Rethinking landscape ecological risk assessment and its applicability: Counterintuitive findings from coastal areas

Abstract

AbstractLandscape ecological risk assessment (LERA) serves as a crucial tool for guiding effective environmental management. However, the conventional approach of LERA suffers from two notable drawbacks: the utilization of low‐resolution land‐use data (e.g., 30 × 30 m) and the application of arbitrary evaluation units (e.g., uniformly‐sized grids), both of which introduce uncertainty and inaccuracies into the assessment outcomes. Moreover, the extent to which the traditional LERA accurately reflects the true ecological risk level remains unexplored. To address these limitations, this study presents a modified LERA conducted in Xiapu, a coastal county in China, spanning the years 2013–2015. Fine‐grained land‐use data were employed to overcome the shortcomings of low‐resolution data. Additionally, spatial correlations between land‐use changes and ecological risk alterations were analyzed to unravel the mechanisms behind land‐use changes' impact on ecological risk, while also testing the accuracy of LERA results. Major findings can be summarized as follows: (1) Ecological risk changes in Xiapu during 2013–2015 were relatively minor, with high‐risk areas predominantly concentrated along the coast. (2) A total of 1137 ha of land in Xiapu County experienced changes, with construction land witnessing the most substantial increase. (3) Counterintuitive and unreasonable LERA outcomes were identified, particularly pertaining to illogical ecological risk changes arising from transformations between construction and non‐construction land. (4) Based on the counterintuitive findings, potential factors affecting the limitations and applicability of LERA were discussed. This study represents the first critical examination of the limitations of LERA, offering valuable insights to stimulate future researchers to rethink LERA and emphasize the importance of validating assessment outcomes during its application.