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Lake Tahoe Basin Thermal Variability Analysis

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The Lake Tahoe Basin Thermal Variability Analysis is a subcontract through the US Geological Survey under the Department of the Interior. The project focuses on performing advanced data analysis of thermal regimes and their subsequent impacts on aquatic ecosystems. The selected contractor will analyze long-term Forest Service monitoring data to identify ecological thresholds, evaluate trends, and determine the primary drivers of thermal patterns. All work must be conducted in strict adherence to USGS Fundamental Science Practices and established peer-review guidelines. The primary deliverables for this engagement include comprehensive data analyses and the production of peer-reviewed manuscripts. The opportunity was posted on October 30, 2026, with a response deadline of November 30, 2026, falling under NAICS code 541720.

General Info

USGS subcontract for Lake Tahoe thermal analysis, data evaluation, and peer-reviewed manuscripts.

Agency

Department Of The Interior → US Geological Survey

Place of Performance

Not specified

Set-Aside

NONE

Documents

This scope was carved out of G27AS00045.

The full solicitation package (5 documents), including the RFP, is on the prime solicitation, not on this scope.

View the prime solicitation

Cooperative Agreement for affiliated Partner with Great Basin Cooperative Ecosystem Studies Unit

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Timeline

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Organization & Contact Information

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AgencyDepartment Of The Interior → US Geological Survey
ContactsNo contacts available
OfficeN/A
Organization / Agency
Department Of The Interior → US Geological Survey
Office AddressN/A
ContactsNo contact information available

Full Description

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Performs advanced data analysis of thermal regimes and aquatic ecosystem impacts for prime contractors on USGS research projects. Analyzes long-term Forest Service monitoring data to evaluate trends, identify ecological thresholds, and determine drivers of thermal patterns. Adheres to USGS Fundamental Science Practices and peer-review guidelines. Delivers data analyses and peer-reviewed manuscripts.

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