Articles | Volume 14, issue 7
https://doi.org/10.5194/bg-14-2003-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/bg-14-2003-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
12 Apr 2017
Research article |
| 12 Apr 2017
Modelling the demand for new nitrogen fixation by terrestrial ecosystems
Xu-Ri
CORRESPONDING AUTHOR
Key Laboratory of Alpine Ecology and Biodiversity, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
CAS Center for Excellence in Tibetan Plateau Earth Sciences, Beijing 100101, China
I. Colin Prentice
AXA Chair of Biosphere and Climate Impacts, Department of Life Sciences, Imperial College London, Silwood Park Campus, Buckhurst Road, Ascot SL5 7PY, UK
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Y. W. Liu, Xu-Ri, Y. S. Wang, Y. P. Pan, and S. L. Piao
Atmos. Chem. Phys., 15, 11683–11700, https://doi.org/10.5194/acp-15-11683-2015, https://doi.org/10.5194/acp-15-11683-2015, 2015
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We investigated inorganic N wet deposition at five sites in the Tibetan Plateau (TP). Combining in situ measurements in this and previous studies, the average wet deposition of NH4+-N, NO3--N, and inorganic N in the TP was estimated to be 1.06, 0.51, and 1.58 kg N ha−1 yr−1, respectively. Results suggest that earlier estimations based on chemical transport model simulations and/or limited field measurements likely overestimated substantially the regional inorganic N wet deposition in the TP.
Sam S. Rabin, Joe R. Melton, Gitta Lasslop, Dominique Bachelet, Matthew Forrest, Stijn Hantson, Jed O. Kaplan, Fang Li, Stéphane Mangeon, Daniel S. Ward, Chao Yue, Vivek K. Arora, Thomas Hickler, Silvia Kloster, Wolfgang Knorr, Lars Nieradzik, Allan Spessa, Gerd A. Folberth, Tim Sheehan, Apostolos Voulgarakis, Douglas I. Kelley, I. Colin Prentice, Stephen Sitch, Sandy Harrison, and Almut Arneth
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Global vegetation models are important tools for understanding how the Earth system will change in the future, and fire is a critical process to include. A number of different methods have been developed to represent vegetation burning. This paper describes the protocol for the first systematic comparison of global fire models, which will allow the community to explore various drivers and evaluate what mechanisms are important for improving performance. It also includes equations for all models.
Y. W. Liu, Xu-Ri, Y. S. Wang, Y. P. Pan, and S. L. Piao
Atmos. Chem. Phys., 15, 11683–11700, https://doi.org/10.5194/acp-15-11683-2015, https://doi.org/10.5194/acp-15-11683-2015, 2015
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We investigated inorganic N wet deposition at five sites in the Tibetan Plateau (TP). Combining in situ measurements in this and previous studies, the average wet deposition of NH4+-N, NO3--N, and inorganic N in the TP was estimated to be 1.06, 0.51, and 1.58 kg N ha−1 yr−1, respectively. Results suggest that earlier estimations based on chemical transport model simulations and/or limited field measurements likely overestimated substantially the regional inorganic N wet deposition in the TP.
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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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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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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.
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.
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Short summary
We estimated the global demand for new N fixation (NNF) by terrestrial ecosystem using a DyN-LPJ model. Modelled NPP and C : N ratios of litter and soil organic matter were consistent with independent estimates. Modelled NNF was sensitive to the fraction of litter carbon respired to CO2 during decomposition and plant-type-specific C : N ratios of litter and soil. The modelled annual NNF increased 15% due to increasing CO2, while the future capacity of N sources to support this is unknown.
We estimated the global demand for new N fixation (NNF) by terrestrial ecosystem using a DyN-LPJ...
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