Pre-seasonal temperature trend break dominating the trend break in autumn grassland phenology in China

Interannual variations in the end of the growing season (EOS) play a crucial role in assessing carbon and energy cycling within grassland ecosystems. Previous studies have often fixed the trend breakpoint in autumn phenology around the year 2000 to examine the response of the vegetation EOS to long-...
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Autor*in:	Ning Qi [verfasserIn] Yanzheng Yang [verfasserIn] Guijun Yang [verfasserIn] Weizhong Li [verfasserIn] Chunjiang Zhao [verfasserIn] Jun Zhao [verfasserIn] Boheng Wang [verfasserIn] Shaofeng Su [verfasserIn] Pengxiang Zhao [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	Autumn phenology Trend break Pre-season climate Chinese grasslands Contribution

Übergeordnetes Werk:	In: International Journal of Applied Earth Observations and Geoinformation - Elsevier, 2022, 125(2023), Seite 103590-
Übergeordnetes Werk:	volume:125 ; year:2023 ; pages:103590-

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1016/j.jag.2023.103590

Katalog-ID:	DOAJ09919354X

Internformat


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520			\|a Interannual variations in the end of the growing season (EOS) play a crucial role in assessing carbon and energy cycling within grassland ecosystems. Previous studies have often fixed the trend breakpoint in autumn phenology around the year 2000 to examine the response of the vegetation EOS to long-term climate change. However, the asymmetry of climate change and the diversity of grass species may lead to spatial disparities in EOS trend breakpoints, but little research has been done to quantify their characteristics and underlying climatic driving mechanisms. Focusing on the period from 1982 to 2015, this study extracts EOS data from six different grassland subregions in China to identify EOS trend breakpoints, and then investigates the associated climatic driving mechanisms. The results highlight the presence of significant breakpoints in the EOS trend within 54.1% of China's grasslands. Prior to 1997, the grassland EOS trend exhibited a pronounced delay, with a rate of 0.29 days per year (P < 0.01), which subsequently shifted to 0.10 days per year. In addition, pre-seasonal climate factors emerged as the dominant driver, contributing a remarkable 98.8% to the timing of the grassland EOS, with pre-seasonal temperature and solar radiation standing out as the dominant climate variables influencing the grassland EOS. Furthermore, the main driver of the trend break in the grassland EOS was the trend break in pre-seasonal temperature, which contributed to 52.2% of the trend break in the grassland EOS. These results confirm the presence of breakpoints in the autumn phenological trend across Chinese grasslands, and elucidate the intrinsic climate-driven mechanism responsible for the autumn phenological trend break at the pixel scale. These findings provide valuable insights to better understand and model the complex interactions between ecosystems and the climate system.
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allfields_unstemmed	10.1016/j.jag.2023.103590 doi (DE-627)DOAJ09919354X (DE-599)DOAJ50eb54a952f3444eb4f48d7655760c52 DE-627 ger DE-627 rakwb eng GB3-5030 GE1-350 Ning Qi verfasserin aut Pre-seasonal temperature trend break dominating the trend break in autumn grassland phenology in China 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Interannual variations in the end of the growing season (EOS) play a crucial role in assessing carbon and energy cycling within grassland ecosystems. Previous studies have often fixed the trend breakpoint in autumn phenology around the year 2000 to examine the response of the vegetation EOS to long-term climate change. However, the asymmetry of climate change and the diversity of grass species may lead to spatial disparities in EOS trend breakpoints, but little research has been done to quantify their characteristics and underlying climatic driving mechanisms. Focusing on the period from 1982 to 2015, this study extracts EOS data from six different grassland subregions in China to identify EOS trend breakpoints, and then investigates the associated climatic driving mechanisms. The results highlight the presence of significant breakpoints in the EOS trend within 54.1% of China's grasslands. Prior to 1997, the grassland EOS trend exhibited a pronounced delay, with a rate of 0.29 days per year (P < 0.01), which subsequently shifted to 0.10 days per year. In addition, pre-seasonal climate factors emerged as the dominant driver, contributing a remarkable 98.8% to the timing of the grassland EOS, with pre-seasonal temperature and solar radiation standing out as the dominant climate variables influencing the grassland EOS. Furthermore, the main driver of the trend break in the grassland EOS was the trend break in pre-seasonal temperature, which contributed to 52.2% of the trend break in the grassland EOS. These results confirm the presence of breakpoints in the autumn phenological trend across Chinese grasslands, and elucidate the intrinsic climate-driven mechanism responsible for the autumn phenological trend break at the pixel scale. These findings provide valuable insights to better understand and model the complex interactions between ecosystems and the climate system. Autumn phenology Trend break