Articles | Volume 16, issue 2
https://doi.org/10.5194/bg-16-207-2019
© Author(s) 2019. 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-16-207-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
21 Jan 2019
Research article |
| 21 Jan 2019
| 21 Jan 2019
Quantifying global N2O emissions from natural ecosystem soils using trait-based biogeochemistry models
Tong Yu
Earth, Atmospheric, and Planetary Sciences, Purdue University, West Lafayette, IN 47907, USA
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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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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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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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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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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This study investigates present-day carbon cycle variables in CMIP5 and CMIP6 simulations. Overall, CMIP6 models perform better but also show many remaining biases. A significant improvement in the simulation of photosynthesis in models with a nitrogen cycle is found, with only small differences between emission- and concentration-based simulations. Thus, we recommend using emission-driven simulations in CMIP7 by default and including the nitrogen cycle in all future carbon cycle models.
Sven Armin Westermann, Anke Hildebrandt, Souhail Bousetta, and Stephan Thober
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Plants at the land surface mediate between soil and the atmosphere regarding water and carbon transport. Since plant growth is a dynamic process, models need to consider these dynamics. Two models that predict water and carbon fluxes by considering plant temporal evolution were tested against observational data. Currently, dynamizing plants in these models did not enhance their representativeness, which is caused by a mismatch between implemented physical relations and observable connections.
Kamal Nyaupane, Umakant Mishra, Feng Tao, Kyongmin Yeo, William J. Riley, Forrest M. Hoffman, and Sagar Gautam
Biogeosciences, 21, 5173–5183, https://doi.org/10.5194/bg-21-5173-2024, https://doi.org/10.5194/bg-21-5173-2024, 2024
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Representing soil organic carbon (SOC) dynamics in Earth system models (ESMs) is a key source of uncertainty in predicting carbon–climate feedbacks. Using machine learning, we develop and compare predictive relationships in observations (Obs) and ESMs. We find different relationships between environmental factors and SOC stocks in Obs and ESMs. SOC prediction in ESMs may be improved by representing the functional relationships of environmental controllers in a way consistent with observations.
Jacob A. Nelson, Sophia Walther, Fabian Gans, Basil Kraft, Ulrich Weber, Kimberly Novick, Nina Buchmann, Mirco Migliavacca, Georg Wohlfahrt, Ladislav Šigut, Andreas Ibrom, Dario Papale, Mathias Göckede, Gregory Duveiller, Alexander Knohl, Lukas Hörtnagl, Russell L. Scott, Weijie Zhang, Zayd Mahmoud Hamdi, Markus Reichstein, Sergio Aranda-Barranco, Jonas Ardö, Maarten Op de Beeck, Dave Billesbach, David Bowling, Rosvel Bracho, Christian Brümmer, Gustau Camps-Valls, Shiping Chen, Jamie Rose Cleverly, Ankur Desai, Gang Dong, Tarek S. El-Madany, Eugenie Susanne Euskirchen, Iris Feigenwinter, Marta Galvagno, Giacomo A. Gerosa, Bert Gielen, Ignacio Goded, Sarah Goslee, Christopher Michael Gough, Bernard Heinesch, Kazuhito Ichii, Marcin Antoni Jackowicz-Korczynski, Anne Klosterhalfen, Sara Knox, Hideki Kobayashi, Kukka-Maaria Kohonen, Mika Korkiakoski, Ivan Mammarella, Mana Gharun, Riccardo Marzuoli, Roser Matamala, Stefan Metzger, Leonardo Montagnani, Giacomo Nicolini, Thomas O'Halloran, Jean-Marc Ourcival, Matthias Peichl, Elise Pendall, Borja Ruiz Reverter, Marilyn Roland, Simone Sabbatini, Torsten Sachs, Marius Schmidt, Christopher R. Schwalm, Ankit Shekhar, Richard Silberstein, Maria Lucia Silveira, Donatella Spano, Torbern Tagesson, Gianluca Tramontana, Carlo Trotta, Fabio Turco, Timo Vesala, Caroline Vincke, Domenico Vitale, Enrique R. Vivoni, Yi Wang, William Woodgate, Enrico A. Yepez, Junhui Zhang, Donatella Zona, and Martin Jung
Biogeosciences, 21, 5079–5115, https://doi.org/10.5194/bg-21-5079-2024, https://doi.org/10.5194/bg-21-5079-2024, 2024
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The movement of water, carbon, and energy from the Earth's surface to the atmosphere, or flux, is an important process to understand because it impacts our lives. Here, we outline a method called FLUXCOM-X to estimate global water and CO2 fluxes based on direct measurements from sites around the world. We go on to demonstrate how these new estimates of net CO2 uptake/loss, gross CO2 uptake, total water evaporation, and transpiration from plants compare to previous and independent estimates.
