GROWTH AND SURVIVAL OF SEA SCALLOPS PLACOPECTEN-MAGELLANICUS - EFFECTS OF CULTURE DEPTH

We combined extensive water sampling with monthly growth measurements of juvenile sea scallops held in cages 0 to 200 cm above the bottom to (1) construct predictive empirical models of shell and soft-tissue gr owth based on oceanographic variables, and (2) determine whether scall ops on or near the bottom can derive a food supplement from resuspende d sediment when seasonal phytoplankton production is low, Variation in growth was strongly dependent on depth, but this relationship was not consistent over time or tissue type. In late fall, when phytoplankton biomass was generally low (approximately 1 mug chl l-1), the adductor muscle of scallops on the bottom lost mass (approximately 1.5 mg dry wt d-1), but for scallops held only 20 cm higher in the water column, growth was 2.5 mg d-1. During the winter, soft-tissue growth on the bo ttom was significantly lower than that of scallops held above the sedi ment surface. At this time, there was no variation in shell growth wit h respect to depth. At the end of the study, soft-tissue weight (exclu ding muscle tissue) of scallops on the bottom was approximately 40 % l ess than that of scallops growing greater-than-or-equal-to 50 cm above bottom. Rather than providing an energetic benefit, results suggest t hat high concentrations of seston near the bottom inhibit growth. Empi rical regression models of scallop growth using data from water sampli ng every 2 wk accounted for up to 68% of growth variation, with temper ature and seston quality being the most important predictor variables. Marginal improvements to the model using data collected hourly with i n situ probes suggest that estimates of food supply should be correcte d, i.e. reduced, when high flows or high seston concentrations limit f iltration rates. In addition, results indicate that attention to the m agnitude and variation of predictor variables without consideration of their seasonal coherence may be a primary factor limiting the ability to construct truly predictive models of bivalve growth.