Spring Phenological Sensitivity to Climate Change in the Northern Hemisphere: Comprehensive Evaluation and Driving Force Analysis

Plant phenology depends largely on temperature, but temperature alone cannot explain the Northern Hemisphere shifts in the start of the growing season (SOS). The spatio–temporal distribution of SOS sensitivity to climate variability has also changed in recent years. We applied the partial least squa...

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Main Authors: Kaiwei Li, Chunyi Wang, Qing Sun, Guangzhi Rong, Zhijun Tong, Xingpeng Liu, Jiquan Zhang
Format: Article
Language:English
Published: MDPI AG 2021-05-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/13/10/1972
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spelling doaj-5fe229804c45436cbd0afb2fcfaeafca2021-06-01T00:22:56ZengMDPI AGRemote Sensing2072-42922021-05-01131972197210.3390/rs13101972Spring Phenological Sensitivity to Climate Change in the Northern Hemisphere: Comprehensive Evaluation and Driving Force AnalysisKaiwei Li0Chunyi Wang1Qing Sun2Guangzhi Rong3Zhijun Tong4Xingpeng Liu5Jiquan Zhang6School of Environment, Northeast Normal University, Changchun 130024, ChinaChinese Academy of Meteorological Sciences, Beijing 100081, ChinaChinese Academy of Meteorological Sciences, Beijing 100081, ChinaSchool of Environment, Northeast Normal University, Changchun 130024, ChinaSchool of Environment, Northeast Normal University, Changchun 130024, ChinaSchool of Environment, Northeast Normal University, Changchun 130024, ChinaSchool of Environment, Northeast Normal University, Changchun 130024, ChinaPlant phenology depends largely on temperature, but temperature alone cannot explain the Northern Hemisphere shifts in the start of the growing season (SOS). The spatio–temporal distribution of SOS sensitivity to climate variability has also changed in recent years. We applied the partial least squares regression (PLSR) method to construct a standardized SOS sensitivity evaluation index and analyzed the combined effects of air temperature (Tem), water balance (Wbi), radiation (Srad), and previous year’s phenology on SOS. The spatial and temporal distributions of SOS sensitivity to Northern Hemisphere climate change from 1982 to 2014 were analyzed using time windows of 33 and 15 years; the dominant biological and environmental drivers were also assessed. The results showed that the combined sensitivity of SOS to climate change (S<sub>Com</sub>) is most influenced by preseason temperature sensitivity. However, because of the asymmetric response of SOS to daytime/night temperature (Tmax/Tmin) and non-negligible moderating of Wbi and Srad on SOS, S<sub>Com</sub> was more effective in expressing the effect of climate change on SOS than any single climatic factor. Vegetation cover (or type) was the dominant factor influencing the spatial pattern of SOS sensitivity, followed by spring temperature (Tmin > Tmax), and the weakest was water balance. Forests had the highest S<sub>Com</sub> absolute values. A significant decrease in the sensitivity of some vegetation (22.2%) led to a decreasing trend in sensitivity in the Northern Hemisphere. Although temperature remains the main climatic factor driving temporal changes in S<sub>Com</sub>, the temperature effects were asymmetric between spring and winter (Tems/Temw). More moisture might mitigate the asymmetric response of S<sub>Com</sub> to spring/winter warming. Vegetation adaptation has a greater influence on the temporal variability of SOS sensitivity relative to each climatic factor (Tems, Temw, Wbi, Srad). More moisture might mitigate the asymmetric response of S<sub>Com</sub> to spring/winter warming. This study provides a basis for vegetation phenology sensitivity assessment and prediction.https://www.mdpi.com/2072-4292/13/10/1972vegetation phenologyclimate changephenological sensitivitystart of the growing seasondriving forcepartial least squares regression
collection DOAJ
language English
format Article
sources DOAJ
author Kaiwei Li
Chunyi Wang
Qing Sun
Guangzhi Rong
Zhijun Tong
Xingpeng Liu
Jiquan Zhang
spellingShingle Kaiwei Li
Chunyi Wang
Qing Sun
Guangzhi Rong
Zhijun Tong
Xingpeng Liu
Jiquan Zhang
Spring Phenological Sensitivity to Climate Change in the Northern Hemisphere: Comprehensive Evaluation and Driving Force Analysis
Remote Sensing
vegetation phenology
climate change
phenological sensitivity
start of the growing season
driving force
partial least squares regression
author_facet Kaiwei Li
Chunyi Wang
Qing Sun
Guangzhi Rong
Zhijun Tong
Xingpeng Liu
Jiquan Zhang
author_sort Kaiwei Li
title Spring Phenological Sensitivity to Climate Change in the Northern Hemisphere: Comprehensive Evaluation and Driving Force Analysis
title_short Spring Phenological Sensitivity to Climate Change in the Northern Hemisphere: Comprehensive Evaluation and Driving Force Analysis
title_full Spring Phenological Sensitivity to Climate Change in the Northern Hemisphere: Comprehensive Evaluation and Driving Force Analysis
title_fullStr Spring Phenological Sensitivity to Climate Change in the Northern Hemisphere: Comprehensive Evaluation and Driving Force Analysis
title_full_unstemmed Spring Phenological Sensitivity to Climate Change in the Northern Hemisphere: Comprehensive Evaluation and Driving Force Analysis
title_sort spring phenological sensitivity to climate change in the northern hemisphere: comprehensive evaluation and driving force analysis
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2021-05-01
description Plant phenology depends largely on temperature, but temperature alone cannot explain the Northern Hemisphere shifts in the start of the growing season (SOS). The spatio–temporal distribution of SOS sensitivity to climate variability has also changed in recent years. We applied the partial least squares regression (PLSR) method to construct a standardized SOS sensitivity evaluation index and analyzed the combined effects of air temperature (Tem), water balance (Wbi), radiation (Srad), and previous year’s phenology on SOS. The spatial and temporal distributions of SOS sensitivity to Northern Hemisphere climate change from 1982 to 2014 were analyzed using time windows of 33 and 15 years; the dominant biological and environmental drivers were also assessed. The results showed that the combined sensitivity of SOS to climate change (S<sub>Com</sub>) is most influenced by preseason temperature sensitivity. However, because of the asymmetric response of SOS to daytime/night temperature (Tmax/Tmin) and non-negligible moderating of Wbi and Srad on SOS, S<sub>Com</sub> was more effective in expressing the effect of climate change on SOS than any single climatic factor. Vegetation cover (or type) was the dominant factor influencing the spatial pattern of SOS sensitivity, followed by spring temperature (Tmin > Tmax), and the weakest was water balance. Forests had the highest S<sub>Com</sub> absolute values. A significant decrease in the sensitivity of some vegetation (22.2%) led to a decreasing trend in sensitivity in the Northern Hemisphere. Although temperature remains the main climatic factor driving temporal changes in S<sub>Com</sub>, the temperature effects were asymmetric between spring and winter (Tems/Temw). More moisture might mitigate the asymmetric response of S<sub>Com</sub> to spring/winter warming. Vegetation adaptation has a greater influence on the temporal variability of SOS sensitivity relative to each climatic factor (Tems, Temw, Wbi, Srad). More moisture might mitigate the asymmetric response of S<sub>Com</sub> to spring/winter warming. This study provides a basis for vegetation phenology sensitivity assessment and prediction.
topic vegetation phenology
climate change
phenological sensitivity
start of the growing season
driving force
partial least squares regression
url https://www.mdpi.com/2072-4292/13/10/1972
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