Pre-season climate Chinese grasslands Contribution Physical geography Environmental sciences Yanzheng Yang verfasserin aut Guijun Yang verfasserin aut Weizhong Li verfasserin aut Chunjiang Zhao verfasserin aut Jun Zhao verfasserin aut Boheng Wang verfasserin aut Shaofeng Su verfasserin aut Pengxiang Zhao verfasserin aut In International Journal of Applied Earth Observations and Geoinformation Elsevier, 2022 125(2023), Seite 103590- (DE-627)359784119 (DE-600)2097960-5 1872826X nnns volume:125 year:2023 pages:103590- https://doi.org/10.1016/j.jag.2023.103590 kostenfrei https://doaj.org/article/50eb54a952f3444eb4f48d7655760c52 kostenfrei http://www.sciencedirect.com/science/article/pii/S1569843223004144 kostenfrei https://doaj.org/toc/1569-8432 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2014 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 125 2023 103590-
allfieldsGer	10.1016/j.jag.2023.103590 doi (DE-627)DOAJ09919354X (DE-599)DOAJ50eb54a952f3444eb4f48d7655760c52 DE-627 ger DE-627 rakwb eng GB3-5030 GE1-350 Ning Qi verfasserin aut Pre-seasonal temperature trend break dominating the trend break in autumn grassland phenology in China 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Interannual variations in the end of the growing season (EOS) play a crucial role in assessing carbon and energy cycling within grassland ecosystems. Previous studies have often fixed the trend breakpoint in autumn phenology around the year 2000 to examine the response of the vegetation EOS to long-term climate change. However, the asymmetry of climate change and the diversity of grass species may lead to spatial disparities in EOS trend breakpoints, but little research has been done to quantify their characteristics and underlying climatic driving mechanisms. Focusing on the period from 1982 to 2015, this study extracts EOS data from six different grassland subregions in China to identify EOS trend breakpoints, and then investigates the associated climatic driving mechanisms. The results highlight the presence of significant breakpoints in the EOS trend within 54.1% of China's grasslands. Prior to 1997, the grassland EOS trend exhibited a pronounced delay, with a rate of 0.29 days per year (P < 0.01), which subsequently shifted to 0.10 days per year. In addition, pre-seasonal climate factors emerged as the dominant driver, contributing a remarkable 98.8% to the timing of the grassland EOS, with pre-seasonal temperature and solar radiation standing out as the dominant climate variables influencing the grassland EOS. Furthermore, the main driver of the trend break in the grassland EOS was the trend break in pre-seasonal temperature, which contributed to 52.2% of the trend break in the grassland EOS. These results confirm the presence of breakpoints in the autumn phenological trend across Chinese grasslands, and elucidate the intrinsic climate-driven mechanism responsible for the autumn phenological trend break at the pixel scale. These findings provide valuable insights to better understand and model the complex interactions between ecosystems and the climate system. Autumn phenology Trend break Pre-season climate Chinese grasslands Contribution Physical geography Environmental sciences Yanzheng Yang verfasserin aut Guijun Yang verfasserin aut Weizhong Li verfasserin aut Chunjiang Zhao verfasserin aut Jun Zhao verfasserin aut Boheng Wang verfasserin aut Shaofeng Su verfasserin aut Pengxiang Zhao verfasserin aut In International Journal of Applied Earth Observations and Geoinformation Elsevier, 2022 125(2023), Seite 103590- (DE-627)359784119 (DE-600)2097960-5 1872826X nnns volume:125 year:2023 pages:103590- https://doi.org/10.1016/j.jag.2023.103590 kostenfrei https://doaj.org/article/50eb54a952f3444eb4f48d7655760c52 kostenfrei http://www.sciencedirect.com/science/article/pii/S1569843223004144 kostenfrei https://doaj.org/toc/1569-8432 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2014 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 125 2023 103590-
allfieldsSound	10.1016/j.jag.2023.103590 doi (DE-627)DOAJ09919354X (DE-599)DOAJ50eb54a952f3444eb4f48d7655760c52 DE-627 ger DE-627 rakwb eng GB3-5030 GE1-350 Ning Qi verfasserin aut Pre-seasonal temperature trend break dominating the trend break in autumn grassland phenology in China 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Interannual variations in the end of the growing season (EOS) play a crucial role in assessing carbon and energy cycling within grassland ecosystems. Previous studies have often fixed the trend breakpoint in autumn phenology around the year 2000 to examine the response of the vegetation EOS to long-term climate change. However, the asymmetry of climate change and the diversity of grass species may lead to spatial disparities in EOS trend breakpoints, but little research has been done to quantify their characteristics and underlying climatic driving mechanisms. Focusing on the period from 1982 to 2015, this study extracts EOS data from six different grassland subregions in China to identify EOS trend breakpoints, and then investigates the associated climatic driving mechanisms. The results highlight the presence of significant breakpoints in the EOS trend within 54.1% of China's grasslands. Prior to 1997, the grassland EOS trend exhibited a pronounced delay, with a rate of 0.29 days per year (P < 0.01), which subsequently shifted to 0.10 days per