4.7 Article

Mapping the Extent of Mangrove Ecosystem Degradation by Integrating an Ecological Conceptual Model with Satellite Data

Journal

REMOTE SENSING
Volume 13, Issue 11, Pages -

Publisher

MDPI
DOI: 10.3390/rs13112047

Keywords

mangrove; ecosystem assessment; Myanmar; Everglades; satellite imagery; degradation; ecosystem conceptual model

Funding

  1. Australian Government Research Training Program Scholarship
  2. Australian Research Council Discovery Early Career Research Award [DE190100101]
  3. Office of the Chief scientist of Victoria [IWF01]
  4. Australian Research Council [FT190100234, LP170101143]
  5. AXA Research Fund
  6. NASA Carbon Monitoring System Program Project Estimating Total Ecosystem Carbon in Blue Carbon and Tropical Peatland Ecosystems [16-CMS16-0073]
  7. Australian Research Council [LP170101143, DE190100101, FT190100234] Funding Source: Australian Research Council

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This study developed a quantitative classification model of mangrove ecosystem degradation using freely available earth observation data and applied it to two case studies, showing degradation extents of 40% and 97.4%. The use of an ecological conceptual model as a basis for building quantitative classification models ensures ecological relevance and supports ecosystem risk assessments, natural capital accounting, and restoration planning.
Anthropogenic and natural disturbances can cause degradation of ecosystems, reducing their capacity to sustain biodiversity and provide ecosystem services. Understanding the extent of ecosystem degradation is critical for estimating risks to ecosystems, yet there are few existing methods to map degradation at the ecosystem scale and none using freely available satellite data for mangrove ecosystems. In this study, we developed a quantitative classification model of mangrove ecosystem degradation using freely available earth observation data. Crucially, a conceptual model of mangrove ecosystem degradation was established to identify suitable remote sensing variables that support the quantitative classification model, bridging the gap between satellite-derived variables and ecosystem degradation with explicit ecological links. We applied our degradation model to two case-studies, the mangroves of Rakhine State, Myanmar, which are severely threatened by anthropogenic disturbances, and Shark River within the Everglades National Park, USA, which is periodically disturbed by severe tropical storms. Our model suggested that 40% (597 km(2)) of the extent of mangroves in Rakhine showed evidence of degradation. In the Everglades, the model suggested that the extent of degraded mangrove forest increased from 5.1% to 97.4% following the Category 4 Hurricane Irma in 2017. Quantitative accuracy assessments indicated the model achieved overall accuracies of 77.6% and 79.1% for the Rakhine and the Everglades, respectively. We highlight that using an ecological conceptual model as the basis for building quantitative classification models to estimate the extent of ecosystem degradation ensures the ecological relevance of the classification models. Our developed method enables researchers to move beyond only mapping ecosystem distribution to condition and degradation as well. These results can help support ecosystem risk assessments, natural capital accounting, and restoration planning and provide quantitative estimates of ecosystem degradation for new global biodiversity targets.

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