Efficiency estimates from depletion experiments for sedentary invertebrates: evaluation of sources of uncertainty in experimental design
Introduction
The ocean quahog (Arctica islandica) and the Atlantic surfclam (Spisula solidissima) support substantial fisheries on the northeast U.S. continental shelf. Hydraulic dredges are the commercial gear exclusively used by the commercial fishery and for the stock assessment survey. Ocean quahogs are reputed to be the longest-lived non-colonial marine species (Butler et al., 2013) - they are certainly the most abundant of the very-long-lived species - and, on the U.S. East coast continental shelf, are typically found offshore in deep water, between 30 m and 220 m (NEFSC (Northeast Fisheries Science Center), 2017b) with life spans exceeding 250 years (Pace et al., 2017). The Atlantic surfclam has a lifespan of about 30 years and is found in more inshore waters, typically between 8 and 66 m depth (NEFSC (Northeast Fisheries Science Center), 2017a). They coexist with ocean quahogs along their offshore range boundary that approximately follows the 15 C summer bottom water temperature isotherm (NEFSC (Northeast Fisheries Science Center), 2017b; Powell et al., 2020). Surveys conducted in the 2000s show evidence that a range shift is occurring as the western North Atlantic warms, with surfclams invading deeper water, presently often occupied by ocean quahogs, throughout the mid-Atlantic region (Hofmann et al., 2018; Powell et al., 2020).
The ability to accurately estimate abundance from the National Marine Fisheries Service (NMFS) ocean quahog (Arctica islandica) and Atlantic surfclam (Spisula solidissima) stock assessment surveys benefits from empirical estimates of the efficiency of the survey dredge (NEFSC (Northeast Fisheries Science Center), 2003; Powell et al., 2007). However, efficiency is a key source of uncertainty in stock assessments. Efficiency estimates are notoriously variable (Vølstad et al., 2000; Powell et al., 2007; Hennen et al., 2012; Morson et al., 2018) at least in part because little is known about how experimental variables can influence the efficiency of a dredge. Gear efficiency is defined as the probability that an organism in an area intersected by the dredge will be caught (Hennen et al., 2012). Efficiency estimates have been obtained for a range of dredge types, including oyster dredges (Powell et al., 2007; Morson et al., 2018), crab dredges (Vølstad et al., 2000; Bohrmann and Christman, 2012; Wilberg et al., 2013), and scallop dredges (Beukers-Stewart and Beukers-Stewart, 2009; Lasta and Iribarne, 1997). These are all dry dredges designed to harvest epibenthic animals. In contrast, hydraulic dredges are designed to harvest infaunal clams by using water pressure to liquefy the sediment, thereby penetrating deeply into the sediment and exhuming the clams (Da Ros et al., 2003; Hauton et al., 2007; Meseck et al., 2014). Hydraulic dredges are efficient in comparison to dry dredges (Thórarinsdóttir et al., 2010).
A typical hydraulic dredge is a large rectangular box constructed of steel bars evenly spaced apart mounted on skids and towed along a seabed (Lambert and Goudreau, 1996; Meyer et al., 1981). A cutting blade in front of the dredge digs into the sediment as high-pressure water is pumped through a series of jets from a manifold, serving to liquefy the sediment, thus permitting the dredge to be towed with little resistance through the surficial sediment and thereby increasing the catchability of the target bivalve species (Gilkinson et al., 2003). Parker (1971) provides a historical account of the development of hydraulic dredges in the surfclam fishery.
Despite the increased focus on quantitative stock assessments in recent years and the industrial success of the hydraulic dredge, gear efficiency is still an uncertain parameter that is affected by many variables, including spatial characteristics such as the size frequency of clams in the population and the patchiness of clams in the benthos. Little is known about exactly how these factors might cause variation in efficiency estimates for hydraulic dredges.
Depletion experiments are commonly used to estimate gear efficiency and density of the target organism in the benthos (Leslie and Davis, 1939; Skalski et al., 1983; Lasta and Iribarne, 1997; Gedamke et al., 2005; Wilberg et al., 2013). Depletion experiments consist of deploying the gear multiple times in a target area, allowing the catch per tow to decline as a result of decreasing organism density. This rate of decline is used to estimate gear efficiency and the initial abundance of the organism.
A series of depletion experiments was conducted between 1997 and 2013 by academic and industry collaborators on commercial and survey vessels to estimate the efficiency of the commercial clam dredges and infer the efficiency of the National Marine Fisheries Service survey dredge (NEFSC (Northeast Fisheries Science Center), 2010c, 2013). The depletion experiments were carried out at locations specified in Appendix 3 of NEFSC (Northeast Fisheries Science Center) (2017a).
The Patch Model (Rago et al., 2006) was developed to analyze depletion experiments and estimate gear efficiency, stock abundance, and dispersion of organisms in a target area. The Patch Model has been important in informing stock assessments of commercially exploited populations of Atlantic surfclam, ocean quahog, monkfish (Lophius americanus) and Atlantic sea scallop (Placopecten magellanicus; (NMFS (National Marine Fisheries Service), 2009; NEFSC (Northeast Fisheries Science Center), 2010b, 2010a). Hennen et al. (2012) examined the performance of the Patch Model under a range of conditions and found that uncertainty in dredge position and distribution of dredge tow overlap in the experimental area were important contributors to the uncertainty in estimates of dredge efficiency.