Xin Chen, Tiexi Chen, Xiaodong Li, Yuanfang Chai, Shengjie Zhou, Renjie Guo, and Jie Dai
Biogeosciences, 21, 4285–4300, https://doi.org/10.5194/bg-21-4285-2024, https://doi.org/10.5194/bg-21-4285-2024, 2024
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We provide an ensemble-model-based GPP dataset (ERF_GPP) that explains 85.1 % of the monthly variation in GPP across 170 sites, which is higher than other GPP estimate models. In addition, ERF_GPP improves the phenomenon of “high-value underestimation and low-value overestimation” in GPP estimation to some extent. Overall, ERF_GPP provides a more reliable estimate of global GPP and will facilitate further development of carbon cycle research.
Reza Kusuma Nurrohman, Tomomichi Kato, Hideki Ninomiya, Lea Végh, Nicolas Delbart, Tatsuya Miyauchi, Hisashi Sato, Tomohiro Shiraishi, and Ryuichi Hirata
Biogeosciences, 21, 4195–4227, https://doi.org/10.5194/bg-21-4195-2024, https://doi.org/10.5194/bg-21-4195-2024, 2024
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SPITFIRE (SPread and InTensity of FIRE) was integrated into a spatially explicit individual-based dynamic global vegetation model to improve the accuracy of depicting Siberian forest fire frequency, intensity, and extent. Fires showed increased greenhouse gas and aerosol emissions in 2006–2100 for Representative Concentration Pathways. This study contributes to understanding fire dynamics, land ecosystem–climate interactions, and global material cycles under the threat of escalating fires.
Stefano Manzoni and M. Francesca Cotrufo
Biogeosciences, 21, 4077–4098, https://doi.org/10.5194/bg-21-4077-2024, https://doi.org/10.5194/bg-21-4077-2024, 2024
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Organic carbon and nitrogen are stabilized in soils via microbial assimilation and stabilization of necromass (in vivo pathway) or via adsorption of the products of extracellular decomposition (ex vivo pathway). Here we use a diagnostic model to quantify which stabilization pathway is prevalent using data on residue-derived carbon and nitrogen incorporation in mineral-associated organic matter. We find that the in vivo pathway is dominant in fine-textured soils with low organic matter content.
Huajie Zhu, Xiuli Xing, Mousong Wu, Weimin Ju, and Fei Jiang
Biogeosciences, 21, 3735–3760, https://doi.org/10.5194/bg-21-3735-2024, https://doi.org/10.5194/bg-21-3735-2024, 2024
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Ecosystem carbonyl sulfide (COS) fluxes were employed to optimize GPP estimation across ecosystems with the Biosphere-atmosphere Exchange Process Simulator (BEPS), which was developed for simulating the canopy COS uptake under its state-of-the-art two-leaf modeling framework. Our results showcased the efficacy of COS in improving model prediction and reducing prediction uncertainty of GPP and enhanced insights into the sensitivity, identifiability, and interactions of parameters related to COS.
Moritz Laub, Magdalena Necpalova, Marijn Van de Broek, Marc Corbeels, Samuel Mathu Ndungu, Monicah Wanjiku Mucheru-Muna, Daniel Mugendi, Rebecca Yegon, Wycliffe Waswa, Bernard Vanlauwe, and Johan Six
Biogeosciences, 21, 3691–3716, https://doi.org/10.5194/bg-21-3691-2024, https://doi.org/10.5194/bg-21-3691-2024, 2024
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We used the DayCent model to assess the potential impact of integrated soil fertility management (ISFM) on maize production, soil fertility, and greenhouse gas emission in Kenya. After adjustments, DayCent represented measured mean yields and soil carbon stock changes well and N2O emissions acceptably. Our results showed that soil fertility losses could be reduced but not completely eliminated with ISFM and that, while N2O emissions increased with ISFM, emissions per kilogram yield decreased.
