Abstract
We address the global deficit of data describing kelp forest distribution, relative covers and biomass by testing the ability of species distribution models to predict these attributes at locations where data are currently limited. We integrated biological ground truth data with high-resolution environmental datasets to develop generalized additive models that accurately predict the structure of Laminaria forests within the Bay of Morlaix (48°42′42″N, 3°55′40″W). Forest distribution and proportional covers were predicted using water depth, light availability, wave exposure and sediment dynamics. The biomass of individual kelp species was modeled by supplementing these same variables with measures of seafloor slope and benthic position. Biomass predictions for Laminaria digitata and Laminaria hyperborea contrast the physiological tolerances of these species to light and wave exposure gradients. As a direct management output, we produced high-resolution maps (25 m2 grids) that closely match independent field data and provide vital information for marine spatial planning.
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Acknowledgments
This research was supported by funds from Agence des aires marines protégées and the Réseau Benthique network. The research outcomes have contributed toward the development of an ecological baseline for French Atlantic and English Channel Natura 2000 sites. The authors would like to thank the staff of the Service des Applications Géomatiques and in particular E. Giocomini, E. Autret and C. Carré for considerable support throughout the project. We acknowledge all data providers and those persons who helped us gain access to these resources. We also thank B.D. Russell, T.M. Ward and two anonymous reviewers for helpful comments that improved the manuscript.
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Gorman, D., Bajjouk, T., Populus, J. et al. Modeling kelp forest distribution and biomass along temperate rocky coastlines. Mar Biol 160, 309–325 (2013). https://doi.org/10.1007/s00227-012-2089-0
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DOI: https://doi.org/10.1007/s00227-012-2089-0