A trophic modelling framework: Key metrics for the ecological assessment of artificial structures

Abstract

As the global population expands, marine coastal ecosystems face mounting pressures from human activities, that have led to habitat deterioration and dwindling fishery resources. In this context, Artificial Reefs (ARs) have emerged as one of the promising solutions. They are generally implemented to provide habitat, to create a protective, physical boundary, to support sustainable fisheries and to facilitate ecosystem rehabilitation. Evaluating their ecological performance is crucial to ensuring they meet their objectives. Initially, assessment relied on comparing ARs to natural reefs using mainly ecological metrics which focused on fish assemblage and dynamics. Despite there being more research and documentation on effectiveness today, assessing ARs remains challenging due to the number of environmental factors that can affect the ecological systems. Moreover, ecological studies mainly used metrics that investigated the reef fish populations or ecological metrics such as fish assemblages or trophic structure that are often overlooked in studies that primarily focus on commercial fishery dynamics. Therefore, new ways of assessing artificial reef performance and the set-up of comprehensive metrics which integrate this level of complexity are needed. In this study, we focused on the "Rade de Cherbourg" in the English Channel, employing a trophic modeling approach using Ecopath with Ecosim (EwE). The study emphasizes the importance of Ecological Network Analysis (ENA) metrics for evaluating changes in the systems’ properties—such as complexity, flow diversity, and recycling capacity— which result from AR implementation. Furthermore, we identified which metrics are suitable for assessing specific AR objectives. The proposed metrics serve as a command-and-control tool for AR site managers, enabling them to evaluate the performance of each AR objective effectively. With the anticipated increase in AR projects, especially those which compensate for human impact like the Cherbourg ARs, this research offers valuable insights and future perspectives to continuously improve the ecological performance of ARs.