SEA TEMPERATURE AND WAVE HEIGHT AS PREDICTORS OF POPULATION SIZE STRUCTURE AND DENSITY OF MEGASTRAEA (LITHOPOMA) UNDOSA: IMPLICATIONS FOR FISHERY MANAGEMENT

摘要

We tested the hypothesis that population characteristics (density, basal diameter, and shell volume as a surrogate for biomass) of the wavy turban snail, Megas-traea (Lithopoma) undosa (Wood, 1928) in the Channel Islands, California could be predicted using temperature and wave height information from a single ocean buoy, thus improving the management of the species in a cost effective manner. Megastraea undosa is expected to become an increasingly important fishery and may serve as an indicator to gauge the effectiveness of marine protected areas in the region. Using the U.S. National Park Service Kelp Forest Monitoring Program (KFMP) and two other similar sampling programs in the region, M. undosa data from 1982 to 2003 were correlated with averaged monthly temperature and wave height data from the Santa Barbara buoy (46053) and in situ temperature loggers at the KFMP sites. Ordination and regression were used to predict density (ind m~(-2)), size (mm basal diameter), and volume (ml m~(-2)) estimates using monthly averages for temperature and wave height in the current year, the previous year, and from 2 yrs prior. Results demonstrated that a combination of spring temperatures and summer/fall wave heights in the current, previous, and 2 yrs prior could be used to predict average density (R~2 = 0.74, P = 0.048), size (R~2 = 0.83, P = 0.0002), and volume (R~2 = 0.80 P = 0.024). Predictions were attained using four (size) or five (density, volume) variables consisting of monthly averages. Megastraea undosa recruitment and survival appears strongly correlated to El Nino-Southern Oscillation (ENSO) cycles, suggesting that oceanographic regimes should be considered in the management of the species.