Southwest Forest Vulnerability Index rasters, which contain the modeled vegetation exposure scores for several projected future climate scenarios. This raster can be used as an index of the vegetation type being modeled at each location.
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In 2017, California was experiencing its most severe drought in over a millennia. Low rainfall and record high temperatures resulted in increased tree mortality and complete forest diebacks across the West. Though land managers scrambled to respond, they lacked information needed to make informed decisions. Focusing on California’s central and southern Sierra Nevada Mountains, this project seeks to determine whether a key forest management practice – forest thinning via prescribed fire – can help forests better survive drought. Prescribed fire is commonly used in the western U.S. to remove potential wildfire fuel, such as small trees and shrubs. It is also thought that this act of selectively removing trees helps...
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Millions of acres of California’s forest cover have been lost due to severe wildfire and drought mediatedinsect outbreaks. These acres may not grow back as forests without management action, which could negatively impact carbon sequestration, access to clean drinking water, wildlife habitat and recreation opportunities. Various factors, including limited regeneration potential, hotter and more extreme climatic conditions, and the threat of reburning hinder forest recovery. In recent year researchers have developed numerous tools and resources to help forest managers prioritize where to reforest, and how to implement climate-adaptive strategies. However, forest managers lack the time and resources to review each...
Exposure (vulnerability) index for the baseline time period (1950-2000) representing historical conditions. The exposure model uses LANDFIRE vegetation data and Worldclim climate data . This raster represents the baseline exposure values from the Worldclim "Current" time period (1950-2000). There were four climate scenarios evaluated under the Southwest Climate Change Vulnerability project (MG - RCP 45; MG - RCP 85; MI - RCP 45; MI - RCP 85). Because the model is fit on the four scenarios independently, there are minor differences in the baseline exposure values. This raster simplifies the outputs by combining the four baseline exposure rasters, and can be used with any of the projected futures.The raster values...
Exposure (vulnerability) index for the future time period (2041-2060) representing projected climate conditions from the Meteorological Research Institute's Coupled Atmosphere-Ocean General Circulation Model, version 3, and the rcp85 emissions scenario. The exposure model uses LANDFIRE vegetation data and Worldclim climate data .The raster values represent exposure scores for the corresponding vegetation type. The modeled vegetation types can be spatially associated with the exposure values by overlaying them with the "landfire_veg_sw_300m.tif" raster.Exposure values represent where the location falls in climate space relative to its recent historical distribution:5 (core 5% of historical climate space); 10 (5 -...
Exposure (vulnerability) index for the future time period (2061-2080) representing projected climate conditions from the Model for Interdisciplinary Research on Climate, Earth System Model, Chemistry Coupled (MIROC-ESM-CHEM) and the rcp85 emissions scenario. The exposure model uses LANDFIRE vegetation data and Worldclim climate data .The raster values represent exposure scores for the corresponding vegetation type. The modeled vegetation types can be spatially associated with the exposure values by overlaying them with the "landfire_veg_sw_300m.tif" raster.Exposure values represent where the location falls in climate space relative to its recent historical distribution:5 (core 5% of historical climate space); 10...
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In the southwestern United States, droughts of 10 or more years are projected to become more frequent by 2100. It also is projected that there will be fewer wet days per year, with more precipitation falling on those wet days. Such climatic extremes can strongly affect wild animals and plants, ecosystems, and humans. In the Southwest, more frequent and intense storms may negatively affect protected species in coastal salt marshes; changes in the timing and amount of precipitation could lead to increases in fuel loads; and increasingly humid heat waves could lead to higher incidence of heat-related illness among visitors to national parks. This project will improve understanding of climate extremes and their potential...
Exposure (vulnerability) index for the future time period (2041-2060) representing projected climate conditions from the Model for Interdisciplinary Research on Climate, Earth System Model, Chemistry Coupled (MIROC-ESM-CHEM) and the rcp45 emissions scenario. The exposure model uses LANDFIRE vegetation data and Worldclim climate data .The raster values represent exposure scores for the corresponding vegetation type. The modeled vegetation types can be spatially associated with the exposure values by overlaying them with the "landfire_veg_sw_300m.tif" raster.Exposure values represent where the location falls in climate space relative to its recent historical distribution:5 (core 5% of historical climate space); 10...
Exposure (vulnerability) index for the future time period (2061-2080) representing projected climate conditions from the Model for Interdisciplinary Research on Climate, Earth System Model, Chemistry Coupled (MIROC-ESM-CHEM) and the rcp45 emissions scenario. The exposure model uses LANDFIRE vegetation data and Worldclim climate data .The raster values represent exposure scores for the corresponding vegetation type. The modeled vegetation types can be spatially associated with the exposure values by overlaying them with the "landfire_veg_sw_300m.tif" raster.Exposure values represent where the location falls in climate space relative to its recent historical distribution:5 (core 5% of historical climate space); 10...
    map background search result map search result map Assessment of Available Climate Models and Projections for the Southwest Region Climate Change and Federal Land Management: Assessing Priorities Using a Social Network Approach Improving Understanding of Climate Extremes in the Southwestern United States Vegetation data for Southwest Forest Vulnerability Index Can Prescribed Fire Help Forests Survive Drought in the Sierra Nevada Mountains? Improving and Accelerating the Application of Science to Natural Resource Management in California California Reforestation Management Toolshed: A Web-Based Dashboard of Integrating Existing Resources Can Prescribed Fire Help Forests Survive Drought in the Sierra Nevada Mountains? Improving and Accelerating the Application of Science to Natural Resource Management in California California Reforestation Management Toolshed: A Web-Based Dashboard of Integrating Existing Resources Assessment of Available Climate Models and Projections for the Southwest Region Improving Understanding of Climate Extremes in the Southwestern United States Vegetation data for Southwest Forest Vulnerability Index Climate Change and Federal Land Management: Assessing Priorities Using a Social Network Approach