Final Report Period covered by Report: 05/01/2018 - 4/30/2019 Sea Scallop Research NOAA Grant Number: NA18NMF4540018 Award Date: 5/1/2018 End Date: 4/30/2019 Project Title: High resolution drop camera survey examining sea star dynamics in extremely dense scallop beds of the Nantucket Lightship Closed Area Principal Investigators: Kevin D. E. Stokesbury, Ph.D., N.David Bethoney, Ph.D., Craig A. Lego, M.S. candidate Address: School for Marine Science and Technology, University of Massachusetts Dartmouth, 836 S. Rodney French Blvd. New Bedford, MA 02744 Phone: (508) 910-6373 Fax: (508) 910-6374 Email: [email protected] Amount: We were allocated 38,288 lbs. ($421,171) for research and compensation. Project Summary: The goal of this project was to investigate sea scallop and sea star predator- prey interactions and produce a 2018 biomass estimate of scallops to aid in management of the area. We surveyed the Nantucket Lightship Closed Area (NLCA) with a centric systematic design resulting in 509 stations sampled in 2018. We produced spatial specific estimates and associated error of scallop size as well as maps of exploitable and juvenile scallop distributions at the time of the survey. This information was supplied to the New England Fisheries Management Council and the National Marine Fisheries Service and included in the annual scallop allocation setting process. To investigate predator-prey interactions station and quadrat level data from 2010-2018 were utilized. Scallop and sea star density, ratio, and size trends at the spatial scale of the NLCA indicate an extremely high scallop recruitment event in this area linked to decreases in sea star densities. Additionally, Morisita’s indexes show similar increases and decreases in aggregation of scallops and sea stars following this extreme recruitment event. At smaller spatial scales scallops and sea stars were found clustered within 130 cm or less of each other. This increase in proximity could lead to more encounters and possibly captures of sea scallops by sea stars in densely populated beds created after extremely high recruitment events. 2 Project Goals: The goal of this project was to investigate the effects of extreme recruitment of juvenile sea scallops in relation to the distributions, abundance and predator-prey interactions of predatory sea stars in the Nantucket Lightship Closed Area (NLCA) on Georges Bank and produce a biomass estimate of scallops to aid in management of the area. Objectives and Deliverables: • Identify if predatory sea stars are aggregating and persisting in extreme recruitment areas in the Nantucket Lightship Closed Area: Results will include 1) spatial and size specific estimates of sea stars and scallops, 2) maps of adult and juvenile scallop distributions in addition to sea star distributions within the Nantucket Lightship and 3) densities of individuals in m2. • Examine spatial relationships between sea stars, juvenile and adult scallops in the Nantucket Lightship Closed Area: Results will include 1) nearest neighbor analysis 2) correlation analysis of sea scallops and sea stars on multiple different spatial scales. • This project will also produce an additional year of estimates of total, exploitable sea scallop biomass and mean meat weight (g) at the time of the survey. Mean meat weight (g) will be derived from shell height(mm) frequencies and shell height to meat weight regressions used in the 50th Scallop Stock Assessment Workshop (SAW) or as specified by the New England Fisheries Management Council Scallop Plan Development Team. Estimates of total and exploitable biomass of scallops will be derived from area-specific shell heights and meat weight relationships, and commercial dredge selectivity equations (NEFSC 2010) and presented to the Scallop PDT on 1 August 2018. Habitat characteristics will also be recorded. Methods: We surveyed the Nantucket Lightship Closed Area on a 2.8 km (1.5 nmi) grid totaling approximately 509 stations. These stations were sampled as part of two research cruises (Figure 1). During each survey, the SMAST sampling pyramid, supporting cameras and lights was deployed from a commercial fishing vessel (Stokesbury 2002, Bethoney and Stokesbury 2018, Figure 2). A mobile studio including monitors, computers for image capturing, data entry, and survey navigation (software integrated with the differential global positioning system) was assembled in the vessel’s wheelhouse. The vessel stopped at each pre-determined station and the pyramid was lowered to the sea floor. Two downward facing cameras mounted on the sampling pyramid provided 2.3 m2 and 2.5 m2 quadrat images of the sea floor for all stations (Figure 2). Additionally, a third camera providing a 0.6 m2 view of the seafloor was deployed. Quadrat images from all cameras and video footage from the 2.5 m2 quadrat view of the first quadrat were saved and then the pyramid was raised, so the seafloor was longer seen. The pyramid was then lowered to the seafloor again to obtain a second quadrat; this was repeated four times at each station. Onboard the survey vessel, scallop counts, station location, and depth was recorded and saved through a specialized field application for entry into a SQL Server Relational Database Management System. 