Mafi-Gholami Davood, Pirasteh Saied, Ellison Joanna C, Jaafari Abolfazl
Department of Surveying and Geoinformatics, Faculty of Geosciences and Environmental Engineering (FGEE), Southwest Jiaotong University, Chengdu, 611756, China; Department of Forest Sciences, Faculty of Natural Resources and Earth Sciences, Shahrekord University, Shahrekord, Iran.
Department of Surveying and Geoinformatics, Faculty of Geosciences and Environmental Engineering (FGEE), Southwest Jiaotong University, Chengdu, 611756, China.
J Environ Manage. 2021 Dec 1;299:113573. doi: 10.1016/j.jenvman.2021.113573. Epub 2021 Sep 3.
Climate change and combining related parameters of environmental hazards have left a considerable challenge in assessing social-ecological vulnerability. Here we integrated a fuzzy-based approach in the vulnerability assessment of mangrove social-ecological systems combining environmental parameters, socio-economic, and vegetative components from exposure dimensions, sensitivity and adaptive capacity along the northern coasts of the Persian Gulf and the Gulf of Oman for the first time. This study aims to provide critical information for habitat-scale management strategies and adaptation plans by assessing the vulnerability of mangrove social-ecological systems. This study provides a methodology framework that consists of five steps. Step 1: We combined the fuzzy weighted maps of seven environmental hazards, including tidal range, maximum wind speeds, drought magnitude, maximum temperatures, extreme storm surge, sea-level rise, significant wave height, and social vulnerability. This map combination determined that the computed exposure index is from 1.07 to 4.32 across the study areas, with an increasing trend from the coasts of the Persian Gulf to the Gulf of Oman. Step 2: We integrated the fuzzy weighted maps of four sensitivity variables, including area change, health change, seaward edge retreat, and production potential change. The findings show that the sensitivity index is from 1.40 to 2.64 across the study areas, increasing the trend from the Persian Gulf coast to the Gulf of Oman. Step 3: Besides, we combined the fuzzy weighted maps of three adaptive capacity variables, including the availability of migration areas, recruitment, and local communities' participation in restoration projects and education programs. The result showed that the index value across the study areas varies between 0.087 and 2.38, decreasing the trend from the Persian Gulf coast to the Gulf of Oman. Step 4: Implementing fuzzy hierarchical analysis process to determine the relative weight of variables corresponding to exposure, sensitivity and adaptive capacity. Step 5: The integration of exposure, sensitivity and adaptive capacity and the vulnerability index maps in the study areas showed variation from 0.25 to 5.92, with the vulnerability of mangroves from the west coast of the Persian Gulf (Nayband) decreasing towards Khamir, then increasing to the eastern coasts of the Gulf of Oman (Jask and Gwadar). Overall, the results indicate the importance of the proposed approach to the vulnerability of mangroves at the habitat scale along a coastal area and across environmental gradients of climatic, maritime and socio-economic variables. This study validated the findings based on the ground truth measurements, and high-resolution satellite data incorporated the Consistency Rate (CR) in the Fuzzy Analytic Hierarchy Process (FAHP). The overall accuracy of all classified remote sensing images and maps consistently exceeded 90%, and the CR of the 25 completed questionnaires was <0.1. Finally, this study indicates differences in vulnerability of various habitats, leading to focus conservation completion and rehabilitation and climate change adaptation planning to support the Sustainable Development Goal (SDG)-13 implementation.
气候变化以及相关环境危害参数的综合,给社会生态脆弱性评估带来了巨大挑战。在此,我们首次将基于模糊的方法整合到红树林社会生态系统的脆弱性评估中,该评估结合了波斯湾和阿曼湾北部海岸沿线暴露维度、敏感性和适应能力方面的环境参数、社会经济及植被组成部分。本研究旨在通过评估红树林社会生态系统的脆弱性,为栖息地尺度的管理策略和适应计划提供关键信息。本研究提供了一个由五个步骤组成的方法框架。步骤1:我们将包括潮差、最大风速、干旱强度、最高温度、极端风暴潮、海平面上升、有效波高和社会脆弱性在内的七种环境危害的模糊加权地图进行了合并。这种地图合并确定,整个研究区域计算出的暴露指数在1.07至4.32之间,从波斯湾海岸到阿曼湾呈上升趋势。步骤2:我们整合了四个敏感性变量的模糊加权地图,包括面积变化、健康变化、向海边缘退缩和生产潜力变化。研究结果表明,整个研究区域的敏感性指数在1.40至2.64之间,从波斯湾海岸到阿曼湾呈上升趋势。步骤3:此外,我们还合并了三个适应能力变量的模糊加权地图,包括迁移区域的可用性、补充以及当地社区对恢复项目和教育计划的参与情况。结果显示,整个研究区域的指数值在0.087至2.38之间变化,从波斯湾海岸到阿曼湾呈下降趋势。步骤4:实施模糊层次分析过程,以确定与暴露、敏感性和适应能力相对应的变量的相对权重。步骤5:研究区域内暴露、敏感性和适应能力以及脆弱性指数地图的整合显示,其变化范围在0.25至5.92之间,波斯湾西海岸(奈班德)的红树林脆弱性朝着卡米尔方向降低,然后在阿曼湾东海岸(贾斯克和瓜达尔)又有所增加。总体而言,结果表明所提出的方法对于沿海地区栖息地尺度上红树林脆弱性以及跨越气候、海洋和社会经济变量的环境梯度的重要性。本研究基于实地测量结果进行了验证,高分辨率卫星数据在模糊层次分析法(FAHP)中纳入了一致性率(CR)。所有分类遥感图像和地图的总体精度始终超过90%,25份完整问卷的CR<0.1。最后,本研究指出了不同栖息地脆弱性的差异,从而促使关注保护完善与恢复以及气候变化适应规划,以支持可持续发展目标(SDG)-13的实施。