A network analysis of connected biophysical pathways to advice eelgrass (Zostera marina) restoration. (July 2022) - Pastor, Ane; Ospina-Alvarez, Andrés; Larsen, Janus; Thorbjørn Hansen, Flemming; Krause-Jensen, Dorte; Maar, Marie
Abstract: The North Sea and the Baltic Sea, including Danish coastal waters, have experienced a drastic decline in eelgrass Zostera marina coverage during the past century. Around 1900, eelgrass meadows covered about 6700 km 2 of Danish coastal waters while the current potential distribution area is only about one third of this. In some areas, the potential distribution area is far from realized, and restoration efforts are needed to assist recovery. Such efforts are challenging, and resource-demanding and careful site selection is, therefore, important. In the present study, we aim to identify the connectivity of eelgrass populations as a basis for guiding site selection for restoration. We developed a coupled biophysical model to study eelgrass dispersal in the Kattegat. Partly submerged particles simulated the dispersal of reproductive eelgrass shoots containing seeds during the flowering season July–September. We then used network analysis to identify the potential connectivity between populations. We evaluated connectivity based on In-strength, Betweenness and Eigenvector centrality metrics and identified key areas in the Kattegat such as the central part of Aalborg Bay, to be considered to restore the network of Z. marina patches. The study proves the potentials of combining hydrodynamic models and network analysis to support marine conservation and planning, and highlights the importance of collaboration between ecologists, oceanographers, and practitioners in this endeavour. Highlights: Dispersal of eelgrass Z. marina was investigated with an individual-based model. Connectivity between patches was estimated in the inner Danish waters. Betweenness, in-strength and eigenvector centrality metrics were used. Aalborg Bay is an important area where restoration efforts could be focused. Modelling tools can help guide the selection of priority areas for restoration.