A novel modeling approach for the “end-to-end” analysis of marine ecosystems

There is a growing demand for “end-to-end” models, which are modeling tools used to analyze and understand the fundamental complexities of marine ecosystems and processes emerging from the interaction of individuals from different trophic groups with respect to the physical environment and, even, human activity. These models are valuable quantitative tools for ecosystem-based management. To explore potential answers to complex questions regarding ecosystems using these models, it is necessary to incorporate classical ontogenic changes through the life cycle of target individuals, in addition to inherited behavioral strategies, as an additional differentiating aspect, particularly when the behavior has a direct impact on the ecosystem phenomena under study. However, it is difficult to combine different fine scale time and spatial granularities to infer animal behavior and ontogenic development. This complexity has kept these two levels of analysis separated, because most current tools do not have the required computational resources and advanced software architecture. To address this issue, we propose an individual-based modeling framework that is capable of handling and unifying the two experimental categories with a comprehensive biological and behavioral model that strictly adheres to the physiological functions of ingestion, growth, and metabolism of organisms. In addition, this model incorporates the exchange and transfer of mass and energy through local interactions at all trophic levels (lower to higher), the physical environment, and anthropogenic activity. For the framework to model short time events, such as classical predator–prey interactions, while also generating long-term ecosystem emergent properties, a special interleaving scheduling engine and physical space computer model was devised, which optimizes memory and processing resources. The framework was tested through several experiments with a three-population ecosystem containing up to 40 thousand organisms evolving inside a 200,000m2 simulation environment during 12,000 model-hours; yet, requiring only a few hours of program execution on a regular personal computer. The model included various environmental physical elements, such as several hundred shelters, the number of which can be easily modified in each experiment to simulate substrate degradation and its impact on populations. With the aid of the quantitative and qualitative tools provided by the model, it was possible to observe a coupling between prey and predator population dynamics. In conclusion, we confirmed that the end-to-end model developed here could successfully generate detailed specific hypotheses about fish behavior and quantify impacts on population dynamics.