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Phase 1 & 2 (2010, 2012): This project developed a sampling design and monitoring protocol for wintering shorebirds in the Central Valley and in the San Francisco Bay Estuary and develop an LCC-specific online shorebird monitoring portal publicly available at the California Avian Data Center. The three objectives in Phase II of this project are: 1) Complete the shorebird monitoring plan for the CA LCC by developing a sampling design and monitoring protocol for wintering shorebirds in coastal southern California and northern Mexico. 2) Develop models to evaluate the influence of habitat factors from multiple spatial scales on shorebird use of San Francisco Bay and managed wetlands in the Sacramento Valley, as a model...
Categories: Data, Project; Types: Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: 2010, 2011, 2013, Academics & scientific researchers, Academics & scientific researchers, All tags...
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This project used species distribution modeling to assess the risk to habitat change under various climate change scenarios for rare plants. To predict the response of rare plant species to climate change, the project modeled the current distribution of the species using climate and environmental data (e.g., soils, disturbance, land-use), use these models to predict the species distribution given climate change, calculate current and future range size, calculate the amount of overlap of predicted future distribution with current distribution, and assess where barriers and protected areas are located with reference to the change in species distribution. Given the results of the distribution modeling, each species...
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 project integrates fire risk models, species distribution models (SDMs) and population models with scenarios of future climate and land cover to project how the effects of climate-induced changes to species distributions and land use change will impact threatened species in fire-prone ecosystems. This project also identifies and prioritizes potential management responses to climate change (e.g. assisted colonization, fire management, land protection, dispersal corridors). Anticipated products include: 1) maps (digital and hard copy) of habitat suitability under current and future climate change, current and future projected urban growth and combinations of climate change and future projected urban growth, under...
Categories: Data, Project; Tags: 2011, Academics & scientific researchers, CA, CA-Southern, California Landscape Conservation Cooperative, All tags...
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 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...
This project used species distribution modeling, population genetics, and geospatial analysis of historical vs. modern vertebrate populations to identify climate change refugia and population connectivity across the Sierra Nevada. It is hypothesized that climate change refugia will increase persistence and stability of populations and, as a result, maintain higher genetic diversity. This work helps managers assess the need to include connectivity and refugia in climate change adaptation strategies. Results help Sierra Nevada land managers allocate limited resources, aid future scenario assessment at landscape scales, and develop a performance measure for assessing resilience.
Categories: Data, Project; Tags: 2011, 2013, CA, California Landscape Conservation Cooperative, Conservation Design, All tags...
This project evaluates the effects of global climate change and sea level rise on estuarine intertidal habitat in the San Francisco Bay and the Pacific Flyway migratory waterbirds that rely on this habitat. Phase 2 of this project is a continuation of work to evaluate the effects of global climate change and sea level rise (SLR) on intertidal shoals in the San Francisco Bay Estuary and the migratory waterbirds that rely on this critically important resource in the Pacific Flyway. The primary objectives are to: 1) use downscaled global climate change models to translate SLR and climate scenarios into habitat quantity predictions through Delft3D and Dflow-FM (unstructured grid) geomorphic modeling; 2) model the response...
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 -...
The goal of this project is to create critically needed coastal fog datasets. Anticipated products from the collaboration between on-the-ground natural resource managers and a multidisciplinary coalition of physical scientists are: 1) a compilation of existing fog related data from multiple sources: satellite (AVHRR, GOES, Modis, Landsat), NOAA buoy , and airport and meteorological stations, 2) USGS Open File report documenting the results of a multiday working session with climatologists, remote sensing specialists, fog modelers, statisticians, and natural resource managers, convened to review the data, examine and assess the correlations between data streams and models, specify initial parameters to be extracted...
Categories: Data, Project; Tags: evapotranspiration, 2011, California Landscape Conservation Cooperative, California coast, Coastal, All tags...
The CA Academy of Science and Point Blue Conservation Science conducted a systematic analysis of uncertainty in modeling the future distributions of ~50 California endemic plant species and ~50 California land birds, explicitly partitioning among 5 alternative sources of variation and testing for their respective contributions to overall variation among modeled outcomes. They mapped the uncertainty from identified sources, which can guide decisions about monitoring, restoration, acquisition, infrastructure, etc., in relation to climate change.
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...
In its first funded year this project created an online environment in which land managers and their technical support staff can quickly find the climate adaptation information they need and communicate with the researchers producing the data. Phase 2 of the project focused on reaching out to the user community to get them engaged in the Climate Commons, and continuing development of the site. In year 3 and beyond, the Climate Commons became the CA LCC’s project data management platform as well as a digital library offering a starting place to find climate change science relevant to conservation decision-making. http://climate.calcommons.org.
Categories: Data, Project; Tags: 2011, 2012, Academics & scientific researchers, Applications and Tools, CA, All tags...
California’s native fishes are mostly endemic, with no place to go as climate change increases water temperatures and alters stream flows. Many of the alien fishes, however, are likely to benefit from the effects of climate change. The goal of this project is to synthesize life history traits, population trends, status, and threats, including climate change, for all fishes in the state. We have found that 25% of the endemic fishes are now in danger of extinction. Climate change in conjunction with alien species, agriculture, and dams pose the greatest threat to native fishes. Preliminary results from two regional analyses suggest that native fishes in the Sierra Nevada are slightly less (74%) vulnerable to climate...
This project researched the expected variation in avian demographic responses to environmental change across a gradient of species and landscapes from the San Francisco Bay to the Central Valley of California. We used two avian taxa, waterfowl and songbirds, as case studies for the integration of long-term demographic data with climate change variables. For each taxon, we assessed and synthesized several demographic responses to climate change variables (i.e., precipitation and temperature) to explore the relationship between four large-scale climate indices and bird species arrival dates and nest survival. A web-based application provides natural resource managers with project results.
Why Rangelands: The Central Valley of California, the surrounding foothills and the interior Coast Range include over 18 million acres of grassland. Most of this land is privately owned and managed for livestock production. Because grasslands are found in some of California’s fastest-growing counties, they are severely threatened by land conversion and development. In addition climate change stresses grasslands by potentially changing water availability and species distributions.Maintaining a ranching landscape can greatly support biodiversity conservation in the California Landscape Conservation Cooperative (LCC) region. In addition ranches generate multiple ecosystem services—defined as human benefits provided...
Categories: Data, Project; Tags: 2011, 2012, 2013, Applications and Tools, CA, All tags...
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...
To be successful, natural resource managers need to synthesize diverse information on the effects of management actions, climate change and other stressors on wildlife populations at appropriate scales. The project team developed a Decision Support Tool (DST) that integrates the results of multi-disciplinary, multi-taxa modeling allowing users to project outcomes of conservation actions, accounting for effects of climate change and other stressors. This DST builds on work to improve a sea level rise tool for adaptive tidal wetland restoration and management. The DST provides information on how restoration can increase population resilience and long-term persistence at multiple scales for multiple species throughout...


map background search result map search result map Assessing and Mapping Rare Plant Species Vulnerability to Climate Change A Monitoring Protocol to Assess Wintering Shorebird Population Trends A Monitoring Protocol to Assess Wintering Shorebird Population Trends Assessing and Mapping Rare Plant Species Vulnerability to Climate Change