Abstract
Seagrasses are marine flowering plants found in both temperate and tropical coastal environments, that offer vital ecosystem services and adaptations. However, due to their proximity to the shore, they are heavily impacted by human activities and climate change, endangering seagrasses and their services. To manage seagrass meadows effectively and sustainably, detailed monitoring and data on distribution and extent are essential. Unfortunately, past under-prioritization of reliable baseline data impedes understanding of ecosystem dynamics and rapid response to declines. This study employs satellite imagery, coupled with ground truthing, to comprehensively report seagrass coverage along Tanzania's mainland coast and Zanzibar islands. By utilizing machine-learning technologies, the study achieves 84.2% accuracy, and found that Tanzania has 2817 km2 of seagrass coverage, which is five times higher than previously reported. In addition, the results also provide coverage of additional benthic habitats, such as corals, rocks/rubble, and sand. This study provides the first comprehensive overview of seagrass coverage in Tanzania and will function as a valuable tool and baseline for understanding and managing these habitats. The findings suggest that seagrasses in Tanzania are still relatively abundant, but due to a number of threats, including pollution, coastal development, and climate change, these habitats require improvement in management strategies including regular monitoring to understand their status and trends in their area coverage. The study highlights the significance of remote sensing and machine learning in mapping and monitoring coastal habitats across extensive geographical areas. We aspire for the presented results to be utilized among stakeholders and researchers to develop more effective conservation measures for seagrasses in Tanzania and the Western Indian Ocean.
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