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Current binomial (presence/absence) model of Brown Creeper (Certhia americana) using a Boosted Regression Tree model (Hastie & Tibshirani 2000) informed by breeding season avian point count data, modeled vegetation types, and climate data from PRISM (Daly et al. 2004) averaged for the years 1971-2000.
This workshop is part of a broader research project aimed at better understanding how communities can engage in the process of wind energy development. The research is funded through a National Science Foundation grant (#SES 0724672) to Roopali Phadke at Macalester College. This report was prepared by a research team from Macalester College. Throughout the day of the workshop, the research team collected demographic data about participants, gauged their familiarity with wind energy, and elicited their perceptions about landscape impacts. This was done through the use of interactive keypad polling, photographic analysis within focus groups, open-ended writing exercises and a final evaluation. The data were brought...
Geothermal energy, carbon sequestration, and enhanced oil and gas recovery have a clear role in U.S. energy policy, both in securing cost-effective energy and reducing atmospheric CO2 accumulations. Recent publicity surrounding induced seismicity at several geothermal and oil and gas sites points out the need to develop improved standards and practices to avoid issues that may unduly inhibit or stop the above technologies from fulfilling their full potential. It is critical that policy makers and the general community be assured that EGS, CO2 sequestration, enhanced oil/gas recovery, and other technologies relying on fluid injections, will be designed to reduce induced seismicity to an acceptable level, and be developed...
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For his MS thesis, Brendan Rogers used the vegetation model MC1 to simulate vegetation dynamics, associated carbon and nitrogen cycle, water budget and wild fire impacts across the western 2/3 of the states of Oregon and Washington using climate input data from the PRISM group (Chris Daly, OSU) at a 30arc second (800m) spatial grain. The model was run from 1895 to 2100 assuming that nitrogen demand from the plants was always met so that the nitrogen concentrations in various plant parts never dropped below their minimum reported values. A CO2 enhancement effect increased productivity and water use efficiency as the atmospheric CO2 concentration increased. Future climate change scenarios were generated through statistical...
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ClimateWNA was used to downscale historical data and future climate projections to a 1-km 2 grid. ClimateWNA is a program that generates both directly calculated and derived climate variables for specific locations across western North America (Wang et al. 2012) using Parameter-elevation Regressions on Independent Slopes Model (PRISM). We generated annual, seasonal and monthly climate data for the period 1961 to 1990. For future climate projections, we used the SRES A2 greenhouse-gas emissions scenario from the IPCC Fourth Assessment Report. We generated five sets of future climate projections averaged for the time period 2070-2099: BCCR BCM2.0, CCCMA CGCM3, CSIRO MK 3.0, INMCM 3.0, MIROC3.2 MEDRES. Downloads:...
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For his MS thesis, Brendan Rogers used the vegetation model MC1 to simulate vegetation dynamics, associated carbon and nitrogen cycle, water budget and wild fire impacts across the western 2/3 of the states of Oregon and Washington using climate input data from the PRISM group (Chris Daly, OSU) at a 30arc second (800m) spatial grain. The model was run from 1895 to 2100 assuming that nitrogen demand from the plants was always met so that the nitrogen concentrations in various plant parts never dropped below their minimum reported values. A CO2 enhancement effect increased productivity and water use efficiency as the atmospheric CO2 concentration increased. Future climate change scenarios were generated through statistical...
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Soil residual water corresponds to the model variable "total streamflow." In the model MC1, this is calculated (in cm of water) as the water flowing through the soil profile below the last soil layer (streamflow), water leached into the subsoil (baseflow) and also includes runoff. The output is presented here as a monthly average. Soil residual water is part of the model output from Brendan Rogers' MS thesis work. Brendan used the vegetation model MC1 to simulate vegetation dynamics, associated carbon and nitrogen cycle, water budget and wild fire impacts across the western 2/3 of the states of Oregon and Washington using climate input data from the PRISM group (Chris Daly, OSU) at a 30arc second (800m) spatial...
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Soil residual water corresponds to the model variable "total streamflow." In the model MC1, this is calculated (in cm of water) as the water flowing through the soil profile below the last soil layer (streamflow), water leached into the subsoil (baseflow) and also includes runoff. The output is presented here as a monthly average. Soil residual water is part of the model output from Brendan Rogers' MS thesis work. Brendan used the vegetation model MC1 to simulate vegetation dynamics, associated carbon and nitrogen cycle, water budget and wild fire impacts across the western 2/3 of the states of Oregon and Washington using climate input data from the PRISM group (Chris Daly, OSU) at a 30arc second (800m) spatial...
