Relative Bias in Catch Among Long-Term Fish Monitoring Surveys Within the San Francisco Estuary

Abstract

Fish monitoring gears rarely capture all available fish, an inherent bias in monitoring programs referred to as catchability. Catchability is a source of bias that can be affected by numerous aspects of gear deployment (e.g., deployment speed, mesh size, and avoidance behavior). Thus, care must be taken when multiple surveys—especially those using different sampling methods—are combined to answer spatio-temporal questions about population and community dynamics. We assessed relative catchability differences among four long-term fish monitoring surveys from the San Francisco Estuary: the Bay Study Otter Trawl (BSOT), the Bay Study Midwater Trawl (BSMT), the Fall Midwater Trawl (FMWT), and the Suisun Marsh Otter Trawl (SMOT). We used generalized additive models with a spatio-temporal smoother and survey as a fixed effect to predict gear-specific estimates of catch for 45 different fish species within large and small size classes. We used estimates of the fixed effect coefficients for each survey (e.g., BSOT) relative to the reference gear (FMWT) to develop relative measures of catchability among taxa, surveys, and fish-size classes, termed the catch-ratio. We found higher relative catchability of 27%, 22%, and 57% of fish species in large size classes from the FMWT than in the BSMT, BSOT, or SMOT, respectively. In the small size class, relative catchability was higher in the FMWT than the BSMT, BSOT, or SMOT for 50%, 18%, and 25% of fish species, respectively. As expected, relative catchability of demersal species was higher in the otter trawls (BSOT, SMOT) while relative catchability of pelagic species was higher in the midwater trawls (FMWT, BSMT). Our results demonstrate that catchability is a source of bias among monitoring efforts within the San Francisco Estuary, and assuming equal catchability among surveys, species, and size classes could result in significant bias when describing spatio-temporal patterns in catch if ignored.

Hydrodynamics and habitat interact to structure fish communities within terminal channels of a tidal freshwater delta

“…Although standardized protocols were used to sample during this study, issues of catchability are potentially a significant source of bias in our and other fish community analyses. Recent efforts in the San Francisco Estuary have demonstrated significant differences among fish species in their catchability using common surveying gears, and these differences can also be detected using the same gear types for similar fish species depending on fish life stage and the habitat types sampled (Huntsman et al, 2022; Huntsman, Feyrer, & Young, 2021; Huntsman, Feyrer, Young, Hobbs, et al, 2021; Mitchell et al, 2017; Mitchell & Baxter, 2021). We used gill nets during our sampling, which target active fishes and potentially bias our sampling toward fishes with active life‐history traits (Feyrer & Healey, 2002).…”

A Spatiotemporal History of Key San Francisco Estuary Pelagic Fish Species

“…Previous publications have identified the potential pitfalls of generating models using disparate datasets in an integrated format (Walker et al 2017; Moriarty et al 2020; Huntsman et al 2022). When unaccounted for, differences in survey effort, gear efficiency, and overall catchability can introduce significant biases in abundance and spatiotemporal density trends (Walker et al 2017; Huntsman et al 2022). However, our inclusion of survey as a fixed effect accounts for these biases, allowing separate intercepts to be fit for each of the eight surveys.…”

“…Catch per unit effort was calculated as total number of fish caught per seine or trawl, with a total of 103,341 sampling events. While other Estuary data integration efforts have instead chosen to index catch by the volume of water sampled (Huntsman et al 2022), not all surveys we include record this metric, nor is it as meaningful of a metric for some gear types (i.e. beach seines).…”

“…The often-piecemeal implementation of surveys complicates traditional analyses of species trends. In some cases, this results in underutilization of data due to concerns about differences in methodology and bias (Stompe et al 2020; Huntsman et al 2022). Unfortunately, logistical and/or financial limitations of surveys means that trends in abundance and distribution of estuarine species are often incomplete when based on analysis of a single survey.…”

A Framework for Evaluating the Effects of Reduced Spatial or Temporal Monitoring Effort

“…Understanding these effects is important for determining (1) the sensitivity of the estuary monitoring program to disruptions in sampling, and (2) whether sampling effort could be reduced without compromising the value of the information these surveys provide. Discovering redundancies in the sampling program could also help release resources to address issues of catchability (Huntsman and Mahardja 2021;Huntsman et al 2022) or redirect monitoring efforts to less-sampled regions, taxa, or habitats. In this study, I developed a framework for datafocused statistical evaluations of the estuary monitoring program.…”