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<p>Occupying critical ecological areas at the land-sea interface, mangrove ecosystems are increasingly recognized as potent nature-based solutions supporting diverse sustainable development goals. Leveraging spatially explicit remote sensing for monitoring mangrove biodiversity is essential, however, measurement challenges arise due to their narrow and fragmented distribution over impenetrable muddy substrates compared to terrestrial forests. This study presents the first attempt to map mangrove functional diversity (FD) using a multi-trait-based approach, incorporating key spectral vegetation indexes as well as optically derived functional traits: leaf chlorophyll content (LCC), leaf mass per area (LMA), and equivalent water thickness (EWT) retrieved from Sentinel-2. A moving window approach was employed to quantify three independent FD components: richness, divergence, and evenness. While spatial scale dependence primarily influenced richness, the moving window size significantly impacted spatial FD results, especially in fragmented mangrove areas. Both ecological relevance and independence of selected traits/VIs dominated the construction of more ecologically representative niches in computational three-dimensional space, leading to different estimations of mangrove FD based on input correlations. This study advances remote sensing applications for quantifying mangrove FD, meanwhile highlighting challenges of scaling, fragmentation, and input selection for providing valuable biodiversity insights into mangrove blue carbon ecosystems.</p>

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Mapping mangrove multi-trait functional diversity from satellite observations across dense and fragmented stands using spectral-biophysical derivatives

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年7月1日

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  • Nguyen An Binh,
  • Leon T. Hauser

摘要

Occupying critical ecological areas at the land-sea interface, mangrove ecosystems are increasingly recognized as potent nature-based solutions supporting diverse sustainable development goals. Leveraging spatially explicit remote sensing for monitoring mangrove biodiversity is essential, however, measurement challenges arise due to their narrow and fragmented distribution over impenetrable muddy substrates compared to terrestrial forests. This study presents the first attempt to map mangrove functional diversity (FD) using a multi-trait-based approach, incorporating key spectral vegetation indexes as well as optically derived functional traits: leaf chlorophyll content (LCC), leaf mass per area (LMA), and equivalent water thickness (EWT) retrieved from Sentinel-2. A moving window approach was employed to quantify three independent FD components: richness, divergence, and evenness. While spatial scale dependence primarily influenced richness, the moving window size significantly impacted spatial FD results, especially in fragmented mangrove areas. Both ecological relevance and independence of selected traits/VIs dominated the construction of more ecologically representative niches in computational three-dimensional space, leading to different estimations of mangrove FD based on input correlations. This study advances remote sensing applications for quantifying mangrove FD, meanwhile highlighting challenges of scaling, fragmentation, and input selection for providing valuable biodiversity insights into mangrove blue carbon ecosystems.