Building bridges between global information systems on marine organisms and ecosystem models

Calibration of complex, process-based ecosystem models is a timely task with modellers challenged by many parameters, multiple outputs of interest and often a scarcity of empirical data. Incorrect calibration can lead to unrealistic ecological and socio-economic predictions with the modeller's experience and available knowledge of the modelled system largely determining the success of model calibration. Here we provide an overview of best practices when calibrating an Atlantis marine ecosystem model, a widely adopted framework that includes the parameters and processes comprised in many different ecosystem models. We highlight the importance of understanding the model structure and data sources of the modelled system. We then focus on several model outputs (biomass trajectories, age distributions, condition at age, realised diet proportions, and spatial maps) and describe diagnostic routines that can assist modellers to identify likely erroneous parameter values. We detail strategies to fine tune values of four groups of core parameters: growth, predator-prey interactions, recruitment and mortality. Additionally, we provide a pedigree routine to evaluate the uncertainty of an Atlantis ecosystem model based on data sources used. Describing best and current practices will better equip future modellers of complex, processed-based ecosystem models to provide a more reliable means of explaining and predicting the dynamics of marine ecosystems. Moreover, it promotes greater transparency between modellers and end-users, including resource managers.Please note that this is an author-produced PDF of an article accepted for publication following peer review. The definitive publisher-authenticated version is available on the publisher Web site. Highlights► Best practices for calibrating complex process-based ecosystem models are described. ► We emphasize the importance of understanding the model structure and data sources. ► Strategies to estimate core parameters for an Atlantis ecosystem model are defined. ► Key diagnostic routines to help modelers identify erroneous parameters are outlined. ► A pedigree to evaluate ecosystem model confidence and data quality is proposed.

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Calibrating process-based marine ecosystem models: An example case using Atlantis

Weijerman

Perryman

Audzijonytė

et al. 2019

Ecological Modelling

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Scientific knowledge gaps on the biology of non-fish marine species across European Seas

Abucay,

Sorongon-Yap,

Kesner-Reyes

et al. 2023

Front. Mar. Sci.

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Available information and potential data gaps for non-fish marine organisms (cnidarians, crustaceans, echinoderms, molluscs, sponges, mammals, reptiles, and seabirds) covered by the global database SeaLifeBase were reviewed for eight marine ecosystems (Adriatic Sea, Aegean Sea, Baltic Sea, Bay of Biscay/Celtic Sea/Iberian Coast, Black Sea, North Sea, western Mediterranean Sea, Levantine Sea) across European Seas. The review of the SeaLifeBase dataset, which is based on published literature, analyzed information coverage for eight biological characteristics (diet, fecundity, maturity, length-weight relationships, spawning, growth, lifespan, and natural mortality). These characteristics are required for the development of ecosystem and ecological models to evaluate the status of marine resources and related fisheries. Our analyses revealed that information regarding these biological characteristics in the literature was far from complete across all studied areas. The level of available information was nonetheless reasonably good for sea turtles and moderate for marine mammals in some areas (Baltic Sea, Bay of Biscay/Celtic Sea/Iberian Coast, Black Sea, North Sea and western Mediterranean Sea). Further, seven of the areas have well-studied species in terms of information coverage for biological characteristics of some commercial species whereas threatened species are generally not well studied. Across areas, the most well-studied species are the cephalopod common cuttlefish (Sepia officinalis) and the crustacean Norway lobster (Nephrops norvegicus). Overall, the information gap is narrowest for length-weight relationships followed by growth and maturity, and widest for fecundity and natural mortality. Based on these insights, we provide recommendations to prioritize species with insufficient or missing biological data that are common across the studied marine ecosystems and to address data deficiencies.

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Building bridges between global information systems on marine organisms and ecosystem models

Cited by 2 publications

References 64 publications

Calibrating process-based marine ecosystem models: An example case using Atlantis

Calibrating process-based marine ecosystem models: An example case using Atlantis

Scientific knowledge gaps on the biology of non-fish marine species across European Seas

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