year. In addition, pre-seasonal climate factors emerged as the dominant driver, contributing a remarkable 98.8% to the timing of the grassland EOS, with pre-seasonal temperature and solar radiation standing out as the dominant climate variables influencing the grassland EOS. Furthermore, the main driver of the trend break in the grassland EOS was the trend break in pre-seasonal temperature, which contributed to 52.2% of the trend break in the grassland EOS. These results confirm the presence of breakpoints in the autumn phenological trend across Chinese grasslands, and elucidate the intrinsic climate-driven mechanism responsible for the autumn phenological trend break at the pixel scale. These findings provide valuable insights to better understand and model the complex interactions between ecosystems and the climate system. Autumn phenology Trend break Pre-season climate Chinese grasslands Contribution Physical geography Environmental sciences Yanzheng Yang verfasserin aut Guijun Yang verfasserin aut Weizhong Li verfasserin aut Chunjiang Zhao verfasserin aut Jun Zhao verfasserin aut Boheng Wang verfasserin aut Shaofeng Su verfasserin aut Pengxiang Zhao verfasserin aut In International Journal of Applied Earth Observations and Geoinformation Elsevier, 2022 125(2023), Seite 103590- (DE-627)359784119 (DE-600)2097960-5 1872826X nnns volume:125 year:2023 pages:103590- https://doi.org/10.1016/j.jag.2023.103590 kostenfrei https://doaj.org/article/50eb54a952f3444eb4f48d7655760c52 kostenfrei http://www.sciencedirect.com/science/article/pii/S1569843223004144 kostenfrei https://doaj.org/toc/1569-8432 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2014 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 125 2023 103590-
language	English
source	In International Journal of Applied Earth Observations and Geoinformation 125(2023), Seite 103590- volume:125 year:2023 pages:103590-
sourceStr	In International Journal of Applied Earth Observations and Geoinformation 125(2023), Seite 103590- volume:125 year:2023 pages:103590-
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Autumn phenology Trend break Pre-season climate Chinese grasslands Contribution Physical geography Environmental sciences
isfreeaccess_bool	true
container_title	International Journal of Applied Earth Observations and Geoinformation
authorswithroles_txt_mv	Ning Qi @@aut@@ Yanzheng Yang @@aut@@ Guijun Yang @@aut@@ Weizhong Li @@aut@@ Chunjiang Zhao @@aut@@ Jun Zhao @@aut@@ Boheng Wang @@aut@@ Shaofeng Su @@aut@@ Pengxiang Zhao @@aut@@
publishDateDaySort_date	2023-01-01T00:00:00Z
hierarchy_top_id	359784119
id	DOAJ09919354X
language_de	englisch
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callnumber-first	G - Geography, Anthropology, Recreation
author	Ning Qi
spellingShingle	Ning Qi misc GB3-5030 misc GE1-350 misc Autumn phenology misc Trend break misc Pre-season climate misc Chinese grasslands misc Contribution misc Physical geography misc Environmental sciences Pre-seasonal temperature trend break dominating the trend break in autumn grassland phenology in China
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topic_title	GB3-5030 GE1-350 Pre-seasonal temperature trend break dominating the trend break in autumn grassland phenology in China Autumn phenology Trend break Pre-season climate Chinese grasslands Contribution
topic	misc GB3-5030 misc GE1-350 misc Autumn phenology misc Trend break misc Pre-season climate misc Chinese grasslands misc Contribution misc Physical geography misc Environmental sciences
topic_unstemmed	misc GB3-5030 misc GE1-350 misc Autumn phenology misc Trend break misc Pre-season climate misc Chinese grasslands misc Contribution misc Physical geography misc Environmental sciences
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title	Pre-seasonal temperature trend break dominating the trend break in autumn grassland phenology in China
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title_full	Pre-seasonal temperature trend break dominating the trend break in autumn grassland phenology in China
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author_browse	Ning Qi Yanzheng Yang Guijun Yang Weizhong Li Chunjiang Zhao Jun Zhao Boheng Wang Shaofeng Su Pengxiang Zhao
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title_sort	pre-seasonal temperature trend break dominating the trend break in autumn grassland phenology in china
callnumber	GB3-5030
title_auth	Pre-seasonal temperature trend break dominating the trend break in autumn grassland phenology in China
abstract	Interannual variations in the end of the growing season (EOS) play a crucial role in assessing carbon and energy cycling within grassland ecosystems. Previous studies have often fixed the trend breakpoint in autumn phenology around the year 2000 to examine the response of the vegetation EOS to long-term climate change. However, the asymmetry of climate change and the diversity of grass species may lead to spatial disparities in EOS trend breakpoints, but little research has been done to quantify their characteristics and underlying climatic driving mechanisms. Focusing on the period from 1982 to 2015, this study extracts EOS data from six different grassland subregions in China to identify EOS trend breakpoints, and then investigates the associated climatic driving mechanisms. The results highlight the presence of significant breakpoints in the EOS trend within 