Articles | Volume 20, issue 1
https://doi.org/10.5194/bg-20-251-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-20-251-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
16 Jan 2023
Research article |
| 16 Jan 2023
| 16 Jan 2023
Peatlands and their carbon dynamics in northern high latitudes from 1990 to 2300: a process-based biogeochemistry model analysis
Bailu Zhao
Department of Earth, Atmospheric, and Planetary Sciences, Purdue
University, West Lafayette, IN 47907, USA
Department of Earth, Atmospheric, and Planetary Sciences, Purdue
University, West Lafayette, IN 47907, USA
Department of Agronomy, Purdue University, West Lafayette, IN 47907,
USA
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Zhen Zhang, Benjamin Poulter, Joe R. Melton, William J. Riley, George H. Allen, David J. Beerling, Philippe Bousquet, Josep G. Canadell, Etienne Fluet-Chouinard, Philippe Ciais, Nicola Gedney, Peter O. Hopcroft, Akihiko Ito, Robert B. Jackson, Atul K. Jain, Katherine Jensen, Fortunat Joos, Thomas Kleinen, Sara Knox, Tingting Li, Xin Li, Xiangyu Liu, Kyle McDonald, Gavin McNicol, Paul A. Miller, Jurek Müller, Prabir K. Patra, Changhui Peng, Shushi Peng, Zhangcai Qin, Ryan M. Riggs, Marielle Saunois, Qing Sun, Hanqin Tian, Xiaoming Xu, Yuanzhi Yao, Xi Yi, Wenxin Zhang, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
EGUsphere, https://doi.org/10.5194/egusphere-2024-1584, https://doi.org/10.5194/egusphere-2024-1584, 2024
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This study assesses global methane emissions from wetlands between 2000 and 2020 using multiple models. We found that wetland emissions increased by 6–7 Tg CH4 per year in the 2010s compared to the 2000s. Rising temperatures primarily drove this increase, while changes in precipitation and CO2 levels also played roles. Our findings highlight the importance of wetlands in the global methane budget and the need for continuous monitoring to understand their impact on climate change.
Marielle Saunois, Adrien Martinez, Benjamin Poulter, Zhen Zhang, Peter Raymond, Pierre Regnier, Joseph G. Canadell, Robert B. Jackson, Prabir K. Patra, Philippe Bousquet, Philippe Ciais, Edward J. Dlugokencky, Xin Lan, George H. Allen, David Bastviken, David J. Beerling, Dmitry A. Belikov, Donald R. Blake, Simona Castaldi, Monica Crippa, Bridget R. Deemer, Fraser Dennison, Giuseppe Etiope, Nicola Gedney, Lena Höglund-Isaksson, Meredith A. Holgerson, Peter O. Hopcroft, Gustaf Hugelius, Akihito Ito, Atul K. Jain, Rajesh Janardanan, Matthew S. Johnson, Thomas Kleinen, Paul Krummel, Ronny Lauerwald, Tingting Li, Xiangyu Liu, Kyle C. McDonald, Joe R. Melton, Jens Mühle, Jurek Müller, Fabiola Murguia-Flores, Yosuke Niwa, Sergio Noce, Shufen Pan, Robert J. Parker, Changhui Peng, Michel Ramonet, William J. Riley, Gerard Rocher-Ros, Judith A. Rosentreter, Motoki Sasakawa, Arjo Segers, Steven J. Smith, Emily H. Stanley, Joel Thanwerdas, Hanquin Tian, Aki Tsuruta, Francesco N. Tubiello, Thomas S. Weber, Guido van der Werf, Doug E. Worthy, Yi Xi, Yukio Yoshida, Wenxin Zhang, Bo Zheng, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-115, https://doi.org/10.5194/essd-2024-115, 2024
Preprint under review for ESSD
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Methane (CH4) is the second most important human-influenced greenhouse gas in terms of climate forcing after carbon dioxide (CO2). A consortium of multi-disciplinary scientists synthesize and update the budget of the sources and sinks of CH4. This edition benefits from important progresses in estimating emissions from lakes and ponds, reservoirs, and streams and rivers. For the 2010s decade, global CH4 emissions are estimated at 575 Tg CH4 yr-1, including ~65 % from anthropogenic sources.
Yiming Xu, Qianlai Zhuang, Bailu Zhao, Michael Billmire, Christopher Cook, Jeremy Graham, Nancy French, and Ronald Prinn
EGUsphere, https://doi.org/10.5194/egusphere-2024-1324, https://doi.org/10.5194/egusphere-2024-1324, 2024
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We use a process-based model to simulate the fire impacts on soil thermal and hydrological dynamics and carbon budget of forest ecosystems in Northern Eurasia based on satellite-derived burn severity data. We find that fire severity generally increases in this region during the study period. Simulations indicate that fires increase soil temperature and water runoff. Fires lead the forest ecosystems to lose 2.3 Pg C, shifting the forests from a carbon sink to a source in this period.
Ye Yuan, Qianlai Zhuang, Bailu Zhao, and Narasinha Shurpali
EGUsphere, https://doi.org/10.5194/egusphere-2023-1047, https://doi.org/10.5194/egusphere-2023-1047, 2023
Preprint archived
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We use a biogeochemistry model to calculate the regional N2O emissions considering the effects of N2O uptake, thawing permafrost, and N deposition. Our simulations show there is an increasing trend in regional net N2O emissions from 1969 to 2019. Annual N2O emissions exhibited big spatial variabilities. Nitrogen deposition leads to a significant increase in emission. Our results suggest that in the future, the pan-Arctic terrestrial ecosystem might act as an even larger N2O.
Xiangyu Liu and Qianlai Zhuang
Biogeosciences, 20, 1181–1193, https://doi.org/10.5194/bg-20-1181-2023, https://doi.org/10.5194/bg-20-1181-2023, 2023
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We are among the first to quantify methane emissions from inland water system in the pan-Arctic. The total CH4 emissions are 36.46 Tg CH4 yr−1 during 2000–2015, of which wetlands and lakes were 21.69 Tg yr−1 and 14.76 Tg yr−1, respectively. By using two non-overlap area change datasets with land and lake models, our simulation avoids small lakes being counted twice as both lake and wetland, and it narrows the gap between two different methods used to quantify regional CH4 emissions.
Junrong Zha and Qianlai Zhuang
Biogeosciences, 18, 6245–6269, https://doi.org/10.5194/bg-18-6245-2021, https://doi.org/10.5194/bg-18-6245-2021, 2021
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This study incorporated moss into an extant biogeochemistry model to simulate the role of moss in carbon dynamics in the Arctic. The interactions between higher plants and mosses and their competition for energy, water, and nutrients are considered in our study. We found that, compared with the previous model without moss, the new model estimated a much higher carbon accumulation in the region during the last century and this century.
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.
Marielle Saunois, Ann R. Stavert, Ben Poulter, Philippe Bousquet, Josep G. Canadell, Robert B. Jackson, Peter A. Raymond, Edward J. Dlugokencky, Sander Houweling, Prabir K. Patra, Philippe Ciais, Vivek K. Arora, David Bastviken, Peter Bergamaschi, Donald R. Blake, Gordon Brailsford, Lori Bruhwiler, Kimberly M. Carlson, Mark Carrol, Simona Castaldi, Naveen Chandra, Cyril Crevoisier, Patrick M. Crill, Kristofer Covey, Charles L. Curry, Giuseppe Etiope, Christian Frankenberg, Nicola Gedney, Michaela I. Hegglin, Lena Höglund-Isaksson, Gustaf Hugelius, Misa Ishizawa, Akihiko Ito, Greet Janssens-Maenhout, Katherine M. Jensen, Fortunat Joos, Thomas Kleinen, Paul B. Krummel, Ray L. Langenfelds, Goulven G. Laruelle, Licheng Liu, Toshinobu Machida, Shamil Maksyutov, Kyle C. McDonald, Joe McNorton, Paul A. Miller, Joe R. Melton, Isamu Morino, Jurek Müller, Fabiola Murguia-Flores, Vaishali Naik, Yosuke Niwa, Sergio Noce, Simon O'Doherty, Robert J. Parker, Changhui Peng, Shushi Peng, Glen P. Peters, Catherine Prigent, Ronald Prinn, Michel Ramonet, Pierre Regnier, William J. Riley, Judith A. Rosentreter, Arjo Segers, Isobel J. Simpson, Hao Shi, Steven J. Smith, L. Paul Steele, Brett F. Thornton, Hanqin Tian, Yasunori Tohjima, Francesco N. Tubiello, Aki Tsuruta, Nicolas Viovy, Apostolos Voulgarakis, Thomas S. Weber, Michiel van Weele, Guido R. van der Werf, Ray F. Weiss, Doug Worthy, Debra Wunch, Yi Yin, Yukio Yoshida, Wenxin Zhang, Zhen Zhang, Yuanhong Zhao, Bo Zheng, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Earth Syst. Sci. Data, 12, 1561–1623, https://doi.org/10.5194/essd-12-1561-2020, https://doi.org/10.5194/essd-12-1561-2020, 2020
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Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. We have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate new research aimed at improving and regularly updating the global methane budget. This is the second version of the review dedicated to the decadal methane budget, integrating results of top-down and bottom-up estimates.
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.
Sofya Guseva, Tobias Bleninger, Klaus Jöhnk, Bruna Arcie Polli, Zeli Tan, Wim Thiery, Qianlai Zhuang, James Anthony Rusak, Huaxia Yao, Andreas Lorke, and Victor Stepanenko
Hydrol. Earth Syst. Sci., 24, 697–715, https://doi.org/10.5194/hess-24-697-2020, https://doi.org/10.5194/hess-24-697-2020, 2020
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We compare lake models with different complexity focusing on the key factors (e.g., eddy diffusivity) which can have an influence on the distribution of the dissolved gases in water. For the first time, we compare the biogeochemical modules in the ALBM and LAKE models. The result showed a good agreement with observed data (O2), but not for CO2. It indicates the need to improve the representation of physical and biogeochemical processes in lake models.
