An evaluation of survey designs and model-based inferences of fish aggregations using active acoustics

Abstract

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“Star” survey designs have become an increasingly popular alternative to parallel line designs in fisheries-independent sampling of areas with isolated fish aggregations, such as artificial reefs, seamounts, fish aggregating devices, and spawning aggregation sites. In this study, we simulated three scenarios of fish aggregating around a feature of interest with variations in the size and complexity of aggregations as well as their location relative to the habitat feature. Simulated and empirical data representing goliath grouper (Epinephalus itajara) spawning aggregations at artificial reefs were utilized as a case study, and scenarios were generated in relation to both a single habitat feature and a reef complex with multiple structures. Seven variations of survey design using both star and parallel transects were examined and compared by geostatistical and generalized additive models (GAMs) to identify the most robust approach to quantify fish aggregations in each scenario. In most scenarios, precision in the mean and variability of backscatter estimates is not significantly affected by the number of transects passing over the habitat feature as long as at least one pass is made. Estimation error is minimized using the GAM approach, and is further reduced when sampling variance is high, which was better accomplished by parallel designs overall. These results will help inform surveyors on the best overall approach to improve precision in quantifying fish aggregations given basic knowledge of their behavior around an established habitat feature and help them to adapt their survey designs based on common difficulties in sampling these populations simulated below.

Keywords

• fish aggregations
• active acoustics
• survey design
• star surveys
• model-based inference
• generalized additive models