Cooperative Ecosystem Studies Unit, Rocky Mountain CESU
Sector: Advanced Electronics • Location: United States of America
Source: Grants.gov
The U.S. Geological Survey (USGS) Fort Collins Science Center (FORT) is offering a funding opportunity to a CESU partner to collaboratively develop a soil-climate modeling application that utilizes contemporary environmental data with the Newhall Soil Simulation Model (NSM) to describe patterns and trends in soil moisture and related growing conditions for plants. The study region is sagebrush eco
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Participants
Sponsoring Agency | Obfuscated Data |
Company | Obfuscated Data |
Status
Original status | archived |
Taiyo status | Obfuscated Data |
Taiyo last update | 00-00-0000 |
Available timestamps | 00-00-0000 |
Available timestamp type | Obfuscated Data |
Contact
Contact name | Obfuscated Data |
Phone | 0000000000 |
ObfuscatedData@email.com | |
Address | Obfuscated Data, Obfuscated data, obfuscated data, Obfuscated data |
Description
Description | The U.S. Geological Survey (USGS) Fort Collins Science Center (FORT) is offering a funding opportunity to a CESU partner to collaboratively develop a soil-climate modeling application that utilizes contemporary environmental data with the Newhall Soil Simulation Model (NSM) to describe patterns and trends in soil moisture and related growing conditions for plants. The study region is sagebrush ecosystem which is distributed across the western U.S., and the results of this project are expected to help address the effects of disturbances, such as fire, habitat treatments, fuel treatments, energy development, restoration and other land-uses, on the dynamics of habitats and species to support regional planning and local management decisions in the sagebrush ecosystem, shrublands, semi-arid rangelands and woodlands. Public lands are part of a network of important wildlife habitats distributed across the western U.S. and a diversity of uses and management actions and natural processes affect the condition of these lands. For example, recent decision by Fish and Wildlife Service regarding Greater Sage-grouse (2016), and pending re-evaluation of the species¿ status (2021) has led to revisions to dozens of land-management plans (federal agencies) and wildlife management plans (state agencies), elevating the information needs of planners and managers for improved, practical information regarding the ecology and management of the sagebrush ecosystem and focal wildlife populations which utilize this resource. Public agencies manage important wildlife habitats and a wide array of land-uses, including energy development, grazing, resource extraction and recreation across the western U.S. and the diversity of uses, management actions and natural processes affect the condition of these lands. Changing conditions lead to variations in the services these lands provide, the quality of wildlife habitats, and the abundance and distribution of wildlife populations. Better understanding of the role environmental patterns and natural dynamics play in habitat quality and management outcomes, including economic implications, will improve the connection between scientific information and management applications. Here, we solicit research that will directly support and inform management decisions related to restoration, fire and fuels management, and habitat treatments that affect planning and implementation. This information will come from interpretation of a spatially explicit model (NSM) that accounts for water budgets and evapotranspiration based on climatic, pedologic, and geographic information. The model-coding structure should be created such that code and inputs can be substituted to enable historic and scenario comparisons. |
Original sub-sector | Obfuscated |
Original Currency | USD |
Original budget | 000000000000000 |
Procurement method | Obfuscated Data |
Budget | 000000000000000 |
Location
Region | Obfuscated |
Country | Obfuscated |
State | Obfuscated Data |
County | Obfuscated |
Location | Obfuscated Data, Obfuscated data, obfuscated data, Obfuscated data |
Source
Source reliability | High |
Data quality score | 100% |
Source | Obfuscated Data |
URL | obfuscated_data,obfuscateddata.com |
More Details
Project Type | Obfuscated Data |
Article Published Date | Obfuscated Data |