Tong Yu and Qianlai Zhuang
Biogeosciences, 16, 207–222, https://doi.org/10.5194/bg-16-207-2019, https://doi.org/10.5194/bg-16-207-2019, 2019
Junrong Zha and Qianlai Zhuang
Biogeosciences, 15, 5621–5634, https://doi.org/10.5194/bg-15-5621-2018, https://doi.org/10.5194/bg-15-5621-2018, 2018
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This study used a detailed microbial-based soil decomposition biogeochemistry model to examine the fate of much arctic soil carbon under changing climate conditions. We found that the detailed microbial decomposition biogeochemistry model estimated a much lower carbon accumulation in the region during this century. The amount of soil carbon considered in the 21st-century simulations determines the regional carbon sink and source strengths, regardless of the complexity of models used.
Hanbo Yun, Qingbai Wu, Qianlai Zhuang, Anping Chen, Tong Yu, Zhou Lyu, Yuzhong Yang, Huijun Jin, Guojun Liu, Yang Qu, and Licheng Liu
The Cryosphere, 12, 2803–2819, https://doi.org/10.5194/tc-12-2803-2018, https://doi.org/10.5194/tc-12-2803-2018, 2018
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Here we reported the QTP permafrost region was a CH4 sink of −0.86 ± 0.23 g CH4-C m−2 yr−1 over 2012–2016, soil temperature and soil water content were dominant factors controlling CH4 fluxes, and their correlations changed with soil depth due to cryoturbation dynamics. This region was a net CH4 sink in autumn, but a net source in spring, despite both seasons experiencing similar top soil thawing and freezing dynamics.
Yang Qu, Shamil Maksyutov, and Qianlai Zhuang
Biogeosciences, 15, 3967–3973, https://doi.org/10.5194/bg-15-3967-2018, https://doi.org/10.5194/bg-15-3967-2018, 2018
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We developed an algorithm for a fast spin-up by finding the exact solution of a linearized system representing the cyclo-stationary state of a model and implemented it in a biogeochemistry model, the Terrestrial Ecosystem Model. For the test sites with five different plant functional types, the new method saves over 90 % of the original spin-up time in site-level simulations. The developed spin-up method will be used for future quantification of carbon dynamics at fine spatiotemporal scales.
Licheng Liu, Qianlai Zhuang, Qing Zhu, Shaoqing Liu, Hella van Asperen, and Mari Pihlatie
Atmos. Chem. Phys., 18, 7913–7931, https://doi.org/10.5194/acp-18-7913-2018, https://doi.org/10.5194/acp-18-7913-2018, 2018
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carbon monoxide (CO) plays an important role in atmosphere. We developed a model to quantify soil CO exchanges with the atmosphere. The simulation is conducted for various ecosystems on a global scale during the 20th and 21st centuries. We found that areas near the Equator, the eastern US, Europe and eastern Asia are the largest sinks due to optimum soil moisture and high temperature. This study will benefit the modeling of the global climate and atmospheric chemistry.
Thibaud Thonat, Marielle Saunois, Philippe Bousquet, Isabelle Pison, Zeli Tan, Qianlai Zhuang, Patrick M. Crill, Brett F. Thornton, David Bastviken, Ed J. Dlugokencky, Nikita Zimov, Tuomas Laurila, Juha Hatakka, Ove Hermansen, and Doug E. J. Worthy
Atmos. Chem. Phys., 17, 8371–8394, https://doi.org/10.5194/acp-17-8371-2017, https://doi.org/10.5194/acp-17-8371-2017, 2017
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Atmospheric methane simulations in the Arctic have been made for 2012 and compared to continuous observations at six measurement sites. All methane sources significantly affect the measurements at all stations, at least at the synoptic scale, except for biomass burning. An appropriate modelling framework combined with continuous observations of atmospheric methane enables us to gain knowledge on regional methane sources, including those which are usually poorly represented, such as freshwater.
Sirui Wang, Qianlai Zhuang, and Zicheng Yu
Biogeosciences, 13, 6305–6319, https://doi.org/10.5194/bg-13-6305-2016, https://doi.org/10.5194/bg-13-6305-2016, 2016
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We used a model to quantify the carbon stock and its changes in terrestrial ecosystems of Alaska during the last 15 000 years. We found that the changes in vegetation distribution due to climate were the key factors in the spatial variations of carbon in different time periods. The warming during 11–9 k years ago characterized by the increased summer temperature and seasonality of radiation, along with the high precipitation, might play an important role in causing the high carbon accumulation.
Zeli Tan, Qianlai Zhuang, Daven K. Henze, Christian Frankenberg, Ed Dlugokencky, Colm Sweeney, Alexander J. Turner, Motoki Sasakawa, and Toshinobu Machida
Atmos. Chem. Phys., 16, 12649–12666, https://doi.org/10.5194/acp-16-12649-2016, https://doi.org/10.5194/acp-16-12649-2016, 2016
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Methane emissions from the pan-Arctic could be important in understanding the global carbon cycle but are still poorly constrained to date. This study demonstrated that satellite retrievals can be used to reduce the uncertainty of the estimates of these emissions. We also provided additional evidence for the existence of large methane emissions from pan-Arctic lakes in the Siberian yedoma permafrost region. We found that biogeochemical models should be improved for better estimates.
X. Lu and Q. Zhuang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmdd-8-10411-2015, https://doi.org/10.5194/gmdd-8-10411-2015, 2015
Revised manuscript has not been submitted
T. J. Bohn, J. R. Melton, A. Ito, T. Kleinen, R. Spahni, B. D. Stocker, B. Zhang, X. Zhu, R. Schroeder, M. V. Glagolev, S. Maksyutov, V. Brovkin, G. Chen, S. N. Denisov, A. V. Eliseev, A. Gallego-Sala, K. C. McDonald, M.A. Rawlins, W. J. Riley, Z. M. Subin, H. Tian, Q. Zhuang, and J. O. Kaplan
Biogeosciences, 12, 3321–3349, https://doi.org/10.5194/bg-12-3321-2015, https://doi.org/10.5194/bg-12-3321-2015, 2015
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We evaluated 21 forward models and 5 inversions over western Siberia in terms of CH4 emissions and simulated wetland areas and compared these results to an intensive in situ CH4 flux data set, several wetland maps, and two satellite inundation products. In addition to assembling a definitive collection of methane emissions estimates for the region, we were able to identify the types of wetland maps and model features necessary for accurate simulations of high-latitude wetlands.
Q. Zhu, Q. Zhuang, D. Henze, K. Bowman, M. Chen, Y. Liu, Y. He, H. Matsueda, T. Machida, Y. Sawa, and W. Oechel
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-14-22587-2014, https://doi.org/10.5194/acpd-14-22587-2014, 2014
Revised manuscript not accepted
Y. He, Q. Zhuang, J. W. Harden, A. D. McGuire, Z. Fan, Y. Liu, and K. P. Wickland
Biogeosciences, 11, 4477–4491, https://doi.org/10.5194/bg-11-4477-2014, https://doi.org/10.5194/bg-11-4477-2014, 2014
X. Zhu, Q. Zhuang, X. Lu, and L. Song
Biogeosciences, 11, 1693–1704, https://doi.org/10.5194/bg-11-1693-2014, https://doi.org/10.5194/bg-11-1693-2014, 2014
Q. Zhu and Q. Zhuang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmdd-6-6835-2013, https://doi.org/10.5194/gmdd-6-6835-2013, 2013
Revised manuscript not accepted
Q. Zhu and Q. Zhuang
Biogeosciences, 10, 7943–7955, https://doi.org/10.5194/bg-10-7943-2013, https://doi.org/10.5194/bg-10-7943-2013, 2013
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Stomata are pores on leaves that regulate gas exchange between plants and the atmosphere. Existing land models unrealistically assume stomata can jump between steady states when the environment changes. We implemented dynamic modeling to predict gradual stomatal responses at different scales. Results suggested that considering this effect on plant behavior patterns in diurnal cycles was important. Our framework also simplified simulations and can contribute to further efficiency improvements.
Melanie A. Thurner, Silvia Caldararu, Jan Engel, Anja Rammig, and Sönke Zaehle
Biogeosciences, 21, 1391–1410, https://doi.org/10.5194/bg-21-1391-2024, https://doi.org/10.5194/bg-21-1391-2024, 2024
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Jinyun Tang and William J. Riley
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Biogeosciences, 21, 1017–1036, https://doi.org/10.5194/bg-21-1017-2024, https://doi.org/10.5194/bg-21-1017-2024, 2024
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Observations are used to reduce uncertainty in land surface models (LSMs) by optimising poorly constraining parameters. However, optimising against current conditions does not necessarily ensure that the parameters treated as invariant will be robust in a changing climate. Manipulation experiments offer us a unique chance to optimise our models under different (here atmospheric CO2) conditions. By using these data in optimisations, we gain confidence in the future projections of LSMs.
Kelsey T. Foster, Wu Sun, Yoichi P. Shiga, Jiafu Mao, and Anna M. Michalak
Biogeosciences, 21, 869–891, https://doi.org/10.5194/bg-21-869-2024, https://doi.org/10.5194/bg-21-869-2024, 2024
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Assessing agreement between bottom-up and top-down methods across spatial scales can provide insights into the relationship between ensemble spread (difference across models) and model accuracy (difference between model estimates and reality). We find that ensemble spread is unlikely to be a good indicator of actual uncertainty in the North American carbon balance. However, models that are consistent with atmospheric constraints show stronger agreement between top-down and bottom-up estimates.
Victoria R. Dutch, Nick Rutter, Leanne Wake, Oliver Sonnentag, Gabriel Hould Gosselin, Melody Sandells, Chris Derksen, Branden Walker, Gesa Meyer, Richard Essery, Richard Kelly, Phillip Marsh, Julia Boike, and Matteo Detto
Biogeosciences, 21, 825–841, https://doi.org/10.5194/bg-21-825-2024, https://doi.org/10.5194/bg-21-825-2024, 2024
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We undertake a sensitivity study of three different parameters on the simulation of net ecosystem exchange (NEE) during the snow-covered non-growing season at an Arctic tundra site. Simulations are compared to eddy covariance measurements, with near-zero NEE simulated despite observed CO2 release. We then consider how to parameterise the model better in Arctic tundra environments on both sub-seasonal timescales and cumulatively throughout the snow-covered non-growing season.
