A new modeling approach to define marine ecosystems food-web status with uncertainty assessment

摘要

Ecosystem models are currently one of the most powerful approaches used to project and analyse the consequences of anthropogenic and climate-driven changes in food web structure and function. The modeling community is however still finding the effective representation of microbial processes as challenging and lacks of techniques for assessing flow uncertainty explicitly. A linear inverse model of the Bay of Biscay continental shelf was built using a Monte Carlo method coupled with a Markov Chain (LIM-MCMC) to characterize the system's trophic food-web status and its associated structural and functional properties. By taking into account the natural variability of ecosystems (and their associated flows) and the lack of data on these environments, this innovative approach enabled the quantification of uncertainties for both estimated flows and derived food-web indices. This uncertainty assessment constituted a real improvement on the existing Ecopath model for the same area and both models results were compared.