Articles | Volume 15, issue 21
Biogeosciences, 15, 6559–6572, 2018
https://doi.org/10.5194/bg-15-6559-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Biogeosciences, 15, 6559–6572, 2018
https://doi.org/10.5194/bg-15-6559-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
07 Nov 2018
Research article
| 07 Nov 2018
Ecosystem carbon transit versus turnover times in response to climate warming and rising atmospheric CO2 concentration
Xingjie Lu et al.
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Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-177, https://doi.org/10.5194/essd-2022-177, 2022
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SMCI1.0 is a 1 km resolution dataset of daily soil moisture for 2010–2020 derived through machine learning trained with in-situ measurements of 1,789 stations from China. It contains 10 layers with 10 cm intervals up to 100 cm deep at daily resolution over the period 2010–2020. Compared to ERA5-Land, SMAP-L4 and SoMo.ml, SIMI1.0 has higher accuracy over China.
Shuang Ma, Lifen Jiang, Rachel M. Wilson, Jeff P. Chanton, Scott Bridgham, Shuli Niu, Colleen M. Iversen, Avni Malhotra, Jiang Jiang, Xingjie Lu, Yuanyuan Huang, Jason Keller, Xiaofeng Xu, Daniel M. Ricciuto, Paul J. Hanson, and Yiqi Luo
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The relative ratio of wetland methane (CH4) emission pathways determines how much CH4 is oxidized before leaving the soil. We found an ebullition modeling approach that has a better performance in deep layer pore water CH4 concentration. We suggest using this approach in land surface models to accurately represent CH4 emission dynamics and response to climate change. Our results also highlight that both CH4 flux and belowground concentration data are important to constrain model parameters.
Yongjiu Dai, Wei Shangguan, Nan Wei, Qinchuan Xin, Hua Yuan, Shupeng Zhang, Shaofeng Liu, Xingjie Lu, Dagang Wang, and Fapeng Yan
SOIL, 5, 137–158, https://doi.org/10.5194/soil-5-137-2019, https://doi.org/10.5194/soil-5-137-2019, 2019
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Soil data are widely used in various Earth science fields. We reviewed soil property maps for Earth system models, which can also offer insights to soil data developers and users. Old soil datasets are often based on limited observations and have various uncertainties. Updated and comprehensive soil data are made available to the public and can benefit related research. Good-quality soil data are identified and suggestions on how to improve and use them are provided.
Qianyu Li, Xingjie Lu, Yingping Wang, Xin Huang, Peter M. Cox, and Yiqi Luo
Biogeosciences, 15, 6909–6925, https://doi.org/10.5194/bg-15-6909-2018, https://doi.org/10.5194/bg-15-6909-2018, 2018
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Land-surface models have been widely used to predict the responses of terrestrial ecosystems to climate change. A better understanding of model mechanisms that govern terrestrial ecosystem responses to rising atmosphere [CO2] is needed. Our study for the first time shows that the expansion of leaf area under rising [CO2] is the most important response for the stimulation of land carbon accumulation by a land-surface model: CABLE. Processes related to leaf area should be better calibrated.
Yiqi Luo, Zheng Shi, Xingjie Lu, Jianyang Xia, Junyi Liang, Jiang Jiang, Ying Wang, Matthew J. Smith, Lifen Jiang, Anders Ahlström, Benito Chen, Oleksandra Hararuk, Alan Hastings, Forrest Hoffman, Belinda Medlyn, Shuli Niu, Martin Rasmussen, Katherine Todd-Brown, and Ying-Ping Wang
Biogeosciences, 14, 145–161, https://doi.org/10.5194/bg-14-145-2017, https://doi.org/10.5194/bg-14-145-2017, 2017
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Climate change is strongly regulated by land carbon cycle. However, we lack the ability to predict future land carbon sequestration. Here, we develop a novel framework for understanding what determines the direction and rate of future change in land carbon storage. The framework offers a suite of new approaches to revolutionize land carbon model evaluation and improvement.
Shengyun Chen, Wenjie Liu, Qian Zhao, Lin Zhao, Qingbai Wu, Xingjie Lu, Shichang Kang, Xiang Qin, Shilong Chen, Jiawen Ren, and Dahe Qin
The Cryosphere Discuss., https://doi.org/10.5194/tc-2016-80, https://doi.org/10.5194/tc-2016-80, 2016
Revised manuscript not accepted
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Experimental warming was manipulated using open top chambers in alpine grassland ecosystem in the permafrost regions of the Qinghai-Tibet Plateau. The results revealed variations of earlier thawing, later freezing and longer freezing-thawing periods in shallow soil. Further, the estimated permafrost table declined under the warming scenarios. The work will be helpful to evaluate the stability of Qinghai-Tibet Railway/Highway and estimate the release of carbon under the future climate warming.
Qingliang Li, Gaosong Shi, Wei Shangguan, Jianduo Li, Lu Li, Feini Huang, Ye Zhang, Chunyan Wang, Dagang Wang, Jianxiu Qiu, Xingjie Lu, and Yongjiu Dai
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-177, https://doi.org/10.5194/essd-2022-177, 2022
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SMCI1.0 is a 1 km resolution dataset of daily soil moisture for 2010–2020 derived through machine learning trained with in-situ measurements of 1,789 stations from China. It contains 10 layers with 10 cm intervals up to 100 cm deep at daily resolution over the period 2010–2020. Compared to ERA5-Land, SMAP-L4 and SoMo.ml, SIMI1.0 has higher accuracy over China.
Shuang Ma, Lifen Jiang, Rachel M. Wilson, Jeff P. Chanton, Scott Bridgham, Shuli Niu, Colleen M. Iversen, Avni Malhotra, Jiang Jiang, Xingjie Lu, Yuanyuan Huang, Jason Keller, Xiaofeng Xu, Daniel M. Ricciuto, Paul J. Hanson, and Yiqi Luo
Biogeosciences, 19, 2245–2262, https://doi.org/10.5194/bg-19-2245-2022, https://doi.org/10.5194/bg-19-2245-2022, 2022
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The relative ratio of wetland methane (CH4) emission pathways determines how much CH4 is oxidized before leaving the soil. We found an ebullition modeling approach that has a better performance in deep layer pore water CH4 concentration. We suggest using this approach in land surface models to accurately represent CH4 emission dynamics and response to climate change. Our results also highlight that both CH4 flux and belowground concentration data are important to constrain model parameters.
Jennifer A. Holm, David M. Medvigy, Benjamin Smith, Jeffrey S. Dukes, Claus Beier, Mikhail Mishurov, Xiangtao Xu, Jeremy W. Lichstein, Craig D. Allen, Klaus S. Larsen, Yiqi Luo, Cari Ficken, William T. Pockman, William R. L. Anderegg, and Anja Rammig
Biogeosciences Discuss., https://doi.org/10.5194/bg-2022-65, https://doi.org/10.5194/bg-2022-65, 2022
Preprint under review for BG
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Unprecedented climate extremes (UCEs) are expected to have dramatic impacts for ecosystems. We examine extreme droughts with rising CO2 and temperatures using two dynamic vegetation models, to assess ecological processes to measure, and reduce model uncertainties. The models predict strong nonlinear responses to UCEs. Due to different model representations, the models differ in magnitude and trajectory of forest loss. Therefore, we explored specific plant responses that reflect knowledge gaps.
Xianjin He, Laurent Augusto, Daniel S. Goll, Bruno Ringeval, Yingping Wang, Julian Helfenstein, Yuanyuan Huang, Kailiang Yu, Zhiqiang Wang, Yongchuan Yang, and Enqing Hou
Earth Syst. Sci. Data, 13, 5831–5846, https://doi.org/10.5194/essd-13-5831-2021, https://doi.org/10.5194/essd-13-5831-2021, 2021
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Our database of globally distributed natural soil total P (STP) concentration showed concentration ranged from 1.4 to 9630.0 (mean 570.0) mg kg−1. Global predictions of STP concentration increased with latitude. Global STP stocks (excluding Antarctica) were estimated to be 26.8 and 62.2 Pg in the topsoil and subsoil, respectively. Our global map of STP concentration can be used to constrain Earth system models representing the P cycle and to inform quantification of global soil P availability.
Juhwan Lee, Raphael A. Viscarra Rossel, Mingxi Zhang, Zhongkui Luo, and Ying-Ping Wang
Biogeosciences, 18, 5185–5202, https://doi.org/10.5194/bg-18-5185-2021, https://doi.org/10.5194/bg-18-5185-2021, 2021
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We performed Roth C simulations across Australia and assessed the response of soil carbon to changing inputs and future climate change using a consistent modelling framework. Site-specific initialisation of the C pools with measurements of the C fractions is essential for accurate simulations of soil organic C stocks and composition at a large scale. With further warming, Australian soils will become more vulnerable to C loss: natural environments > native grazing > cropping > modified grazing.