Erik Schwarz, Samia Ghersheen, Salim Belyazid, and Stefano Manzoni
EGUsphere, https://doi.org/10.5194/egusphere-2024-348, https://doi.org/10.5194/egusphere-2024-348, 2024
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Occurrence of unstable equilibrium points (EPs) could impede applicability of microbial-explicit soil organic carbon models. For archetypal model versions we identified when instability can occur and describe mathematical conditions to avoid such unstable EPs. We discuss implications for further model development, highlighting the important role of considering basic ecological principles to ensure biologically meaningful models.
Bertrand Guenet, Jérémie Orliac, Lauric Cécillon, Olivier Torres, Laura Sereni, Philip A. Martin, Pierre Barré, and Laurent Bopp
Biogeosciences, 21, 657–669, https://doi.org/10.5194/bg-21-657-2024, https://doi.org/10.5194/bg-21-657-2024, 2024
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Heterotrophic respiration fluxes are a major flux between surfaces and the atmosphere, but Earth system models do not yet represent them correctly. Here we benchmarked Earth system models against observation-based products, and we identified the important mechanisms that need to be improved in the next-generation Earth system models.
Shuyue Li, Bonnie Waring, Jennifer Powers, and David Medvigy
Biogeosciences, 21, 455–471, https://doi.org/10.5194/bg-21-455-2024, https://doi.org/10.5194/bg-21-455-2024, 2024
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We used an ecosystem model to simulate primary production of a tropical forest subjected to 3 years of nutrient fertilization. Simulations parameterized such that relative allocation to fine roots increased with increasing soil phosphorus had leaf, wood, and fine root production consistent with observations. However, these simulations seemed to over-allocate to fine roots on multidecadal timescales, affecting aboveground biomass. Additional observations across timescales would benefit models.
Stephen Björn Wirth, Arne Poyda, Friedhelm Taube, Britta Tietjen, Christoph Müller, Kirsten Thonicke, Anja Linstädter, Kai Behn, Sibyll Schaphoff, Werner von Bloh, and Susanne Rolinski
Biogeosciences, 21, 381–410, https://doi.org/10.5194/bg-21-381-2024, https://doi.org/10.5194/bg-21-381-2024, 2024
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In dynamic global vegetation models (DGVMs), the role of functional diversity in forage supply and soil organic carbon storage of grasslands is not explicitly taken into account. We introduced functional diversity into the Lund Potsdam Jena managed Land (LPJmL) DGVM using CSR theory. The new model reproduced well-known trade-offs between plant traits and can be used to quantify the role of functional diversity in climate change mitigation using different functional diversity scenarios.
Huajie Zhu, Xiuli Xing, Mousong Wu, Weimin Ju, and Fei Jiang
EGUsphere, https://doi.org/10.5194/egusphere-2023-3032, https://doi.org/10.5194/egusphere-2023-3032, 2024
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In this study, ecosystem COS fluxes data were employed to optimize GPP estimation across various ecosystems with the Boreal Ecosystem Productivity Simulator (BEPS), which was further developed for simulating the leaf COS uptake under its state-of-the-art ‘two-leaf’ framework. our results showcased the efficacy of COS in enhancing model prediction and reducing prediction uncertainty of GPP, and deepened insights into the sensitivity, identifiability, and interactions of parameters related to COS.
Joe R. McNorton and Francesca Di Giuseppe
Biogeosciences, 21, 279–300, https://doi.org/10.5194/bg-21-279-2024, https://doi.org/10.5194/bg-21-279-2024, 2024
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Wildfires have wide-ranging consequences for local communities, air quality and ecosystems. Vegetation amount and moisture state are key components to forecast wildfires. We developed a combined model and satellite framework to characterise vegetation, including the type of fuel, whether it is alive or dead, and its moisture content. The daily data is at high resolution globally (~9 km). Our characteristics correlate with active fire data and can inform fire danger and spread modelling efforts.
Brooke A. Eastman, William R. Wieder, Melannie D. Hartman, Edward R. Brzostek, and William T. Peterjohn
Biogeosciences, 21, 201–221, https://doi.org/10.5194/bg-21-201-2024, https://doi.org/10.5194/bg-21-201-2024, 2024
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We compared soil model performance to data from a long-term nitrogen addition experiment in a forested ecosystem. We found that in order for soil carbon models to accurately predict future forest carbon sequestration, two key processes must respond dynamically to nitrogen availability: (1) plant allocation of carbon to wood versus roots and (2) rates of soil organic matter decomposition. Long-term experiments can help improve our predictions of the land carbon sink and its climate impact.
Jan De Pue, Sebastian Wieneke, Ana Bastos, José Miguel Barrios, Liyang Liu, Philippe Ciais, Alirio Arboleda, Rafiq Hamdi, Maral Maleki, Fabienne Maignan, Françoise Gellens-Meulenberghs, Ivan Janssens, and Manuela Balzarolo
Biogeosciences, 20, 4795–4818, https://doi.org/10.5194/bg-20-4795-2023, https://doi.org/10.5194/bg-20-4795-2023, 2023
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The gross primary production (GPP) of the terrestrial biosphere is a key source of variability in the global carbon cycle. To estimate this flux, models can rely on remote sensing data (RS-driven), meteorological data (meteo-driven) or a combination of both (hybrid). An intercomparison of 11 models demonstrated that RS-driven models lack the sensitivity to short-term anomalies. Conversely, the simulation of soil moisture dynamics and stress response remains a challenge in meteo-driven models.
Sian Kou-Giesbrecht, Vivek Arora, Christian Seiler, and Libo Wang
EGUsphere, https://doi.org/10.5194/egusphere-2023-2711, https://doi.org/10.5194/egusphere-2023-2711, 2023
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Terrestrial biosphere models can either prescribe the geographical distribution of biomes or simulate them dynamically, capturing climate change-driven biome shifts. We isolate and examine the differences between these different land cover implementations. We find that the simulated terrestrial carbon sink at the end of the 21st century is twice as large in simulations with dynamic land cover than in simulations with prescribed land cover due to important range shifts in the Arctic and Amazon.
Chad A. Burton, Luigi J. Renzullo, Sami W. Rifai, and Albert I. J. M. Van Dijk
Biogeosciences, 20, 4109–4134, https://doi.org/10.5194/bg-20-4109-2023, https://doi.org/10.5194/bg-20-4109-2023, 2023
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Australia's land-based ecosystems play a critical role in controlling the variability in the global land carbon sink. However, uncertainties in the methods used for quantifying carbon fluxes limit our understanding. We develop high-resolution estimates of Australia's land carbon fluxes using machine learning methods and find that Australia is, on average, a stronger carbon sink than previously thought and that the seasonal dynamics of the fluxes differ from those described by other methods.
Yuan Yan, Anne Klosterhalfen, Fernando Moyano, Matthias Cuntz, Andrew C. Manning, and Alexander Knohl
Biogeosciences, 20, 4087–4107, https://doi.org/10.5194/bg-20-4087-2023, https://doi.org/10.5194/bg-20-4087-2023, 2023
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A better understanding of O2 fluxes, their exchange ratios with CO2 and their interrelations with environmental conditions would provide further insights into biogeochemical ecosystem processes. We, therefore, used the multilayer canopy model CANVEG to simulate and analyze the flux exchange for our forest study site for 2012–2016. Based on these simulations, we further successfully tested the application of various micrometeorological methods and the prospects of real O2 flux measurements.
Jie Zhang, Elisabeth Larsen Kolstad, Wenxin Zhang, Iris Vogeler, and Søren O. Petersen
Biogeosciences, 20, 3895–3917, https://doi.org/10.5194/bg-20-3895-2023, https://doi.org/10.5194/bg-20-3895-2023, 2023
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Manure application to agricultural land often results in large and variable N2O emissions. We propose a model with a parsimonious structure to investigate N transformations around such N2O hotspots. The model allows for new detailed insights into the interactions between transport and microbial activities regarding N2O emissions in heterogeneous soil environments. It highlights the importance of solute diffusion to N2O emissions from such hotspots which are often ignored by process-based models.
Jukka Alm, Antti Wall, Jukka-Pekka Myllykangas, Paavo Ojanen, Juha Heikkinen, Helena M. Henttonen, Raija Laiho, Kari Minkkinen, Tarja Tuomainen, and Juha Mikola
Biogeosciences, 20, 3827–3855, https://doi.org/10.5194/bg-20-3827-2023, https://doi.org/10.5194/bg-20-3827-2023, 2023
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In Finland peatlands cover one-third of land area. For half of those, with 4.3 Mha being drained for forestry, Finland reports sinks and sources of greenhouse gases in forest lands on organic soils following its UNFCCC commitment. We describe a new method for compiling soil CO2 balance that follows changes in tree volume, tree harvests and temperature. An increasing trend of emissions from 1.4 to 7.9 Mt CO2 was calculated for drained peatland forest soils in Finland for 1990–2021.
Elizabeth S. Duan, Luciana Chavez Rodriguez, Nicole Hemming-Schroeder, Baptiste Wijas, Habacuc Flores-Moreno, Alexander W. Cheesman, Lucas A. Cernusak, Michael J. Liddell, Paul Eggleton, Amy E. Zanne, and Steven D. Allison
EGUsphere, https://doi.org/10.5194/egusphere-2023-1952, https://doi.org/10.5194/egusphere-2023-1952, 2023
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Understanding the link between climate and carbon fluxes is crucial in predicting how climate change will impact carbon sinks. We estimated CO2 fluxes from deadwood in tropical Australia using wood microclimate variables (wood moisture content and temperature). Our model predicted that the majority of deadwood carbon is released as CO2, except when termite activity is detected. Future models should also incorporate wood traits, like species and chemical composition, to better predict fluxes.
