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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.
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The percentage difference between mean modeled snow-water-equivalent (meters) on April 1 for the reference (1989-2011) climate period and mean modeled snow-water-equivalent on April 1 for the T4 climate change scenario. Reference period: the period 1989 – 2011 for the Upper Deschutes River Basin domain, for which observed historical meteorology is used for model input. T4 scenario: the observed historical (reference period) meteorology is perturbed by adding +4°C to each daily temperature record in the reference period meteorology, and this data is then used as input to the model.
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Mean modeled snow-water-equivalent (meters) on February 20, the date of peak basin-integrated mean modeled snow-water-equivalent (meters) for the T4 climate change scenario. Reference period: the period 1989 – 2011 for the Upper Deschutes River Basin domain, for which observed historical meteorology is used for model input. T4 scenario: the observed historical (reference period) meteorology is perturbed by adding +4°C to each daily temperature record in the reference period meteorology, and this data is then used as input to the model.
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The USGS National Climate Change and Wildlife Science Center (NCCWSC), as part of the work of the Interagency Land Management Adaptation Group (ILMAG), initiated a project in 2013 to develop plans for a searchable, public registry on climate change vulnerability assessments. Member agencies from the USGCRP Adaptation Science Work Group, the Association of Fish and Wildlife Agencies (AFWA), and several NGO’s also contributed. Vulnerability assessments are important for identifying resources that are most likely to be affected by climate change and providing insights on why certain resources are vulnerable. Consequently, they provide valuable information for informing climate change adaptation planning. CRAVe allows...
This project gallery includes all project reports and associated assessment materials, including interactive and downloadable connectivity and climate datasets for the project " Creating Practitioner-driven, Science-based Plans for Connectivity Conservation in a Changing Climate: A Collaborative Assessment of Climate-Connectivity Needs in the Washington-British Columbia Transboundary Region".
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Mean modeled snow-water-equivalent (meters) on March 13, the date of peak basin-integrated mean modeled snow-water-equivalent (meters) for the T2 climate change scenario. Reference period: the period 1989 – 2011 for the Upper Deschutes River Basin domain, for which observed historical meteorology is used for model input. T2 scenario: the observed historical (reference period) meteorology is perturbed by adding +2oC to each daily temperature record in the reference period meteorology, and this data is then used as input to the model.
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The percentage difference between mean modeled snow-water-equivalent (meters) on April 1 for the reference (1989-2011) climate period and mean modeled snow-water-equivalent on April 1 for the T2 climate change scenario. Reference period: the period 1989 – 2011 for the Upper Deschutes River Basin domain, for which observed historical meteorology is used for model input. T2 scenario: the observed historical (reference period) meteorology is perturbed by adding +2°C to each daily temperature record in the reference period meteorology, and this data is then used as input to the model.
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The absolute difference between mean modeled snow-water-equivalent on March 28 for the reference period and mean modeled snow-water-equivalent on February 20 for the T4P10 climate change scenario, which are the dates of peak basin-integrated SWE for each period, respectively.Reference period: the period 1989 – 2011 for the Upper Deschutes River Basin domain, for which observed historical meteorology is used for model input. T4P10 scenario: the observed historical (reference period) meteorology is perturbed by adding +4°C to each daily temperature record, and +10% precipitation to each daily precipitation record in the reference period meteorology, and this data is then used as input to the model.
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Globally, changing fire regimes due to climate is one of the greatest threats to ecosystems and society. This dataset presents projections of historic and future fire probability for the southcentral U.S. using downscaled climate projections and the Physical Chemistry Fire Frequency Model (PC2FM, Guyette et al., 2012). Climate data from 1900-1929 and projected climate data for 2040-2069 and 2070-2099 were used as model inputs to the Physical Chemistry Fire Frequency Model (Guyette et al. 2012) to estimate fire probability. Baseline and future time period data are from three global climate models (GCMs): CGCM, GFDL, and HadCM3. The nine associated data sets (tiffs) represent estimated change in mean fire probability...
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The Arizona Game and Fish Department (AGFD) recognizes the need for a strong data foundation to inform science-based decisions for fisheries management at a watershed level. In preparation for a shift towards comprehensive watershed-scale planning, AGFD is developing a fisheries data management system with an initial focus on compiling and formatting several hundred thousand fish survey and stocking records. Fish data will be integrated within a Geographic Information System (GIS) by georeferencing observations to an existing national spatial framework (National Hydrography Dataset), which will allow for broader transferability to watersheds shared with neighboring states, creating a seamless layer not limited by...
