Description: © The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Kavanaugh, M. T., Bell, T., Catlett, D. C., Cimino, M. A., Doney, S. C., Klajbor, W., Messie, M., Montes, E., Muller-Karger, F. E., Otis, D., Santora, J. A., Schroeder, I. D., Trinanes, J., & Siegel, D. A. Satellite remote sensing and the Marine Biodiversity Observation Network: current science and future steps. Oceanography, 34(2), (2021): 62–79, https://doi.org/10.5670/oceanog.2021.215.

Description: Coastal ecosystems are rapidly changing due to human-caused global warming, rising sea level, changing circulation patterns, sea ice loss, and acidification that in turn alter the productivity and composition of marine biological communities. In addition, regional pressures associated with growing human populations and economies result in changes in infrastructure, land use, and other development; greater extraction of fisheries and other natural resources; alteration of benthic seascapes; increased pollution; and eutrophication. Understanding biodiversity is fundamental to assessing and managing human activities that sustain ecosystem health and services and mitigate humankind’s indiscretions. Remote-sensing observations provide rapid and synoptic data for assessing biophysical interactions at multiple spatial and temporal scales and thus are useful for monitoring biodiversity in critical coastal zones. However, many challenges remain because of complex bio-optical signals, poor signal retrieval, and suboptimal algorithms. Here, we highlight four approaches in remote sensing that complement the Marine Biodiversity Observation Network (MBON). MBON observations help quantify plankton community composition, foundation species, and unique species habitat relationships, as well as inform species distribution models. In concert with in situ observations across multiple platforms, these efforts contribute to monitoring biodiversity changes in complex coastal regions by providing oceanographic context, contributing to algorithm and indicator development, and creating linkages between long-term ecological studies, the next generations of satellite sensors, and marine ecosystem management.

Description: The authors would like to acknowledge the support of the Marine Biodiversity Observation Network (MBON), through National Aeronautics and Space Administration (NASA) awards NNX14AP62A, 80NSSC20K0017MK, NNX14AR62AFMK, 80NSSC20M0001, and 80NSSC20M008; and National Oceanic and Atmospheric Administration (NOAA) Integrated Ocean Observing System grant NA19NOS0120199. In addition, the work was supported by the Group on Earth Observations NASA awards 80NSSC18K0318 to EM and 80NSSC18K0412 to MK. FMK acknowledges the US National Science Foundation (NSF) grant 2500-1710-00 to the OceanObs Research Coordination Network, and the Gulf of Mexico Coastal Ocean Observing System NOAA Cooperative Agreement NA16NOS0120018. MM and JS were also supported by the NASA Life in Moving Oceans award 80NSSC17K0574. DS, TB, and DC acknowledge Plumes and Blumes NASA award 80NSSC18K0735, the Bureau of Ocean and Energy Management Ecosystem Studies program award MC15AC00006, NASA PACE Science Team award 80NSSC20M0226, and NSF Santa Barbara Coastal Long Term Ecological Research site award OCE-1831937.