Cooperative Ecosystem Studies Unit, Rocky Mountain CESU
Sector: Oil and Gas • Location: United States of America
Source: Grants.gov
The US Geological Survey, Northern Rocky Mountain Science Center (NOROCK), is offering a funding opportunity to develop a methodology to combine data on habitat conversion and species distribution to describe and predict how disturbance affects biodiversity within the Williston Basin. The methods developed should be scalable and transferable to other types of habitat conversion, regions and taxa.
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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 US Geological Survey, Northern Rocky Mountain Science Center (NOROCK), is offering a funding opportunity to develop a methodology to combine data on habitat conversion and species distribution to describe and predict how disturbance affects biodiversity within the Williston Basin. The methods developed should be scalable and transferable to other types of habitat conversion, regions and taxa. Specifically, the Center would like to have the following products developed from this opportunity: dataset delineating all oil well pads in the Williston Basin; a total species distribution map detailing species richness for all avian species and a weighted species distribution map prioritizing species of concern; an ecological effects layer mapping ecological effects (i.e., avoidance, reproductive success, etc.) in relation to energy development; habitat suitability maps integrating total and weighted species distribution maps with the ecological effects layer; models to predict habitat and biodiversity loss from future energy development. |
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 |