3 Figure 1. SMAST drop camera stations in 2018 displayed by vessel with survey dates. Figure 2. University of Massachusetts Dartmouth, School for Marine Science and Technology drop camera survey pyramid including cameras and lights used for data collection with the area of each quadrat. 4 After the survey, the 2.3 m2 high resolution digital still images were used as the primary data source. Within each quadrat, scallops and other macrobenthos were counted and the substrate was identified (Stokesbury 2002, Stokesbury et al. 2004, Bethoney and Stokesbury 2018). Scallop shell heights were also measured at this time. After the images were digitized, a quality assurance check was performed on each image for accuracy of counted and identified species. Sediments in digital still images were visually identified following the Wentworth particle grade scale from images, where the sediment particle size categories are based on a doubling or halving of the fixed reference point of 1 mm; sand = 0.0625 to 2.0 mm, gravel = 2.0 to 256.0 mm and boulders > 256.0 mm (Lincoln et al. 1992). Gravel was divided into two categories, granule/pebble = 2.0 to 64.0 mm and cobble = 64.0 to 256.0 mm (Lincoln et al. 1992). Shell debris was also identified. Analysis for abundance estimates included increasing the camera view area to account for counting scallops that lie on the edge of the image. This expansion was reviewed and accepted in the 50th SAW and is based on the average shell height of scallops in the area. The length and width of each image were increased by the mean shell height of measured scallops within the survey area using the equation: (1) 퐸푥푝푎푛푑푒푑 푉푖푒푤 퐴푟푒푎 = (푙 + 푆퐻̅̅̅̅) × (푤 + 푆퐻̅̅̅̅) where l and w are quadrat length and width and 푆퐻̅̅̅̅ is mean shell height (O’Keefe et al. 2010). Mean densities and standard errors of scallops were calculated using equations for a two-stage sampling design where the mean of the total sample is (Cochran 1977): n xi (2) x = i=1 n where n is the number of stations and xi is the mean of the 4 quadrats at station i. The SE of this 2-stage mean was calculated as: 1 2 (3) S.E.(x) = (s ) n n 2 2 where: s = (xi − x) /(n −1) . According to Cochran (1977) and Krebs (1999) this simplified version of the 2-stage variance is appropriate when the ratio of sample area to survey area (n/N) is small. In this case, thousands of square meters (n) were sampled compared with thousands of square kilometers (N) in the study areas. All calculations used number of scallops per square meter. The number of scallops in the survey areas was calculated by multiplying scallop density by the total area surveyed (Stokesbury 2002). Estimates of scallop meat weight in grams were derived from shell height (mm) frequencies collected during each survey and shell height to meat weight regressions used in the 65th SAW or as specified by the NEFMC Scallop PDT. The mean meat weight for each 5 mm size bin was multiplied by the total number of scallops in the survey 5 area to estimate the total biomass of scallop meats. Exploitable biomass was calculated using the commercial scallop dredge selectivity equation determined by Yochum & Dupaul (2008). To investigate the effects of extreme recruitment of juvenile sea scallops in relation to the distributions, abundance and predator-prey interactions with predatory sea stars 1,888 stations surveyed within the NLCA over from 2010-2018 were utilized. Scallop counts and measurements in all images had already been quantified and quality controlled. For this project, sea star arm lengths and distance between nearest neighbors were measured. Due to interannual differences in locations of stations within the NLCA and total area surveyed (km2), only stations that were in areas surveyed more than 4 years in a row were utilized for density and scallop-sea star ratio results. To identify these stations the NLCA was divided into a 5.6 km grid, matching the maximum distance between stations within a year. Densities and associated error for sea stars were calculated following equations (2) and (3). Yearly ratios for sea scallop counts to sea star counts were calculated by dividing the cumulative total number of sea scallop counts by the cumulative total number of sea star counts for all stations in that year. Ratios for sea scallops to sea star maps were calculated by dividing the total number of counts of sea scallops per station by the total number of sea stars at that same station.