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  1. Article: Temporal Stability of Seagrass Extent, Leaf Area, and Carbon Storage in St. Joseph Bay, Florida: a Semi-automated Remote Sensing Analysis.

    Lebrasse, Marie Cindy / Schaeffer, Blake A / Coffer, Megan M / Whitman, Peter J / Zimmerman, Richard C / Hill, Victoria J / Islam, Kazi A / Li, Jiang / Osburn, Christopher L

    Estuaries and coasts : journal of the Estuarine Research Federation

    2023  Volume 45, Page(s) 2082–2101

    Abstract: Seagrasses are globally recognized for their contribution to blue carbon sequestration. However, accurate quantification of their carbon storage capacity remains uncertain due, in part, to an incomplete inventory of global seagrass extent and assessment ... ...

    Abstract Seagrasses are globally recognized for their contribution to blue carbon sequestration. However, accurate quantification of their carbon storage capacity remains uncertain due, in part, to an incomplete inventory of global seagrass extent and assessment of its temporal variability. Furthermore, seagrasses are undergoing significant decline globally, which highlights the urgent need to develop change detection techniques applicable to both the scale of loss and the spatial complexity of coastal environments. This study applied a deep learning algorithmto a 30-year time series of Landsat 5 through 8 imagery to quantify seagrass extent, leaf area index (LAI), and belowground organic carbon (BGC) in St. Joseph Bay, Florida, between 1990 and 2020. Consistent with previous field-based observations regarding stability of seagrass extent throughout St. Joseph Bay, there was no temporal trend in seagrass extent (23 ± 3 km
    Language English
    Publishing date 2023-04-03
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2229170-2
    ISSN 1559-2731 ; 1559-2723
    ISSN (online) 1559-2731
    ISSN 1559-2723
    DOI 10.1007/s12237-022-01050-4
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Providing a framework for seagrass mapping in United States coastal ecosystems using high spatial resolution satellite imagery.

    Coffer, Megan M / Graybill, David D / Whitman, Peter J / Schaeffer, Blake A / Salls, Wilson B / Zimmerman, Richard C / Hill, Victoria / Lebrasse, Marie Cindy / Li, Jiang / Keith, Darryl J / Kaldy, James / Colarusso, Phil / Raulerson, Gary / Ward, David / Kenworthy, W Judson

    Journal of environmental management

    2023  Volume 337, Page(s) 117669

    Abstract: Seagrasses have been widely recognized for their ecosystem services, but traditional seagrass monitoring approaches emphasizing ground and aerial observations are costly, time-consuming, and lack standardization across datasets. This study leveraged ... ...

    Abstract Seagrasses have been widely recognized for their ecosystem services, but traditional seagrass monitoring approaches emphasizing ground and aerial observations are costly, time-consuming, and lack standardization across datasets. This study leveraged satellite imagery from Maxar's WorldView-2 and WorldView-3 high spatial resolution, commercial satellite platforms to provide a consistent classification approach for monitoring seagrass at eleven study areas across the continental United States, representing geographically, ecologically, and climatically diverse regions. A single satellite image was selected at each of the eleven study areas to correspond temporally to reference data representing seagrass coverage and was classified into four general classes: land, seagrass, no seagrass, and no data. Satellite-derived seagrass coverage was then compared to reference data using either balanced agreement, the Mann-Whitney U test, or the Kruskal-Wallis test, depending on the format of the reference data used for comparison. Balanced agreement ranged from 58% to 86%, with better agreement between reference- and satellite-indicated seagrass absence (specificity ranged from 88% to 100%) than between reference- and satellite-indicated seagrass presence (sensitivity ranged from 17% to 73%). Results of the Mann-Whitney U and Kruskal-Wallis tests demonstrated that satellite-indicated seagrass percentage cover had moderate to large correlations with reference-indicated seagrass percentage cover, indicative of moderate to strong agreement between datasets. Satellite classification performed best in areas of dense, continuous seagrass compared to areas of sparse, discontinuous seagrass and provided a suitable spatial representation of seagrass distribution within each study area. This study demonstrates that the same methods can be applied across scenes spanning varying seagrass bioregions, atmospheric conditions, and optical water types, which is a significant step toward developing a consistent, operational approach for mapping seagrass coverage at the national and global scales. Accompanying this manuscript are instructional videos describing the processing workflow, including data acquisition, data processing, and satellite image classification. These instructional videos may serve as a management tool to complement field- and aerial-based mapping efforts for monitoring seagrass ecosystems.
    MeSH term(s) United States ; Ecosystem ; Satellite Imagery ; Environmental Monitoring/methods
    Language English
    Publishing date 2023-03-24
    Publishing country England
    Document type Journal Article
    ZDB-ID 184882-3
    ISSN 1095-8630 ; 0301-4797
    ISSN (online) 1095-8630
    ISSN 0301-4797
    DOI 10.1016/j.jenvman.2023.117669
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Simulated response of St. Joseph Bay, Florida, seagrass meadows and their belowground carbon to anthropogenic and climate impacts.

