Unlocking spatial ecological assessment for tropical seagrass habitats using a new rapid assessment method (SEARAM)
Abstract
Seagrass meadows are key coastal ecosystems supporting biodiversity, carbon storage, and essential trophic functions, yet they are increasingly threatened by anthropogenic and climatic pressures. Based on the Seagrass Meadows Rapid Assessment Method (SEARAM), a standardized protocol grounded in seagrass biodiversity indicators (SBIs), we developed a reliable and operational index to assess seagrass ecological state at high spatial resolution. Using 536 circular plots and 144 faunal stations across three intertidal reef habitats in Mayotte (Western Indian Ocean), SEARAM integrates structural and vitality sub-indices into a composite seagrass ecological state index (SESI), spatialized by geostatistical interpolation and analyzed using ANOVA, PCA, and multiple regression models. Results revealed highly fragmented meadows dominated by Halodule uninervis and Halophila ovalis, with low canopy height (5 ± 2 cm) and substantial epiphyte loads (37 ± 17%). The inner fringing reef flat showed the poorest ecological state (SESI = 4.8 ± 0.7/10), whereas the barrier reef (5.4 ± 0.8/10) and exposed fringing reef flat (5.6 ± 0.8/10) exhibited moderate scores. Key environmental drivers (turbidity, grain size, pH), significantly explained spatial patterns of seagrass structure and vitality, confirming the influence of sediment and light regimes. Functional relationships were also demonstrated between seagrass condition and associated fauna, particularly green turtle density and dugong feeding traces. SEARAM proved to be a rapid and robust tool for diagnosing tropical seagrass states. Its multimetric framework connects benthic condition to habitat suitability for megafauna, offering an operational foundation for ecological monitoring, management, and impact mitigation within the Avoid-Reduce-Offset (ARO) doctrine.
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BibTeX
@article{pinault2026unlocking,
title = {{Unlocking spatial ecological assessment for tropical seagrass habitats using a new rapid assessment method (SEARAM)}},
author = {Mathieu Pinault and Léo Broudic and Julien Wickel and Jean-Benoit Nicet and Fanny Kerninon and Katia Ballorain and Touria Bajjouk and Oriane Lepeigneul and Benjamin Bergerot},
journal = {Environmental and Sustainability Indicators},
year = {2026},
month = sep,
doi = {10.1016/j.indic.2026.101538},
url = {https://univ-reunion.hal.science/hal-05762852v1},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Unlocking spatial ecological assessment for tropical seagrass habitats using a new rapid assessment method (SEARAM)
AU - Mathieu Pinault
AU - Léo Broudic
AU - Julien Wickel
AU - Jean-Benoit Nicet
AU - Fanny Kerninon
AU - Katia Ballorain
AU - Touria Bajjouk
AU - Oriane Lepeigneul
AU - Benjamin Bergerot
PY - 2026
DA - 2026/09/19
JO - Environmental and Sustainability Indicators
DO - 10.1016/j.indic.2026.101538
UR - https://univ-reunion.hal.science/hal-05762852v1
AB - Seagrass meadows are key coastal ecosystems supporting biodiversity, carbon storage, and essential trophic functions, yet they are increasingly threatened by anthropogenic and climatic pressures. Based on the Seagrass Meadows Rapid Assessment Method (SEARAM), a standardized protocol grounded in seagrass biodiversity indicators (SBIs), we developed a reliable and operational index to assess seagrass ecological state at high spatial resolution. Using 536 circular plots and 144 faunal stations across three intertidal reef habitats in Mayotte (Western Indian Ocean), SEARAM integrates structural and vitality sub-indices into a composite seagrass ecological state index (SESI), spatialized by geostatistical interpolation and analyzed using ANOVA, PCA, and multiple regression models. Results revealed highly fragmented meadows dominated by Halodule uninervis and Halophila ovalis, with low canopy height (5 ± 2 cm) and substantial epiphyte loads (37 ± 17%). The inner fringing reef flat showed the poorest ecological state (SESI = 4.8 ± 0.7/10), whereas the barrier reef (5.4 ± 0.8/10) and exposed fringing reef flat (5.6 ± 0.8/10) exhibited moderate scores. Key environmental drivers (turbidity, grain size, pH), significantly explained spatial patterns of seagrass structure and vitality, confirming the influence of sediment and light regimes. Functional relationships were also demonstrated between seagrass condition and associated fauna, particularly green turtle density and dugong feeding traces. SEARAM proved to be a rapid and robust tool for diagnosing tropical seagrass states. Its multimetric framework connects benthic condition to habitat suitability for megafauna, offering an operational foundation for ecological monitoring, management, and impact mitigation within the Avoid-Reduce-Offset (ARO) doctrine.
SN - 2665-9727
ER -