Siqi Li, Bo Zhu, Xunhua Zheng, Pengcheng Hu, Shenghui Han, Jihui Fan, Tao Wang, Rui Wang, Kai Wang, Zhisheng Yao, Chunyan Liu, Wei Zhang, and Yong Li
Biogeosciences, 20, 3555–3572, https://doi.org/10.5194/bg-20-3555-2023, https://doi.org/10.5194/bg-20-3555-2023, 2023
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Physical soil erosion and particulate carbon, nitrogen and phosphorus loss modules were incorporated into the process-oriented hydro-biogeochemical model CNMM-DNDC to realize the accurate simulation of water-induced erosion and subsequent particulate nutrient losses at high spatiotemporal resolution.
Ivan Cornut, Nicolas Delpierre, Jean-Paul Laclau, Joannès Guillemot, Yann Nouvellon, Otavio Campoe, Jose Luiz Stape, Vitoria Fernanda Santos, and Guerric le Maire
Biogeosciences, 20, 3093–3117, https://doi.org/10.5194/bg-20-3093-2023, https://doi.org/10.5194/bg-20-3093-2023, 2023
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Potassium is an essential element for living organisms. Trees are dependent upon this element for certain functions that allow them to build their trunks using carbon dioxide. Using data from experiments in eucalypt plantations in Brazil and a simplified computer model of the plantations, we were able to investigate the effect that a lack of potassium can have on the production of wood. Understanding nutrient cycles is useful to understand the response of forests to environmental change.
Ivan Cornut, Guerric le Maire, Jean-Paul Laclau, Joannès Guillemot, Yann Nouvellon, and Nicolas Delpierre
Biogeosciences, 20, 3119–3135, https://doi.org/10.5194/bg-20-3119-2023, https://doi.org/10.5194/bg-20-3119-2023, 2023
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After simulating the effects of low levels of potassium on the canopy of trees and the uptake of carbon dioxide from the atmosphere by leaves in Part 1, here we tried to simulate the way the trees use the carbon they have acquired and the interaction with the potassium cycle in the tree. We show that the effect of low potassium on the efficiency of the trees in acquiring carbon is enough to explain why they produce less wood when they are in soils with low levels of potassium.
Xiaojuan Yang, Peter Thornton, Daniel Ricciuto, Yilong Wang, and Forrest Hoffman
Biogeosciences, 20, 2813–2836, https://doi.org/10.5194/bg-20-2813-2023, https://doi.org/10.5194/bg-20-2813-2023, 2023
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We evaluated the performance of a land surface model (ELMv1-CNP) that includes both nitrogen (N) and phosphorus (P) limitation on carbon cycle processes. We show that ELMv1-CNP produces realistic estimates of present-day carbon pools and fluxes. We show that global C sources and sinks are significantly affected by P limitation. Our study suggests that introduction of P limitation in land surface models is likely to have substantial consequences for projections of future carbon uptake.
Kevin R. Wilcox, Scott L. Collins, Alan K. Knapp, William Pockman, Zheng Shi, Melinda D. Smith, and Yiqi Luo
Biogeosciences, 20, 2707–2725, https://doi.org/10.5194/bg-20-2707-2023, https://doi.org/10.5194/bg-20-2707-2023, 2023
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The capacity for carbon storage (C capacity) is an attribute that determines how ecosystems store carbon in the future. Here, we employ novel data–model integration techniques to identify the carbon capacity of six grassland sites spanning the US Great Plains. Hot and dry sites had low C capacity due to less plant growth and high turnover of soil C, so they may be a C source in the future. Alternately, cooler and wetter ecosystems had high C capacity, so these systems may be a future C sink.
Ara Cho, Linda M. J. Kooijmans, Kukka-Maaria Kohonen, Richard Wehr, and Maarten C. Krol
Biogeosciences, 20, 2573–2594, https://doi.org/10.5194/bg-20-2573-2023, https://doi.org/10.5194/bg-20-2573-2023, 2023
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Carbonyl sulfide (COS) is a useful constraint for estimating photosynthesis. To simulate COS leaf flux better in the SiB4 model, we propose a novel temperature function for enzyme carbonic anhydrase (CA) activity and optimize conductances using observations. The optimal activity of CA occurs below 40 °C, and Ball–Woodrow–Berry parameters are slightly changed. These reduce/increase uptakes in the tropics/higher latitudes and contribute to resolving discrepancies in the COS global budget.
Yunyao Ma, Bettina Weber, Alexandra Kratz, José Raggio, Claudia Colesie, Maik Veste, Maaike Y. Bader, and Philipp Porada
Biogeosciences, 20, 2553–2572, https://doi.org/10.5194/bg-20-2553-2023, https://doi.org/10.5194/bg-20-2553-2023, 2023
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We found that the modelled annual carbon balance of biocrusts is strongly affected by both the environment (mostly air temperature and CO2 concentration) and physiology, such as temperature response of respiration. However, the relative impacts of these drivers vary across regions with different climates. Uncertainty in driving factors may lead to unrealistic carbon balance estimates, particularly in temperate climates, and may be explained by seasonal variation of physiology due to acclimation.
Alexander J. Norton, A. Anthony Bloom, Nicholas C. Parazoo, Paul A. Levine, Shuang Ma, Renato K. Braghiere, and T. Luke Smallman
Biogeosciences, 20, 2455–2484, https://doi.org/10.5194/bg-20-2455-2023, https://doi.org/10.5194/bg-20-2455-2023, 2023
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This study explores how the representation of leaf phenology affects our ability to predict changes to the carbon balance of land ecosystems. We calibrate a new leaf phenology model against a diverse range of observations at six forest sites, showing that it improves the predictive capability of the processes underlying the ecosystem carbon balance. We then show how changes in temperature and rainfall affect the ecosystem carbon balance with this new model.
Libo Wang, Vivek K. Arora, Paul Bartlett, Ed Chan, and Salvatore R. Curasi
Biogeosciences, 20, 2265–2282, https://doi.org/10.5194/bg-20-2265-2023, https://doi.org/10.5194/bg-20-2265-2023, 2023
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Plant functional types (PFTs) are groups of plant species used to represent vegetation distribution in land surface models. There are large uncertainties associated with existing methods for mapping land cover datasets to PFTs. This study demonstrates how fine-resolution tree cover fraction and land cover datasets can be used to inform the PFT mapping process and reduce the uncertainties. The proposed largely objective method makes it easier to implement new land cover products in models.
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, 20, 2117–2142, https://doi.org/10.5194/bg-20-2117-2023, https://doi.org/10.5194/bg-20-2117-2023, 2023
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Unprecedented climate extremes (UCEs) are expected to have dramatic impacts on ecosystems. We present a road map of how dynamic vegetation models can explore extreme drought and climate change and 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 explore specific plant responses that reflect knowledge gaps.
Veronika Kronnäs, Klas Lucander, Giuliana Zanchi, Nadja Stadlinger, Salim Belyazid, and Cecilia Akselsson
Biogeosciences, 20, 1879–1899, https://doi.org/10.5194/bg-20-1879-2023, https://doi.org/10.5194/bg-20-1879-2023, 2023
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In a future climate, extreme droughts might become more common. Climate change and droughts can have negative effects on soil weathering and plant health.
In this study, climate change effects on weathering were studied on sites in Sweden using the model ForSAFE, a climate change scenario and an extreme drought scenario. The modelling shows that weathering is higher during summer and increases with global warming but that weathering during drought summers can become as low as winter weathering.
Agustín Sarquis and Carlos A. Sierra
Biogeosciences, 20, 1759–1771, https://doi.org/10.5194/bg-20-1759-2023, https://doi.org/10.5194/bg-20-1759-2023, 2023
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Although plant litter is chemically and physically heterogenous and undergoes multiple transformations, models that represent litter dynamics often ignore this complexity. We used a multi-model inference framework to include information content in litter decomposition datasets and studied the time it takes for litter to decompose as measured by the transit time. In arid lands, the median transit time of litter is about 3 years and has a negative correlation with mean annual temperature.
Qi Guan, Jing Tang, Lian Feng, Stefan Olin, and Guy Schurgers
Biogeosciences, 20, 1635–1648, https://doi.org/10.5194/bg-20-1635-2023, https://doi.org/10.5194/bg-20-1635-2023, 2023
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Understanding terrestrial sources of nitrogen is vital to examine lake eutrophication changes. Combining process-based ecosystem modeling and satellite observations, we found that land-leached nitrogen in the Yangtze Plain significantly increased from 1979 to 2018, and terrestrial nutrient sources were positively correlated with eutrophication trends observed in most lakes, demonstrating the necessity of sustainable nitrogen management to control eutrophication.
Vivek K. Arora, Christian Seiler, Libo Wang, and Sian Kou-Giesbrecht
Biogeosciences, 20, 1313–1355, https://doi.org/10.5194/bg-20-1313-2023, https://doi.org/10.5194/bg-20-1313-2023, 2023
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The behaviour of natural systems is now very often represented through mathematical models. These models represent our understanding of how nature works. Of course, nature does not care about our understanding. Since our understanding is not perfect, evaluating models is challenging, and there are uncertainties. This paper illustrates this uncertainty for land models and argues that evaluating models in light of the uncertainty in various components provides useful information.
Benjamin S. Felzer
Biogeosciences, 20, 573–587, https://doi.org/10.5194/bg-20-573-2023, https://doi.org/10.5194/bg-20-573-2023, 2023
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The future of the terrestrial carbon sink depends upon the legacy of past land use, which determines the stand age of the forest and nutrient levels in the soil, both of which affect vegetation growth. This study uses a modeling approach to determine the effects of land-use legacy in the conterminous US from 1750 to 2099. Not accounting for land legacy results in a low carbon sink and high biomass, while water variables are not as highly affected.
