Quantitative assessment of the impact of climatic factors on phenological changes in the Qilian Mountains, China

Quantitative assessment of the impact of climatic factors on phenological changes in the Qilian Mountains, China

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Quantitative assessment of the impact of climatic factors on phenological changes in the Qilian Mountains, China

Highlights

Four methods were combined to extract phenological metrics.

GeoDetector was used to quantify the contribution of climatic factors and interaction of two factors.

The phenological sensitivity of grassland was highest.

The interaction between climatic factors played a critical role.

Abstract

Mountain ecosystems are highly susceptible to climate change. The climate tends to be warm and wet in the arid mountains of China because of the intensified water cycle under global warming, and the vegetation is undergoing profound changes. However, how vegetation phenology responds to climate change is not been entirely understood. Using MODIS-NDVI during 2000–2019, we analyzed the spatiotemporal variations in the SOS, EOS, and LOS in the Qilian Mountains (QLMs), China. These parameters were extracted using four methods, and geographic detector model was used to quantify the explanatory power of climatic factors on phenological change. The results showed that the SOS was advanced by an average of 0.26 d/yr, the EOS was delayed by an average of 0.12 d/yr, and the LOS was prolonged by an average of 0.38 d/yr during 2000–2019. The phenological characteristics of different vegetation types differed in their sensitivities to climatic factors, and the sensitivity of grassland to climatic factors was higher than those of other vegetation types. The preseason temperature and sunshine duration contributed more to SOS and EOS changes of forests than that of other vegetation types. Moreover, the SOS was more sensitive to preseason precipitation, and it was the main SOS determinant across grassland and meadows. The EOS was more sensitive to the daily minimum temperature. More importantly, climatic factors did not act independently on vegetation phenological changes. The interactions between preseason precipitation and temperature and between preseason sunshine duration and temperature had significantly affected the changes in the SOS and EOS, respectively. The results of this study highlight the response of different vegetation types to climate change in the arid mountainous areas, which is significant for improving the performance of phenology models.

Keywords

Spring phenology

Autumn phenology

Driving factors

Geographical detector

Qilian Mountains

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© 2021 Elsevier B.V. All rights reserved.

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