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Soil residual water corresponds to the model variable "total streamflow." In the model MC1, this is calculated (in cm of water) as the water flowing through the soil profile below the last soil layer (streamflow), water leached into the subsoil (baseflow) and also includes runoff. The output is presented here as a monthly average. Soil residual water is part of the model output from Brendan Rogers' MS thesis work. Brendan used the vegetation model MC1 to simulate vegetation dynamics, associated carbon and nitrogen cycle, water budget and wild fire impacts across the western 2/3 of the states of Oregon and Washington using climate input data from the PRISM group (Chris Daly, OSU) at a 30arc second (800m) spatial...
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Soil residual water corresponds to the model variable "total streamflow." In the model MC1, this is calculated (in cm of water) as the water flowing through the soil profile below the last soil layer (streamflow), water leached into the subsoil (baseflow) and also includes runoff. The output is presented here as a monthly average. Soil residual water is part of the model output from Brendan Rogers' MS thesis work. Brendan used the vegetation model MC1 to simulate vegetation dynamics, associated carbon and nitrogen cycle, water budget and wild fire impacts across the western 2/3 of the states of Oregon and Washington using climate input data from the PRISM group (Chris Daly, OSU) at a 30arc second (800m) spatial...
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Soil residual water corresponds to the model variable "total streamflow." In the model Mc1, this is calculated (in cm of water) as the water flowing through the soil profile below the last soil layer (streamflow), Water leached in the subsoil (baseflow) and also includes runoff. the output is prsented here as a monthly average. Soil residual water is part of the model output from Brendan Rogers' MS thesis work. Brendan used the vegetation model MC1 to simulate vegetation dynamics, associated carbon and nitrogen cycle, water budget and wild fire impacts across the western 2/3 of the states of Oregon and Washington using climate input data from the PRISM group (Chris Daly, OSU) at a 30arc second (800m) spatial grain....
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This dataset represents the average net primary production for each HUC5 watershed, simulated by the model MC1 for the 30-year period 1971-2000. Mean net primary production (in g m-2 per yr), was determined for each HUC5 watershed by averaging values of original ~ 4 km raster data. Watersheds represent 5th level (HUC5, 10-digit) hydrologic unit boundaries and were acquired from the Natural Resources Conservation Service. Background: The dynamic global vegetation model MC1 (see Bachelet et al.2001) was used to simulate vegetation dynamics, associated carbon and nitrogen cycle, water budget, and wild fire impacts for OR, WA, AZ and NM, for a project funded by the USDA Forest Service (PNW09-JV-11261900-003). The MC1...
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For a description of each map layer, select the Details tab, then select a Layer Name. This GIS dataset is part of a suite of wildlife habitat connectivity data produced by the Washington Wildlife Habitat Connectivity Working Group (WHCWG). The WHCWG is a voluntary public-private partnership between state and federal agencies, universities, tribes, and non-governmental organizations. The WHCWG is co-led by the Washington Department of Fish and Wildlife (WDFW) and the Washington Department of Transportation (WSDOT). This dataset quantifies current wildlife habitat connectivity patterns for the Columbia Plateau Ecoregion in Washington, Oregon, and Idaho. Available WHCWG raster data include model base layers, resistance,...
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There are three main components to the ESI: shoreline habitats, sensitive biological resources, and human-use resources. The shoreline and intertidal areas are ranked based on sensitivity determined by: (1) Shoreline type (substrate, grain size, tidal elevation, origin); (2) Exposure to wave and tidal energy; (3) Biological productivity and sensitivity; and (4) Ease of cleanup. The biology layers focus on threatened/endangered species, areas of high concentration and areas where sensitive life stages may occur. Supporting data tables provide species/location-specific abundance, seasonality, status, life history, and source information Human use resources mapped include managed areas (parks, refuges, critical habitats,...
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For his MS thesis, Brendan Rogers used the vegetation model MC1 to simulate vegetation dynamics, associated carbon and nitrogen cycle, water budget and wild fire impacts across the western 2/3 of the states of Oregon and Washington using climate input data from the the PRISM group (Chris Daly, OSU) at a 30arc second (800m) spatial grain. The model was run from 1895 to 2100 assuming that nitrogen demand from the plants was always met so that the nitrogen concentrations in various plant parts never dropped below their minimum reported values. A CO2 enhancement effect increased productivity and water use efficiency as the atmospheric CO2 concentration increased. Future climate change scenarios were generated through...
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In order to predict the impacts of climate change induced sea-level rise on Pacific Northwest coastal habitats, the Sea Level Affecting Marshes Model (SLAMM) was utilized to simulate future coastal habitat configurations under various sea-level rise scenarios. The model was run for 2025, 2050, 2075, and 2100. Historical or "initial condition" habitat classifications are also available for some sites. The sea-level rise scenarios include: 1. A1B greenhouse gas emission mean : 0.39 meter rise by 2100 2. A1B greenhouse gas emission maximum : 0.69 meter rise by 2100 3. 1 meter rise by 2100 4. 1.5 meter rise by 2100 5. 2 meter rise by 2100 Due to differing site conditions, local sea-level rise varies slightly from...
