Mapping the structure of mixed seagrass meadows in the Mexican Caribbean

• Published in: Frontiers in Marine Science 2022-12, Vol.9
• Main Authors: de Almeida, Laura R., Ávila-Mosqueda, S. Valery, Silva, Rodolfo, Mendoza, Edgar, van Tussenbroek, Brigitta I.
• Format: Article
• Language: English
• Subjects: LAI estimation; multiparameter classification; PlanetScope satellite image; reef lagoon; seagrass mapping
• ISSN: 2296-7745; 2296-7745
• DOI: 10.3389/fmars.2022.1063007

The physical and ecological importance of seagrass meadows in coastal processes is widely recognized, and the development of tools facilitating characterization of their structure and distribution is important for improving our understanding of these processes. Mixed (multi-specific) meadows in a Mexican Caribbean reef lagoon were mapped employing a multiparameter approach, using PlanetScope remote sensing images, and supervised classification based on parameters related to the structure of the seagrasses meadows, including the cover percentages of seagrass/algae/sediment, algae thalli and seagrass shoot densities, canopy heights and estimated leaf area index (LAI). The cover, seagrass and algae densities, and seagrass canopy heights were obtained using ground truth sampling, while the LAI was estimated using data obtained from long-term monitoring programs. The maps do not show the differentiation of seagrass species, but ground truthing contemplated characterization of the density of Thalassia testudinum, Syringodium filiforme and Halodule wrightii and their respective LAIs. S. filiforme was the dominant species in terms of shoot density, and T. testudinum was dominant in terms of LAI. In the multiparameter-based map four classes were defined, based on the cover and structural characteristics, and its overall accuracy was very high (~90%). Maps based on sediment cover and LAI alone also had 4 classes, but they were less accurate than the multiparameter-based map (~70% and ~80%, respectively). The multiparameter-based seagrass map provided spatially-explicit data on the abundance and structure of seagrasses, useful for future monitoring of the changes in the meadows, and also for studies of that require data of large-scale meadow structure, such as inventories of associated biota, blue carbon storage, or modelling of the local hydrodynamics.