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A strong data foundation is needed to inform science-based decisions for fisheries management at a watershed level. In preparation for a shift towards comprehensive watershed-scale planning, Arizona Game and Fish Department (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 state boundaries. In...
Categories: Data, Project; Types: Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: 2012, AZ-01, AZ-02, AZ-03, AZ-04, All tags...
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The Grassland, Shrubland, Desert Program of the U.S. Forest Service, Rocky Mountain Research Station intends to evaluate the interactive effects of fire and climate change on the presence and long-term persistence of native and non-native species within Rio Grande riparian and wetland habitats of the Desert and Southern Rockies LCCs. Decision support tools and maps will be produced that will help resource managers identify conditions and locations where biodiversity will be most affected by future changes and identify needs with respect to species conservation and invasive species management.This project was co-funded by multiple Landscape Conservation Cooperatives: Desert LCC and the Southern Rockies LCC.


    map background search result map search result map A Landscape Approach for Fisheries Database Compilation and Predictive Modeling Vulnerability of Riparian Obligate Species in the Rio Grande to the Interactive Effects of Fire, Hydrological Variation and Climate Change Vulnerability of Riparian Obligate Species in the Rio Grande to the Interactive Effects of Fire, Hydrological Variation and Climate Change A Landscape Approach for Fisheries Database Compilation and Predictive Modeling