We developed a demographic and management model for the Manila clam Tapes philippinarum (one of the most important commercial mollusc species in Europe) from data collected in the Sacca di Goro lagoon, Italy. Herein, we describe growth and survival processes by 2 submodels incorporating temperature-driven fluctuations in vital parameters, density-dependent effects on survival, and sediment type as an indicator of the hydrodynamic regime. Nonlinear fitting and nonparametric statistics are used to calibrate the body growth and the survival models from the available data and to associate a probability distribution to parameter estimates. The 2 models are stochastic in their formulation to account for environmental variability. We assess the suitability of our model to reproduce the life cycle of T. philippinarum at other sites by applying our model to data from the Bassin d'Arcachon (France) and the Eo estuary (Spain). We use Monte-Carlo simulations to forecast the expected biomass yield corresponding to different seeding and harvesting times along with its confidence intervals. The maximum obtainable yield is about 6 kg m-2 and can be obtained by seeding in spring and harvesting in late fall of the following year. We show, however, that there is a trade-off between maximizing the average yield and minimizing yield variance.

Density and temperature-dependence of vital rates in the Manila clam Tapes philippinarum: a stochastic demographic model

MELIA', PACO VASCO ALDO;GATTO, MARINO
2004-01-01

Abstract

We developed a demographic and management model for the Manila clam Tapes philippinarum (one of the most important commercial mollusc species in Europe) from data collected in the Sacca di Goro lagoon, Italy. Herein, we describe growth and survival processes by 2 submodels incorporating temperature-driven fluctuations in vital parameters, density-dependent effects on survival, and sediment type as an indicator of the hydrodynamic regime. Nonlinear fitting and nonparametric statistics are used to calibrate the body growth and the survival models from the available data and to associate a probability distribution to parameter estimates. The 2 models are stochastic in their formulation to account for environmental variability. We assess the suitability of our model to reproduce the life cycle of T. philippinarum at other sites by applying our model to data from the Bassin d'Arcachon (France) and the Eo estuary (Spain). We use Monte-Carlo simulations to forecast the expected biomass yield corresponding to different seeding and harvesting times along with its confidence intervals. The maximum obtainable yield is about 6 kg m-2 and can be obtained by seeding in spring and harvesting in late fall of the following year. We show, however, that there is a trade-off between maximizing the average yield and minimizing yield variance.
2004
AUT
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/555702
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