Between a Rock and Soft Bottom: Evaluating the Use of Rod and Reel to Monitor Tautog in Southern Massachusetts

Abstract

Fishery‐independent trawl surveys are commonly used to monitor the status and trends of marine finfish species. Although bottom trawls are powerful sampling tools, they are limited to surveying relatively featureless bottom habitats and, as a result, may not accurately represent the trends in the relative abundance of fish species associated with structured and complex habitats. We evaluated the feasibility of rod and reel as an alternative fishery‐independent survey methodology to monitor the abundance of Tautog Tautoga onitis, a recreationally and commercially important structure‐dwelling reef fish, in the coastal waters of Massachusetts. Results suggest that a rod‐and‐reel survey is an effective, low‐cost approach to monitor the structured habitats inaccessible to trawl gears. Using a generalized linear mixed modeling framework we were able to identify important predictor variables influencing catch rates; variables that would be important in the design of a continued long‐term monitoring program and in the standardization of these data as an index of relative abundance. Variables retained in the top model included year, month, depth strata, bottom water temperature, tidal phase, fishing vessel, angler avidity, and random effects that accounted for the repeated measures survey design. Power analyses revealed that the directed rod‐and‐reel survey had far greater power to detect changes in Tautog abundance than the extant trawl survey, which had very little power to detect even large shifts in abundance. The results of this pilot study suggest that the continued use of rod and reel as a complementary survey tool would be warranted to further compare the trends in Tautog abundance generated using the two different survey methodologies, to reduce uncertainty in the stock assessment, and to improve the information upon which Tautog management is predicated in Massachusetts waters.

Climate alters the migration phenology of coastal marine species

“…Atlantic herring, tautog, northern searobin, and fourspot flounder did not exhibit a significant change in their residence times between the first and last 10 yr of the URI GSO trawl survey time series, although the residence times of Atlantic herring and fourspot flounder appeared to display larger shifts between these intervals. While tautog and Atlantic herring met the abundance thresholds to be included in this analysis, neither is well-sampled by bottom trawl gear (Jech & Sullivan 2014, Vidal et al 2018. The majority of the annual catch of fourspot flounder, which exhibited a significant shift toward earlier ingress (Table 3), and tautog occurs in early summer (Fig.…”

“…2), after which observations are less frequent. Tautog are known to spawn during this time period (Vidal et al 2018) and, based upon collections of young-of-the-year individuals in late fall in the URI GSO survey and in other surveys of the southern New England region (Sullivan et al 2000), it may be the spawning season for fourspot flounder as well. Therefore, it is possible that variable catchability or a link between detectability and spawning behavior affected the phenology observations of these 3 species.…”

A Habitat‐Based, Fishery‐Independent Survey Using Actively Fished Hooked Gear Successfully Characterizes Reef Fish Populations in the Eastern Gulf of Mexico

“…Vidal et al. (2018) is the only fishery‐independent hook‐and‐line study that we were able to find that accounted for angler effects within its sampling design. They included individual anglers as a random effect in their catch model, with angler avidity included as a covariate.…”

Upstream and Downstream Dispersal Behavior of Hard‐ and Soft‐Released Juvenile Atlantic Salmon

“…To test for the effect of water discharge rate (flow) on the daily number of detections, we fit the daily detection count data to a generalized linear model, assuming our response variable to be Poisson distributed and zero inflated (Vidal et al 2018), using mean daily discharge rate and treatment as predictor variables and an interaction term between the two predictor variables.…”