Lin Yu, Silvia Caldararu, Bernhard Ahrens, Thomas Wutzler, Marion Schrumpf, Julian Helfenstein, Chiara Pistocchi, and Sönke Zaehle
Biogeosciences, 20, 57–73, https://doi.org/10.5194/bg-20-57-2023, https://doi.org/10.5194/bg-20-57-2023, 2023
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In this study, we addressed a key weakness in current ecosystem models regarding the phosphorus exchange in the soil and developed a new scheme to describe this process. We showed that the new scheme improved the model performance for plant productivity, soil organic carbon, and soil phosphorus content at five beech forest sites in Germany. We claim that this new model could be used as a better tool to study ecosystems under future climate change, particularly phosphorus-limited systems.
Bimal K. Bhattacharya, Kaniska Mallick, Devansh Desai, Ganapati S. Bhat, Ross Morrison, Jamie R. Clevery, William Woodgate, Jason Beringer, Kerry Cawse-Nicholson, Siyan Ma, Joseph Verfaillie, and Dennis Baldocchi
Biogeosciences, 19, 5521–5551, https://doi.org/10.5194/bg-19-5521-2022, https://doi.org/10.5194/bg-19-5521-2022, 2022
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Evaporation retrieval in heterogeneous ecosystems is challenging due to empirical estimation of ground heat flux and complex parameterizations of conductances. We developed a parameter-sparse coupled ground heat flux-evaporation model and tested it across different limits of water stress and vegetation fraction in the Northern/Southern Hemisphere. The model performed particularly well in the savannas and showed good potential for evaporative stress monitoring from thermal infrared satellites.
Jie Zhang, Wenxin Zhang, Per-Erik Jansson, and Søren O. Petersen
Biogeosciences, 19, 4811–4832, https://doi.org/10.5194/bg-19-4811-2022, https://doi.org/10.5194/bg-19-4811-2022, 2022
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In this study, we relied on a properly controlled laboratory experiment to test the model’s capability of simulating the dominant microbial processes and the emissions of one greenhouse gas (nitrous oxide, N2O) from agricultural soils. This study reveals important processes and parameters that regulate N2O emissions in the investigated model framework and also suggests future steps of model development, which have implications on the broader communities of ecosystem modelers.
Jan De Pue, José Miguel Barrios, Liyang Liu, Philippe Ciais, Alirio Arboleda, Rafiq Hamdi, Manuela Balzarolo, Fabienne Maignan, and Françoise Gellens-Meulenberghs
Biogeosciences, 19, 4361–4386, https://doi.org/10.5194/bg-19-4361-2022, https://doi.org/10.5194/bg-19-4361-2022, 2022
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The functioning of ecosystems involves numerous biophysical processes which interact with each other. Land surface models (LSMs) are used to describe these processes and form an essential component of climate models. In this paper, we evaluate the performance of three LSMs and their interactions with soil moisture and vegetation. Though we found room for improvement in the simulation of soil moisture and drought stress, the main cause of errors was related to the simulated growth of vegetation.
Jarmo Mäkelä, Laura Arppe, Hannu Fritze, Jussi Heinonsalo, Kristiina Karhu, Jari Liski, Markku Oinonen, Petra Straková, and Toni Viskari
Biogeosciences, 19, 4305–4313, https://doi.org/10.5194/bg-19-4305-2022, https://doi.org/10.5194/bg-19-4305-2022, 2022
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Soils account for the largest share of carbon found in terrestrial ecosystems, and accurate depiction of soil carbon decomposition is essential in understanding how permanent these carbon storages are. We present a straightforward way to include carbon isotope concentrations into soil decomposition and carbon storages for the Yasso model, which enables the model to use 13C as a natural tracer to track changes in the underlying soil organic matter decomposition.
Vasileios Myrgiotis, Thomas Luke Smallman, and Mathew Williams
Biogeosciences, 19, 4147–4170, https://doi.org/10.5194/bg-19-4147-2022, https://doi.org/10.5194/bg-19-4147-2022, 2022
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This study shows that livestock grazing and grass cutting can determine whether a grassland is adding (source) or removing (sink) carbon (C) to/from the atmosphere. The annual C balance of 1855 managed grassland fields in Great Britain was quantified for 2017–2018 using process modelling and earth observation data. The examined fields were, on average, small C sinks, but the summer drought of 2018 led to a 9-fold increase in the number of fields that became C sources in 2018 compared to 2017.
J. Robert Logan, Kathe E. Todd-Brown, Kathryn M. Jacobson, Peter J. Jacobson, Roland Vogt, and Sarah E. Evans
Biogeosciences, 19, 4129–4146, https://doi.org/10.5194/bg-19-4129-2022, https://doi.org/10.5194/bg-19-4129-2022, 2022
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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 not in deserts. 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 and/or dew.
Carlos A. Sierra, Verónika Ceballos-Núñez, Henrik Hartmann, David Herrera-Ramírez, and Holger Metzler
Biogeosciences, 19, 3727–3738, https://doi.org/10.5194/bg-19-3727-2022, https://doi.org/10.5194/bg-19-3727-2022, 2022
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Empirical work that estimates the age of respired CO2 from vegetation tissue shows that it may take from years to decades to respire previously produced photosynthates. However, many ecosystem models represent respiration processes in a form that cannot reproduce these observations. In this contribution, we attempt to provide compelling evidence, based on recent research, with the aim to promote a change in the predominant paradigm implemented in ecosystem models.
César Dionisio Jiménez-Rodríguez, Mauro Sulis, and Stanislaus Schymanski
Biogeosciences, 19, 3395–3423, https://doi.org/10.5194/bg-19-3395-2022, https://doi.org/10.5194/bg-19-3395-2022, 2022
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Vegetation relies on soil water reservoirs during dry periods. However, when this source is depleted, the plants may access water stored deeper in the rocks. This rock moisture contribution is usually omitted in large-scale models, which affects modeled plant water use during dry periods. Our study illustrates that including this additional source of water in the Community Land Model improves the model's ability to reproduce observed plant water use at seasonally dry sites.
Marco Carozzi, Raphaël Martin, Katja Klumpp, and Raia Silvia Massad
Biogeosciences, 19, 3021–3050, https://doi.org/10.5194/bg-19-3021-2022, https://doi.org/10.5194/bg-19-3021-2022, 2022
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Crop and grassland production indicates a strong reduction due to the shortening of the length of the growing cycle associated with rising temperatures. Greenhouse gas emissions will increase exponentially over the century, often exceeding the CO2 accumulation of agro-ecosystems. Water demand will double in the next few decades, whereas the benefits in terms of yield will not fill the gap of C losses due to climate perturbation. Climate change will have a regionally distributed effect in the EU.
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
Short summary
Short summary
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.
Cited articles
Allen, R. G., Pereira, L. S., Raes, D., and Smith, M.: Crop
evapotranspiration – Guidelines for computing crop water requirements – FAO
Irrigation and drainage paper, 56, ISBN 92-5-104219-5, 1998.
Bartholomé, E. and Belward, A. S.: GLC2000: a new approach to global
land cover mapping from Earth observation data, Int. J.
Remote Sens., 26, 1959–1977, https://doi.org/10.1080/01431160412331291297, 2005.
Beven, K. J. and Kirkby, M. J.: A physically based, variable contributing
area model of basin hydrology / Un modèle à base physique de zone
d'appel variable de l'hydrologie du bassin versant, Hydrol. Sci.
Bull., 24, 43–69, https://doi.org/10.1080/02626667909491834, 1979.
Blok, D., Heijmans, M. M. P. D., Schaepman-Strub, G., Kononov, A. V.,
Maximov, T. C., and Berendse, F.: Shrub expansion may reduce summer
permafrost thaw in Siberian tundra, Glob. Change Biol., 16, 1296–1305,
https://doi.org/10.1111/j.1365-2486.2009.02110.x, 2010.
Bohn, T. J., Podest, E., Schroeder, R., Pinto, N., McDonald, K. C.,
Glagolev, M., Filippov, I., Maksyutov, S., Heimann, M., Chen, X., and
Lettenmaier, D. P.: Modeling the large-scale effects of surface moisture
heterogeneity on wetland carbon fluxes in the West Siberian Lowland,
Biogeosciences, 10, 6559–6576, https://doi.org/10.5194/bg-10-6559-2013, 2013.
Brooks, R. H.: Hydraulic properties of porous media, Ph.D., Colorado State
University, Ann Arbor, 101 pp., 1965.
Carter, A. J. and Scholes, R. J.: SoilData v2.0: Generating a Global
Database of Soil Properties CSIR Environmentek, Pretoria, South Africa,
2000.
Chaudhary, N., Miller, P. A., and Smith, B.: Modelling past, present and
future peatland carbon accumulation across the pan-Arctic region,
Biogeosciences, 14, 4023–4044, https://doi.org/10.5194/bg-14-4023-2017, 2017.
Chaudhary, N., Westermann, S., Lamba, S., Shurpali, N., Sannel, A. B. K.,
Schurgers, G., Miller, P. A., and Smith, B.: Modelling past and future
peatland carbon dynamics across the pan-Arctic, Glob. Change Biol., 26, 4119–4133, https://doi.org/10.1111/gcb.15099, 2020.
Davidson, N. C.: How much wetland has the world lost? Long-term and recent
trends in global wetland area, Mar. Fresh. Res., 65, 934–941,
https://doi.org/10.1071/MF14173, 2014.
Fan, Y., Li, H., and Miguez-Macho, G.: Global Patterns of Groundwater Table Depth, Science, 339, 940–943, 2013.
FAO/UNESCO: Soil Map of the World, Food and Agriculture Organization of the
United Nations, Paris, ISBN: 92-3-101125-1, 1974.
Finger Higgens, R. A., Chipman, J. W., Lutz, D. A., Culler, L. E., Virginia,
R. A., and Ogden, L. A.: Changing Lake Dynamics Indicate a Drier Arctic in
Western Greenland, J. Geophys. Res.-Biogeo., 124,
870–883, https://doi.org/10.1029/2018JG004879, 2019.
Finlayson, C. M. and Milton, G. R.: Peatlands, in: The Wetland Book: II:
Distribution, Description, and Conservation, edited by: Finlayson, C. M.,
Milton, G. R., Prentice, R. C., and Davidson, N. C., Springer Netherlands,
Dordrecht, 227–244, https://doi.org/10.1007/978-94-007-4001-3_202, 2018.