Xin Huang, Dan Lu, Daniel M. Ricciuto, Paul J. Hanson, Andrew D. Richardson, Xuehe Lu, Ensheng Weng, Sheng Nie, Lifen Jiang, Enqing Hou, Igor F. Steinmacher, and Yiqi Luo
Geosci. Model Dev., 14, 5217–5238, https://doi.org/10.5194/gmd-14-5217-2021, https://doi.org/10.5194/gmd-14-5217-2021, 2021
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In the data-rich era, data assimilation is widely used to integrate abundant observations into models to reduce uncertainty in ecological forecasting. However, applications of data assimilation are restricted by highly technical requirements. To alleviate this technical burden, we developed a model-independent data assimilation (MIDA) module which is friendly to ecologists with limited programming skills. MIDA also supports a flexible switch of different models or observations in DA analysis.
Erqian Cui, Chenyu Bian, Yiqi Luo, Shuli Niu, Yingping Wang, and Jianyang Xia
Biogeosciences, 17, 6237–6246, https://doi.org/10.5194/bg-17-6237-2020, https://doi.org/10.5194/bg-17-6237-2020, 2020
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Mean annual net ecosystem productivity (NEP) is related to the magnitude of the carbon sink of a specific ecosystem, while its inter-annual variation (IAVNEP) characterizes the stability of such a carbon sink. Thus, a better understanding of the co-varying NEP and IAVNEP is critical for locating the major and stable carbon sinks on land. Based on daily NEP observations from eddy-covariance sites, we found local indicators for the spatially varying NEP and IAVNEP, respectively.
Jian Zhou, Jianyang Xia, Ning Wei, Yufu Liu, Chenyu Bian, Yuqi Bai, and Yiqi Luo
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-76, https://doi.org/10.5194/gmd-2020-76, 2020
Revised manuscript not accepted
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The increase of model complexity and data volume challenges the evaluation of Earth system models (ESMs), which mainly stems from the untraceable, unautomatic, and high computational costs. Here, we built up an online Traceability analysis system for Model Evaluation (TraceME), which is traceable, automatic and shareable. The TraceME (v1.0) can trace the structural uncertainty of simulated carbon (C) storage in ESMs and provide some new implications for the next generation of model evaluation.
Alexander J. Norton, Peter J. Rayner, Ernest N. Koffi, Marko Scholze, Jeremy D. Silver, and Ying-Ping Wang
Biogeosciences, 16, 3069–3093, https://doi.org/10.5194/bg-16-3069-2019, https://doi.org/10.5194/bg-16-3069-2019, 2019
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This study presents an estimate of global terrestrial photosynthesis. We make use of satellite chlorophyll fluorescence measurements, a visible indicator of photosynthesis, to optimize model parameters and estimate photosynthetic carbon uptake. This new framework incorporates nonlinear, process-based understanding of the link between fluorescence and photosynthesis, an advance on past approaches. This will aid in the utility of fluorescence to quantify terrestrial carbon cycle feedbacks.
Yongjiu Dai, Wei Shangguan, Nan Wei, Qinchuan Xin, Hua Yuan, Shupeng Zhang, Shaofeng Liu, Xingjie Lu, Dagang Wang, and Fapeng Yan
SOIL, 5, 137–158, https://doi.org/10.5194/soil-5-137-2019, https://doi.org/10.5194/soil-5-137-2019, 2019
Short summary
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Soil data are widely used in various Earth science fields. We reviewed soil property maps for Earth system models, which can also offer insights to soil data developers and users. Old soil datasets are often based on limited observations and have various uncertainties. Updated and comprehensive soil data are made available to the public and can benefit related research. Good-quality soil data are identified and suggestions on how to improve and use them are provided.
Yuanyuan Huang, Mark Stacy, Jiang Jiang, Nilutpal Sundi, Shuang Ma, Volodymyr Saruta, Chang Gyo Jung, Zheng Shi, Jianyang Xia, Paul J. Hanson, Daniel Ricciuto, and Yiqi Luo
Geosci. Model Dev., 12, 1119–1137, https://doi.org/10.5194/gmd-12-1119-2019, https://doi.org/10.5194/gmd-12-1119-2019, 2019
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Predicting future changes in ecosystem services is not only highly desirable but is also becoming feasible as several forces are converging to transform ecological research into quantitative forecasting. To realize ecological forecasting, we have developed an Ecological Platform for Assimilating Data (EcoPAD) into models. EcoPAD also has the potential to become an interactive tool for resource management, stimulate citizen science in ecology, and transform environmental education.
Jing Wang, Jianyang Xia, Xuhui Zhou, Kun Huang, Jian Zhou, Yuanyuan Huang, Lifen Jiang, Xia Xu, Junyi Liang, Ying-Ping Wang, Xiaoli Cheng, and Yiqi Luo
Biogeosciences, 16, 917–926, https://doi.org/10.5194/bg-16-917-2019, https://doi.org/10.5194/bg-16-917-2019, 2019
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Soil is critical in mitigating climate change mainly because soil carbon turns over much slower in soils than vegetation and the atmosphere. However, Earth system models (ESMs) have large uncertainty in simulating carbon dynamics due to their biased estimation of soil carbon transit time (τsoil). Here, the τsoil estimates from 12 ESMs that participated in CMIP5 were evaluated by a database of measured τsoil. We detected a large spatial variation in measured τsoil across the globe.
Qianyu Li, Xingjie Lu, Yingping Wang, Xin Huang, Peter M. Cox, and Yiqi Luo
Biogeosciences, 15, 6909–6925, https://doi.org/10.5194/bg-15-6909-2018, https://doi.org/10.5194/bg-15-6909-2018, 2018
Short summary
Short summary
Land-surface models have been widely used to predict the responses of terrestrial ecosystems to climate change. A better understanding of model mechanisms that govern terrestrial ecosystem responses to rising atmosphere [CO2] is needed. Our study for the first time shows that the expansion of leaf area under rising [CO2] is the most important response for the stimulation of land carbon accumulation by a land-surface model: CABLE. Processes related to leaf area should be better calibrated.
Zhenggang Du, Ensheng Weng, Lifen Jiang, Yiqi Luo, Jianyang Xia, and Xuhui Zhou
Geosci. Model Dev., 11, 4399–4416, https://doi.org/10.5194/gmd-11-4399-2018, https://doi.org/10.5194/gmd-11-4399-2018, 2018
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In this study, based on a traceability analysis technique, we evaluated alternative representations of C–N interactions and their impacts on the C cycle using the TECO model framework. Our results showed that different representations of C–N coupling processes lead to divergent effects on plant production, C residence time, and thus the ecosystem C storage capacity. Identifying those effects can help us to improve the N limitation assumptions employed in terrestrial ecosystem models.
Yilong Wang, Philippe Ciais, Daniel Goll, Yuanyuan Huang, Yiqi Luo, Ying-Ping Wang, A. Anthony Bloom, Grégoire Broquet, Jens Hartmann, Shushi Peng, Josep Penuelas, Shilong Piao, Jordi Sardans, Benjamin D. Stocker, Rong Wang, Sönke Zaehle, and Sophie Zechmeister-Boltenstern
Geosci. Model Dev., 11, 3903–3928, https://doi.org/10.5194/gmd-11-3903-2018, https://doi.org/10.5194/gmd-11-3903-2018, 2018
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We present a new modeling framework called Global Observation-based Land-ecosystems Utilization Model of Carbon, Nitrogen and Phosphorus (GOLUM-CNP) that combines a data-constrained C-cycle analysis with data-driven estimates of N and P inputs and losses and with observed stoichiometric ratios. GOLUM-CNP provides a traceable tool, where a consistency between different datasets of global C, N, and P cycles has been achieved.
Alexander J. Norton, Peter J. Rayner, Ernest N. Koffi, Marko Scholze, Jeremy D. Silver, and Ying-Ping Wang
Biogeosciences Discuss., https://doi.org/10.5194/bg-2018-270, https://doi.org/10.5194/bg-2018-270, 2018
Revised manuscript has not been submitted
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This study presents a global estimate of land carbon uptake through photosynthesis. We make use satellite chlorophyll fluorescence measurements, a visible indicator of photosynthesis, to optimize model parameters and then use the optimized model to estimate photosynthetic carbon uptake. This provides a new tool that can combine measurements and observations in a systematic way and maximise the use of chlorophyll fluorescence to improve our understanding of the land carbon cycle.
Donghai Wu, Philippe Ciais, Nicolas Viovy, Alan K. Knapp, Kevin Wilcox, Michael Bahn, Melinda D. Smith, Sara Vicca, Simone Fatichi, Jakob Zscheischler, Yue He, Xiangyi Li, Akihiko Ito, Almut Arneth, Anna Harper, Anna Ukkola, Athanasios Paschalis, Benjamin Poulter, Changhui Peng, Daniel Ricciuto, David Reinthaler, Guangsheng Chen, Hanqin Tian, Hélène Genet, Jiafu Mao, Johannes Ingrisch, Julia E. S. M. Nabel, Julia Pongratz, Lena R. Boysen, Markus Kautz, Michael Schmitt, Patrick Meir, Qiuan Zhu, Roland Hasibeder, Sebastian Sippel, Shree R. S. Dangal, Stephen Sitch, Xiaoying Shi, Yingping Wang, Yiqi Luo, Yongwen Liu, and Shilong Piao
Biogeosciences, 15, 3421–3437, https://doi.org/10.5194/bg-15-3421-2018, https://doi.org/10.5194/bg-15-3421-2018, 2018
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Our results indicate that most ecosystem models do not capture the observed asymmetric responses under normal precipitation conditions, suggesting an overestimate of the drought effects and/or underestimate of the watering impacts on primary productivity, which may be the result of inadequate representation of key eco-hydrological processes. Collaboration between modelers and site investigators needs to be strengthened to improve the specific processes in ecosystem models in following studies.