The correction for dredge efficiency continues to be a primary source of uncertainty in the estimation of stock abundance for both clam species. In this study, we extend the analytical approach of Hennen et al. (2012) to develop metrics that can be used to guide retrospective evaluation of the effectiveness of experimental design of previous depletion experiments and to proffer an improved experimental design for future dredge efficiency estimates. To do so, a simulation protocol (Hennen et al., 2012) is implemented to test Patch Model efficiency estimates under a variety of conditions involving experiment methodology and dispersion and density of the target species to ascertain the characteristics of depletion experiments that contribute to the accuracy of efficiency estimates.
Section snippets
The Patch Model
The Patch Model estimates capture efficiency (the probability of capture of an organism intersected by the dredge), and density of organisms in the target area (numbers per m2) by tracking the relative depletion (reduction in catch) over the tow series. Capture efficiency is theoretically a measurable characteristic of the gear. Here, we examine the influence of the number of tows in an experiment, the distribution of organisms in the benthos, the density of organisms in the benthos, the degree
Effects of tow number per simulation, clam density, and clam distribution on efficiency
Simulations with higher numbers of tows and more even distributions of clams produce more reliable efficiency estimates. Clam density does not influence the accuracy of the efficiency estimate, but it can combine with an irregular clam distribution to increase the uncertainty in the efficiency estimate. At an inherent efficiency of 0.6, clam distribution, tow number, clam density, and their pairwise interaction terms significantly affected the error in efficiency estimates (Table 1). At
Discussion
The simulations show that low tow number, certain patchy distributions, and low effective area swept (EAS) generate the largest deviations in estimated efficiency from the true efficiency. Uniform clam distributions and high tow numbers which also ordinarily generate low EAS (indicating more dredge overlap) routinely conduce highly accurate efficiency estimates. Save for rare occurrences, clam density has no significant influence on the efficiency estimate.
The error in efficiency estimates, the
Funding
This research was supported by the National Science Foundation (NSF) Science Center for Marine Fisheries (SCeMFiS)under NSF award 1266057 and through membership fees provided by the SCeMFiS Industry Advisory Board. This article is based, in part, on a thesis submitted by the senior author for fulfillment of the Master of Science degree at The University of Southern Mississippi.
CRediT authorship contribution statement
Leanne M. Poussard: Software, Investigation, Formal analysis, Writing - original draft, Visualization. Eric N. Powell: Conceptualization, Software, Formal analysis, Validation, Resources, Writing - review & editing, Funding acquisition. Daniel R. Hennen: Software, Formal analysis, Resources, Writing - review & editing.
Declaration of Competing Interest
The authors reported no declarations of interest.
Acknowledgments
The authors thank Dr. Paul Rago and Dr. Larry Jacobson for their contributions to developing and using the Patch Model and depletion experiment design. We thank the captains, crew, and scientific staff aboard the vessels who worked for hours participating in field depletion experiments used to inform this study. We thank the Science Center for Marine Fisheries (SCeMFiS) member organizations for providing detailed information on vessel characteristics for all vessels involved in depletion
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Sampling high biomass but rare benthic animals: Methods for surveying commercial clam stocks using a hydraulic dredge
2023, Fisheries ResearchCitation Excerpt :Capture efficiency of survey gear (the fraction of clams caught by the gear relative to the total on the bottom), and the catchability coefficient (the inverse of capture efficiency) (Morson et al., 2018), are used to convert the catch observed by the gear to the true abundance on the bottom and are an important source of uncertainty in stock assessments (Thorarinsdóttir et al., 2010). Efficiency can be estimated directly using depletion experiments (Latsa and Iribarne, 1997; Gedamke et al., 2004; Rago et al., 2006; Hennen et al., 2012; Wilberg et al., 2013; Poussard et al., 2021). Capture efficiency of many types of fishing or sampling gear will vary spatially (Powell et al., 2002, 2007; Doray et al., 2010; Marenghi et al., 2017) and temporally (Walters and Martell, 2004; Powell et al., 2007), likely due to changes in abundance, stock area, the environment, and the sampling gear itself (Wilberg et al., 2010).
Potential highly variable catch efficiency estimates complicate estimation of abundance
2022, Fisheries ResearchCitation Excerpt :The influence of potential gear positional error was tested by re-running the Patch Model a further 40 times for each lane, whilst randomly adjusting each observed vessel position up to 12 m (Appendix Methods). Next, the influence of patchiness and scallop distribution were tested by simulating a scallop population in each lane that conformed to a specified distribution, and then simulating catches based on haul paths, similar to Hennen et al. (2012) and Poussard et al. (2021) (Appendix). The three scallop distributions tested were patchy, half of the lane populated and entirely random placement (Appendix).