Franchini, M. and Pacciani, M.: Comparative analysis of several conceptual
rainfall-runoff models, J. Hydrol., 122, 161–219,
https://doi.org/10.1016/0022-1694(91)90178-K, 1991.
Friedl, M. A., McIver, D. K., Hodges, J. C. F., Zhang, X. Y., Muchoney, D.,
Strahler, A. H., Woodcock, C. E., Gopal, S., Schneider, A., Cooper, A.,
Baccini, A., Gao, F., and Schaaf, C.: Global land cover mapping from MODIS:
algorithms and early results, Remote Sens. Environ., 83, 287–302,
https://doi.org/10.1016/S0034-4257(02)00078-0, 2002.
Gallego-Sala, A. V., Charman, D. J., Brewer, S., Page, S. E., Prentice, I.
C., Friedlingstein, P., Moreton, S., Amesbury, M. J., Beilman, D. W.,
Björck, S., Blyakharchuk, T., Bochicchio, C., Booth, R. K., Bunbury, J.,
Camill, P., Carless, D., Chimner, R. A., Clifford, M., Cressey, E.,
Courtney-Mustaphi, C., De Vleeschouwer, F., de Jong, R., Fialkiewicz-Koziel,
B., Finkelstein, S. A., Garneau, M., Githumbi, E., Hribjlan, J., Holmquist,
J., Hughes, P. D. M., Jones, C., Jones, M. C., Karofeld, E., Klein, E. S.,
Kokfelt, U., Korhola, A., Lacourse, T., Le Roux, G., Lamentowicz, M., Large,
D., Lavoie, M., Loisel, J., Mackay, H., MacDonald, G. M., Makila, M.,
Magnan, G., Marchant, R., Marcisz, K., Martínez Cortizas, A., Massa,
C., Mathijssen, P., Mauquoy, D., Mighall, T., Mitchell, F. J. G., Moss, P.,
Nichols, J., Oksanen, P. O., Orme, L., Packalen, M. S., Robinson, S.,
Roland, T. P., Sanderson, N. K., Sannel, A. B. K., Silva-Sánchez, N.,
Steinberg, N., Swindles, G. T., Turner, T. E., Uglow, J., Väliranta, M.,
van Bellen, S., van der Linden, M., van Geel, B., Wang, G., Yu, Z.,
Zaragoza-Castells, J., and Zhao, Y.: Latitudinal limits to the predicted
increase of the peatland carbon sink with warming, Nat. Clim. Change, 8,
907–913, https://doi.org/10.1038/s41558-018-0271-1, 2018.
Gandois, L., Hoyt, A. M., Hatté, C., Jeanneau, L., Teisserenc, R.,
Liotaud, M., and Tananaev, N.: Contribution of Peatland Permafrost to
Dissolved Organic Matter along a Thaw Gradient in North Siberia,
Environ. Sci. Technol., 53, 14165–14174, https://doi.org/10.1021/acs.est.9b03735, 2019.
Gasser, T., Kechiar, M., Ciais, P., Burke, E. J., Kleinen, T., Zhu, D.,
Huang, Y., Ekici, A., and Obersteiner, M.: Path-dependent reductions in CO2
emission budgets caused by permafrost carbon release, Nat. Geosci., 11,
830–835, https://doi.org/10.1038/s41561-018-0227-0, 2018.
GISTEMP-Team: GISS Surface Temperature Analysis (GISTEMP), version 4, NASA
Goddard Institute for Space Studies [dataset], https://data.giss.nasa.gov/gistemp/
(last access date: 1 November 2023), 2021.
Hamman, J. J., Nijssen, B., Bohn, T. J., Gergel, D. R., and Mao, Y.: The
Variable Infiltration Capacity model version 5 (VIC-5): infrastructure
improvements for new applications and reproducibility, Geosci. Model Dev.,
11, 3481–3496, https://doi.org/10.5194/gmd-11-3481-2018, 2018.
Hanson, P. J., Griffiths, N. A., Iversen, C. M., Norby, R. J., Sebestyen, S.
D., Phillips, J. R., Chanton, J. P., Kolka, R. K., Malhotra, A., Oleheiser,
K. C., Warren, J. M., Shi, X., Yang, X., Mao, J., and Ricciuto, D. M.: Rapid
Net Carbon Loss From a Whole-Ecosystem Warmed Peatland, AGU Advances, 1,
e2020AV000163, https://doi.org/10.1029/2020AV000163, 2020.
Harris, I., Jones, P. D., Osborn, T. J., and Lister, D. H.: Updated
high-resolution grids of monthly climatic observations – the CRU TS3.10
Dataset, Int. J. Climatol., 34, 623–642,
https://doi.org/10.1002/joc.3711, 2014.
He, F.: Simulating transient climate evolution of the last deglaciation with
CCSM3, Atmospheric and Oceanic Sciences, University of Wisconsin-Madison,
Madison, 2011.
Helbig, M., Chasmer, L. E., Desai, A. R., Kljun, N., Quinton, W. L., and
Sonnentag, O.: Direct and indirect climate change effects on carbon dioxide
fluxes in a thawing boreal forest–wetland landscape, Glob. Change Biol.,
23, 3231–3248, https://doi.org/10.1111/gcb.13638, 2017.
Hu, S., Niu, Z., Chen, Y., Li, L., and Zhang, H.: Global wetlands: Potential
distribution, wetland loss, and status, Sci. Total Environ.,
586, 319–327, https://doi.org/10.1016/j.scitotenv.2017.02.001,
2017.
Huang, Y., Ciais, P., Luo, Y., Zhu, D., Wang, Y., Qiu, C., Goll, D. S.,
Guenet, B., Makowski, D., De Graaf, I., Leifeld, J., Kwon, M. J., Hu, J.,
and Qu, L.: Tradeoff of CO2 and CH4 emissions from global peatlands under
water-table drawdown, Nat. Clim. Change, 11, 618–622, https://doi.org/10.1038/s41558-021-01059-w, 2021.
Hugelius, G., Bockheim, J. G., Camill, P., Elberling, B., Grosse, G.,
Harden, J. W., Johnson, K., Jorgenson, T., Koven, C. D., Kuhry, P.,
Michaelson, G., Mishra, U., Palmtag, J., Ping, C. L., O'Donnell, J.,
Schirrmeister, L., Schuur, E. A. G., Sheng, Y., Smith, L. C., Strauss, J.,
and Yu, Z.: A new data set for estimating organic carbon storage to 3 m
depth in soils of the northern circumpolar permafrost region, Earth Syst.
Sci. Data, 5, 393–402, https://doi.org/10.5194/essd-5-393-2013, 2013.
Hugelius, G., Loisel, J., Chadburn, S., Jackson, R. B., Jones, M.,
MacDonald, G., Marushchak, M., Olefeldt, D., Packalen, M., Siewert, M. B.,
Treat, C., Turetsky, M., Voigt, C., and Yu, Z.: Large stocks of peatland
carbon and nitrogen are vulnerable to permafrost thaw, P.
Natl. Acad. Sci. USA, 117, 20438, https://doi.org/10.1073/pnas.1916387117, 2020.
Iversen, C. M., Latimer, J., Brice, D. J., Childs, J., Vander Stel, H. M.,
Defrenne, C. E., Graham, J., Griffiths, N. A., Malhotra, A., Norby, R. J.,
Oleheiser, K. C., Phillips, J. R., Salmon, V. G., Sebestyen, S. D., Yang,
X., and Hanson, P. J.: Whole-Ecosystem Warming Increases Plant-Available
Nitrogen and Phosphorus in an Ombrotrophic Bog, Ecosystems, https://doi.org/10.1007/s10021-022-00744-x, 2022.
Kåresdotter, E., Destouni, G., Ghajarnia, N., Hugelius, G., and
Kalantari, Z.: Mapping the Vulnerability of Arctic Wetlands to Global
Warming, Earth's Future, 9, e2020EF001858, https://doi.org/10.1029/2020EF001858, 2021.
Kleinen, T., Mikolajewicz, U., and Brovkin, V.: Terrestrial methane
emissions from the Last Glacial Maximum to the preindustrial period, Clim.
Past, 16, 575–595, https://doi.org/10.5194/cp-16-575-2020, 2020.
Lawrence, D. M., Slater, A. G., and Swenson, S. C.: Simulation of
Present-Day and Future Permafrost and Seasonally Frozen Ground Conditions in
CCSM4, J. Clim., 25, 2207–2225, https://doi.org/10.1175/JCLI-D-11-00334.1, 2012.
Lehner, B. and Döll, P.: Development and validation of a global database
of lakes, reservoirs and wetlands, J. Hydrol., 296, 1–22,
https://doi.org/10.1016/j.jhydrol.2004.03.028, 2004.
Li, X., Bellerby, R., Craft, C., and Widney, S. E.: Coastal wetland loss,
consequences, and challenges for restoration, Anthropocene Coasts, 1, 1–15, https://doi.org/10.1139/anc-2017-0001, 2018.
Liang, X., Lettenmaier, D. P., Wood, E. F., and Burges, S. J.: A simple
hydrologically based model of land surface water and energy fluxes for
general circulation models, J. Geophys. Res.-Atmos.,
99, 14415–14428, https://doi.org/10.1029/94JD00483, 1994.
Liu, C., Sun, G., McNulty, S. G., Noormets, A., and Fang, Y.: Environmental
controls on seasonal ecosystem evapotranspiration/potential
evapotranspiration ratio as determined by the global eddy flux measurements,
Hydrol. Earth Syst. Sci., 21, 311–322, https://doi.org/10.5194/hess-21-311-2017, 2017.