Rhys Whitley, Jason Beringer, Lindsay B. Hutley, Gabriel Abramowitz, Martin G. De Kauwe, Bradley Evans, Vanessa Haverd, Longhui Li, Caitlin Moore, Youngryel Ryu, Simon Scheiter, Stanislaus J. Schymanski, Benjamin Smith, Ying-Ping Wang, Mathew Williams, and Qiang Yu
Biogeosciences, 14, 4711–4732, https://doi.org/10.5194/bg-14-4711-2017, https://doi.org/10.5194/bg-14-4711-2017, 2017
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This paper attempts to review some of the current challenges faced by the modelling community in simulating the behaviour of savanna ecosystems. We provide a particular focus on three dynamic processes (phenology, root-water access, and fire) that are characteristic of savannas, which we believe are not adequately represented in current-generation terrestrial biosphere models. We highlight reasons for these misrepresentations, possible solutions and a future direction for research in this area.
Rachel M. Law, Tilo Ziehn, Richard J. Matear, Andrew Lenton, Matthew A. Chamberlain, Lauren E. Stevens, Ying-Ping Wang, Jhan Srbinovsky, Daohua Bi, Hailin Yan, and Peter F. Vohralik
Geosci. Model Dev., 10, 2567–2590, https://doi.org/10.5194/gmd-10-2567-2017, https://doi.org/10.5194/gmd-10-2567-2017, 2017
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The paper describes a version of the Australian Community Climate and Earth System Simulator that has been enabled to simulate the carbon cycle, which is designated ACCESS-ESM1. The model performance for pre-industrial conditions is assessed and land and ocean carbon fluxes are found to be simulated realistically.
Yiqi Luo, Zheng Shi, Xingjie Lu, Jianyang Xia, Junyi Liang, Jiang Jiang, Ying Wang, Matthew J. Smith, Lifen Jiang, Anders Ahlström, Benito Chen, Oleksandra Hararuk, Alan Hastings, Forrest Hoffman, Belinda Medlyn, Shuli Niu, Martin Rasmussen, Katherine Todd-Brown, and Ying-Ping Wang
Biogeosciences, 14, 145–161, https://doi.org/10.5194/bg-14-145-2017, https://doi.org/10.5194/bg-14-145-2017, 2017
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Climate change is strongly regulated by land carbon cycle. However, we lack the ability to predict future land carbon sequestration. Here, we develop a novel framework for understanding what determines the direction and rate of future change in land carbon storage. The framework offers a suite of new approaches to revolutionize land carbon model evaluation and improvement.
Eva A. Kowalczyk, Lauren E. Stevens, Rachel M. Law, Ian N. Harman, Martin Dix, Charmaine N. Franklin, and Ying-Ping Wang
Geosci. Model Dev., 9, 2771–2791, https://doi.org/10.5194/gmd-9-2771-2016, https://doi.org/10.5194/gmd-9-2771-2016, 2016
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This paper compares two ACCESS model versions that differ only in their land surface scheme. Differences in the simulated present-day climate are attributed to differences in the representation of various land surface processes.
Rashid Rafique, Jianyang Xia, Oleksandra Hararuk, Ghassem R. Asrar, Guoyong Leng, Yingping Wang, and Yiqi Luo
Earth Syst. Dynam., 7, 649–658, https://doi.org/10.5194/esd-7-649-2016, https://doi.org/10.5194/esd-7-649-2016, 2016
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Traceability analysis was used to diagnose the causes of differences in simulating ecosystem carbon storage capacity between two land models: CLMA-CASA and CABLE. Results showed that the simulated ecosystem carbon storage capacity is largely influenced by the photosynthesis parameterization, residence time and organic matter decomposition.
Anna M. Ukkola, Andy J. Pitman, Mark Decker, Martin G. De Kauwe, Gab Abramowitz, Jatin Kala, and Ying-Ping Wang
Hydrol. Earth Syst. Sci., 20, 2403–2419, https://doi.org/10.5194/hess-20-2403-2016, https://doi.org/10.5194/hess-20-2403-2016, 2016
Rhys Whitley, Jason Beringer, Lindsay B. Hutley, Gab Abramowitz, Martin G. De Kauwe, Remko Duursma, Bradley Evans, Vanessa Haverd, Longhui Li, Youngryel Ryu, Benjamin Smith, Ying-Ping Wang, Mathew Williams, and Qiang Yu
Biogeosciences, 13, 3245–3265, https://doi.org/10.5194/bg-13-3245-2016, https://doi.org/10.5194/bg-13-3245-2016, 2016
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In this study we assess how well terrestrial biosphere models perform at predicting water and carbon cycling for savanna ecosystems. We apply our models to five savanna sites in Northern Australia and highlight key causes for model failure. Our assessment of model performance uses a novel benchmarking system that scores a model’s predictive ability based on how well it is utilizing its driving information. On average, we found the models as a group display only moderate levels of performance.
Shengyun Chen, Wenjie Liu, Qian Zhao, Lin Zhao, Qingbai Wu, Xingjie Lu, Shichang Kang, Xiang Qin, Shilong Chen, Jiawen Ren, and Dahe Qin
The Cryosphere Discuss., https://doi.org/10.5194/tc-2016-80, https://doi.org/10.5194/tc-2016-80, 2016
Revised manuscript not accepted
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Experimental warming was manipulated using open top chambers in alpine grassland ecosystem in the permafrost regions of the Qinghai-Tibet Plateau. The results revealed variations of earlier thawing, later freezing and longer freezing-thawing periods in shallow soil. Further, the estimated permafrost table declined under the warming scenarios. The work will be helpful to evaluate the stability of Qinghai-Tibet Railway/Highway and estimate the release of carbon under the future climate warming.
Y. P. Wang, J. Jiang, B. Chen-Charpentier, F. B. Agusto, A. Hastings, F. Hoffman, M. Rasmussen, M. J. Smith, K. Todd-Brown, Y. Wang, X. Xu, and Y. Q. Luo
Biogeosciences, 13, 887–902, https://doi.org/10.5194/bg-13-887-2016, https://doi.org/10.5194/bg-13-887-2016, 2016
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Comparing two nonlinear microbial models, we found that,
in response to warming, soil C decreases in one model but can increase or decrease in the other model, and sensitivity of priming response to carbon input increases with soil T in one model but decreases in the other model
Significance: these differences in the responses can be used to discern which model is more realistic, which will improve our understanding of the significance of soil microbial processes in the terrestrial C cycle.
M. G. De Kauwe, S.-X. Zhou, B. E. Medlyn, A. J. Pitman, Y.-P. Wang, R. A. Duursma, and I. C. Prentice
Biogeosciences, 12, 7503–7518, https://doi.org/10.5194/bg-12-7503-2015, https://doi.org/10.5194/bg-12-7503-2015, 2015
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Future climate change has the potential to increase drought in many regions of the globe. Recent data syntheses show that drought sensitivity varies considerably among plants from different climate zones, but state-of-the-art models currently assume the same drought sensitivity for all vegetation. Our results indicate that models will over-estimate drought impacts in drier climates unless different sensitivity of vegetation to drought is taken into account.
J. Kala, M. G. De Kauwe, A. J. Pitman, R. Lorenz, B. E. Medlyn, Y.-P Wang, Y.-S Lin, and G. Abramowitz
Geosci. Model Dev., 8, 3877–3889, https://doi.org/10.5194/gmd-8-3877-2015, https://doi.org/10.5194/gmd-8-3877-2015, 2015
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We implement a new stomatal conductance scheme within a land surface model coupled to a global climate model. The new model differs from the default in that it allows model parameters to vary by the different plant functional types, derived from global synthesis of observations. We show that the new scheme results in improvements in the model climatology and improves existing biases in warm temperature extremes by up to 10-20% over the boreal forests during summer.
I. C. Prentice, X. Liang, B. E. Medlyn, and Y.-P. Wang
Atmos. Chem. Phys., 15, 5987–6005, https://doi.org/10.5194/acp-15-5987-2015, https://doi.org/10.5194/acp-15-5987-2015, 2015
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Land surface models (LSMs) describe how carbon and water fluxes react to environmental change. They are key component of climate models, yet they differ enormously. Many perform poorly, despite having many parameters. We outline a development strategy emphasizing robustness, reliability and realism, none of which is guaranteed by complexity alone. We propose multiple constraints, benchmarking and data assimilation, and representing unresolved processes stochastically, as tools in this endeavour.
