Influence of soak time and fish accumulation on catches of reef fishes in a multispecies trap survey

Abstract

Abstract-Catch rates from fisheryindependent surveys often are assumed to vary in proportion to the actual abundance of a population, but this approach assumes that the catchability coefficient (q) is constant. When fish accumulate in a gear, the rate at which the gear catches fish can decline, and, as a result, catch asymptotes and q declines with longer fishing times. We used data from long-term trap surveys in the southeastern U.S. Atlantic to determine whether traps saturated for 8 reef fish species because of the amount of time traps soaked or the level of fish accumulation (the total number of individuals of all fish species caught in a trap). We used a deltageneralized-additive model to relate the catch of each species to a variety of predictor variables to determine how catch was influenced by soak time and fish accumulation after accounting for variability in catch due to the other predictor variables in the model. We found evidence of trap saturation for all 8 reef fish species examined. Traps became saturated for most species across the range of soak times examined, but trap saturation occurred for 3 fish species because of fish accumulation levels in the trap. Our results indicate that, to infer relative abundance levels from catch data, future studies should standardize catch or catch rates with nonlinear regression models that incorporate soak time, fish accumulation, and any other predictor variable that may ultimately influence catch. Determination of the exact mechanisms that cause trap saturation is a critical need for accurate stock assessment, and our results indicate that these mechanisms may vary considerably among species.

Spatial and Temporal Patterns of Black Sea Bass Sizes and Catches in the Southeastern United States Inferred from Spatially Explicit Nonlinear Models

“…Moreover, large Black Sea Bass have not been observed excluding small Black Sea Bass from entering traps, and asymptotic catch of Black Sea Bass is highly related to local abundance (Bacheler et al 2013b(Bacheler et al , 2013c. Catch of small or large Black Sea Bass was fourth-root transformed, which resulted in better model fit than any other types of transformations or error distributions using standard model diagnostics (e.g., Bacheler et al 2013a). Unlike the length model described above, chevron traps that did not catch any Black Sea Bass were included in the catch models.…”

“…Thus, the base length model ("Base length ") was formulated as: where z doy,y,pos is the log-transformed mean TL of Black Sea Bass on day of the year doy in year y at spatial position pos, temp is bottom temperature, f 1 is a categorical function, g 1-5 are nonparametric smoothing functions, and e doy,y,pos is the 526 random error assumed to be normally distributed with a mean of zero and finite variance. Catch models were coded similarly except five additional variables were included based on the results of Bacheler et al (2013a). Station type was included as a factor variable and described any potential variation in catch between randomly selected stations and those newly found and sampled for the first time.…”

“…The overall influence of predictor variables on mean length or catch of Black Sea Bass was calculated using a bootstrapping approach described by Bacheler et al (2013a). Briefly, we resampled the predictions (N D 10,000) for each model at mean values of all other predictor variables according to the pointwise estimates of error that were assumed to be normally distributed.…”

The effect of random and density‐dependent variation in sampling efficiency on variance of abundance estimates from fishery surveys

“…However, limited observations by O'Driscol et al (), Hoffman et al (), and Kotwicki et al () indicate that q may be affected by gear avoidance behaviour or trawl saturation. Gear saturation has been also known to affect the CPUE of gear such as pots or traps (Bacheler, Bartolino, & Reichert, ), longlines (Rodgveller, Sigler, Hanselman, & Ito, ) and gillnets (Li, Jiao, & He, ), indicating that density‐dependent effects should be considered when obtaining AIs from surveys using these gears. The prevalence of density‐dependent effects on q in fishery surveys worldwide is unknown, but given the results of existing studies, we conclude that it may be common and should be considered in future for all fishery surveys and stock assessments.…”

Investigating three sources of bias in hook-and-line surveys: survey design, gear saturation, and multispecies interactions

“…However acoustic surveys cannot adequately resolve demersal species in the acoustic dead zone near the ocean floor (Ona and Mitson 1996;Patel et al 2009) and require additional extractive sampling to confirm species identification and collect biological information such as length, sex, age, and genetic data. Trap surveys are most useful for crabs and lobsters that are commercially caught using the same gear, but are affected by trap saturation (Fogarty and Addison 1997;Bacheler et al 2013aBacheler et al , 2013b) and other factors. Visual survey methods, including divers and underwater vehicles, are nonlethal and can collect both habitat information and species information (Yoklavich et al 2000(Yoklavich et al , 2007.…”