Cooperative Ecosystem Studies Unit, Rocky Mountain CESU
Sector: Government • Location: United States of America
Source: Grants.gov
The USGS, Northern Rocky Mountain Science Center (NOROCK), is offering a funding opportunity to a CESU partner to develop an evolutionary framework to investigate possible ultimate outcomes of Chronic Wasting Disease (CWD) infection at the population and landscape scales. It currently is not clear whether enough data exist to develop a data-driven CWD specific evolutionary ecology model or not. A
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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 USGS, Northern Rocky Mountain Science Center (NOROCK), is offering a funding opportunity to a CESU partner to develop an evolutionary framework to investigate possible ultimate outcomes of Chronic Wasting Disease (CWD) infection at the population and landscape scales. It currently is not clear whether enough data exist to develop a data-driven CWD specific evolutionary ecology model or not. As part of this research, the Center would like to investigate the feasibility of a data driven CWD model versus a more theoretical approach. Once the approach is determined, an appropriate model structure will investigate the hypotheses using sensitivity analysis. Therefore, the overall objectives of this study are to 1) review literature to assess availability of parameters and feasibility of developing a data-driving CWD specific evolutionary ecology model while at the same time determine a reasonable structure for either a data-driven or a more theoretical model that would be informative about CWD; 2) develop a n appropriate model, analyze possible outcomes predicted by the model and perform sensitivity analysis; and 3) prepare results for publication in a peer-reviewed scientific journal. |
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 |