C. Le Quéré, R. Moriarty, R. M. Andrew, G. P. Peters, P. Ciais, P. Friedlingstein, S. D. Jones, S. Sitch, P. Tans, A. Arneth, T. A. Boden, L. Bopp, Y. Bozec, J. G. Canadell, L. P. Chini, F. Chevallier, C. E. Cosca, I. Harris, M. Hoppema, R. A. Houghton, J. I. House, A. K. Jain, T. Johannessen, E. Kato, R. F. Keeling, V. Kitidis, K. Klein Goldewijk, C. Koven, C. S. Landa, P. Landschützer, A. Lenton, I. D. Lima, G. Marland, J. T. Mathis, N. Metzl, Y. Nojiri, A. Olsen, T. Ono, S. Peng, W. Peters, B. Pfeil, B. Poulter, M. R. Raupach, P. Regnier, C. Rödenbeck, S. Saito, J. E. Salisbury, U. Schuster, J. Schwinger, R. Séférian, J. Segschneider, T. Steinhoff, B. D. Stocker, A. J. Sutton, T. Takahashi, B. Tilbrook, G. R. van der Werf, N. Viovy, Y.-P. Wang, R. Wanninkhof, A. Wiltshire, and N. Zeng
Earth Syst. Sci. Data, 7, 47–85, https://doi.org/10.5194/essd-7-47-2015, https://doi.org/10.5194/essd-7-47-2015, 2015
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Carbon dioxide (CO2) emissions from human activities (burning fossil fuels and cement production, deforestation and other land-use change) are set to rise again in 2014.
This study (updated yearly) makes an accurate assessment of anthropogenic CO2 emissions and their redistribution between the atmosphere, ocean, and terrestrial biosphere in order to better understand the global carbon cycle, support the development of climate policies, and project future climate change.
M. G. De Kauwe, J. Kala, Y.-S. Lin, A. J. Pitman, B. E. Medlyn, R. A. Duursma, G. Abramowitz, Y.-P. Wang, and D. G. Miralles
Geosci. Model Dev., 8, 431–452, https://doi.org/10.5194/gmd-8-431-2015, https://doi.org/10.5194/gmd-8-431-2015, 2015
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Stomatal conductance affects the fluxes of carbon, energy and water between the vegetated land surface and the atmosphere. We test an implementation of an optimal stomatal conductance model within the CABLE land surface model (LSM). The new implementation resulted in a large reduction in the annual fluxes of transpiration across evergreen needleleaf, tundra and C4 grass regions. We conclude that optimisation theory can yield a tractable approach to predicting stomatal conductance in LSMs.
Y. P. Wang, B. C. Chen, W. R. Wieder, M. Leite, B. E. Medlyn, M. Rasmussen, M. J. Smith, F. B. Agusto, F. Hoffman, and Y. Q. Luo
Biogeosciences, 11, 1817–1831, https://doi.org/10.5194/bg-11-1817-2014, https://doi.org/10.5194/bg-11-1817-2014, 2014
J.-F. Exbrayat, A. J. Pitman, Q. Zhang, G. Abramowitz, and Y.-P. Wang
Biogeosciences, 10, 7095–7108, https://doi.org/10.5194/bg-10-7095-2013, https://doi.org/10.5194/bg-10-7095-2013, 2013
Q. Zhang, A. J. Pitman, Y. P. Wang, Y. J. Dai, and P. J. Lawrence
Earth Syst. Dynam., 4, 333–345, https://doi.org/10.5194/esd-4-333-2013, https://doi.org/10.5194/esd-4-333-2013, 2013
Related subject area
Biogeochemistry: Modelling, Terrestrial
Assimilation of passive microwave vegetation optical depth in LDAS-Monde: a case study over the continental USA
Global modelling of soil carbonyl sulfide exchanges
Assessing the impacts of agricultural managements on soil carbon stocks, nitrogen loss, and crop production – a modelling study in eastern Africa
The effects of varying drought-heat signatures on terrestrial carbon dynamics and vegetation composition
Accounting for non-rainfall moisture and temperature improves litter decay model performance in a fog-dominated dryland system
Resolving temperature limitation on spring productivity in an evergreen conifer forest using a model–data fusion framework
A robust initialization method for accurate soil organic carbon simulations
Evaluation of carbonyl sulfide biosphere exchange in the Simple Biosphere Model (SiB4)
Model simulations of arctic biogeochemistry and permafrost extent are highly sensitive to the implemented snow scheme in LPJ-GUESS
Theoretical insights from upscaling Michaelis–Menten microbial dynamics in biogeochemical models: a dimensionless approach
Effects of climate change in the European croplands and grasslands: productivity, GHG balance and soil carbon storage
Estimated effect of the permafrost carbon feedback on the zero emissions commitment to climate change
An improved process-oriented hydro-biogeochemical model for simulating dynamic fluxes of methane and nitrous oxide in alpine ecosystems with seasonally frozen soils
A novel representation of biological nitrogen fixation and competitive dynamics between nitrogen-fixing and non-fixing plants in a land model (GFDL LM4.1-BNF)
Organic phosphorus cycling may control grassland responses to nitrogen deposition: a long-term field manipulation and modelling study
A triple tree-ring constraint for tree growth and physiology in a global land surface model
Simulating shrubs and their energy and carbon dioxide fluxes in Canada's Low Arctic with the Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC)
Competing effects of nitrogen deposition and ozone exposure on northern hemispheric terrestrial carbon uptake and storage, 1850–2099
Carbonyl sulfide: comparing a mechanistic representation of the vegetation uptake in a land surface model and the leaf relative uptake approach
Optimal model complexity for terrestrial carbon cycle prediction
CO2 physiological effect can cause rainfall decrease as strong as large-scale deforestation in the Amazon
Plant phenology evaluation of CRESCENDO land surface models – Part 1: Start and end of the growing season
Understanding the effect of fire on vegetation composition and gross primary production in a semi-arid shrubland ecosystem using the Ecosystem Demography (EDv2.2) model
Impacts of fertilization on grassland productivity and water quality across the European Alps under current and warming climate: insights from a mechanistic model
The climate benefit of carbon sequestration
Extending a land-surface model with Sphagnum moss to simulate responses of a northern temperate bog to whole ecosystem warming and elevated CO2
Improving the representation of high-latitude vegetation distribution in dynamic global vegetation models
Robust processing of airborne laser scans to plant area density profiles
Investigating the sensitivity of soil heterotrophic respiration to recent snow cover changes in Alaska using a satellite-based permafrost carbon model
Hysteretic temperature sensitivity of wetland CH4 fluxes explained by substrate availability and microbial activity
Modelling the habitat preference of two key Sphagnum species in a poor fen as controlled by capitulum water content
Evaluating two soil carbon models within the global land surface model JSBACH using surface and spaceborne observations of atmospheric CO2
Assessing impacts of selective logging on water, energy, and carbon budgets and ecosystem dynamics in Amazon forests using the Functionally Assembled Terrestrial Ecosystem Simulator
Microbial dormancy and its impacts on northern temperate and boreal terrestrial ecosystem carbon budget
Historical CO2 emissions from land use and land cover change and their uncertainty
A Bayesian approach to evaluation of soil biogeochemical models
Rainfall intensification increases the contribution of rewetting pulses to soil heterotrophic respiration
Wide discrepancies in the magnitude and direction of modeled solar-induced chlorophyll fluorescence in response to light conditions
Modeling biological nitrogen fixation in global natural terrestrial ecosystems
The impact of a simple representation of non-structural carbohydrates on the simulated response of tropical forests to drought
Benchmarking and parameter sensitivity of physiological and vegetation dynamics using the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) at Barro Colorado Island, Panama
Modelling nitrification inhibitor effects on N2O emissions after fall- and spring-applied slurry by reducing nitrifier NH4+ oxidation rate
DRIFTS band areas as measured pool size proxy to reduce parameter uncertainty in soil organic matter models
Wintertime grassland dynamics may influence belowground biomass under climate change: a model analysis
Low sensitivity of gross primary production to elevated CO2 in a mature eucalypt woodland
Metabolic tradeoffs and heterogeneity in microbial responses to temperature determine the fate of litter carbon in simulations of a warmer world
Competition alters predicted forest carbon cycle responses to nitrogen availability and elevated CO2: simulations using an explicitly competitive, game-theoretic vegetation demographic model
The importance of physiological, structural and trait responses to drought stress in driving spatial and temporal variation in GPP across Amazon forests
Modelling the response of net primary productivity of the Zambezi teak forests to climate change along a rainfall gradient in Zambia
Three decades of simulated global terrestrial carbon fluxes from a data assimilation system confronted with different periods of observations
Anthony Mucia, Bertrand Bonan, Clément Albergel, Yongjun Zheng, and Jean-Christophe Calvet
Biogeosciences, 19, 2557–2581, https://doi.org/10.5194/bg-19-2557-2022, https://doi.org/10.5194/bg-19-2557-2022, 2022
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For the first time, microwave vegetation optical depth data are assimilated in a land surface model in order to analyze leaf area index and root zone soil moisture. The advantage of microwave products is the higher observation frequency. A large variety of independent datasets are used to verify the added value of the assimilation. It is shown that the assimilation is able to improve the representation of soil moisture, vegetation conditions, and terrestrial water and carbon fluxes.