Future density (birds per hectare) 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 the Regional Climate Model v3 (RCM3) with boundary conditions driven by the Third Generation Coupled Global Climate Model (CGCM3) averaged for the years 2041-2070 and available from http://www.narccap.ucar.edu/.
Future density (birds per hectare) 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 the Canadian Regional Climate Model (CRCM) with boundary conditions driven by the Community Climate System Model (CCSM) averaged for the years 2041-2070 and available from http://www.narccap.ucar.edu/.
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Current probability of occurrence model of Scrub Jay (Aphelocoma californica) 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.
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The absolute difference between mean modeled snow-water-equivalent (meters) on April 1 for the reference (1989-2011) climate period and mean modeled snow-water-equivalent on April 1 for the T4P10 climate change scenario. Reference period: the period 1989 – 2011 for the Upper Deschutes River Basin domain, for which observed historical meteorology is used for model input. T4P10 scenario: the observed historical (reference period) meteorology is perturbed by adding +4°C to each daily temperature record, and +10% precipitation to each daily precipitation record in the reference period meteorology, and this data is then used as input to the model.
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Average projected future (across 5 regional climate models using the A2 emissions scenario) density (birds per hectare) model of Scrub Jay (Aphelocoma californica) using a Boosted Regression Tree model (Hastie & Tibshirani 2000) informed by breeding season avian point count data, modeled vegetation types, and climate data from 1) Weather Research Forecasting Grell Model (WRFG) with boundary conditions driven by the Third Generation Coupled Global Climate Model (CGCM3); 2) Weather Research Forecasting Grell Model (WRFG) with boundary conditions driven by the Community Climate System Model (CCSM); 3) Regional Climate Model v3 (RCM3) with boundary conditions driven by the Geophysical Fluid Dynamics Laboratory Global...
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The absolute difference between mean modeled snow-water-equivalent on March 28 for the reference period and mean modeled snow-water-equivalent on March 13 for the T2P10 climate change scenario, which are the dates of peak basin-integrated SWE for each period, respectively. Reference period: the period 1989 – 2011 for the Upper Deschutes River Basin domain, for which observed historical meteorology is used for model input. T2P10 scenario: the observed historical (reference period) meteorology is perturbed by adding +2°C to each daily temperature record, and +10% precipitation to each daily precipitation record in the reference period meteorology, and this data is then used as input to the model.
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The absolute difference between mean modeled snow-water-equivalent on March 28 for the reference period and mean modeled snow-water-equivalent on February 20 for the T4 climate change scenario, which are the dates of peak basin-integrated SWE for each period, respectively. Reference period: the period 1989 – 2011 for the Upper Deschutes River Basin domain, for which observed historical meteorology is used for model input. T4 scenario: the observed historical (reference period) meteorology is perturbed by adding +4°C to each daily temperature record in the reference period meteorology, and this data is then used as input to the model.
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Mean modeled snow-water-equivalent (meters) on February 20, the date of peak basin-integrated mean modeled snow-water-equivalent (meters) for the T4P10 climate change scenario. Reference period: the period 1989 – 2011 for the Upper Deschutes River Basin domain, for which observed historical meteorology is used for model input. T4P10 scenario: the observed historical (reference period) meteorology is perturbed by adding +4°C to each daily temperature record, and +10% precipitation to each daily precipitation record in the reference period meteorology, and this data is then used as input to the model.
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Mean modeled snow-water-equivalent (meters) on April 1 for the T2 climate change scenario. T2 scenario: the observed historical (reference period) meteorology is perturbed by adding +2°C to each daily temperature record in the reference period meteorology, and this data is then used as input to the model.
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The absolute difference between mean modeled snow-water-equivalent on March 28 for the reference period and mean modeled snow-water-equivalent on March 13 for the T2P10 climate change scenario, which are the dates of peak basin-integrated SWE for each period, respectively. Reference period: the period 1989 – 2009 for the McKenzie River Basin domain, and 1989 – 2011 for the Upper Deschutes River Basin domain, for which observed historical meteorology is used for model input. T2P10 scenario: the observed historical (reference period) meteorology is perturbed by adding +2°C to each daily temperature record, and +10% precipitation to each daily precipitation record in the reference period meteorology, and this data...