54.1% of China's grasslands. Prior to 1997, the grassland EOS trend exhibited a pronounced delay, with a rate of 0.29 days per year (P < 0.01), which subsequently shifted to 0.10 days per year. In addition, pre-seasonal climate factors emerged as the dominant driver, contributing a remarkable 98.8% to the timing of the grassland EOS, with pre-seasonal temperature and solar radiation standing out as the dominant climate variables influencing the grassland EOS. Furthermore, the main driver of the trend break in the grassland EOS was the trend break in pre-seasonal temperature, which contributed to 52.2% of the trend break in the grassland EOS. These results confirm the presence of breakpoints in the autumn phenological trend across Chinese grasslands, and elucidate the intrinsic climate-driven mechanism responsible for the autumn phenological trend break at the pixel scale. These findings provide valuable insights to better understand and model the complex interactions between ecosystems and the climate system.
abstractGer	Interannual variations in the end of the growing season (EOS) play a crucial role in assessing carbon and energy cycling within grassland ecosystems. Previous studies have often fixed the trend breakpoint in autumn phenology around the year 2000 to examine the response of the vegetation EOS to long-term climate change. However, the asymmetry of climate change and the diversity of grass species may lead to spatial disparities in EOS trend breakpoints, but little research has been done to quantify their characteristics and underlying climatic driving mechanisms. Focusing on the period from 1982 to 2015, this study extracts EOS data from six different grassland subregions in China to identify EOS trend breakpoints, and then investigates the associated climatic driving mechanisms. The results highlight the presence of significant breakpoints in the EOS trend within 54.1% of China's grasslands. Prior to 1997, the grassland EOS trend exhibited a pronounced delay, with a rate of 0.29 days per year (P < 0.01), which subsequently shifted to 0.10 days per year. In addition, pre-seasonal climate factors emerged as the dominant driver, contributing a remarkable 98.8% to the timing of the grassland EOS, with pre-seasonal temperature and solar radiation standing out as the dominant climate variables influencing the grassland EOS. Furthermore, the main driver of the trend break in the grassland EOS was the trend break in pre-seasonal temperature, which contributed to 52.2% of the trend break in the grassland EOS. These results confirm the presence of breakpoints in the autumn phenological trend across Chinese grasslands, and elucidate the intrinsic climate-driven mechanism responsible for the autumn phenological trend break at the pixel scale. These findings provide valuable insights to better understand and model the complex interactions between ecosystems and the climate system.
abstract_unstemmed	Interannual variations in the end of the growing season (EOS) play a crucial role in assessing carbon and energy cycling within grassland ecosystems. Previous studies have often fixed the trend breakpoint in autumn phenology around the year 2000 to examine the response of the vegetation EOS to long-term climate change. However, the asymmetry of climate change and the diversity of grass species may lead to spatial disparities in EOS trend breakpoints, but little research has been done to quantify their characteristics and underlying climatic driving mechanisms. Focusing on the period from 1982 to 2015, this study extracts EOS data from six different grassland subregions in China to identify EOS trend breakpoints, and then investigates the associated climatic driving mechanisms. The results highlight the presence of significant breakpoints in the EOS trend within 54.1% of China's grasslands. Prior to 1997, the grassland EOS trend exhibited a pronounced delay, with a rate of 0.29 days per year (P < 0.01), which subsequently shifted to 0.10 days per year. In addition, pre-seasonal climate factors emerged as the dominant driver, contributing a remarkable 98.8% to the timing of the grassland EOS, with pre-seasonal temperature and solar radiation standing out as the dominant climate variables influencing the grassland EOS. Furthermore, the main driver of the trend break in the grassland EOS was the trend break in pre-seasonal temperature, which contributed to 52.2% of the trend break in the grassland EOS. These results confirm the presence of breakpoints in the autumn phenological trend across Chinese grasslands, and elucidate the intrinsic climate-driven mechanism responsible for the autumn phenological trend break at the pixel scale. These findings provide valuable insights to better understand and model the complex interactions between ecosystems and the climate system.
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title_short	Pre-seasonal temperature trend break dominating the trend break in autumn grassland phenology in China
url	https://doi.org/10.1016/j.jag.2023.103590 https://doaj.org/article/50eb54a952f3444eb4f48d7655760c52 http://www.sciencedirect.com/science/article/pii/S1569843223004144 https://doaj.org/toc/1569-8432
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Pre-seasonal temperature trend break dominating the trend break in autumn grassland phenology in China

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