Hazel Cathcart, Julian Aherne, Michael D. Moran, Verica Savic-Jovcic, Paul A. Makar, and Amanda Cole
EGUsphere, https://doi.org/10.5194/egusphere-2024-2371, https://doi.org/10.5194/egusphere-2024-2371, 2024
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Deposition from sulfur and nitrogen pollution can harm ecosystems, and recovery from this type of pollution can take decades or longer. To identify risk to Canadian soils, we created maps showing sensitivity to sulfur and nitrogen pollution. Results show that some ecosystems are at risk from acid and nutrient nitrogen deposition; 10 % of protected areas are receiving acid deposition beyond their damage threshold and 70 % may be receiving nitrogen deposition that could cause biodiversity loss.
Matthew Forrest, Jessica Hetzer, Maik Billing, Simon P. K. Bowring, Eric Kosczor, Luke Oberhagemann, Oliver Perkins, Dan Warren, Fátima Arrogante-Funes, Kirsten Thonicke, and Thomas Hickler
EGUsphere, https://doi.org/10.5194/egusphere-2024-1973, https://doi.org/10.5194/egusphere-2024-1973, 2024
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Climate change is causing an increase in extreme wildfires in Europe but drivers of fire are not well understood, especially across different land cover types. We used statistical models with satellite data, climate data and socioeconomic data to determine what affects burning in cropland and non-cropland area Europe. We found different drivers of burning in cropland burning vs non-cropland, to the point that some variable, e.g. population density, had completely the opposite effects.
Erik Schwarz, Samia Ghersheen, Salim Belyazid, and Stefano Manzoni
Biogeosciences, 21, 3441–3461, https://doi.org/10.5194/bg-21-3441-2024, https://doi.org/10.5194/bg-21-3441-2024, 2024
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The occurrence of unstable equilibrium points (EPs) could impede the applicability of microbial-explicit soil organic carbon models. For archetypal model versions we identify 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.
Sian Kou-Giesbrecht, Vivek K. Arora, Christian Seiler, and Libo Wang
Biogeosciences, 21, 3339–3371, https://doi.org/10.5194/bg-21-3339-2024, https://doi.org/10.5194/bg-21-3339-2024, 2024
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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.
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
Biogeosciences, 21, 3321–3338, https://doi.org/10.5194/bg-21-3321-2024, https://doi.org/10.5194/bg-21-3321-2024, 2024
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Understanding the link between climate and carbon fluxes is crucial for predicting how climate change will impact carbon sinks. We estimated carbon dioxide (CO2) fluxes from deadwood in tropical Australia using 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.
Daniel Nadal-Sala, Rüdiger Grote, David Kraus, Uri Hochberg, Tamir Klein, Yael Wagner, Fedor Tatarinov, Dan Yakir, and Nadine K. Ruehr
Biogeosciences, 21, 2973–2994, https://doi.org/10.5194/bg-21-2973-2024, https://doi.org/10.5194/bg-21-2973-2024, 2024
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A hydraulic model approach is presented that can be added to any physiologically based ecosystem model. Simulated plant water potential triggers stomatal closure, photosynthesis decline, root–soil resistance increases, and sapwood and foliage senescence. The model has been evaluated at an extremely dry site stocked with Aleppo pine and was able to represent gas exchange, soil water content, and plant water potential. The model also responded realistically regarding leaf senescence.
Patrick Neri, Lianhong Gu, and Yang Song
Biogeosciences, 21, 2731–2758, https://doi.org/10.5194/bg-21-2731-2024, https://doi.org/10.5194/bg-21-2731-2024, 2024
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A first-of-its-kind global-scale model of temperature resilience and tolerance of photosystem II maximum quantum yield informs how plants maintain their efficiency of converting light energy to chemical energy for photosynthesis under temperature changes. Our finding explores this variation across plant functional types and habitat climatology, highlighting diverse temperature response strategies and a method to improve global-scale photosynthesis modeling under climate change.
Liyuan He, Jorge L. Mazza Rodrigues, Melanie A. Mayes, Chun-Ta Lai, David A. Lipson, and Xiaofeng Xu
Biogeosciences, 21, 2313–2333, https://doi.org/10.5194/bg-21-2313-2024, https://doi.org/10.5194/bg-21-2313-2024, 2024
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Soil microbes are the driving engine for biogeochemical cycles of carbon and nutrients. This study applies a microbial-explicit model to quantify bacteria and fungal biomass carbon in soils from 1901 to 2016. Results showed substantial increases in bacterial and fungal biomass carbon over the past century, jointly influenced by vegetation growth and soil temperature and moisture. This pioneering century-long estimation offers crucial insights into soil microbial roles in global carbon cycling.
