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  • Remote sensing  (2)
  • Massachusetts Institute of Technology and Woods Hole Oceanographic Institution  (1)
  • Wiley  (1)
  • Cell Press
  • Nature Research
  • PANGAEA
  • 2020-2023  (2)
  • 1935-1939
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  • 1
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    Disturbance and nutrients synchronise kelp forests across scales through interacting Moran effects (2022)
    Wiley
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    Publication Date: 2022-10-20
    Description: © The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Castorani, M. C. N., Bell, T. W., Walter, J. A., Reuman, D. C., Cavanaugh, K. C., & Sheppard, L. W. Disturbance and nutrients synchronise kelp forests across scales through interacting Moran effects. Ecology Letters, 25(8), (2022): 1854-1868, https://doi.org/10.1111/ele.14066.
    Description: Spatial synchrony is a ubiquitous and important feature of population dynamics, but many aspects of this phenomenon are not well understood. In particular, it is largely unknown how multiple environmental drivers interact to determine synchrony via Moran effects, and how these impacts vary across spatial and temporal scales. Using new wavelet statistical techniques, we characterised synchrony in populations of giant kelp Macrocystis pyrifera, a widely distributed marine foundation species, and related synchrony to variation in oceanographic conditions across 33 years (1987–2019) and 〉900 km of coastline in California, USA. We discovered that disturbance (storm-driven waves) and resources (seawater nutrients)—underpinned by climatic variability—act individually and interactively to produce synchrony in giant kelp across geography and timescales. Our findings demonstrate that understanding and predicting synchrony, and thus the regional stability of populations, relies on resolving the synergistic and antagonistic Moran effects of multiple environmental drivers acting on different timescales.
    Description: This study was funded by the U.S. National Science Foundation (NSF) through linked NSF-OCE awards 2023555, 2023523, 2140335, and 2023474 to M.C.N.C., K.C.C., T.W.B., and D.C.R., respectively. The research was initiated during a synthesis working group at the Long Term Ecological Research Network Office and National Center for Ecological Analysis and Synthesis funded under NSF-DEB award 1545288. D.C.R. and L.W.S. were also partly supported by NSF award 1714195, the McDonnell Foundation, and the California Department of Fish and Wildlife Delta Science Program. This project used data developed through the Santa Barbara Coastal Long Term Ecological Research project, funded through NSF-OCE award 1831937.
    Keywords: Coherence ; Disturbance ; Moran effect ; Nitrate ; North Pacific Gyre Oscillation ; Oceanography ; Population dynamics ; Remote sensing ; Spatial synchrony ; Wavelet transforms
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 2
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    Computational approaches for sub-meter ocean color remote sensing (2020)
    Massachusetts Institute of Technology and Woods Hole Oceanographic Institution
    Details
    Publication Date: 2022-10-20
    Description: Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Mechanical and Oceanographic Engineering at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution February 2021.
    Description: The satellite ocean color remote sensing paradigm developed by government space agencies enables the assessment of ocean color products on global scales at kilometer resolutions. A similar paradigm has not yet been developed for regional scales at sub-meter resolutions, but it is essential for specific ocean color applications (e.g., mapping algal biomass in the marginal ice zone). While many aspects of the satellite ocean color remote sensing paradigm are applicable to sub-meter scales, steps within the paradigm must be adapted to the optical character of the ocean at these scales and the opto-electronics of the available sensing instruments. This dissertation adapts the three steps of the satellite ocean color remote sensing paradigm that benefit the most from reassessment at sub-meter scales, namely the correction for surface-reflected light, the design and selection of the opto-electronics and the post-processing of over-sampled regions. First, I identify which surface-reflected light removal algorithm and view angle combination are optimal at sub-meter scales, using data collected during a field deployment to the Martha’s Vineyard Coastal Observatory. I find that of the three most widely used glint correction algorithms, a spectral optimization based approach applied to measurements with a 40∘ view angle best recovers the remotesensing reflectance and chlorophyll concentration despite centimeter scale variability in the surface-reflected light. Second, I develop a simulation framework to assess the impact of higher optical and electronics noise on ocean color product retrieval from unique ocean color scenarios. I demonstrate the framework’s power as a design tool by identifying hardware limitations, and developing potential solutions, for estimating algal biomass from high dynamic range sensing in the marginal ice zone. Third, I investigate a spectral super-resolution technique for application to spatially over-sampled oceanic regions. I determine that this technique more accurately represents spectral frequencies beyond the Nyquist and that it can be trained to be invariant to noise sources characteristic of ocean color remote sensing on images with similar statistics as the training dataset. Overall, the developed and critically assessed sub-meter ocean color remote sensing paradigm enables researchers to collect high fidelity sub-meter data from imaging spectrometers in unique ocean color scenarios.
    Description: Ryan O’Shea was supported by the Department of Defense (DoD) through the National Defense Science & Engineering Graduate Fellowship (NDSEG) Program. This research was funded by Woods Hole Oceanographic Institution’s Edwin W. Hiam Ocean Science and Technology Award Fund, its Ocean Venture Funds, its Academic Programs Office, and the National Aeronautics and Space Administration via grant number CCE NNX17AI72G to Dr. Samuel Laney. The raw data for Figures 3-3 and 3-4 were provided through Australian Antarctic Science grants 2678 and 4390.
    Keywords: Ocean color ; Hyperspectral ; Remote sensing
    Repository Name: Woods Hole Open Access Server
    Type: Thesis
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