Camille Abadie, Fabienne Maignan, Marine Remaud, Jérôme Ogée, J. Elliott Campbell, Mary E. Whelan, Florian Kitz, Felix M. Spielmann, Georg Wohlfahrt, Richard Wehr, Wu Sun, Nina Raoult, Ulli Seibt, Didier Hauglustaine, Sinikka T. Lennartz, Sauveur Belviso, David Montagne, and Philippe Peylin
Biogeosciences, 19, 2427–2463, https://doi.org/10.5194/bg-19-2427-2022, https://doi.org/10.5194/bg-19-2427-2022, 2022
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A better constraint of the components of the carbonyl sulfide (COS) global budget is needed to exploit its potential as a proxy of gross primary productivity. In this study, we compare two representations of oxic soil COS fluxes, and we develop an approach to represent anoxic soil COS fluxes in a land surface model. We show the importance of atmospheric COS concentration variations on oxic soil COS fluxes and provide new estimates for oxic and anoxic soil contributions to the COS global budget.
Jianyong Ma, Sam S. Rabin, Peter Anthoni, Anita D. Bayer, Sylvia S. Nyawira, Stefan Olin, Longlong Xia, and Almut Arneth
Biogeosciences, 19, 2145–2169, https://doi.org/10.5194/bg-19-2145-2022, https://doi.org/10.5194/bg-19-2145-2022, 2022
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Improved agricultural management plays a vital role in protecting soils from degradation in eastern Africa. We simulated the impacts of seven management practices on soil carbon pools, nitrogen loss, and crop yield under different climate scenarios in this region. This study highlights the possibilities of conservation agriculture when targeting long-term environmental sustainability and food security in crop ecosystems, particularly for those with poor soil conditions in tropical climates.
Elisabeth Tschumi, Sebastian Lienert, Karin van der Wiel, Fortunat Joos, and Jakob Zscheischler
Biogeosciences, 19, 1979–1993, https://doi.org/10.5194/bg-19-1979-2022, https://doi.org/10.5194/bg-19-1979-2022, 2022
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Droughts and heatwaves are expected to occur more often in the future, but their effects on land vegetation and the carbon cycle are poorly understood. We use six climate scenarios with differing extreme occurrences and a vegetation model to analyse these effects. Tree coverage and associated plant productivity increase under a climate with no extremes. Frequent co-occurring droughts and heatwaves decrease plant productivity more than the combined effects of single droughts or heatwaves.
J. Robert Logan, Kathe E. Todd-Brown, Kathryn M. Jacobson, Peter J. Jacobson, Roland Vogt, and Sarah E. Evans
Biogeosciences Discuss., https://doi.org/10.5194/bg-2022-16, https://doi.org/10.5194/bg-2022-16, 2022
Revised manuscript accepted for BG
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Understanding how plants decompose is important for understanding where the atmospheric CO2 they absorb ends up after they die. In forests, decomposition is controlled by rain but in deserts, it’s a different story. We performed a 2.5-year study in one of the driest places on Earth (the Namib Desert in southern Africa) and found that fog and dew, not rainfall, closely controlled how quickly plants decompose. We also created a model to help predict decomposition in drylands with lots of fog/dew.
Stephanie G. Stettz, Nicholas C. Parazoo, A. Anthony Bloom, Peter D. Blanken, David R. Bowling, Sean P. Burns, Cédric Bacour, Fabienne Maignan, Brett Raczka, Alexander J. Norton, Ian Baker, Mathew Williams, Mingjie Shi, Yongguang Zhang, and Bo Qiu
Biogeosciences, 19, 541–558, https://doi.org/10.5194/bg-19-541-2022, https://doi.org/10.5194/bg-19-541-2022, 2022
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Uncertainty in the response of photosynthesis to temperature poses a major challenge to predicting the response of forests to climate change. In this paper, we study how photosynthesis in a mountainous evergreen forest is limited by temperature. This study highlights that cold temperature is a key factor that controls spring photosynthesis. Including the cold-temperature limitation in an ecosystem model improved its ability to simulate spring photosynthesis.
Eva Kanari, Lauric Cécillon, François Baudin, Hugues Clivot, Fabien Ferchaud, Sabine Houot, Florent Levavasseur, Bruno Mary, Laure Soucémarianadin, Claire Chenu, and Pierre Barré
Biogeosciences, 19, 375–387, https://doi.org/10.5194/bg-19-375-2022, https://doi.org/10.5194/bg-19-375-2022, 2022
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Soil organic carbon (SOC) is crucial for climate regulation, soil quality, and food security. Predicting its evolution over the next decades is key for appropriate land management policies. However, SOC projections lack accuracy. Here we show for the first time that PARTYSOC, an approach combining thermal analysis and machine learning optimizes the accuracy of SOC model simulations at independent sites. This method can be applied at large scales, improving SOC projections on a continental scale.
Linda M. J. Kooijmans, Ara Cho, Jin Ma, Aleya Kaushik, Katherine D. Haynes, Ian Baker, Ingrid T. Luijkx, Mathijs Groenink, Wouter Peters, John B. Miller, Joseph A. Berry, Jerome Ogée, Laura K. Meredith, Wu Sun, Kukka-Maaria Kohonen, Timo Vesala, Ivan Mammarella, Huilin Chen, Felix M. Spielmann, Georg Wohlfahrt, Max Berkelhammer, Mary E. Whelan, Kadmiel Maseyk, Ulli Seibt, Roisin Commane, Richard Wehr, and Maarten Krol
Biogeosciences, 18, 6547–6565, https://doi.org/10.5194/bg-18-6547-2021, https://doi.org/10.5194/bg-18-6547-2021, 2021
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The gas carbonyl sulfide (COS) can be used to estimate photosynthesis. To adopt this approach on regional and global scales, we need biosphere models that can simulate COS exchange. So far, such models have not been evaluated against observations. We evaluate the COS biosphere exchange of the SiB4 model against COS flux observations. We find that the model is capable of simulating key processes in COS biosphere exchange. Still, we give recommendations for further improvement of the model.
Alexandra Pongracz, David Wårlind, Paul A. Miller, and Frans-Jan W. Parmentier
Biogeosciences, 18, 5767–5787, https://doi.org/10.5194/bg-18-5767-2021, https://doi.org/10.5194/bg-18-5767-2021, 2021
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This study shows that the introduction of a multi-layer snow scheme in the LPJ-GUESS DGVM improved simulations of high-latitude soil temperature dynamics and permafrost extent compared to observations. In addition, these improvements led to shifts in carbon fluxes that contrasted within and outside of the permafrost region. Our results show that a realistic snow scheme is essential to accurately simulate snow–soil–vegetation relationships and carbon–climate feedbacks.
Chris H. Wilson and Stefan Gerber
Biogeosciences, 18, 5669–5679, https://doi.org/10.5194/bg-18-5669-2021, https://doi.org/10.5194/bg-18-5669-2021, 2021
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To better mitigate against climate change, it is imperative that ecosystem scientists understand how microbes decompose organic carbon in the soil and thereby release it as carbon dioxide into the atmosphere. A major challenge is the high variability across ecosystems in microbial biomass and in the environmental factors like temperature that drive their activity. In this paper, we use math to better understand how this variability impacts carbon dioxide release over large scales.
Marco Carozzi, Raphaël Martin, Katja Klumpp, and Raia Silvia Massad
Biogeosciences Discuss., https://doi.org/10.5194/bg-2021-241, https://doi.org/10.5194/bg-2021-241, 2021
Revised manuscript accepted for BG
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This work presents original results regarding the effects of climate change on the European croplands and grasslands systems. We provided a detailed analysis about productivity, greenhouse gas emissions, carbon balance and water demand. Our integrative results can be useful in support decision making to identify future actions targeted to sustain productivity and reduce environmental impacts.
Andrew H. MacDougall
Biogeosciences, 18, 4937–4952, https://doi.org/10.5194/bg-18-4937-2021, https://doi.org/10.5194/bg-18-4937-2021, 2021
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Permafrost soils hold about twice as much carbon as the atmosphere. As the Earth warms the organic matter in these soils will decay, releasing CO2 and CH4. It is expected that these soils will continue to release carbon to the atmosphere long after man-made emissions of greenhouse gases cease. Here we use a method employing hundreds of slightly varying model versions to estimate how much warming permafrost carbon will cause after human emissions of CO2 end.
Wei Zhang, Zhisheng Yao, Siqi Li, Xunhua Zheng, Han Zhang, Lei Ma, Kai Wang, Rui Wang, Chunyan Liu, Shenghui Han, Jia Deng, and Yong Li
Biogeosciences, 18, 4211–4225, https://doi.org/10.5194/bg-18-4211-2021, https://doi.org/10.5194/bg-18-4211-2021, 2021
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The hydro-biogeochemical model Catchment Nutrient Management Model – DeNitrification-DeComposition (CNMM-DNDC) is improved by incorporating a soil thermal module to simulate the soil thermal regime in the presence of freeze–thaw cycles. The modified model is validated at a seasonally frozen catchment with typical alpine ecosystems (wetland, meadow and forest). The simulated aggregate emissions of methane and nitrous oxide are highest for the wetland, which is dominated by the methane emissions.
