Amending survey design to improve statistical inferences: Monitoring recruitment of juvenile reef fish in the eastern Gulf of Mexico
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Amending survey design to improve statistical inferences: Monitoring recruitment of juvenile reef fish in the eastern Gulf of Mexico

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Details:

  • Journal Title:
    Fisheries Research
  • Description:
    Many species of interest to management and conservation remain data-limited, and the data that are available are often unable to produce statistically reliable population trends. We examined 10 years of juvenile reef fish catch data from two gear-specific, fishery-independent surveys in the eastern Gulf of Mexico to assess our ability 1) to characterize population trends for various reef species sampled using haul seines or otter trawls and 2) to amend our survey, as logistics would allow, to improve those characterizations. Species richness, catch-per-unit-effort, and length-frequency distributions were generally similar between gear types, suggesting a single survey (i.e., one gear type) may be sufficient. Simulation-based power analyses for the reef fish species indicated that overall, otter trawl data provided greater power for detecting trends over a 10-year period (41–75 % probability to detect a 50 % change in abundance) than haul seine data (27–52 %). Likewise, otter trawl data provided greater power for detecting trends from one year to the next (22–53 % probability to detect a 50 % change in abundance in one year) than haul seine data (15–33 %). Simplifying data collection from two surveys to a single, trawl-only survey (and approximately doubling the number of trawl tows) was more efficient, more effective, and more powerful (64–91 % for the amended design with more tows) in detecting abundance trends. Furthermore, by increasing sample size but retaining all other design elements, the data collected during the trawl survey before and after the change remain comparable; the time series was not interrupted. These changes increase our confidence in estimating population trends, predicting productivity, and informing management and conservation decisions.
  • Source:
    Fisheries Research, 241, 106015
  • ISSN:
    0165-7836
  • Format:
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  • Rights Information:
    Accepted Manuscript
  • Compliance:
    Library
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