Loisel, J., Yu, Z., Beilman, D. W., Camill, P., Alm, J., Amesbury, M. J.,
Anderson, D., Andersson, S., Bochicchio, C., Barber, K., Belyea, L. R.,
Bunbury, J., Chambers, F. M., Charman, D. J., De Vleeschouwer, F., Fiałkiewicz-Kozieł, B., Finkelstein, S. A., Gałka, M., Garneau, M.,
Hammarlund, D., Hinchcliffe, W., Holmquist, J., Hughes, P., Jones, M. C.,
Klein, E. S., Kokfelt, U., Korhola, A., Kuhry, P., Lamarre, A., Lamentowicz,
M., Large, D., Lavoie, M., MacDonald, G., Magnan, G., Mäkilä, M.,
Mallon, G., Mathijssen, P., Mauquoy, D., McCarroll, J., Moore, T. R.,
Nichols, J., O'Reilly, B., Oksanen, P., Packalen, M., Peteet, D., Richard,
P. J. H., Robinson, S., Ronkainen, T., Rundgren, M., Sannel, A. B. K.,
Tarnocai, C., Thom, T., Tuittila, E.-S., Turetsky, M., Väliranta, M.,
van der Linden, M., van Geel, B., van Bellen, S., Vitt, D., Zhao, Y., and
Zhou, W.: A database and synthesis of northern peatland soil properties and
Holocene carbon and nitrogen accumulation, The Holocene, 24, 1028–1042, https://doi.org/10.1177/0959683614538073, 2014.
Loisel, J., Gallego-Sala, A. V., Amesbury, M. J., Magnan, G., Anshari, G.,
Beilman, D. W., Benavides, J. C., Blewett, J., Camill, P., Charman, D. J.,
Chawchai, S., Hedgpeth, A., Kleinen, T., Korhola, A., Large, D., Mansilla,
C. A., Müller, J., van Bellen, S., West, J. B., Yu, Z., Bubier, J. L.,
Garneau, M., Moore, T., Sannel, A. B. K., Page, S., Väliranta, M.,
Bechtold, M., Brovkin, V., Cole, L. E. S., Chanton, J. P., Christensen, T.
R., Davies, M. A., De Vleeschouwer, F., Finkelstein, S. A., Frolking, S.,
Gałka, M., Gandois, L., Girkin, N., Harris, L. I., Heinemeyer, A., Hoyt,
A. M., Jones, M. C., Joos, F., Juutinen, S., Kaiser, K., Lacourse, T.,
Lamentowicz, M., Larmola, T., Leifeld, J., Lohila, A., Milner, A. M.,
Minkkinen, K., Moss, P., Naafs, B. D. A., Nichols, J., O'Donnell, J., Payne,
R., Philben, M., Piilo, S., Quillet, A., Ratnayake, A. S., Roland, T. P.,
Sjögersten, S., Sonnentag, O., Swindles, G. T., Swinnen, W., Talbot, J.,
Treat, C., Valach, A. C., and Wu, J.: Expert assessment of future
vulnerability of the global peatland carbon sink, Nat. Clim. Change, 11,
70–77, https://doi.org/10.1038/s41558-020-00944-0, 2021.
Loveland, T. R., Reed, B. C., Brown, J. F., Ohlen, D. O., Zhu, Z., Yang, L.,
and Merchant, J. W.: Development of a global land cover characteristics
database and IGBP DISCover from 1 km AVHRR data, Int. J.
Remote Sens., 21, 1303–1330, https://doi.org/10.1080/014311600210191, 2000.
Lu, X. and Zhuang, Q.: Modeling methane emissions from the Alaskan Yukon
River basin, 1986–2005, by coupling a large-scale hydrological model and a
process-based methane model, J. Geophys. Res.-Biogeo., 117, https://doi.org/10.1029/2011JG001843,
2012.
MacDougall, A. H. and Knutti, R.: Projecting the release of carbon from
permafrost soils using a perturbed parameter ensemble modelling approach,
Biogeosciences, 13, 2123–2136, https://doi.org/10.5194/bg-13-2123-2016, 2016.
Mäkiranta, P., Laiho, R., Mehtätalo, L., Straková, P., Sormunen,
J., Minkkinen, K., Penttilä, T., Fritze, H., and Tuittila, E.: Responses
of phenology and biomass production of boreal fens to climate warming under
different water-table level regimes, Glob. Change Biol., 24, 944–956, https://doi.org/10.1111/gcb.13934, 2018.
Marthews, T. R., Dadson, S. J., Lehner, B., Abele, S., and Gedney, N.:
High-resolution global topographic index values for use in large-scale
hydrological modelling, Hydrol. Earth Syst. Sci., 19, 91–104, https://doi.org/10.5194/hess-19-91-2015, 2015.
McGuire, A. D., Lawrence, D. M., Koven, C., Clein, J. S., Burke, E., Chen,
G., Jafarov, E., MacDougall, A. H., Marchenko, S., Nicolsky, D., Peng, S.,
Rinke, A., Ciais, P., Gouttevin, I., Hayes, D. J., Ji, D., Krinner, G.,
Moore, J. C., Romanovsky, V., Schädel, C., Schaefer, K., Schuur, E. A.
G., and Zhuang, Q.: Dependence of the evolution of carbon dynamics in the
northern permafrost region on the trajectory of climate change, P. Natl. Acad. Sci. USA, 115, 3882, https://doi.org/10.1073/pnas.1719903115,
2018.
Meinshausen, M., Smith, S. J., Calvin, K., Daniel, J. S., Kainuma, M. L. T.,
Lamarque, J. F., Matsumoto, K., Montzka, S. A., Raper, S. C. B., Riahi, K.,
Thomson, A., Velders, G. J. M., and van Vuuren, D. P. P.: The RCP greenhouse
gas concentrations and their extensions from 1765 to 2300, Climatic Change,
109, 213, https://doi.org/10.1007/s10584-011-0156-z, 2011.
Melton, J. R., Chan, E., Millard, K., Fortier, M., Winton, R. S., Martín-López, J. M., Cadillo-Quiroz, H., Kidd, D., and Verchot, L. V.: A map of global peatland extent created using machine learning (Peat-ML), Geosci. Model Dev., 15, 4709–4738, https://doi.org/10.5194/gmd-15-4709-2022, 2022.
Miao, C., Duan, Q., Sun, Q., Huang, Y., Kong, D., Yang, T., Ye, A., Di, Z.,
and Gong, W.: Assessment of CMIP5 climate models and projected temperature
changes over Northern Eurasia, Environ. Res. Lett., 9, 055007, https://doi.org/10.1088/1748-9326/9/5/055007, 2014.
Müller, J. and Joos, F.: Committed and projected future changes in
global peatlands – continued transient model simulations since the Last
Glacial Maximum, Biogeosciences, 18, 3657–3687, https://doi.org/10.5194/bg-18-3657-2021,
2021.
Nichols, J. E. and Peteet, D. M.: Rapid expansion of northern peatlands and
doubled estimate of carbon storage, Nat. Geosci., 12, 917–921, https://doi.org/10.1038/s41561-019-0454-z, 2019.
Niu, Z., Zhang, H., Wang, X., Yao, W., Zhou, D., Zhao, K., Zhao, H., Li, N.,
Huang, H., Li, C., Yang, J., Liu, C., Liu, S., Wang, L., Li, Z., Yang, Z.,
Qiao, F., Zheng, Y., Chen, Y., Sheng, Y., Gao, X., Zhu, W., Wang, W., Wang,
H., Weng, Y., Zhuang, D., Liu, J., Luo, Z., Cheng, X., Guo, Z., and Gong,
P.: Mapping wetland changes in China between 1978 and 2008, Chinese Sci.
Bull., 57, 2813–2823, https://doi.org/10.1007/s11434-012-5093-3, 2012.
Obu, J., Westermann, S., Barboux, C., Bartsch, A., Delaloye, R., Grosse, G.,
Heim, B., Hugelius, G., Irrgang, A., Kääb, A. M., Kroisleitner, C.,
Matthes, H., Nitze, I., Pellet, C., Seifert, F. M., Strozzi, T.,
Wegmüller, U., Wieczorek, M., and Wiesmann, A.: ESA Permafrost Climate
Change Initiative (Permafrost_cci): Permafrost Climate
Research Data Package v1., Centre for Environmental Data Analysis [dataset],
https://catalogue.ceda.ac.uk/uuid/1f88068e86304b0fbd34456115b6606f (last access: 1 November 2023), 2020.
Olefeldt, D., Hovemyr, M., Kuhn, M. A., Bastviken, D., Bohn, T. J.,
Connolly, J., Crill, P., Euskirchen, E. S., Finkelstein, S. A., Genet, H.,
Grosse, G., Harris, L. I., Heffernan, L., Helbig, M., Hugelius, G.,
Hutchins, R., Juutinen, S., Lara, M. J., Malhotra, A., Manies, K., McGuire,
A. D., Natali, S. M., O'Donnell, J. A., Parmentier, F. J. W.,
Räsänen, A., Schädel, C., Sonnentag, O., Strack, M., Tank, S.
E., Treat, C., Varner, R. K., Virtanen, T., Warren, R. K., and Watts, J. D.:
The Boreal–Arctic Wetland and Lake Dataset (BAWLD), Earth Syst. Sci. Data,
13, 5127–5149, https://doi.org/10.5194/essd-13-5127-2021, 2021.
Palmer, M. D., Harris, G. R., and Gregory, J. M.: Extending CMIP5
projections of global mean temperature change and sea level rise due to
thermal expansion using a physically-based emulator, Environ. Res.
Lett., 13, 084003, https://doi.org/10.1088/1748-9326/aad2e4, 2018.
Piao, S., Ciais, P., Friedlingstein, P., Peylin, P., Reichstein, M.,
Luyssaert, S., Margolis, H., Fang, J., Barr, A., Chen, A., Grelle, A.,
Hollinger, D. Y., Laurila, T., Lindroth, A., Richardson, A. D., and Vesala,
T.: Net carbon dioxide losses of northern ecosystems in response to autumn
warming, Nature, 451, 49–52, https://doi.org/10.1038/nature06444, 2008.
Qiu, C., Zhu, D., Ciais, P., Guenet, B., and Peng, S.: The role of northern
peatlands in the global carbon cycle for the 21st century, Glob. Ecol. Biogeogr., 29, 956–973, https://doi.org/10.1111/geb.13081, 2020.
