Assessing Impacts of Operations on Fish Reproduction in Missouri River Reservoirs

Abstract

This report describes a method for predicting impacts of system- operating alternatives on fish reproduction in six Missouri River reservoirs (Fort Peck, Sakakawea, Oahe, Sharpe, Francis Case, and Lewis and Clark). Effects of seasonal or annual variations in reservoir hydrology on catches of young-of- year (YOY) fish in summer were quantified using correlation and regression analyses. Software was developed that predicts YOY catch and calculates a fish reproduction index (RI) for every possible year in the 93-year period of record (1898-1990) and any operational alternative. The method allows users to evaluate operational alternatives by comparing results from a long chronology of predicted indices. Small sample sizes and poor correlations between YOY fish catch and most fish stocking variables kept researchers from using stocking variables as covariates in regression analyses. Despite data limitations, the number of fingerling walleye stocked apparently is a legitimate covariate. The YOY walleye catch in Lake Sakakawea was adjusted to include only nonstocked YOY as a dependent variable. This adjustment resulted in a much stronger relation between YOY catch and change in area from April through June than when catch consisted of both stocked and naturally produced walleye. Correlation of YOY catch with weather variables yielded few consistent or useful results, and weather variables were not used in regression analyses. Fish, Modeling, Reservoir, Impact assessment, Operations, Water level, Missouri River, Reproduction

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1993
Accession Number
ADA273465

Entities

People

  • Cliff C. Stone
  • Dennis G. Unkenholz
  • Gene R. Ploskey
  • Greg J. Power
  • Mark C. Harberg

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Data Science
  • Environment
  • Fish
  • Fisheries
  • Habitats
  • Information Science
  • Missouri River
  • Regression Analysis
  • Statistical Analysis
  • Statistics
  • United States
  • Wildlife

Fields of Study

  • Environmental science

Readers

  • Aquatic Ecology
  • Archaeological Resource Survey
  • Computational Modeling and Simulation