A review of the opportunities and challenges for using remote sensing for management of surface-canopy forming kelps

© The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Cavanaugh, K. C., Bell, T., Costa, M., Eddy, N. E., Gendall, L., Gleason, M. G., Hessing-Lewis, M., Martone, R., McPherson, M., Pontier, O., Reshitnyk, L., Beas-Luna, R., Carr, M., Caselle, J. E., Cavanaugh, K. C., Miller, R. F., Hamilton, S., Heady, W. N., Hirsh, H. K., Hohman R., Lee L. C., Lorda J., Ray J., Reed D. C., Saccomanno V. R., Schroeder, S. B. A review of the opportunities and challenges for using remote sensing for management of surface-canopy forming kelps. Frontiers in Marine Science, 8, (2021): 753531, https://doi.org/10.3389/fmars.2021.753531.Surface-canopy forming kelps provide the foundation for ecosystems that are ecologically, culturally, and economically important. However, these kelp forests are naturally dynamic systems that are also threatened by a range of global and local pressures. As a result, there is a need for tools that enable managers to reliably track changes in their distribution, abundance, and health in a timely manner. Remote sensing data availability has increased dramatically in recent years and this data represents a valuable tool for monitoring surface-canopy forming kelps. However, the choice of remote sensing data and analytic approach must be properly matched to management objectives and tailored to the physical and biological characteristics of the region of interest. This review identifies remote sensing datasets and analyses best suited to address different management needs and environmental settings using case studies from the west coast of North America. We highlight the importance of integrating different datasets and approaches to facilitate comparisons across regions and promote coordination of management strategies.Funding was provided by the Nature Conservancy (Grant No. 02042019-5719), the U.S. National Science Foundation (Grant No. OCE 1831937), and the U.S. Department of Energy ARPA-E (Grant No. DE-AR0000922)