The challenge the method addresses is a familiar one in marine ecology. Existing monitoring frameworks, such as Seagrass-Watch and the Western Indian Ocean Seagrass Network, have harmonized field techniques and built valuable long-term datasets, but they rely on fixed transects and quadrats that are logistically demanding and expensive to replicate. As a result, coverage remains geographically uneven and concentrated at a handful of reference sites. Remote sensing offers a broader view but performs poorly in turbid waters or over low-biomass meadows, leaving major gaps in spatially explicit ecological assessment. Rapid Assessment Methods, or RAMs, occupy the middle ground: they sacrifice some quantitative precision in exchange for dramatically reduced sampling effort, lower expertise requirements, and far wider spatial coverage, making them attractive for regional and national management decisions.

SEARAM was developed with support from the French Coral Reef Initiative and tested over a 202.3-hectare intertidal sector of Petite-Terre, Mayotte, stretching from Dzaoudzi and Moya Beach to the southern end of the Pamandzi airport runway. The site is an ecological pressure cooker. Rapid demographic growth, urban expansion, chronic terrigenous runoff, intense shoreline gleaning, and sediment inputs from both of the island’s landmasses converge on nearshore meadows that were once naturally resilient. Over the past two decades, late-successional species such as Thalassodendron ciliatum, now nearly absent, and Thalassia hemprichii have regressed, replaced by pioneer and opportunistic taxa like Halodule uninervis and Halophila ovalis, a classic signature of regressive ecological succession under cumulative stress.

The protocol itself rests on eight seagrass biodiversity indicators, each chosen for its ecological relevance and compatibility with existing monitoring programs. Four describe meadow structure: continuity, or the percentage of soft substrate covered by seagrass; intra-patch cover, the density of shoots within patches; species richness; and canopy height. Four describe vitality: epiphyte load on leaves, macroalgal cover, leaf necrosis, and rhizome exposure caused by erosion. During an eight-day snorkeling campaign in September 2022, two divers surveyed 536 circular plots of 100 square meters each, positioned within a 144-cell grid. Within each plot, a subdivided 0.25-square-meter quadrat was randomly placed three times, allowing nested measurements from large-scale fragmentation down to fine-scale estimates of epiphyte and necrosis cover.

Observer consistency was treated as a critical design element. Both divers, each with more than twenty years of tropical marine survey experience, underwent a two-day training session including a full day of underwater inter-calibration, and standardized graphical scoring guides were printed on the backs of their underwater slates. Daily calibration sessions aboard the survey vessel allowed the team to harmonize indicator interpretation before sampling began. Statistical analysis later confirmed the effort paid off: no significant observer effect was detected for any of the eight indicators, suggesting the calibration procedures successfully minimized systematic bias, although the authors caution that formal repeatability experiments with independent observer teams remain a necessary next step.

Field observations were converted into continuous scores ranging from zero to three using indicator-specific logarithmic transformations, then aggregated into two complementary sub-indices. The Structure Index combines the four structural indicators, which respond slowly to environmental change and increase with habitat maturity. The Vitality Index combines the four stress-related indicators, which react over shorter timescales to physiological stress and degradation. Their arithmetic mean yields the Seagrass Ecological State Index, or SESI, classified into five categories from very bad to very good. Because similar SESI values can arise from different combinations of structure and vitality, the authors stress that the sub-indices should always be interpreted alongside the composite score.

The results painted a nuanced picture of a stressed seascape. Seagrass occurred in 54 percent of plots, but only about 29 percent of soft substrate within vegetated plots was colonized, with a mean total cover of just six percent, indicating strong fragmentation. Eight species were recorded, though the community was dominated by the pioneer Halodule uninervis and Halophila ovalis, while late-successional taxa contributed less than five percent of cover in most habitats. The exposed fringing reef flat showed the best structural development, with the highest meadow continuity and total cover, while the barrier reef flat displayed the highest vitality, with the lowest epiphyte and necrosis levels. The inner fringing reef flat, lagoon-facing and bathed in fine terrigenous sediments near the towns of Dzaoudzi and Pamandzi, emerged as the most degraded habitat, scoring lowest on seven of the eight indicators, with heavy epiphyte loads of around 40 percent and macroalgal cover near 24 percent, pointing to nutrient enrichment from nearby urban areas.

Crucially, the indices proved ecologically meaningful when linked to fauna and environmental drivers. Green turtles, surveyed by ultralight aircraft during three high-tide flights, reached densities of 0.89 individuals per hectare in vegetated sites, nearly double those of unvegetated areas, and were significantly associated with Halodule uninervis cover. Dugong feeding pits, detected at 27 plots almost entirely on the inner fringing reef, were linked to Halophila ovalis patches, consistent with the dugong’s preference for low-fiber, nitrogen-rich seagrasses consumed whole, rhizomes included. Fish species richness, macro-invertebrate abundance, and crustacean burrow densities were all significantly higher in vegetated sites. Regression models showed the composite index increased with coarser sediments and higher temperature but declined with turbidity, reflecting the sensitivity of seagrasses to light limitation, and explained between 17 and 35 percent of spatial variance.

The method also demonstrated remarkable field efficiency, averaging 33.5 stations per diver per day, comparable to the coral-reef CORRAM protocol, while simultaneously recording sediment characteristics and megafauna traces. Comparison with a WIOSN sentinel station monitored by the Mayotte Marine Natural Park showed close agreement on shared indicators, with one instructive discrepancy: SEARAM’s surface-based circular plots recorded lower meadow continuity than the line-intercept transects, precisely because fragmentation is an inherently two-dimensional property that linear transects tend to underestimate. The authors emphasize that SEARAM is designed to complement, not replace, sentinel monitoring and remote sensing, and that its indices must be interpreted relative to the seasonal and spatial context of calibration. Future applications, including SCUBA-based subtidal extensions, automated image analysis, and integration with very-high-resolution satellite imagery, could extend the framework across the tropical seagrass ecosystems that urgently need mapping before they disappear.

Subject of Research: A rapid assessment method for mapping the ecological state of tropical intertidal seagrass meadows

Article Title: Unlocking spatial ecological assessment for tropical seagrass habitats using a new rapid assessment method (SEARAM)

Article References: Unlocking spatial ecological assessment for tropical seagrass habitats using a new rapid assessment method (SEARAM). (n.d.). https://doi.org/10.1016/j.indic.2026.101538

Image Credits: AI Generated

DOI: 10.1016/j.indic.2026.101538

Keywords: seagrass, rapid assessment method, SEARAM, Mayotte, marine ecology, ecological indicators, green turtles, dugongs, coastal monitoring, biodiversity, Indian Ocean, habitat fragmentation