基于栖息地风险评价模型的海岸带滩涂湿地风险评价——以闽三角为例

海岸带湿地是生物多样性最丰富、生产力最高、最具价值的生态系统之一。然而近年来,随着城市化和工业化进程的加快,我国海岸带地区的土地利用正发生深刻变化,生态风险凸显。利用2000、2005、2010和2015年的Landsat TM/ETM+和Landsat 8 OLI遥感影像,融合行政区划图与地形图,并引入一个评价多元海洋、海岸带利用对栖息地造成风险的模型,即Integrated Valuation of Ecosystem Services and Trade-offs(In VEST)模型中的栖息地风险评价(Habitat Risk Assessment,HRA),模型评价闽三角海岸带滩涂湿地的生态风险。结果表明:(1)闽三角海岸带滩涂湿地风险以低风险为主;(2)泉州地区的风险面积最大(约4389.91 hm~2),漳州地区最小(约4630.73 hm~2);(3)修正面积影响的情况下,其他建设用地造成的暴露和影响较大,耕地造成的暴露和影响最小。不同区域滩涂湿地风险程度的可视化表达,可以揭示滩涂湿地高风险地区以及高风险的产生原因,便于管理者对滩涂湿地采取精准的保育措施。

Assessing ecosystem risk in coastal wetland of the South Fujian Golden Delta using a habitat risk assessment model based on the land-use effect on tidal flat wetland

Coastal wetlands are one of our most valuable ecosystems; they have high biodiversity and productivity. In recent years, with the development of urbanization and the acceleration of industry progress, the land use in China has undergone some prominent and profound changes, and the ecological risk is becoming increasingly obvious. Here, using original Landsat TM/ETM+ and Landsat 8 OLI satellite images from the years 2000, 2005, 2010, and 2015, and merging administrative and topographic maps, we introduce a model which assesses the risk of multiple marine and coastal utilization projects to habitats, called the Habitat Risk Assessment (HRA) model. We use this model to reflect the current ecosystem risk in the South Fujian Golden Delta so that managers of the area can take adaptive measures. The results show that (1) overall, the risk to tidal flat wetland in the coastal South Fujian Golden Delta is mainly low; (2) the risk area in Quanzhou is the largest (about 4389.91 hm²) while the risk area in Zhangzhou is the smallest (about 4630.73 hm²); (3) after correcting for the influence of each land-use type''s area, other construction land has the greatest exposure and consequence to coastal tidal wetlands, whereas plantation has the least exposure and consequence. The visualization of tidal flat wetland risk in different areas enables us to monitor high risk areas, and determine factors that cause high risk areas. Thus, it is more convenient for managers to take adaptive conservation measures.