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Journal of Arid Land  2023, Vol. 15 Issue (5): 508-522    DOI: 10.1007/s40333-023-0101-9
Research article     
Heterogeneity and non-linearity of ecosystem responses to climate change in the Qilian Mountains National Park, China
GAO Xiang1, WEN Ruiyang1, Kevin LO2,*(), LI Jie1, YAN An1
1College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China
2Department of Geography, Hong Kong Baptist University, Hong Kong 999077, China
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Ecosystem responses to climate change, particularly in arid environments, is an understudied topic. This study conducted a spatial analysis of ecosystem responses to short-term variability in temperature, precipitation, and solar radiation in the Qilian Mountains National Park, an arid mountainous region in Northwest China. We collected precipitation and temperature data from the National Science and Technology Infrastructure Platform, solar radiation data from the China Meteorological Forcing Dataset, and vegetation cover remote-sensing data from the Moderate Resolution Imaging Spectroradiometer. We used the vegetation sensitivity index to identify areas sensitive to climate change and to determine which climatic factors were significant in this regard. The findings revealed a high degree of heterogeneity and non-linearity of ecosystem responses to climate change. Four types of heterogeneity were identified: longitude, altitude, ecosystem, and climate disturbance. Furthermore, the characteristics of nonlinear ecosystem responses to climate change included: (1) inconsistency in the controlling climatic factors for the same ecosystems in different geographical settings; (2) the interaction between different climatic factors results in varying weights that affect ecosystem stability and makes them difficult to determine; and (3) the hysteresis effect of vegetation increases the uncertainty of ecosystem responses to climate change. The findings are significant because they highlight the complexity of ecosystem responses to climate change. Furthermore, the identification of areas that are particularly sensitive to climate change and the influencing factors has important implications for predicting and managing the impacts of climate change on ecosystems, which can help protect the stability of ecosystems in the Qilian Mountains National Park.

Key wordsecosystem resistance      ecosystem stability      climate change      vegetation sensitivity index (VSI)      Qilian Mountains National Park     
Received: 08 September 2022      Published: 31 May 2023
Corresponding Authors: *Kevin LO (E-mail:
Cite this article:

GAO Xiang, WEN Ruiyang, Kevin LO, LI Jie, YAN An. Heterogeneity and non-linearity of ecosystem responses to climate change in the Qilian Mountains National Park, China. Journal of Arid Land, 2023, 15(5): 508-522.

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Fig. 1 Overview and land cover type of the study area. Land cover type data are derived from Data Center for Resources and Environmental Sciences, Chinese Academy of Sciences (
Fig. 2 Flowchart of vegetation sensitivity index (VSI). TEM, temperature; PRE, precipitation; RAD, solar radiation; EVI, enhanced vegetation index; Z-score, stand score; TEMweight, the weight of temperature; PREweight, the weight of precipitation; RADweight, the weight of solar radiation; TEMsens, the sensitivity to temperature; PREsens, the sensitivity to precipitation; RADsens the sensitivity to solar radiation.
Fig. 3 Changes of temperature (a), precipitation (b), solar radiation (c), and EVI (d) in the Qilian Mountains National Park (QMNP) from 2000 to 2019. The dotted lines represent the linear trends.
Fig. 4 Spatial patterns of EVI (a) and the Hurst index (b) in the QMNP from 2000 to 2019
Fig. 5 VSI distribution frequency histogram (a) and spatial differentiation of ecosystem resistance in the QMNP (b)
Fig. 6 VSI variation with altitude in the QMNP
Fig. 7 Box-plot diagram of VSI in different ecosystems in the QMNP. The upper and lower limits of the box indicate the 75th and 25th percentile values, respectively; the horizontal line in each box represents the median of the distributions; and the upper and lower whiskers show the 95th and 5th percentile values, respectively; the red circles indicate outliers.
Fig. 8 RGB (red, green, and blue) composite of climate factors to ecosystem vegetation in the QMNP. Red, green, and blue represent temperature, precipitation, and solar radiation, respectively.
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