Sian Kou-Giesbrecht, Sergey Malyshev, Isabel Martínez Cano, Stephen W. Pacala, Elena Shevliakova, Thomas A. Bytnerowicz, and Duncan N. L. Menge
Biogeosciences, 18, 4143–4183, https://doi.org/10.5194/bg-18-4143-2021, https://doi.org/10.5194/bg-18-4143-2021, 2021
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Representing biological nitrogen fixation (BNF) is an important challenge for land models. We present a novel representation of BNF and updated nitrogen cycling in a land model. It includes a representation of asymbiotic BNF by soil microbes and the competitive dynamics between nitrogen-fixing and non-fixing plants. It improves estimations of major carbon and nitrogen pools and fluxes and their temporal dynamics in comparison to previous representations of BNF in land models.
Christopher R. Taylor, Victoria Janes-Bassett, Gareth K. Phoenix, Ben Keane, Iain P. Hartley, and Jessica A. C. Davies
Biogeosciences, 18, 4021–4037, https://doi.org/10.5194/bg-18-4021-2021, https://doi.org/10.5194/bg-18-4021-2021, 2021
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We used experimental data to model two phosphorus-limited grasslands and investigated their response to nitrogen (N) deposition. Greater uptake of organic P facilitated a positive response to N deposition, stimulating growth and soil carbon storage. Where organic P access was less, N deposition exacerbated P demand and reduced plant C input to the soil. This caused more C to be released into the atmosphere than is taken in, reducing the climate-mitigation capacity of the modelled grassland.
Jonathan Barichivich, Philippe Peylin, Thomas Launois, Valerie Daux, Camille Risi, Jina Jeong, and Sebastiaan Luyssaert
Biogeosciences, 18, 3781–3803, https://doi.org/10.5194/bg-18-3781-2021, https://doi.org/10.5194/bg-18-3781-2021, 2021
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The width and the chemical signals of tree rings have the potential to test and improve the physiological responses simulated by global land surface models, which are at the core of future climate projections. Here, we demonstrate the novel use of tree-ring width and carbon and oxygen stable isotopes to evaluate the representation of tree growth and physiology in a global land surface model at temporal scales beyond experimentation and direct observation.
Gesa Meyer, Elyn R. Humphreys, Joe R. Melton, Alex J. Cannon, and Peter M. Lafleur
Biogeosciences, 18, 3263–3283, https://doi.org/10.5194/bg-18-3263-2021, https://doi.org/10.5194/bg-18-3263-2021, 2021
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Shrub and sedge plant functional types (PFTs) were incorporated in the land surface component of the Canadian Earth System Model to improve representation of Arctic tundra ecosystems. Evaluated against 14 years of non-winter measurements, the magnitude and seasonality of carbon dioxide and energy fluxes at a Canadian dwarf-shrub tundra site were better captured by the shrub PFTs than by previously used grass and tree PFTs. Model simulations showed the tundra site to be an annual net CO2 source.
Martina Franz and Sönke Zaehle
Biogeosciences, 18, 3219–3241, https://doi.org/10.5194/bg-18-3219-2021, https://doi.org/10.5194/bg-18-3219-2021, 2021
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The combined effects of ozone and nitrogen deposition on the terrestrial carbon uptake and storage has been unclear. Our simulations, from 1850 to 2099, show that ozone-related damage considerably reduced gross primary production and carbon storage in the past. The growth-stimulating effect induced by nitrogen deposition is offset until the 2050s. Accounting for nitrogen deposition without considering ozone effects might lead to an overestimation of terrestrial carbon uptake and storage.
Fabienne Maignan, Camille Abadie, Marine Remaud, Linda M. J. Kooijmans, Kukka-Maaria Kohonen, Róisín Commane, Richard Wehr, J. Elliott Campbell, Sauveur Belviso, Stephen A. Montzka, Nina Raoult, Ulli Seibt, Yoichi P. Shiga, Nicolas Vuichard, Mary E. Whelan, and Philippe Peylin
Biogeosciences, 18, 2917–2955, https://doi.org/10.5194/bg-18-2917-2021, https://doi.org/10.5194/bg-18-2917-2021, 2021
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The assimilation of carbonyl sulfide (COS) by continental vegetation has been proposed as a proxy for gross primary production (GPP). Using a land surface and a transport model, we compare a mechanistic representation of the plant COS uptake (Berry et al., 2013) to the classical leaf relative uptake (LRU) approach linking GPP and vegetation COS fluxes. We show that at high temporal resolutions a mechanistic approach is mandatory, but at large scales the LRU approach compares similarly.
Caroline A. Famiglietti, T. Luke Smallman, Paul A. Levine, Sophie Flack-Prain, Gregory R. Quetin, Victoria Meyer, Nicholas C. Parazoo, Stephanie G. Stettz, Yan Yang, Damien Bonal, A. Anthony Bloom, Mathew Williams, and Alexandra G. Konings
Biogeosciences, 18, 2727–2754, https://doi.org/10.5194/bg-18-2727-2021, https://doi.org/10.5194/bg-18-2727-2021, 2021
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Model uncertainty dominates the spread in terrestrial carbon cycle predictions. Efforts to reduce it typically involve adding processes, thereby increasing model complexity. However, if and how model performance scales with complexity is unclear. Using a suite of 16 structurally distinct carbon cycle models, we find that increased complexity only improves skill if parameters are adequately informed. Otherwise, it can degrade skill, and an intermediate-complexity model is optimal.
Gilvan Sampaio, Marília H. Shimizu, Carlos A. Guimarães-Júnior, Felipe Alexandre, Marcelo Guatura, Manoel Cardoso, Tomas F. Domingues, Anja Rammig, Celso von Randow, Luiz F. C. Rezende, and David M. Lapola
Biogeosciences, 18, 2511–2525, https://doi.org/10.5194/bg-18-2511-2021, https://doi.org/10.5194/bg-18-2511-2021, 2021
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The impact of large-scale deforestation and the physiological effects of elevated atmospheric CO2 on Amazon rainfall are systematically compared in this study. Our results are remarkable in showing that the two disturbances cause equivalent rainfall decrease, though through different causal mechanisms. These results highlight the importance of not only curbing regional deforestation but also reducing global CO2 emissions to avoid climatic changes in the Amazon.
Daniele Peano, Deborah Hemming, Stefano Materia, Christine Delire, Yuanchao Fan, Emilie Joetzjer, Hanna Lee, Julia E. M. S. Nabel, Taejin Park, Philippe Peylin, David Wårlind, Andy Wiltshire, and Sönke Zaehle
Biogeosciences, 18, 2405–2428, https://doi.org/10.5194/bg-18-2405-2021, https://doi.org/10.5194/bg-18-2405-2021, 2021
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Global climate models are the scientist’s tools used for studying past, present, and future climate conditions. This work examines the ability of a group of our tools in reproducing and capturing the right timing and length of the season when plants show their green leaves. This season, indeed, is fundamental for CO2 exchanges between land, atmosphere, and climate. This work shows that discrepancies compared to observations remain, demanding further polishing of these tools.
Karun Pandit, Hamid Dashti, Andrew T. Hudak, Nancy F. Glenn, Alejandro N. Flores, and Douglas J. Shinneman
Biogeosciences, 18, 2027–2045, https://doi.org/10.5194/bg-18-2027-2021, https://doi.org/10.5194/bg-18-2027-2021, 2021
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A dynamic global vegetation model, Ecosystem Demography (EDv2.2), is used to understand spatiotemporal dynamics of a semi-arid shrub ecosystem under alternative fire regimes. Multi-decadal point simulations suggest shrub dominance for a non-fire scenario and a contrasting phase of shrub and C3 grass growth for a fire scenario. Regional gross primary productivity (GPP) simulations indicate moderate agreement with MODIS GPP and a GPP reduction in fire-affected areas before showing some recovery.
Martina Botter, Matthias Zeeman, Paolo Burlando, and Simone Fatichi
Biogeosciences, 18, 1917–1939, https://doi.org/10.5194/bg-18-1917-2021, https://doi.org/10.5194/bg-18-1917-2021, 2021
Carlos A. Sierra, Susan E. Crow, Martin Heimann, Holger Metzler, and Ernst-Detlef Schulze
Biogeosciences, 18, 1029–1048, https://doi.org/10.5194/bg-18-1029-2021, https://doi.org/10.5194/bg-18-1029-2021, 2021
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The climate benefit of carbon sequestration (CBS) is a metric developed to quantify avoided warming by two separate processes: the amount of carbon drawdown from the atmosphere and the time this carbon is stored in a reservoir. This metric can be useful for quantifying the role of forests and soils for climate change mitigation and to better quantify the benefits of carbon removals by sinks.
Xiaoying Shi, Daniel M. Ricciuto, Peter E. Thornton, Xiaofeng Xu, Fengming Yuan, Richard J. Norby, Anthony P. Walker, Jeffrey M. Warren, Jiafu Mao, Paul J. Hanson, Lin Meng, David Weston, and Natalie A. Griffiths
Biogeosciences, 18, 467–486, https://doi.org/10.5194/bg-18-467-2021, https://doi.org/10.5194/bg-18-467-2021, 2021
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The Sphagnum mosses are the important species of a wetland ecosystem. To better represent the peatland ecosystem, we introduced the moss species to the land model component (ELM) of the Energy Exascale Earth System Model (E3SM) by developing water content dynamics and nonvascular photosynthetic processes for moss. We tested the model against field observations and used the model to make projections of the site's carbon cycle under warming and atmospheric CO2 concentration scenarios.
