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Although 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 biogeo- chemical and hydrodynamic models using Simile (www.simulistics.com), a visual simulation en - vironment 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 algo- rithm and can be used to estimate the value of a parameter, or set of parameters, in order to mini- mize the discrepancies between the model results and a dataset chosen by the user. The other crit- ical aspect of modelling exercises is the large amount of data necessary to set up, tune and ground truth 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 man- agement in data-poor environments.

Ecosystem modelling for ecosystem-based management of bivalve aquaculture sites in data‑poor environments