map background search result map search result map Current probability of occurrence model of Scrub Jay (Aphelocoma californica) using a Boosted Regression Tree model Average projected future (across 5 regional climate models using the A2 emissions scenario) density (birds per hectare) model of Scrub Jay (Aphelocoma californica) using a Boosted Regression Tree model Development of the Climate Registry for the Assessment of Vulnerability (CRAVe): A Searchable, Public Online Tool for Understanding Species and Habitat Vulnerability A Landscape Approach for Fisheries Database Compilation and Predictive Modeling (Not listed in the LCC Science Catalog due to Desert LCC co-funding and catalog administering) Modeled snow-water-equivalent, absolute difference between seasonal peak historical and projected values under T2p10 climate change scenario, McKenzie River Basin, Oregon [full and clipped versions] Modeled snow-water-equivalent, absolute difference in historical and projected April 1 values under T4P10 climate change scenario, Upper Deschutes River Basin, Oregon [full and clipped versions] Modeled snow-water-equivalent, percent difference between historical and projected April 1 values under T2 climate change scenario, Upper Deschutes River Basin, Oregon [full and clipped versions] Modeled snow-water-equivalent, percent difference between historical and projected April 1 values under T4 climate change scenario, Upper Deschutes River Basin, Oregon [full and clipped versions] Modeled snow-water-equivalent, projected April 1 values under T2 climate change scenario, Upper Deschutes River Basin, Oregon [full and clipped versions] Modeled snow-water-equivalent, absolute difference in historical and projected seasonal peak values under T2P10 climate change scenario, Upper Deschutes River Basin, Oregon [full and clipped versions] Modeled snow-water-equivalent, absolute difference in historical and projected seasonal peak values under T4 climate change scenario, Upper Deschutes River Basin, Oregon [full and clipped versions] Modeled snow-water-equivalent, absolute difference in historical and projected seasonal peak values under T4P10 climate change scenario, Upper Deschutes River Basin, Oregon [full and clipped versions] Modeled snow-water-equivalent, projected seasonal peak values under T2 climate change scenario, Upper Deschutes River Basin, Oregon [full and clipped versions] Modeled snow-water-equivalent, projected seasonal peak values under T4 climate change scenario, Upper Deschutes River Basin, Oregon [full and clipped versions] Modeled snow-water-equivalent, projected seasonal peak values under T4P10 climate change scenario, Upper Deschutes River Basin, Oregon [full and clipped versions] Fire probability for 1900-1929 using GFDL baseline climate values Modeled snow-water-equivalent, absolute difference in historical and projected April 1 values under T4P10 climate change scenario, Upper Deschutes River Basin, Oregon [full and clipped versions] Modeled snow-water-equivalent, percent difference between historical and projected April 1 values under T2 climate change scenario, Upper Deschutes River Basin, Oregon [full and clipped versions] Modeled snow-water-equivalent, percent difference between historical and projected April 1 values under T4 climate change scenario, Upper Deschutes River Basin, Oregon [full and clipped versions] Modeled snow-water-equivalent, projected April 1 values under T2 climate change scenario, Upper Deschutes River Basin, Oregon [full and clipped versions] Modeled snow-water-equivalent, absolute difference in historical and projected seasonal peak values under T2P10 climate change scenario, Upper Deschutes River Basin, Oregon [full and clipped versions] Modeled snow-water-equivalent, absolute difference in historical and projected seasonal peak values under T4 climate change scenario, Upper Deschutes River Basin, Oregon [full and clipped versions] Modeled snow-water-equivalent, absolute difference in historical and projected seasonal peak values under T4P10 climate change scenario, Upper Deschutes River Basin, Oregon [full and clipped versions] Modeled snow-water-equivalent, projected seasonal peak values under T2 climate change scenario, Upper Deschutes River Basin, Oregon [full and clipped versions] Modeled snow-water-equivalent, projected seasonal peak values under T4 climate change scenario, Upper Deschutes River Basin, Oregon [full and clipped versions] Modeled snow-water-equivalent, projected seasonal peak values under T4P10 climate change scenario, Upper Deschutes River Basin, Oregon [full and clipped versions] Modeled snow-water-equivalent, absolute difference between seasonal peak historical and projected values under T2p10 climate change scenario, McKenzie River Basin, Oregon [full and clipped versions] A Landscape Approach for Fisheries Database Compilation and Predictive Modeling (Not listed in the LCC Science Catalog due to Desert LCC co-funding and catalog administering) Current probability of occurrence model of Scrub Jay (Aphelocoma californica) using a Boosted Regression Tree model Average projected future (across 5 regional climate models using the A2 emissions scenario) density (birds per hectare) model of Scrub Jay (Aphelocoma californica) using a Boosted Regression Tree model Fire probability for 1900-1929 using GFDL baseline climate values Development of the Climate Registry for the Assessment of Vulnerability (CRAVe): A Searchable, Public Online Tool for Understanding Species and Habitat Vulnerability