A meta-analysis of 1,119 manipulative experiments on terrestrial carbon-cycling responses to global change

Abstract: Direct quantification of terrestrial biosphere responses to global change is crucial for projections of future climate change in Earth system models. Here, we synthesized ecosystem carbon-cycling data from 1,119 experiments performed over the past four decades concerning changes in tempera...

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Published in:Nature Ecology & Evolution
Main Authors: Song, Jian, Wan, Shiqiang, Piao, Shilong, Knapp, Alan K., Classen, Aimee T., Vicca, Sara, Ciais, Philippe, Hovenden, Mark J., Leuzinger, Sebastian, Beier, Claus, Kardol, Paul, Xia, Jianyang, Liu, Qiang, Ru, Jingyi, Zhou, Zhenxing, Luo, Yiqi, Guo, Dali, Langley, J. Adam, Zscheischler, Jakob, Dukes, Jeffrey S., Tang, Jianwu, Chen, Jiquan, Hofmockel, Kirsten S., Kueppers, Lara M., Rustad, Lindsey, Liu, Lingli, Smith, Melinda D., Templer, Pamela H., Thomas, R. Quinn, Norby, Richard J., Phillips, Richard P., Niu, Shuli, Fatichi, Simone, Wang, Yingping, Shao, Pengshuai, Han, Hongyan, Wang, Dandan, Lei, Lingjie, Wang, Jiali, Li, Xiaona, Zhang, Qian, Li, Xiaoming, Su, Fanglong, Liu, Bin, Yang, Fan, Ma, Gaigai, Li, Guoyong, Liu, Yanchun, Liu, Yinzhan, Yang, Zhongling, Zhang, Kesheng, Miao, Yuan, Hu, Mengjun, Yan, Chuang, Zhang, Ang, Zhong, Mingxing, Hui, Yan, Li, Ying, Zheng, Mengmei
Format: Article in Journal/Newspaper
Language:English
Published: 2019
Subjects:
Online Access:https://hdl.handle.net/10067/1628380151162165141
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spelling ftunivantwerpen:c:irua:162838 2024-10-06T13:46:47+00:00 A meta-analysis of 1,119 manipulative experiments on terrestrial carbon-cycling responses to global change Song, Jian Wan, Shiqiang Piao, Shilong Knapp, Alan K. Classen, Aimee T. Vicca, Sara Ciais, Philippe Hovenden, Mark J. Leuzinger, Sebastian Beier, Claus Kardol, Paul Xia, Jianyang Liu, Qiang Ru, Jingyi Zhou, Zhenxing Luo, Yiqi Guo, Dali Langley, J. Adam Zscheischler, Jakob Dukes, Jeffrey S. Tang, Jianwu Chen, Jiquan Hofmockel, Kirsten S. Kueppers, Lara M. Rustad, Lindsey Liu, Lingli Smith, Melinda D. Templer, Pamela H. Thomas, R. Quinn Norby, Richard J. Phillips, Richard P. Niu, Shuli Fatichi, Simone Wang, Yingping Shao, Pengshuai Han, Hongyan Wang, Dandan Lei, Lingjie Wang, Jiali Li, Xiaona Zhang, Qian Li, Xiaoming Su, Fanglong Liu, Bin Yang, Fan Ma, Gaigai Li, Guoyong Liu, Yanchun Liu, Yinzhan Yang, Zhongling Zhang, Kesheng Miao, Yuan Hu, Mengjun Yan, Chuang Zhang, Ang Zhong, Mingxing Hui, Yan Li, Ying Zheng, Mengmei 2019 https://hdl.handle.net/10067/1628380151162165141 eng eng info:eu-repo/semantics/altIdentifier/doi/10.1038/S41559-019-0958-3 info:eu-repo/semantics/altIdentifier/isi/000484026600015 info:eu-repo/semantics/closedAccess 2397-334X Nature Ecology & Evolution Chemistry Biology info:eu-repo/semantics/article 2019 ftunivantwerpen https://doi.org/10.1038/S41559-019-0958-3 2024-09-10T04:06:39Z Abstract: Direct quantification of terrestrial biosphere responses to global change is crucial for projections of future climate change in Earth system models. Here, we synthesized ecosystem carbon-cycling data from 1,119 experiments performed over the past four decades concerning changes in temperature, precipitation, CO2 and nitrogen across major terrestrial vegetation types of the world. Most experiments manipulated single rather than multiple global change drivers in temperate ecosystems of the USA, Europe and China. The magnitudes of warming and elevated CO2 treatments were consistent with the ranges of future projections, whereas those of precipitation changes and nitrogen inputs often exceeded the projected ranges. Increases in global change drivers consistently accelerated, but decreased precipitation slowed down carbon-cycle processes. Nonlinear (including synergistic