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Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline data along open-ocean sandy shores of the conterminous United States and parts of Alaska and Hawaii under the National Assessment of Shoreline Change project.There is no widely accepted standard for analyzing shoreline...
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Vegetation types from Kuchler (1975) potential vegetation map were aggregated into 35 classes as part of the VEMAP project (Vegetation/Ecosystem Modeling and Analysis Project, Kittel et al. 1995). Functional vegetation types were reclassified (grouped in ArcMap) by the Conservation Biology Institute to reflect the classification scheme used by Brendan Rogers.
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In order to predict the impacts of climate change induced sea-level rise on Pacific Northwest coastal habitats, the Sea Level Affecting Marshes Model (SLAMM) was utilized to simulate future coastal habitat configurations under various sea-level rise scenarios. The model was run for 2025, 2050, 2075, and 2100. Historical or "initial condition" habitat classifications are also available for some sites. The sea-level rise scenarios include: 1. A1B greenhouse gas emission mean : 0.39 meter rise by 2100 2. A1B greenhouse gas emission maximum : 0.69 meter rise by 2100 3. 1 meter rise by 2100 4. 1.5 meter rise by 2100 5. 2 meter rise by 2100 Due to differing site conditions, local sea-level rise varies slightly from...


map background search result map search result map Okanogan-Wenatchee National Forest Ecology Type Aggregated potential vegetation map from Kuchler (1975) for the western 2/3 of OR and WA Simulated PNW biomass consumed (g C/m2) under MIROC 3.2 medres A2 (2070-2099 average) Simulated runoff under MIROC 3.2 medres A2 (2070-2099 average) in nillimeters for the Pacific Northwest, USA Western North American Climate Data from the Pacific Northwest Climate Change Vulnerability Assessment WA Short Term Shoreline Change Columbia River ESI - 2004 Simulated historical net primary production (1971-2000) for OR and WA, USA Landscape Integrity, Columbia Plateau Ecoregion Pacific Northwest sea-level rise modelling - Habitat classification for site four (2075, A1B mean scenario) Pacific Northwest sea-level rise modelling - Habitat classification for site one (2025, 1.5 meter rise scenario) Total soil residual water simulated under MIROC 3.2 medres A2 in cm for October for the Pacific Northwest, USA (2070-2099 average) Total soil residual water simulated under MIROC 3.2 medres A2 in cm for August for the Pacific Northwest, USA (2070-2099 average) Total soil residual water simulated under MIROC 3.2 medres A2 in cm for April for the Pacific Northwest, USA (2070-2099 average) Total soil residual water simulated under Hadley CM3 A2 in cm for August for the Pacific Northwest, USA (2070-2099 average) Total soil residual water simulated under CSIRO MK3 A2 in cm for June for the Pacific Northwest, USA (2070-2099 average) Simulated potential PNW vegetation the Western 2/3 of Oregon and Washington under CSIRO Mk3 general circulation model run with the A2 SRES emission scenario (2070-2099 mode) using the MC1 dynamic global vegetation model Pacific Northwest sea-level rise modelling - Habitat classification for site four (2075, A1B mean scenario) Pacific Northwest sea-level rise modelling - Habitat classification for site one (2025, 1.5 meter rise scenario) WA Short Term Shoreline Change Okanogan-Wenatchee National Forest Ecology Type Columbia River ESI - 2004 Landscape Integrity, Columbia Plateau Ecoregion Simulated PNW biomass consumed (g C/m2) under MIROC 3.2 medres A2 (2070-2099 average) Simulated potential PNW vegetation the Western 2/3 of Oregon and Washington under CSIRO Mk3 general circulation model run with the A2 SRES emission scenario (2070-2099 mode) using the MC1 dynamic global vegetation model Aggregated potential vegetation map from Kuchler (1975) for the western 2/3 of OR and WA Simulated runoff under MIROC 3.2 medres A2 (2070-2099 average) in nillimeters for the Pacific Northwest, USA Total soil residual water simulated under MIROC 3.2 medres A2 in cm for October for the Pacific Northwest, USA (2070-2099 average) Total soil residual water simulated under MIROC 3.2 medres A2 in cm for August for the Pacific Northwest, USA (2070-2099 average) Total soil residual water simulated under MIROC 3.2 medres A2 in cm for April for the Pacific Northwest, USA (2070-2099 average) Total soil residual water simulated under Hadley CM3 A2 in cm for August for the Pacific Northwest, USA (2070-2099 average) Total soil residual water simulated under CSIRO MK3 A2 in cm for June for the Pacific Northwest, USA (2070-2099 average) Simulated historical net primary production (1971-2000) for OR and WA, USA Western North American Climate Data from the Pacific Northwest Climate Change Vulnerability Assessment