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Less effort but equal result: Introducing the daily run-size estimation method for quantifying fish passage in
Mariana O Côrtes1, Alexandre Peressin1, Alexandre L Godinho1
1Fish Passage Center, Zoology Department, Federal University of Minas Gerais, Belo Horizonte, MG, Brazil.
Plos One
|May 26, 2021
Summary
The new daily run-size estimation (DARSE) method efficiently counts fish in fishways. This sampling technique significantly reduces labor and costs for fisheries management by optimizing data collection frequency.
Area of Science:
- Fisheries Science
- Conservation Biology
- Ecological Monitoring
Background:
- Accurate fish passage counts are vital for fisheries management.
- Traditional fish counting methods are often labor-intensive and costly.
- Efficient methods are needed to estimate daily fish run sizes through fishways.
Purpose of the Study:
- To introduce and evaluate the daily run-size estimation (DARSE) method for estimating fish passage.
- To determine the minimum sampling fraction required for accurate daily run size estimation.
- To assess the impact of sampling strategy on efficiency and accuracy for different fish species.
Main Methods:
- The study employed the daily run-size estimation (DARSE) method using systematic sampling.
- Video data from the Igarapava Fish Ladder, Brazil, over 46 days were analyzed.
- DARSE was applied to seven abundant fish species and a group of 'Others' to estimate daily run size (D).
Main Results:
- The DARSE method successfully estimated daily fish run sizes with known accuracy.
- Sampling efficiency varied based on species' temporal passage patterns and desired accuracy.
- For species with uniform passage, sampling time was reduced by up to 96% by adjusting hourly sampling frequency.
Conclusions:
- The DARSE method offers a significant reduction in sampling effort for fishway monitoring.
- Optimized sampling frequencies, guided by DARSE, enhance the cost-effectiveness of fisheries management.
- The method's effectiveness is influenced by species-specific passage behaviors, requiring tailored sampling strategies.
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