and antagonistic) effects among global change drivers were rare. Belowground carbon allocation responded negatively to increased precipitation and nitrogen addition and positively to decreased precipitation and elevated CO2. The sensitivities of carbon variables to multiple global change drivers depended on the background climate and ecosystem condition, suggesting that Earth system models should be evaluated using site-specific conditions for best uses of this large dataset. Together, this synthesis underscores an urgent need to explore the interactions among multiple global change drivers in under-represented regions such as semi-arid ecosystems, forests in the tropics and subtropics, and Arctic tundra when forecasting future terrestrial carbon-climate feedback. Article in Journal/Newspaper Arctic Climate change Tundra IRUA - Institutional Repository van de Universiteit Antwerpen Arctic Nature Ecology & Evolution 3 9 1309 1320
institution Open Polar
collection IRUA - Institutional Repository van de Universiteit Antwerpen
op_collection_id ftunivantwerpen
language English
topic Chemistry
Biology
spellingShingle Chemistry
Biology
Song, Jian
Wan, Shiqiang
Piao, Shilong
Knapp, Alan K.
Classen, Aimee T.
Vicca, Sara
Ciais, Philippe
Hovenden, Mark J.
Leuzinger, Sebastian
Beier, Claus
Kardol, Paul
Xia, Jianyang
Liu, Qiang
Ru, Jingyi
Zhou, Zhenxing
Luo, Yiqi
Guo, Dali
Langley, J. Adam
Zscheischler, Jakob
Dukes, Jeffrey S.
Tang, Jianwu
Chen, Jiquan
Hofmockel, Kirsten S.
Kueppers, Lara M.
Rustad, Lindsey
Liu, Lingli
Smith, Melinda D.
Templer, Pamela H.
Thomas, R. Quinn
Norby, Richard J.
Phillips, Richard P.
Niu, Shuli
Fatichi, Simone
Wang, Yingping
Shao, Pengshuai
Han, Hongyan
Wang, Dandan
Lei, Lingjie
Wang, Jiali
Li, Xiaona
Zhang, Qian
Li, Xiaoming
Su, Fanglong
Liu, Bin
Yang, Fan
Ma, Gaigai
Li, Guoyong
Liu, Yanchun
Liu, Yinzhan
Yang, Zhongling
Zhang, Kesheng
Miao, Yuan
Hu, Mengjun
Yan, Chuang
Zhang, Ang
Zhong, Mingxing
Hui, Yan
Li, Ying
Zheng, Mengmei
A meta-analysis of 1,119 manipulative experiments on terrestrial carbon-cycling responses to global change
topic_facet Chemistry
Biology
description Abstract: Direct quantification of terrestrial biosphere responses to global change is crucial for projections of future climate change in Earth system models. Here, we synthesized ecosystem carbon-cycling data from 1,119 experiments performed over the past four decades concerning changes in temperature, precipitation, CO2 and nitrogen across major terrestrial vegetation types of the world. Most experiments manipulated single rather than multiple global change drivers in temperate ecosystems of the USA, Europe and China. The magnitudes of warming and elevated CO2 treatments were consistent with the ranges of future projections, whereas those of precipitation changes and nitrogen inputs often exceeded the projected ranges. Increases in global change drivers consistently accelerated, but decreased precipitation slowed down carbon-cycle processes. Nonlinear (including synergistic and antagonistic) effects among global change drivers were rare. Belowground carbon allocation responded negatively to increased precipitation and nitrogen addition and positively to decreased precipitation and elevated CO2. The sensitivities of carbon variables to multiple global change drivers depended on the background climate and ecosystem condition, suggesting that Earth system models should be evaluated using site-specific conditions for best uses of this large dataset. Together, this synthesis underscores an urgent need to explore the interactions among multiple global change drivers in under-represented regions such as semi-arid ecosystems, forests in the tropics and subtropics, and Arctic tundra when forecasting future terrestrial carbon-climate feedback.
format Article in Journal/Newspaper
author Song, Jian
Wan, Shiqiang
Piao, Shilong
Knapp, Alan K.
