Statistical Evaluation of Adaptive Management Study Duration
Sector: Aerospace & Defense • Location: United States of America
Source: Grants.gov
The project will be a collaborative study between selected CESU and the Corps of Engineers (Corps). The purposes of the project are to: 1. Conduct a statistical power analysis to detect changes in native fish populations in Pool 22 of the UMR. 2. Identify indicator species of fish to guide future monitoring efforts. 3. Provide statistical evidence to support the effort required for future
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Participants
Sponsoring Agency | Obfuscated Data |
Company | Obfuscated Data |
Status
Original status | closed |
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 project will be a collaborative study between selected CESU and the Corps of Engineers (Corps). The purposes of the project are to: 1. Conduct a statistical power analysis to detect changes in native fish populations in Pool 22 of the UMR. 2. Identify indicator species of fish to guide future monitoring efforts. 3. Provide statistical evidence to support the effort required for future performance monitoring. Work associated with this project (Task 1) includes: 1. Determining if a change in fish population can be detected in Pool 22 and adjacent Pools of the UMR. a. Identify indicator species of fish. These may contain (but are not limited to): i. Native fish of special interest: · Bigmouth Buffalo · Blue Catfish · Lake Sturgeon · Paddlefish · Shovelnose Sturgeon · Smallmouth Buffalo ii. Invasive fish of special interest: · Silver Carp 2. Using catch per unit effort (CPUE) from long term electrofishing data in Pool 22 and adjacent Pools of the UMR to determine the numbering of sampling sites per sampling period needed to detect a change in fish populations for a range of scenarios: a. Consider multiple sampling scenarios b. Percent population change scenarios: i. 30% change in population ii. 15% change in population c. Power scenarios: i. 80% with 95% confidence interval ii. 90% with 95% confidence interval 3. A summary report containing the findings of the statistical evaluation, data used as a part of this effort, and recommendations for future performance monitoring. Work associated with this project (Task 2) includes: Task 2: Collect and evaluate long term electrofishing data from multiple sites in Pool 22 in Fiscal year 2026 using stratified random sampling techniques. a. A summary report of data collected as a part of this effort. (Optional) Work associated with this project (Task 3) includes: Task 3: Collect and evaluate long term electrofishing data from multiple sites in Pool 22 in Fiscal year 2027 using stratified random sampling techniques. b. A summary report of data collected as a part of this effort. Roles and Responsibilities : The selected CESU will: 1) obtain, process, and analyze long term electrofishing data from the Upper Mississippi River; 2) determine if random stratified sampling methods can be used to detect changes in fish populations; 3) conduct a power analysis to determine the number of sampling sites per period by species needed to detect a population change in fish in Pool 22; 4) provide quarterly project updates to the Corps on study methods, results, and interpretation; 5) collect and evaluate additional data using the same stratified random techniques. |
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
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Article Published Date | Obfuscated Data |
