01946nas a2200157   4500008003900000245011100039210006900150300001200219490000600231520143500237100001701672700001301689700001401702700001501716856005701731       2013                          d00aEcosystem modelling for ecosystem-based management of bivalve aquaculture sites in data‑poor environment0 aEcosystem modelling for ecosystembased management of bivalve aqu  a117-1330 v43 aAlthough models of carrying capacity have been around for some time, their use in aquaculture management has been limited. This is partially due to the cost involved in generating and testing the models. However, the use of more generic and flexible models could facilitate the implementation of modelling in management. We have built a generic core for coupling biogeochemical and hydrodynamic models using Simile (www.simulistics.com), a visual simulation environment software that is well-suited to accommodate fully spatial models. Specifically, Simile integrates PEST (model-independent parameter estimation, Watermark Numerical Computing, www.pesthomepage.org), an optimization tool that uses the Gauss-Marquardt-Levenberg algorithm and can be used to estimate the value of a parameter, or set of parameters, in order to minimize the discrepancies between the model results and a dataset chosen by the user. The other critical aspect of modelling exercises is the large amount of data necessary to set up, tune and groundtruth the ecosystem model. However, ecoinformatics and improvements in remote sensing procedures have facilitated acquisition of these datasets, even in data-poor environments. In this paper we describe the required datasets and stages of model development necessary to build a biogeochemical model that can be used as a decision-making tool for bivalve aquaculture management in data-poor environments.1 aFilgueira, R1 aGrant, J1 aStuart, R1 aBrown, M S  uhttp://www.int-res.com/abstracts/aei/v4/n2/p117-133/