Classen, Aimee T.
Vicca, Sara
Ciais, Philippe
Hovenden, Mark J.
Leuzinger, Sebastian
Beier, Claus
Kardol, Paul
Xia, Jianyang
Liu, Qiang
Ru, Jingyi
Zhou, Zhenxing
Luo, Yiqi
Guo, Dali
Langley, J. Adam
Zscheischler, Jakob
Dukes, Jeffrey S.
Tang, Jianwu
Chen, Jiquan
Hofmockel, Kirsten S.
Kueppers, Lara M.
Rustad, Lindsey
Liu, Lingli
Smith, Melinda D.
Templer, Pamela H.
Thomas, R. Quinn
Norby, Richard J.
Phillips, Richard P.
Niu, Shuli
Fatichi, Simone
Wang, Yingping
Shao, Pengshuai
Han, Hongyan
Wang, Dandan
Lei, Lingjie
Wang, Jiali
Li, Xiaona
Zhang, Qian
Li, Xiaoming
Su, Fanglong
Liu, Bin
Yang, Fan
Ma, Gaigai
Li, Guoyong
Liu, Yanchun
Liu, Yinzhan
Yang, Zhongling
Zhang, Kesheng
Miao, Yuan
Hu, Mengjun
Yan, Chuang
Zhang, Ang
Zhong, Mingxing
Hui, Yan
Li, Ying
Zheng, Mengmei
author_facet Song, Jian
Wan, Shiqiang
Piao, Shilong
Knapp, Alan K.
Classen, Aimee T.
Vicca, Sara
Ciais, Philippe
Hovenden, Mark J.
Leuzinger, Sebastian
Beier, Claus
Kardol, Paul
Xia, Jianyang
Liu, Qiang
Ru, Jingyi
Zhou, Zhenxing
Luo, Yiqi
Guo, Dali
Langley, J. Adam
Zscheischler, Jakob
Dukes, Jeffrey S.
Tang, Jianwu
Chen, Jiquan
Hofmockel, Kirsten S.
Kueppers, Lara M.
Rustad, Lindsey
Liu, Lingli
Smith, Melinda D.
Templer, Pamela H.
Thomas, R. Quinn
Norby, Richard J.
Phillips, Richard P.
Niu, Shuli
Fatichi, Simone
Wang, Yingping
Shao, Pengshuai
Han, Hongyan
Wang, Dandan
Lei, Lingjie
Wang, Jiali
Li, Xiaona
Zhang, Qian
Li, Xiaoming
Su, Fanglong
Liu, Bin
Yang, Fan
Ma, Gaigai
Li, Guoyong
Liu, Yanchun
Liu, Yinzhan
Yang, Zhongling
Zhang, Kesheng
Miao, Yuan
Hu, Mengjun
Yan, Chuang
Zhang, Ang
Zhong, Mingxing
Hui, Yan
Li, Ying
Zheng, Mengmei
author_sort Song, Jian
title A meta-analysis of 1,119 manipulative experiments on terrestrial carbon-cycling responses to global change
title_short A meta-analysis of 1,119 manipulative experiments on terrestrial carbon-cycling responses to global change
title_full A meta-analysis of 1,119 manipulative experiments on terrestrial carbon-cycling responses to global change
title_fullStr A meta-analysis of 1,119 manipulative experiments on terrestrial carbon-cycling responses to global change
title_full_unstemmed A meta-analysis of 1,119 manipulative experiments on terrestrial carbon-cycling responses to global change
title_sort meta-analysis of 1,119 manipulative experiments on terrestrial carbon-cycling responses to global change
publishDate 2019
url https://hdl.handle.net/10067/1628380151162165141
geographic Arctic
geographic_facet Arctic
genre Arctic
Climate change
Tundra
genre_facet Arctic
Climate change
Tundra
op_source 2397-334X
Nature Ecology & Evolution
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container_title Nature Ecology & Evolution
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