ArticleiScience2026
Seagrass monitoring methods: Aligning expert opinion with practice.
Article in iScience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Authors and funding
3 authors.
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Abstract
Seagrass meadows are vital ecosystems, yet methods to monitor their health lack standardization, which makes data comparison challenging. To identify key approaches and evaluate alignment with expert opinion, we compared the most used health monitoring methods across 500 studies with a survey of 34 experts. The most reported methods in studies were environmental parameters (44%), percent cover (41%), biomass (40%), distribution/extent (39%), and species composition (37%). Expert importance ratings closely matched: distribution/extent and species composition (100/100), percent cover (99/100), and environmental parameters (92/100). Notably, few studies used physiological-level (10.4%) methods. Experts also anticipated growing roles for remote sensing, eDNA, and AI-assisted image analysis. Together, this study shows a consensus around core, cost-effective methods despite limited integration across biological scales. To address this gap, we propose a multi-level monitoring framework that pairs traditional indicators with early-warning metrics to strengthen seagrass conservation and restoration at broader scales.
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