Qiu, C., Zhu, D., Ciais, P., Guenet, B., Peng, S., Krinner, G., Tootchi, A.,
Ducharne, A., and Hastie, A.: Modelling northern peatland area and carbon
dynamics since the Holocene with the ORCHIDEE-PEAT land surface model (SVN
r5488), Geosci. Model Dev., 12, 2961–2982, https://doi.org/10.5194/gmd-12-2961-2019, 2019.
Qiu, C., Ciais, P., Zhu, D., Guenet, B., Chang, J., Chaudhary, N., Kleinen,
T., Li, X., Müller, J., Xi, Y., Zhang, W., Ballantyne, A., Brewer, S.
C., Brovkin, V., Charman, D. J., Gustafson, A., Gallego-Sala, A. V., Gasser,
T., Holden, J., Joos, F., Kwon, M. J., Lauerwald, R., Miller, P. A., Peng,
S., Page, S., Smith, B., Stocker, B. D., Sannel, A. B. K., Salmon, E.,
Schurgers, G., Shurpali, N. J., Wårlind, D., and Westermann, S.: A
strong mitigation scenario maintains climate neutrality of northern
peatlands, One Earth, 5, 86–97, https://doi.org/10.1016/j.oneear.2021.12.008, 2022.
Rawls, W. J., Ahuja, L. R., Brakensiek, D. L., and Shirmohammadi, A.:
Infiltration and soil water movement, McGraw-Hill Inc., New York,
5.1–5.51, ISBN: 9780070397323, 1992.
Richardson, A. D., Hufkens, K., Milliman, T., Aubrecht, D. M., Furze, M. E.,
Seyednasrollah, B., Krassovski, M. B., Latimer, J. M., Nettles, W. R.,
Heiderman, R. R., Warren, J. M., and Hanson, P. J.: Ecosystem warming
extends vegetation activity but heightens vulnerability to cold
temperatures, Nature, 560, 368–371, https://doi.org/10.1038/s41586-018-0399-1,
2018.
Schaperow, J. and Li, D.: VICGlobal: soil and vegetation parameters for
the Variable Infiltration Capacity hydrological model (1.6d), Zenodo [dataset],
https://doi.org/10.5281/zenodo.5038653, 2021.
Schneider von Deimling, T., Grosse, G., Strauss, J., Schirrmeister, L.,
Morgenstern, A., Schaphoff, S., Meinshausen, M., and Boike, J.:
Observation-based modelling of permafrost carbon fluxes with accounting for
deep carbon deposits and thermokarst activity, Biogeosciences, 12,
3469–3488, https://doi.org/10.5194/bg-12-3469-2015, 2015.
Schuur, E. A. G., McGuire, A. D., Schädel, C., Grosse, G., Harden, J.
W., Hayes, D. J., Hugelius, G., Koven, C. D., Kuhry, P., Lawrence, D. M.,
Natali, S. M., Olefeldt, D., Romanovsky, V. E., Schaefer, K., Turetsky, M.
R., Treat, C. C., and Vonk, J. E.: Climate change and the permafrost carbon
feedback, Nature, 520, 171–179, https://doi.org/10.1038/nature14338, 2015.
Sheffield, J., Barrett, A., Colle, B., Fernando, D., Fu, R., Geil, K., Hu,
Q., Kinter, J., Kumar, S., Langenbrunner, B., Lombardo, K., Long, L.,
Maloney, E., Mariotti, A., Meyerson, J., Mo, K., Neelin, J., Nigam, S., Pan,
Z., and Yin, L.: North American Climate in CMIP5 Experiments, Part I:
Evaluation of Historical Simulations of Continental and Regional
Climatology*, J. Clim., 26, 9209–9245, https://doi.org/10.1175/JCLI-D-12-00592.1,
2013.
Smith, S. L., O'Neill, H. B., Isaksen, K., Noetzli, J., and Romanovsky, V.
E.: The changing thermal state of permafrost, Nat. Rev. Earth
Environ., 3, 10–23, https://doi.org/10.1038/s43017-021-00240-1, 2022.
Spahni, R., Joos, F., Stocker, B. D., Steinacher, M., and Yu, Z. C.:
Transient simulations of the carbon and nitrogen dynamics in northern
peatlands: from the Last Glacial Maximum to the 21st century, Clim. Past, 9,
1287–1308, https://doi.org/10.5194/cp-9-1287-2013, 2013.
Stocker, B. D., Spahni, R., and Joos, F.: DYPTOP: a cost-efficient TOPMODEL
implementation to simulate sub-grid spatio-temporal dynamics of global
wetlands and peatlands, Geosci. Model Dev., 7, 3089–3110, https://doi.org/10.5194/gmd-7-3089-2014, 2014.
Tang, R., He, B., Chen, H. W., Chen, D., Chen, Y., Fu, Y. H., Yuan, W., Li,
B., Li, Z., Guo, L., Hao, X., Sun, L., Liu, H., Sun, C., and Yang, Y.:
Increasing terrestrial ecosystem carbon release in response to autumn
cooling and warming, Nat. Clim. Change, 12, 380–385, https://doi.org/10.1038/s41558-022-01304-w, 2022.
Tape, K. E. N., Sturm, M., and Racine, C.: The evidence for shrub expansion
in Northern Alaska and the Pan-Arctic, Glob. Change Biol., 12, 686–702,
https://doi.org/10.1111/j.1365-2486.2006.01128.x, 2006.
Treat, C. C., Jones, M. C., Brosius, L., Grosse, G., Walter Anthony, K., and
Frolking, S.: The role of wetland expansion and successional processes in
methane emissions from northern wetlands during the Holocene, Quaternary
Sci. Rev., 257, 106864, https://doi.org/10.1016/j.quascirev.2021.106864, 2021.
Turunen, J., Tomppo, E., Tolonen, K., and Reinikainen, A.: Estimating carbon
accumulation rates of undrained mires in Finland–application to boreal and
subarctic regions, The Holocene, 12, 69–80, https://doi.org/10.1191/0959683602hl522rp, 2002.
Wood, E. F., Lettenmaier, D. P., and Zartarian, V. G.: A land-surface
hydrology parameterization with subgrid variability for general circulation
models, J. Geophys. Res.-Atmos., 97, 2717–2728,
https://doi.org/10.1029/91JD01786, 1992.
Xu, J., Morris, P. J., Liu, J., and Holden, J.: PEATMAP: Refining estimates
of global peatland distribution based on a meta-analysis, CATENA, 160,
134–140, https://doi.org/10.1016/j.catena.2017.09.010, 2018.
Yi, Y. and Kimball, J. S.: ABoVE: Active Layer Thickness from Remote Sensing
Permafrost Model, Alaska, 2001–2015, https://doi.org/10.3334/ORNLDAAC/1760, 2020.
Yokohata, T., Saito, K., Ito, A., Ohno, H., Tanaka, K., Hajima, T., and
Iwahana, G.: Future projection of greenhouse gas emissions due to permafrost
degradation using a simple numerical scheme with a global land surface
model, Prog. Earth Pl. Sci., 7, 56, https://doi.org/10.1186/s40645-020-00366-8, 2020.
Yu, Z., Beilman, D., and Jones, M.: Sensitivity of Northern Peatland Carbon
Dynamics to Holocene Climate Change, Washington DC American Geophysical
Union Geophysical Monograph Series, 184, 55–69, https://doi.org/10.1029/2008GM000822, 2009.
Zhao, B. and Zhuang, Q.: Peatlands and their carbon dynamics in northern high latitudes from 1990 to 2300: A process-based biogeochemistry model analysis, Purdue University Research Repository (data set), https://doi.org/10.4231/QP7V-V527, 2022.
Zhao, B., Zhuang, Q., Treat, C., and Frolking, S.: A Model Intercomparison
Analysis for Controls on C Accumulation in North American Peatlands, J. Geophys. Res.-Biogeo., 127, e2021JG006762, https://doi.org/10.1029/2021JG006762, 2022a.
Zhao, B., Zhuang, Q., and Frolking, S.: Modeling Carbon Accumulation and
Permafrost Dynamics of Northern Peatlands Since the Holocene, J.
Geophys. Res.-Biogeo., 127, e2022JG007009,
https://doi.org/10.1029/2022JG007009, 2022b.
Zhao, R. J., Liu, X. R., and Singh, V. P.: The Xinanjiang model, edited by: Singh, V. P., Water Resources Publications, Colorado,
ISBN: 9780918334916,
1995.
Zhuang, Q., McGuire, A. D., O'Neill, K. P., Harden, J. W., Romanovsky, V.
E., and Yarie, J.: Modeling soil thermal and carbon dynamics of a fire
chronosequence in interior Alaska, J. Geophys. Res.-Atmos., 107, FFR 3-1–FFR 3-26, https://doi.org/10.1029/2001JD001244, 2002.
Zhuang, Q., Melillo, J. M., Kicklighter, D. W., Prinn, R. G., McGuire, A.
D., Steudler, P. A., Felzer, B. S., and Hu, S.: Methane fluxes between
terrestrial ecosystems and the atmosphere at northern high latitudes during
the past century: A retrospective analysis with a process-based
biogeochemistry model, Global Biogeochem. Cy., 18, GB3010, https://doi.org/10.1029/2004GB002239, 2004.
Zomer, R. J., Xu, J., and Trabucco, A.: Version 3 of the Global Aridity Index
and Potential Evapotranspiration Database, Sci. Data, 9, 409,
https://doi.org/10.1038/s41597-022-01493-1, 2022.
Short summary
In this study, we use a process-based model to simulate the northern peatland's C dynamics in response to future climate change during 1990–2300. Northern peatlands are projected to be a C source under all climate scenarios except for the mildest one before 2100 and C sources under all scenarios afterwards.
We find northern peatlands are a C sink until pan-Arctic annual temperature reaches −2.09 to −2.89 °C. This study emphasizes the vulnerability of northern peatlands to climate change.
In this study, we use a process-based model to simulate the northern peatland's C dynamics in...
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