Biological and Economic Optimization of Shell Size and Timing for Sea Scallop (Placopecten magellanicus) Ear-hanging in the Northeast U.S.

The proposed plan of work can be divided into two discrete sections, a biological and an economic component. We plan to combine the results from both sections to parameterize a bioeconomic model of scallop ear-hanging. 

1.Biological analysis of size grading and ear-hanging timing on scallop growth and mortality

We will take a nested effects approach to determine whether timing and/or size improve ear-hanging production through effects on growth and mortality. This experiment will involve two treatments. The first treatment will be the date on which the scallops are graded, drilled, and pinned to dropper lines. We plan to perform this task on three separate occasions: once each in April, May, and June. These three dates simulate when growers ear-hang early (April), a typical example (May), and a late example (June). Every month that growers must hold scallops in lantern nets prior to ear-hanging is a use of valuable time and net space. Ear-hanging "early" (April) can expedite the process and maximize grow-out time spent on ear-hanging lines. However, the process of grading, drilling, and pinning can be stressful to juvenile scallops, and allowing more time for shell growth and ear-hanging "later" (June) may lead to better survival in the long term. On each date, we will use the various screen diameters compatible with the grader to sort scallops into three distinct size classes: 38 - 48 mm (small), 49 - 59 mm (medium), and >60 mm (large). These size grades comprise the second treatment, and will allow us to test the hypothesis that larger scallops are more capable of surviving the physiologically stressful ear-hanging process. We will ear-hang 2 replicate dropper lines of each size class on each date for a total of 18 dropper lines (900 scallops total) from April - June. We will use calipers to measure the shell height of all scallops on each line (n = 50) on each date that they were ear-hung (April, May, or June) to establish initial conditions. Over the course of the following 5 months, we will measure the shell height of all experimental scallops (ear-hung on all dates) once each in August and October. We will also count the number of scallops remaining on each line, as well as dead scallops still attached to the line, to track mortality. On the final measurement date in October, we will dissect a representative sample (n=30) from each experimental treatment (date x size class) to assess final adductor muscle, gonad, and viscera (all remaining tissue) mass. 

The grader will also allow us to efficiently capture the size distribution of scallops within nets prior to ear hanging. While this is a sub-objective of the current plan of work, it will provide valuable insight that complements the main objectives. The mean shell height (the distance from the "hinge" to the furthest edge of the shell) of scallops within a net is a useful metric for growers to track growth over the course of a season. However, if we are able to observe an effect of size grade and timing on growth or mortality in our experiment, understanding the breakdown of sizes within nets will be a useful tool that can allow growers to track inventory and the availability of different size scallops at different points in the year. On each date (April, May, June), we will grade out all scallops within a representative sample of lantern nets based on the same 38 - 48 mm (small), 49 - 59 mm (medium), and >60 mm (large) size classes. The quantity of scallops within each size class will be assessed volumetrically.

We plan on utilizing a variety of statistical analyses to determine whether size grade or date will have an effect on scallop performance. We will calculate shell height specific growth rate, the percent change in shell height per day, for each replicate line based on the average shell height on each measurement date. This metric will allow us to standardize growth between scallops of different starting sizes. We will also calculate a mortality rate (% mortality per day). Finally, we will standardize the final wet weight of the various soft tissue components we measure by shell height to compare between scallops in different treatments that may vary by size. We will then use a two-way (date x size class) analysis of variance (ANOVA), to determine differences in specific growth rate, mortality, and tissue mass between experimental treatment groups. 

2. Economic analysis of ear-hanging

Based on the values obtained from the biological component of the study, the growth and mortality rates, as well as the labor and capital cost requirements over the course of the ear-hanging sessions, we plan to parameterize a bioeconomic model of scallop ear-hanging. Given that detailed information on the procedural and cost requirements of juvenile scallop culture (the first year of growth in nets) already exists (see Previous Work, Coleman et al., unpublished), the proposed work would fill in the ear-hanging specific data that is currently unavailable in the Gulf of Maine. The most important variable in the bioeconomic model will be the labor component. Specifically, we will track the quantity of scallops ear-hung over the course of the project (April - June) as a function of labor (time and personnel) under normal operations of the partner farmer's business. Normal operations in this sense exclude any time dedicated to measuring scallops or recording data. At the end of the project, we will work with Mr. Peters to sum materials costs, labor, and capital expenditures amortized over the lifespan of the equipment. We will also project growth and mortality, based on the biological component of the project, to inform final yield. Based on these inputs, our goal is to arrive at a cost of production figure (USD scallop-1) using a simple spreadsheet based financial model. This information (cost of production) is already available for net cultured scallops, and will provide a useful comparison of the two methods directly relevant to industry members. 

We will use the financial model to explore sensitivities across a range of parameters tested in the biological portion of the study. For example, if we observe a relationship between ear-hanging date and mortality, we will be able to simulate the effects of the full range of mortality rates on cost of production using the financial model. Additionally, if we deduce that the grader improves efficiencies during the ear-hanging process, we can use the financial model to quantify the magnitude of these efficiencies. We will track changes in cost of production under a variety of growth, mortality, timing (ear-hanging date), and final yield (adductor muscle wet weight) scenarios.