Mapping the Loss of Ecosystem Services in a Region Under Intensive Land Use Along the Southern Coast of South Africa
Mapping the Loss of Ecosystem Services in a Region Under Intensive Land Use Along the Southern Coast of South Africa
复制标题
绘制南非南部海岸土地集约利用地区生态系统服务损失情况
作者：
Hanlie Malherbe;S. Pauleit;C. Lorz
全世界的土地集约利用活动已对许多生态系统服务造成了相当大的损失。必须迅速调查这些威胁的动态，以确保及时更新管理战略和政策。与复杂的模型相比，使用评分矩阵将土地利用/土地覆被和景观特性与生态系统服务联系起来的制图方法相对有效，也更容易应用。在这项研究中，评分矩阵的开发和空间明确的评估五个生态系统服务，如侵蚀控制，水流调节，水质维护，土壤质量维护和生物多样性维护，进行了区域下的土地利用强度沿着南非南部海岸。通过对造成生态系统服务损失的高风险地区进行空间概览，进一步阐明了特定景观中土地利用/土地覆被与生态系统服务之间复杂的相互作用。结果表明，农业活动和城市发展都造成了生态系统服务的损失。本研究表明，通过对以往文献的充分了解和专家的意见，评分矩阵的使用可以适应不同的区域特征。这种方法可以通过添加额外的景观属性和/或适应新的数据变得可用的矩阵值来改进。
Intensive land use activities worldwide have caused considerable loss to many ecosystem services. The dynamics of these threats must be quickly investigated to ensure timely update of management strategies and policies. Compared with complex models, mapping approaches that use scoring matrices to link land use/land cover and landscape properties with ecosystem services are relatively efficient and easier to apply. In this study, scoring matrices are developed and spatially explicit assessments of five ecosystem services, such as erosion control, water flow regulation, water quality maintenance, soil quality maintenance, and biodiversity maintenance, are conducted for a region under intense land use along the southern coast of South Africa. The complex interaction of land use/land cover and ecosystem services within a particular landscape is further elucidated by performing a spatial overview of the high-risk areas that contribute to the loss of ecosystem services. Results indicate that both agricultural activities and urban development contribute to the loss of ecosystem services. This study reveals that with sufficient knowledge from previous literature and inputs from experts, the use of scoring matrices can be adapted to different regional characteristics. This approach can be improved by adding additional landscape properties and/or adapting the matrix values as new data become available.