    Lebrasse, Marie Cindy / Schaeffer, Blake A / Zimmerman, Richard C / Hill, Victoria J / Coffer, Megan M / Whitman, Peter J / Salls, Wilson B / Graybill, David D / Osburn, Christopher L

    Marine environmental research

    2022  Volume 179, Page(s) 105694

    Abstract: Seagrass meadows are degraded globally and continue to decline in areal extent due to human pressures and climate change. This study used the bio-optical model GrassLight to explore the impact of climate change and anthropogenic stressors on seagrass ... ...

    Abstract Seagrass meadows are degraded globally and continue to decline in areal extent due to human pressures and climate change. This study used the bio-optical model GrassLight to explore the impact of climate change and anthropogenic stressors on seagrass extent, leaf area index (LAI) and belowground organic carbon (BGC) in St. Joseph Bay, Florida, using water quality data and remotely-sensed sea surface temperature (SST) from 2002 to 2020. Model predictions were compared with satellite-derived measurements of seagrass extent and shoot density from the Landsat images for the same period. The GrassLight-derived area of potential seagrass habitat ranged from 36.2 km
    MeSH term(s) Bays ; Carbon ; Chlorophyll A ; Ecosystem ; Florida ; Humans ; Hydrogen-Ion Concentration ; Seawater
    Chemical Substances Carbon (7440-44-0) ; Chlorophyll A (YF5Q9EJC8Y)
    Language English
    Publishing date 2022-06-30
    Publishing country England
    Document type Journal Article
    ZDB-ID 1502505-6
    ISSN 1879-0291 ; 0141-1136
    ISSN (online) 1879-0291
    ISSN 0141-1136
    DOI 10.1016/j.marenvres.2022.105694
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Simulated response of St. Joseph Bay, Florida, seagrass meadows and their belowground carbon to anthropogenic and climate impacts

    Lebrasse, Marie Cindy / Schaeffer, Blake A. / Zimmerman, Richard C. / Hill, Victoria J. / Coffer, Megan M. / Whitman, Peter J. / Salls, Wilson B. / Graybill, David D. / Osburn, Christopher L.

    Marine Environmental Research. 2022 July, v. 179 p.105694-

    2022  

    Abstract: Seagrass meadows are degraded globally and continue to decline in areal extent due to human pressures and climate change. This study used the bio-optical model GrassLight to explore the impact of climate change and anthropogenic stressors on seagrass ... ...

    Abstract Seagrass meadows are degraded globally and continue to decline in areal extent due to human pressures and climate change. This study used the bio-optical model GrassLight to explore the impact of climate change and anthropogenic stressors on seagrass extent, leaf area index (LAI) and belowground organic carbon (BGC) in St. Joseph Bay, Florida, using water quality data and remotely-sensed sea surface temperature (SST) from 2002 to 2020. Model predictions were compared with satellite-derived measurements of seagrass extent and shoot density from the Landsat images for the same period. The GrassLight-derived area of potential seagrass habitat ranged from 36.2 km² to 39.2 km², averaging 38.0 ± 0.8 km² compared to an observed seagrass extent of 23.0 ± 3.0 km² derived from Landsat (range = 17.9-27.4 km²). GrassLight predicted a mean seagrass LAI of 2.7 m² leaf m⁻² seabed, compared to a mean LAI of 1.9 m² m⁻² estimated from Landsat, indicating that seagrass density in St. Joseph Bay may have been below its light-limited ecological potential. Climate and anthropogenic change simulations using GrassLight predicted the impact of changes in temperature, pH, chlorophyll a, chromophoric dissolved organic matter and turbidity on seagrass meadows. Simulations predicted a 2-8% decline in seagrass extent with rising temperatures that was offset by a 3-11% expansion in seagrass extent in response to ocean acidification when compared to present conditions. Simulations of water quality impacts showed that a doubling of turbidity would reduce seagrass extent by 18% and total leaf area by 21%. Combining climate and water quality scenarios showed that ocean acidification may increase seagrass productivity to offset the negative effects of both thermal stress and declining water quality on the seagrasses growing in St. Joseph Bay. This research highlights the importance of considering multiple limiting factors in understanding the effects of environmental change on seagrass ecosystems.
    Keywords Landsat ; anthropogenic activities ; anthropogenic stressors ; chlorophyll ; climate ; climate change ; dissolved organic matter ; habitats ; humans ; leaf area ; leaf area index ; leaves ; models ; ocean acidification ; organic carbon ; pH ; remote sensing ; research ; seagrasses ; surface water temperature ; thermal stress ; turbidity ; water quality ; Florida ; Seagrass ; GrassLight ; Submerged aquatic vegetation
    Language English
    Dates of publication 2022-07
    Publishing place Elsevier Ltd
    Document type Article ; Online
    Note Use and reproduction
    ZDB-ID 1502505-6
    ISSN 1879-0291 ; 0141-1136
    ISSN (online) 1879-0291
    ISSN 0141-1136
    DOI 10.1016/j.marenvres.2022.105694
    Database NAL-Catalogue (AGRICOLA)

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