Evaluating ecosystem stability based on the dynamic time warping algorithm: A case study in the Minjiang river Basin, China

• Published in: Ecological indicators 2023-10, Vol.154, p.110501, Article 110501
• Main Authors: Ding, Hao, Yuan, Zhe, Yin, Jun, Shi, Xiaoliang, Shi, Mengqi
• Format: Article
• Language: English
• Subjects: Abrupt disturbance; Dynamic time warping algorithm; Ecological system stability; Gradual disturbance; Minjiang river basin
• ISSN: 1470-160X
• DOI: 10.1016/j.ecolind.2023.110501

•A new method for ecosystem stability assessment.•The resistance and resilience of terrestrial ecosystems were quantified.•The vegetation resilience under different disturbance patterns was assessed. With the ongoing impacts of global climate change, the cumulative stress effects of external disturbances on ecosystems are gradually strengthening. Therefore, it is very important to scientifically evaluate the stability of ecosystems. In the terrestrial ecosystems, vegetation serves as a link between the water, energy, and carbon cycles, and is an important index which allows for the measurement of ecosystem stability. In this study, two vegetation indices (normalized difference vegetation index and enhanced vegetation index), along with solar-induced chlorophyll fluorescence data from 2001 to 2021, were used to determine the external disturbance events in the Minjiang river basin using a dynamic time warping (DTW) algorithm. Analyses of the disturbance characteristics during this period, and quantification of the vegetation resistance, resilience, and vegetation regime shift rate were conducted. The results indicated the following. (1) The disturbance results monitored by the DTW algorithm were highly consistent with typical events, and it was feasible to monitor the disturbance of the Minjiang river basin using the DTW algorithm. (2) Disturbance intensity in the river basin increased slightly, while in urban areas it decreased. (3) The resistance of different types of vegetation varied greatly, with the resistance strongest in forests, next in croplands, and weakest in grasslands. In contrast, resilience was the strongest in croplands, next in grasslands, and weakest in forests. (4) The vegetation growth state of the river basin was more significantly affected by external disturbance in 2001–2021, with 58.75% of forest, 54.37% of grassland, and 37.21% of cropland having regime shift rates