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<p>Accurately identifying the causes of mangrove dieback is essential for global coastal management, yet visually similar dieback events can result in incorrect attribution of causes. A significant mangrove dieback in Boambee Creek Estuary (2021) was initially linked to chemical contamination from nearby Coffs Harbour Airport. This study uses a forensic geospatial reconstruction to test the validity of this toxicity hypothesis against a physical-hydrological alternative. Scaling up from localised, site-specific field observations, we used multi-sensor satellite telemetry (Sentinel-2), LiDAR-based geomorphic modelling and ERA5 climatological reanalysis to assess the ecosystem at the landscape scale. The investigation pinpoints a statistically extreme hailstorm on 20 October 2021 as the trigger event, representing a &gt; 1-in-100-year anomaly (<i>Z</i> = 4.10σ). Time-series diagnostics confirm an immediate structural collapse (<i>p</i> &lt; 0.001) coinciding with the storm, ruling out the signature of gradual chemical ageing. Mortality followed a Death Curve, where the likelihood of death neared 100% at elevations below 1.5&#xa0;m AHD (<i>p</i> &lt; 10<sup>–8</sup>) within stagnant topographic basins (&lt; 2° slope). Hydrological routing shows that the main runoff from the airport flows directly into the remaining forest, creating a Runoff Paradox that statistically discredits the chemical vector hypothesis. We conclude that the dieback is best explained by a compound disturbance framework, primarily triggered by a hydrological trap. Sudden physical defoliation halted canopy transpiration, causing rapid soil anoxia and root drowning in geomorphically unstable basins. Secondary chemical stressors may inhibit long-term recovery. Future management should focus on restoring hydrological connectivity rather than chemical remediation. This study highlights the vital need to incorporate landscape-scale multi-sensor remote sensing (Optical, Radar and LiDAR) for validating localised field sampling and accurately diagnosing heterogeneous dieback events worldwide.</p>

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Multi-sensor geospatial modelling to address complex mangrove dieback: misattribution of chemical stressors versus physical impact

  • 期刊论文

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  • 发表日期：

    2026年7月7日

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  • Jade Farrugia

摘要

Accurately identifying the causes of mangrove dieback is essential for global coastal management, yet visually similar dieback events can result in incorrect attribution of causes. A significant mangrove dieback in Boambee Creek Estuary (2021) was initially linked to chemical contamination from nearby Coffs Harbour Airport. This study uses a forensic geospatial reconstruction to test the validity of this toxicity hypothesis against a physical-hydrological alternative. Scaling up from localised, site-specific field observations, we used multi-sensor satellite telemetry (Sentinel-2), LiDAR-based geomorphic modelling and ERA5 climatological reanalysis to assess the ecosystem at the landscape scale. The investigation pinpoints a statistically extreme hailstorm on 20 October 2021 as the trigger event, representing a > 1-in-100-year anomaly (Z = 4.10σ). Time-series diagnostics confirm an immediate structural collapse (p < 0.001) coinciding with the storm, ruling out the signature of gradual chemical ageing. Mortality followed a Death Curve, where the likelihood of death neared 100% at elevations below 1.5 m AHD (p < 10–8) within stagnant topographic basins (< 2° slope). Hydrological routing shows that the main runoff from the airport flows directly into the remaining forest, creating a Runoff Paradox that statistically discredits the chemical vector hypothesis. We conclude that the dieback is best explained by a compound disturbance framework, primarily triggered by a hydrological trap. Sudden physical defoliation halted canopy transpiration, causing rapid soil anoxia and root drowning in geomorphically unstable basins. Secondary chemical stressors may inhibit long-term recovery. Future management should focus on restoring hydrological connectivity rather than chemical remediation. This study highlights the vital need to incorporate landscape-scale multi-sensor remote sensing (Optical, Radar and LiDAR) for validating localised field sampling and accurately diagnosing heterogeneous dieback events worldwide.