Peter Horvath, Hui Tang, Rune Halvorsen, Frode Stordal, Lena Merete Tallaksen, Terje Koren Berntsen, and Anders Bryn
Biogeosciences, 18, 95–112, https://doi.org/10.5194/bg-18-95-2021, https://doi.org/10.5194/bg-18-95-2021, 2021
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We evaluated the performance of three methods for representing vegetation cover. Remote sensing provided the best match to a reference dataset, closely followed by distribution modelling (DM), whereas the dynamic global vegetation model (DGVM) in CLM4.5BGCDV deviated strongly from the reference. Sensitivity tests show that use of threshold values for predictors identified by DM may improve DGVM performance. The results highlight the potential of using DM in the development of DGVMs.
Johan Arnqvist, Julia Freier, and Ebba Dellwik
Biogeosciences, 17, 5939–5952, https://doi.org/10.5194/bg-17-5939-2020, https://doi.org/10.5194/bg-17-5939-2020, 2020
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Data generated by airborne laser scans enable the characterization of surface vegetation for any application that might need it, such as forest management, modeling for numerical weather prediction, or wind energy estimation. In this work we present a new algorithm for calculating the vegetation density using data from airborne laser scans. The new routine is more robust than earlier methods, and an implementation in popular programming languages accompanies the article to support new users.
Yonghong Yi, John S. Kimball, Jennifer D. Watts, Susan M. Natali, Donatella Zona, Junjie Liu, Masahito Ueyama, Hideki Kobayashi, Walter Oechel, and Charles E. Miller
Biogeosciences, 17, 5861–5882, https://doi.org/10.5194/bg-17-5861-2020, https://doi.org/10.5194/bg-17-5861-2020, 2020
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We developed a 1 km satellite-data-driven permafrost carbon model to evaluate soil respiration sensitivity to recent snow cover changes in Alaska. Results show earlier snowmelt enhances growing-season soil respiration and reduces annual carbon uptake, while early cold-season soil respiration is linked to the number of snow-free days after the land surface freezes. Our results also show nonnegligible influences of subgrid variability in surface conditions on model-simulated CO2 seasonal cycles.
Kuang-Yu Chang, William J. Riley, Patrick M. Crill, Robert F. Grant, and Scott R. Saleska
Biogeosciences, 17, 5849–5860, https://doi.org/10.5194/bg-17-5849-2020, https://doi.org/10.5194/bg-17-5849-2020, 2020
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Methane (CH4) is a strong greenhouse gas that can accelerate climate change and offset mitigation efforts. A key assumption embedded in many large-scale climate models is that ecosystem CH4 emissions can be estimated by fixed temperature relations. Here, we demonstrate that CH4 emissions cannot be parameterized by emergent temperature response alone due to variability driven by microbial and abiotic interactions. We also provide mechanistic understanding for observed CH4 emission hysteresis.
Jinnan Gong, Nigel Roulet, Steve Frolking, Heli Peltola, Anna M. Laine, Nicola Kokkonen, and Eeva-Stiina Tuittila
Biogeosciences, 17, 5693–5719, https://doi.org/10.5194/bg-17-5693-2020, https://doi.org/10.5194/bg-17-5693-2020, 2020
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In this study, which combined a field and lab experiment with modelling, we developed a process-based model for simulating dynamics within peatland moss communities. The model is useful because Sphagnum mosses are key engineers in peatlands; their response to changes in climate via altered hydrology controls the feedback of peatland biogeochemistry to climate. Our work showed that moss capitulum traits related to water retention are the mechanism controlling moss layer dynamics in peatlands.
Tea Thum, Julia E. M. S. Nabel, Aki Tsuruta, Tuula Aalto, Edward J. Dlugokencky, Jari Liski, Ingrid T. Luijkx, Tiina Markkanen, Julia Pongratz, Yukio Yoshida, and Sönke Zaehle
Biogeosciences, 17, 5721–5743, https://doi.org/10.5194/bg-17-5721-2020, https://doi.org/10.5194/bg-17-5721-2020, 2020
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Global vegetation models are important tools in estimating the impacts of global climate change. The fate of soil carbon is of the upmost importance as its emissions will enhance the atmospheric carbon dioxide concentration. To evaluate the skill of global vegetation models to model the soil carbon and its responses to environmental factors, it is important to use different data sources. We evaluated two different soil carbon models by using atmospheric carbon dioxide concentrations.
Maoyi Huang, Yi Xu, Marcos Longo, Michael Keller, Ryan G. Knox, Charles D. Koven, and Rosie A. Fisher
Biogeosciences, 17, 4999–5023, https://doi.org/10.5194/bg-17-4999-2020, https://doi.org/10.5194/bg-17-4999-2020, 2020
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The Functionally Assembled Terrestrial Ecosystem Simulator (FATES) is enhanced to mimic the ecological, biophysical, and biogeochemical processes following a logging event. The model can specify the timing and aerial extent of logging events; determine the survivorship of cohorts in the disturbed forest; and modifying the biomass, coarse woody debris, and litter pools. This study lays the foundation to simulate land use change and forest degradation in FATES as part of an Earth system model.
Junrong Zha and Qianla Zhuang
Biogeosciences, 17, 4591–4610, https://doi.org/10.5194/bg-17-4591-2020, https://doi.org/10.5194/bg-17-4591-2020, 2020
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This study incorporated microbial dormancy into a detailed microbe-based biogeochemistry model to examine the fate of Arctic carbon budgets under changing climate conditions. Compared with the model without microbial dormancy, the new model estimated a much higher carbon accumulation in the region during the last and current century. This study highlights the importance of the representation of microbial dormancy in earth system models to adequately quantify the carbon dynamics in the Arctic.
Thomas Gasser, Léa Crepin, Yann Quilcaille, Richard A. Houghton, Philippe Ciais, and Michael Obersteiner
Biogeosciences, 17, 4075–4101, https://doi.org/10.5194/bg-17-4075-2020, https://doi.org/10.5194/bg-17-4075-2020, 2020
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We combine several lines of evidence to provide a robust estimate of historical CO2 emissions from land use change. Our novel approach leads to reduced uncertainty and identifies key remaining sources of uncertainty and discrepancy.
We also quantify the carbon removal by natural ecosystems that would have occurred if these ecosystems had not been destroyed (mostly via deforestation). Over the last decade, this foregone carbon sink amounted to about 50 % of the actual emissions.
Hua W. Xie, Adriana L. Romero-Olivares, Michele Guindani, and Steven D. Allison
Biogeosciences, 17, 4043–4057, https://doi.org/10.5194/bg-17-4043-2020, https://doi.org/10.5194/bg-17-4043-2020, 2020
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Soil biogeochemical models (SBMs) are needed to predict future soil CO2 emissions levels, but we presently lack statistically rigorous frameworks for assessing the predictive utility of SBMs. In this study, we demonstrate one possible approach to evaluating SBMs by comparing the fits of two models to soil CO2 respiration data with recently developed Bayesian statistical goodness-of-fit metrics. Our results demonstrate that our approach is a viable one for continued development and refinement.
Stefano Manzoni, Arjun Chakrawal, Thomas Fischer, Joshua P. Schimel, Amilcare Porporato, and Giulia Vico
Biogeosciences, 17, 4007–4023, https://doi.org/10.5194/bg-17-4007-2020, https://doi.org/10.5194/bg-17-4007-2020, 2020
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Carbon dioxide is produced by soil microbes through respiration, which is particularly fast when soils are moistened by rain. Will respiration increase with future more intense rains and longer dry spells? With a mathematical model, we show that wetter conditions increase respiration. In contrast, if rainfall totals stay the same, but rain comes all at once after long dry spells, the average respiration will not change, but the contribution of the respiration bursts after rain will increase.
Nicholas C. Parazoo, Troy Magney, Alex Norton, Brett Raczka, Cédric Bacour, Fabienne Maignan, Ian Baker, Yongguang Zhang, Bo Qiu, Mingjie Shi, Natasha MacBean, Dave R. Bowling, Sean P. Burns, Peter D. Blanken, Jochen Stutz, Katja Grossmann, and Christian Frankenberg
Biogeosciences, 17, 3733–3755, https://doi.org/10.5194/bg-17-3733-2020, https://doi.org/10.5194/bg-17-3733-2020, 2020
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Satellite measurements of solar-induced chlorophyll fluorescence (SIF) provide a global measure of photosynthetic change. This enables scientists to better track carbon cycle responses to environmental change and tune biochemical processes in vegetation models for an improved simulation of future change. We use tower-instrumented SIF measurements and controlled model experiments to assess the state of the art in terrestrial biosphere SIF modeling and find a wide range of sensitivities to light.
