Detection and attribution of positive net ecosystem productivity extremes in China's terrestrial ecosystems during 2000-2016

Positive net ecosystem productivity (NEP) extreme represents an extreme carbon sink in the terrestrial ecosystem. Studying positive NEP extremes and their control mechanisms is vital for a better understanding of the carbon cycle and mitigation of global warming. However, there are still challenges...

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Autores principales:	Miaomiao Wang, Jian Zhao, Shaoqiang Wang, Bin Chen, Zhipeng Li
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Carbon cycle Positive NEP extremes Ecological model China's terrestrial ecosystems Ecology QH540-549.5
Acceso en línea:	https://doaj.org/article/ef2d3058dc1d48518e0ddb975d695a16
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spelling	oai:doaj.org-article:ef2d3058dc1d48518e0ddb975d695a162021-12-01T05:02:44ZDetection and attribution of positive net ecosystem productivity extremes in China's terrestrial ecosystems during 2000-20161470-160X10.1016/j.ecolind.2021.108323https://doaj.org/article/ef2d3058dc1d48518e0ddb975d695a162021-12-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S1470160X21009882https://doaj.org/toc/1470-160XPositive net ecosystem productivity (NEP) extreme represents an extreme carbon sink in the terrestrial ecosystem. Studying positive NEP extremes and their control mechanisms is vital for a better understanding of the carbon cycle and mitigation of global warming. However, there are still challenges and difficulties in quantifying positive NEP extremes and finding optimal climate conditions to form them in China's terrestrial ecosystems. In this study, we used the Boreal Ecosystem Productivity Simulator (BEPS) to detect and reveal the control mechanisms of NEP extremes in China's terrestrial ecosystems. We found the positive NEP extremes occurred in 2002, 2012, and 2015, with the detrended NEP anomalies of 0.15 Pg C yr−1, 0.11 Pg C yr−1, and 0.09 Pg C yr−1, respectively. Also, the three positive NEP extremes contributed 70% of the NEP uptrend during 2000–2016. Evergreen needle-leaf forests and croplands in the subtropical-tropical monsoonal region played dominant roles in the positive NEP extremes, accounting for 34.2% and 32.6% in the positive NEP extremes on average, respectively. The relationship between the anomalies of Gross primary production (GPP) and NEP was significant (P < 0.001), with the R2 ranging from 0.32 to 0.37 in evergreen needle-leaf forests and ranging from 0.38 to 0.50 in croplands. However, the relationship between the anomalies of ecosystem respiration (Re) and NEP was not significant (P > 0.001). These results mean that GPP (rather than Re) played a decisive role in the positive NEP extremes. Also, the best climate conditions for carbon uptake in the subtropical-tropical region have temperature anomalies ranging from −1.0 to 0.5 °C, and precipitation anomalies ranging from 0 to 600 mm. This study provides new knowledge on the potential carbon sink scientific and technological support for mitigating climate warming in China's terrestrial ecosystem.Miaomiao WangJian ZhaoShaoqiang WangBin ChenZhipeng LiElsevierarticleCarbon cyclePositive NEP extremesEcological modelChina's terrestrial ecosystemsEcologyQH540-549.5ENEcological Indicators, Vol 132, Iss , Pp 108323- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Carbon cycle Positive NEP extremes Ecological model China's terrestrial ecosystems Ecology QH540-549.5
spellingShingle	Carbon cycle Positive NEP extremes Ecological model China's terrestrial ecosystems Ecology QH540-549.5 Miaomiao Wang Jian Zhao Shaoqiang Wang Bin Chen Zhipeng Li Detection and attribution of positive net ecosystem productivity extremes in China's terrestrial ecosystems during 2000-2016
description	Positive net ecosystem productivity (NEP) extreme represents an extreme carbon sink in the terrestrial ecosystem. Studying positive NEP extremes and their control mechanisms is vital for a better understanding of the carbon cycle and mitigation of global warming. However, there are still challenges and difficulties in quantifying positive NEP extremes and finding optimal climate conditions to form them in China's terrestrial ecosystems. In this study, we used the Boreal Ecosystem Productivity Simulator (BEPS) to detect and reveal the control mechanisms of NEP extremes in China's terrestrial ecosystems. We found the positive NEP extremes occurred in 2002, 2012, and 2015, with the detrended NEP anomalies of 0.15 Pg C yr−1, 0.11 Pg C yr−1, and 0.09 Pg C yr−1, respectively. Also, the three positive NEP extremes contributed 70% of the NEP uptrend during 2000–2016. Evergreen needle-leaf forests and croplands in the subtropical-tropical monsoonal region played dominant roles in the positive NEP extremes, accounting for 34.2% and 32.6% in the positive NEP extremes on average, respectively. The relationship between the anomalies of Gross primary production (GPP) and NEP was significant (P < 0.001), with the R2 ranging from 0.32 to 0.37 in evergreen needle-leaf forests and ranging from 0.38 to 0.50 in croplands. However, the relationship between the anomalies of ecosystem respiration (Re) and NEP was not significant (P > 0.001). These results mean that GPP (rather than Re) played a decisive role in the positive NEP extremes. Also, the best climate conditions for carbon uptake in the subtropical-tropical region have temperature anomalies ranging from −1.0 to 0.5 °C, and precipitation anomalies ranging from 0 to 600 mm. This study provides new knowledge on the potential carbon sink scientific and technological support for mitigating climate warming in China's terrestrial ecosystem.
format	article
author	Miaomiao Wang Jian Zhao Shaoqiang Wang Bin Chen Zhipeng Li
author_facet	Miaomiao Wang Jian Zhao Shaoqiang Wang Bin Chen Zhipeng Li
author_sort	Miaomiao Wang
title	Detection and attribution of positive net ecosystem productivity extremes in China's terrestrial ecosystems during 2000-2016
title_short	Detection and attribution of positive net ecosystem productivity extremes in China's terrestrial ecosystems during 2000-2016
title_full	Detection and attribution of positive net ecosystem productivity extremes in China's terrestrial ecosystems during 2000-2016
title_fullStr	Detection and attribution of positive net ecosystem productivity extremes in China's terrestrial ecosystems during 2000-2016
title_full_unstemmed	Detection and attribution of positive net ecosystem productivity extremes in China's terrestrial ecosystems during 2000-2016
title_sort	detection and attribution of positive net ecosystem productivity extremes in china's terrestrial ecosystems during 2000-2016
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/ef2d3058dc1d48518e0ddb975d695a16
work_keys_str_mv	AT miaomiaowang detectionandattributionofpositivenetecosystemproductivityextremesinchinasterrestrialecosystemsduring20002016 AT jianzhao detectionandattributionofpositivenetecosystemproductivityextremesinchinasterrestrialecosystemsduring20002016 AT shaoqiangwang detectionandattributionofpositivenetecosystemproductivityextremesinchinasterrestrialecosystemsduring20002016 AT binchen detectionandattributionofpositivenetecosystemproductivityextremesinchinasterrestrialecosystemsduring20002016 AT zhipengli detectionandattributionofpositivenetecosystemproductivityextremesinchinasterrestrialecosystemsduring20002016
_version_	1718405638268125184

Detection and attribution of positive net ecosystem productivity extremes in China's terrestrial ecosystems during 2000-2016

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