Wood, G*. 1, Griffin, K. 1, Edgeloe, J. 1, Filbee-Dexter, K. 1, 2, Wernberg, T. 1, 2 and Coleman, M.A.1,3.
1 UWA Oceans Institute and School of Biological Sciences, University of Western Australia, Crawley, Western Australia 6009, Australia
2 Institute of Marine Research, His, Norway
3NSW Fisheries, Department of Primary Industries, NSW Australia.
The UN Decade of Ocean Science for Sustainable Development and the Decade of Restoration have strengthened global efforts to farm, restore and ‘future-proof’ declining kelp forests. These efforts require informed selection of genetic units (sources of kelp seedstock) to avoid negative effects on populations and optimise restoration and future-proofing success – but these data are lacking for most kelp species and regions globally. To close this gap, we built an interactive web tool from a global database of seaweed genetic structure mined from > 90 datasets, covering 35 species of high conservation and farming value. Seaweed genetic turnover was modelled as a function of geography, ocean currents and local environmental conditions using generalised dissimilarity models (GDMs) from individual datasets. We then mapped each species’ genetic structure across their respective global range using the best GDM models. These maps allow rapid and explicit delineation of kelp populations that are genetically similar, unique or vulnerable to environmental change. To test this tool in action, we used it to identify “suitable” versus “non-suitable” source populations to restore the kelp Ecklonia radiata on West Australia’s coast, and experimentally compared restoration success using the Green Gravel technique, which enables large-scale planting of kelp genotypes onto natural reefs. This global tool will enable managers, restoration practitioners and aquaculture proponents to interactively identify populations of high conservation value, and identify suitable areas to source kelp populations for restoration, farming and future-proof scenarios to increase resilience to climate change.