Seagrass Restoration Review: Spatial Analysis of Potential Habitats, Innovative Restoration Methods, and Predictive Modeling for Monitoring

Abstract

  Seagrass ecosystems are vital for maintaining marine ecological balance, supporting the blue carbon cycle, offering habitat for marine organisms, and safeguarding coastal areas against erosion. Nevertheless, seagrass ecosystems worldwide are declining substantially due to human activities and climate change. This trend is also evident in Indonesia, where approximately 7% of seagrass coverage is lost annually. This research examines existing literature on seagrass restoration by focusing on three key approaches: spatial assessment of suitable habitats, advancements in physical restoration techniques, and the creation of predictive models for evaluating restoration outcomes. The goal is to offer comprehensive insights into the challenges and prospects for improving management and establishing more effective and sustainable restoration strategies in coastal environments. A Systematic Literature Review (SLR) combined with bibliometric analysis was conducted on 177 publications from the Scopus database spanning 2019 to 2024 to identify research trends, technological advancements, and existing challenges in seagrass restoration. The research emphasizes the necessity of a holistic approach to seagrass restoration, incorporating spatial analysis, developing flexible restoration techniques, and implementing predictive modeling and statistical assessments to enhance long-term planning and monitoring efforts. The case study in Jepara demonstrates the effectiveness of participatory approaches at the local scale, despite limitations in technology and long-term monitoring. Integrating spatial and digital technologies, strengthening local capacity, international collaboration, and multidisciplinary integration are key to improving the effectiveness and sustainability of seagrass restoration, while strengthening its contribution to coastal resilience and climate change mitigation