San Francisco Estuary and Watershed Science
Estimating the Size Selectivity of Fishing Trawls for a Short-Lived Fish Species
- Author(s): Mitchell, Lara
- Newman, Ken
- Baxter, Randall
- et al.
Published Web Locationhttps://doi.org/10.15447/sfews.2019v17iss1art5
Long-term fish survey monitoring programs use a variety of fishing gears to catch fish, and the resulting catches are the basis for status and trends reports on the condition of different fish stocks. These catches can also be part of the data used to set stock assessment models, which establish harvest regulations, and to fit population dynamics models, which are used to analyze population viability. However, most fishing gears are size-selective, and fish size — among other possible covariates, such as environmental conditions — affects the probability that a fish will be caught in the path the gear sweeps. Failing to properly account for selectivity can adversely affect the ability to interpret and use status and trends measures, stock-assessment models, and population-dynamics models. Our side-by-side gear comparison study evaluated the selectivity of multiple open-water trawl surveys that have provided decades worth of information on the imperiled fish species Delta Smelt (Hypomesus transpacificus). We used data from the study to estimate gear selectivity curves for multiple trawls using two methods. The first method examines the total number of fish-at-length caught across all gears, and does not directly use or estimate fish length distribution in the population. The second method examines the total number of fish caught by each gear separately, and explicitly estimates fish length distribution in the population. The results from the two methods were similar, and we found that one trawl was highly efficient at catching larger Delta Smelt. This is the first formal multi-gear evaluation of how well survey gear used to monitor Delta Smelt in the San Francisco Estuary selects fish by size, and we plan to incorporate the results into Delta Smelt population models.