Assessment of mangrove health based on pressure–state–response framework in Guangxi Beibu Gulf, China

• Published in: Ecological indicators 2024-10, Vol.167, p.112685, Article 112685
• Main Authors: Zhang, Bo, Zhang, Li, Chen, Bowei, Deng, Liangchao, Fu, Bolin, Yan, Min, Ji, Chengyun
• Format: Article
• Language: English
• Subjects: Ecological health; Ecosystem dynamics; Large-scale assessment; Mangrove ecosystems; Pressure–state–response (PSR) framework; Remote sensing
• ISSN: 1470-160X
• DOI: 10.1016/j.ecolind.2024.112685

•The study introduces a novel framework for assessing mangrove ecosystem by integrating physical, structural and traditional indicators.•The methodology’s focus on easy measurement, low cost, and high sensitivity to ecological changes offers early warning capabilities.•The study provides a detailed understanding of how human and natural pressures impact mangrove ecosystems. Mangroves, primarily found along tropical and subtropical coastlines, are crucial ecosystems that offer significant ecological services, including coastal protection, carbon sequestration, and biodiversity support. However, these ecosystems are under severe threat from human activities such as aquaculture, agriculture, and urban development, leading to deforestation and degradation. This study aims to develop a comprehensive framework for assessing the health of mangrove ecosystems using the Pressure-State-Response (PSR) model with annual temporal resolution from 2019 to 2023. It consists of three dimensions: Pressure (human activities and natural factors affecting the ecosystem), State (current condition of the ecosystem), and Response (efforts to mitigate adverse effects and restore health). This study incorporates innovative physical and structural parameters alongside traditional indicators to improve the accuracy of the assessment. The method offers advantages such as ease of measurement, low cost, early warning capabilities for ecosystem damage, and high sensitivity to ecological changes. It provides valuable insights for decision-makers and enhances the ability to detect trends in mangrove health over time through a large-scale, multi-temporal analysis. Using remote sensing techniques and the Analytic Hierarchy Process (AHP), we identified 12 key indicators. The AHP method was used to determine the weight of each indicator, achieving a consistency ratio (CR) of less than 0.1, which ensures the reliability of the assessment. The evaluation included calculating and analysing the Comprehensive Health Index (CHI), Pressure (PHI), State (SHI), and Response (RHI) health indices. Results indicated that the mangrove ecosystems in the Beibu Gulf region were “healthy” state by 2019 through 2022. However, in 2023, the health status declined to “relatively healthy,” indicating a downward trend. In conclusion, this study presents a robust framework for assessing mangrove ecosystem health using the PSR model. The findings underscore the urgent need for conservation efforts to reverse the decli