Tong Yu and Qianlai Zhuang
Biogeosciences, 17, 3643–3657, https://doi.org/10.5194/bg-17-3643-2020, https://doi.org/10.5194/bg-17-3643-2020, 2020
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Biological nitrogen fixation (BNF) plays an important role in the global nitrogen cycle. However, the fixation rate has usually been measured or estimated at a particular observational site. This study develops a BNF model considering the symbiotic relationship between legume plants and bacteria. The model is extensively calibrated with site-level observational data and then extrapolated to the global terrestrial ecosystems to quantify the fixation rate in the 1990s.
Simon Jones, Lucy Rowland, Peter Cox, Deborah Hemming, Andy Wiltshire, Karina Williams, Nicholas C. Parazoo, Junjie Liu, Antonio C. L. da Costa, Patrick Meir, Maurizio Mencuccini, and Anna B. Harper
Biogeosciences, 17, 3589–3612, https://doi.org/10.5194/bg-17-3589-2020, https://doi.org/10.5194/bg-17-3589-2020, 2020
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Non-structural carbohydrates (NSCs) are an important set of molecules that help plants to grow and respire when photosynthesis is restricted by extreme climate events. In this paper we present a simple model of NSC storage and assess the effect that it has on simulations of vegetation at the ecosystem scale. Our model has the potential to significantly change predictions of plant behaviour in global vegetation models, which would have large implications for predictions of the future climate.
Charles D. Koven, Ryan G. Knox, Rosie A. Fisher, Jeffrey Q. Chambers, Bradley O. Christoffersen, Stuart J. Davies, Matteo Detto, Michael C. Dietze, Boris Faybishenko, Jennifer Holm, Maoyi Huang, Marlies Kovenock, Lara M. Kueppers, Gregory Lemieux, Elias Massoud, Nathan G. McDowell, Helene C. Muller-Landau, Jessica F. Needham, Richard J. Norby, Thomas Powell, Alistair Rogers, Shawn P. Serbin, Jacquelyn K. Shuman, Abigail L. S. Swann, Charuleka Varadharajan, Anthony P. Walker, S. Joseph Wright, and Chonggang Xu
Biogeosciences, 17, 3017–3044, https://doi.org/10.5194/bg-17-3017-2020, https://doi.org/10.5194/bg-17-3017-2020, 2020
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Tropical forests play a crucial role in governing climate feedbacks, and are incredibly diverse ecosystems, yet most Earth system models do not take into account the diversity of plant traits in these forests and how this diversity may govern feedbacks. We present an approach to represent diverse competing plant types within Earth system models, test this approach at a tropical forest site, and explore how the representation of disturbance and competition governs traits of the forest community.
Robert F. Grant, Sisi Lin, and Guillermo Hernandez-Ramirez
Biogeosciences, 17, 2021–2039, https://doi.org/10.5194/bg-17-2021-2020, https://doi.org/10.5194/bg-17-2021-2020, 2020
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Nitrification inhibitors (NI) have been shown to reduce emissions of nitrous oxide (N20), a potent greenhouse gas, from fertilizer and manure applied to agricultural fields. However difficulties in measuring N20 emissions limit our ability to estimate these reductions. Here we propose and test a mathematical model that may allow us to estimate these reductions under diverse site conditions. These estimates will be useful in determining emission factors for NI-amended fertilizer and manure.
Moritz Laub, Michael Scott Demyan, Yvonne Funkuin Nkwain, Sergey Blagodatsky, Thomas Kätterer, Hans-Peter Piepho, and Georg Cadisch
Biogeosciences, 17, 1393–1413, https://doi.org/10.5194/bg-17-1393-2020, https://doi.org/10.5194/bg-17-1393-2020, 2020
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Loss of soil carbon to the atmosphere represents a global challenge. We tested an innovative way to reduce the high uncertainty related to turnover of carbon stored in soils. With the use of infrared spectra of soils from model bare fallow systems, we were able to better assess the current state of soil carbon and predict its behavior in overdecadal time spans. In agreement with recent studies, carbon turnover seems faster than earlier assumed, with potential for high loss under mismanagement.
Genki Katata, Rüdiger Grote, Matthias Mauder, Matthias J. Zeeman, and Masakazu Ota
Biogeosciences, 17, 1071–1085, https://doi.org/10.5194/bg-17-1071-2020, https://doi.org/10.5194/bg-17-1071-2020, 2020
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In this paper, we demonstrate that high physiological activity levels during the extremely warm winter are allocated into the below-ground biomass and only to a minor extent used for additional plant growth during early spring. This process is so far largely unaccounted for in scenario analysis using global terrestrial biosphere models, and it may lead to carbon accumulation in the soil and/or carbon loss from the soil as a response to global warming.
Jinyan Yang, Belinda E. Medlyn, Martin G. De Kauwe, Remko A. Duursma, Mingkai Jiang, Dushan Kumarathunge, Kristine Y. Crous, Teresa E. Gimeno, Agnieszka Wujeska-Klause, and David S. Ellsworth
Biogeosciences, 17, 265–279, https://doi.org/10.5194/bg-17-265-2020, https://doi.org/10.5194/bg-17-265-2020, 2020
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This study addressed a major knowledge gap in the response of forest productivity to elevated CO2. We first quantified forest productivity of an evergreen forest under both ambient and elevated CO2, using a model constrained by in situ measurements. The simulation showed the canopy productivity response to elevated CO2 to be smaller than that at the leaf scale due to different limiting processes. This finding provides a key reference for the understanding of CO2 impacts on forest ecosystems.
Grace Pold, Seeta A. Sistla, and Kristen M. DeAngelis
Biogeosciences, 16, 4875–4888, https://doi.org/10.5194/bg-16-4875-2019, https://doi.org/10.5194/bg-16-4875-2019, 2019
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The litter decomposition model DEMENT was run under ambient temperatures and with 5 °C; of warming. We found that the loss of litter carbon to the atmosphere as CO2 was exacerbated by warming when the microbes in the model differed in their temperature responses, compared to when all microbes responded identically to warming. Our results therefore indicate that predicted changes in litter carbon stocks are sensitive to heterogeneity in key parameters of soil decomposer physiology.
Ensheng Weng, Ray Dybzinski, Caroline E. Farrior, and Stephen W. Pacala
Biogeosciences, 16, 4577–4599, https://doi.org/10.5194/bg-16-4577-2019, https://doi.org/10.5194/bg-16-4577-2019, 2019
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Our study illustrates that the competition processes for light and soil resources in a game-theoretic vegetation demographic model can substantially change the prediction of the contribution of ecosystems to the global carbon cycle. The model that tracks the competitive allocation strategies can generate significantly different ecosystem-level predictions than those with fixed allocation strategies.
Sophie Flack-Prain, Patrick Meir, Yadvinder Malhi, Thomas Luke Smallman, and Mathew Williams
Biogeosciences, 16, 4463–4484, https://doi.org/10.5194/bg-16-4463-2019, https://doi.org/10.5194/bg-16-4463-2019, 2019
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Across the Amazon rainforest, trees take in carbon through photosynthesis. However, photosynthesis across the basin is threatened by predicted shifts in rainfall patterns. To unpick how changes in rainfall affect photosynthesis, we use a model which combines climate data with our knowledge of photosynthesis and other plant processes. We find that stomatal constraints are less important, and instead shifts in leaf surface area and leaf properties drive changes in photosynthesis with rainfall.
Justine Ngoma, Maarten C. Braakhekke, Bart Kruijt, Eddy Moors, Iwan Supit, James H. Speer, Royd Vinya, and Rik Leemans
Biogeosciences, 16, 3853–3867, https://doi.org/10.5194/bg-16-3853-2019, https://doi.org/10.5194/bg-16-3853-2019, 2019
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The Zambezi teak forests are a source of raw material for the timber industry. Through application of the LPJ-GUESS vegetation model, we determined the forests' response to climate change at the wetter Kabompo, drier Sesheke, and intermediate Namwala sites in Zambia. While increased CO2 concentration enhances forests' productivity at Kabompo and Namwala, the decreased rainfall will reduce forests' productivity at Sesheke by the year 2099, resulting in reduced raw material for saw millers.
Karel Castro-Morales, Gregor Schürmann, Christoph Köstler, Christian Rödenbeck, Martin Heimann, and Sönke Zaehle
Biogeosciences, 16, 3009–3032, https://doi.org/10.5194/bg-16-3009-2019, https://doi.org/10.5194/bg-16-3009-2019, 2019
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To obtain nearly 30 years of global terrestrial carbon fluxes, we simultaneously incorporated in a land surface model three different time periods of two observational data sets: absorbed photosynthetic active radiation and atmospheric CO2 concentrations. One decade of data is enough to improve the modeled long-term trends and seasonal amplitudes of the assimilated variables, particularly in boreal regions. This model has the potential to provide short-term predictions of land carbon fluxes.
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Short summary
How long does C cycle through terrestrial ecosystems is a critical question for understanding land C sequestration capacity under future rising atmosphere [CO2] and climate warming. Under climate change, previous conventional concepts with a steady-state assumption will no longer be suitable for a non-steady state. Our results using the new concept, C transit time, suggest more significant responses in terrestrial C cycle under rising [CO2] and climate warming.
How long does C cycle through terrestrial ecosystems is a critical question for understanding...
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