Xu Menglin, Matsushima Hajime
Graduate School of Agriculture, Hokkaido University, Kita 9 Nishi 9, Kita ward, Sapporo, Hokkaido 060-8589, Japan.
Research Faculty of Agriculture, Hokkaido University, Kita 9 Nishi 9, Kita ward, Sapporo, Hokkaido 060-8589, Japan.
Sci Total Environ. 2024 Jan 15;908:168183. doi: 10.1016/j.scitotenv.2023.168183. Epub 2023 Nov 7.
The eastern coastal areas of Japan are threatened by multiple ecological risks due to frequent natural disasters, climate changes, human activities, etc. Identification spatio-temporal variations and driving mechanisms of landscape ecological risk could be used as significant basis for policymakers. In this study, taking the eastern coastal areas of Japan affected by the 2011 Great East Japan Earthquake and Tsunami Disaster as the study area, the "Nature-Landscape Pattern-Human Society" (NA-LP-HS) multi-dimensional ecological risk assessment framework was established to analyze the spatio-temporal patterns, and identity driving factors using spatial cluster analysis and spatial principal component analysis (SPCA) based on ArcGIS from 2009 to 2021. The findings revealed the distinct geographic patterns in landscape ecological risk, with a noticeable decline from the southwest to the northeast. During the period from 2009 to 2015, the driving factors leading to a sharp risk increase were natural disasters and vegetation coverage. These high-risk areas were concentrated in Sendai Bay and its surroundings. From 2015 to 2021, ecological instability was primarily attributed to a reduction in vegetation coverage, the occurrence of natural disasters, and heightened rainfall erosion. These high-risk areas were mainly clustered within the Tokyo-centered urban agglomeration. Spatial clustering of ecological risks was obvious across all time periods. The key factors contributing to the clustering of high ecological landscape risks focused on the "landscape pattern" criterion, specifically including vegetation coverage, land use land cover. This study demonstrated the ability of multi-dimensional ecological risk assessment to identify high-risk areas and driving factors, and these results could provide a visual analysis and decision-making basis for sustainable development of coastal areas.
由于频繁的自然灾害、气候变化、人类活动等因素，日本东部沿海地区面临多种生态风险。识别景观生态风险的时空变化及驱动机制可为政策制定者提供重要依据。本研究以受2011年东日本大地震及海啸灾害影响的日本东部沿海地区为研究区域，构建了“自然—景观格局—人类社会”（NA-LP-HS）多维生态风险评估框架，基于ArcGIS运用空间聚类分析和空间主成分分析（SPCA），分析2009年至2021年的时空格局并识别驱动因素。研究结果揭示了景观生态风险明显的地理格局，从西南向东北显著降低。在2009年至2015年期间，导致风险急剧增加的驱动因素是自然灾害和植被覆盖度。这些高风险区域集中在仙台湾及其周边地区。2015年至2021年，生态不稳定主要归因于植被覆盖度降低、自然灾害发生以及降雨侵蚀加剧。这些高风险区域主要集中在以东京为中心的城市群内。各时间段生态风险的空间聚类均很明显。导致高生态景观风险聚类的关键因素集中在“景观格局”标准上，具体包括植被覆盖度、土地利用土地覆盖。本研究证明了多维生态风险评估识别高风险区域和驱动因素的能力，这些结果可为沿海地区可持续发展提供直观的分析和决策依据。