Tao Chen, Félicien Meunier, Marc Peaucelle, Guoping Tang, Ye Yuan, and Hans Verbeeck
Biogeosciences, 21, 2253–2272, https://doi.org/10.5194/bg-21-2253-2024, https://doi.org/10.5194/bg-21-2253-2024, 2024
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Chinese subtropical forest ecosystems are an extremely important component of global forest ecosystems and hence crucial for the global carbon cycle and regional climate change. However, there is still great uncertainty in the relationship between subtropical forest carbon sequestration and its drivers. We provide first quantitative estimates of the individual and interactive effects of different drivers on the gross primary productivity changes of various subtropical forest types in China.
Pritha Pande, Sam Bland, Nathan Booth, Jo Cook, Zhaozhong Feng, and Lisa Emberson
EGUsphere, https://doi.org/10.5194/egusphere-2024-694, https://doi.org/10.5194/egusphere-2024-694, 2024
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The DO3SE-crop model extends the DO3SE to simulate ozone's impact on crops with modules for ozone uptake, damage, and crop growth from JULES-Crop. It's versatile, suits China's varied agriculture, and improves yield predictions under ozone stress. It is essential for policy, water management, and climate response, it integrates into Earth System Models for a comprehensive understanding of agriculture's interaction with global systems.
Ke Liu, Yujie Wang, Troy S. Magney, and Christian Frankenberg
Biogeosciences, 21, 1501–1516, https://doi.org/10.5194/bg-21-1501-2024, https://doi.org/10.5194/bg-21-1501-2024, 2024
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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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Due to their crucial role in terrestrial ecosystems, we implemented mycorrhizal fungi into the QUINCY terrestrial biosphere model. Fungi interact with mineral and organic soil to support plant N uptake and, thus, plant growth. Our results suggest that the effect of mycorrhizal interactions on simulated ecosystem dynamics is minor under constant environmental conditions but necessary to reproduce and understand observed patterns under changing conditions, such as rising atmospheric CO2.
Jinyun Tang and William J. Riley
Biogeosciences, 21, 1061–1070, https://doi.org/10.5194/bg-21-1061-2024, https://doi.org/10.5194/bg-21-1061-2024, 2024
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A chemical kinetics theory is proposed to explain the non-monotonic relationship between temperature and biochemical rates. It incorporates the observed thermally reversible enzyme denaturation that is ensured by the ceaseless thermal motion of molecules and ions in an enzyme solution and three well-established theories: (1) law of mass action, (2) diffusion-limited chemical reaction theory, and (3) transition state theory.
Nina Raoult, Louis-Axel Edouard-Rambaut, Nicolas Vuichard, Vladislav Bastrikov, Anne Sofie Lansø, Bertrand Guenet, and Philippe Peylin
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.
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.
Vilna Tyystjärvi, Tiina Markkanen, Leif Backman, Maarit Raivonen, Antti Leppänen, Xuefei Li, Paavo Ojanen, Kari Minkkinen, Roosa Hautala, Mikko Peltoniemi, Jani Anttila, Raija Laiho, Annalea Lohila, Raisa Mäkipää, and Tuula Aalto
EGUsphere, https://doi.org/10.5194/egusphere-2023-3037, https://doi.org/10.5194/egusphere-2023-3037, 2024
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Drainage of boreal peatlands strongly influences soil methane fluxes with important implications to their climatic impacts. Here we simulate methane fluxes in forestry-drained and restored peatlands during the 21st century. We found that restoration turned peatlands to a source of methane but the magnitude varied regionally. In forests, changes in water table level influenced methane fluxes and in general, the sink was weaker under rotational forestry compared to continuous cover forestry.
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.
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.
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.
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.
Cited articles
Anderson, B., Bartlett, K., Frolking, S., Hayhoe, K., Jenkins, J., and Salas,
W.: Methane and Nitrous Oxide Emissions from Natural Sources, Office of
Atmospheric Programs, US EPA, EPA 430-R-10-001, Washington DC, 2010.
Bassirirad, H.: Kinetics of nutrient uptake by roots: responses to
global change, New Phytol., 147, 155–169, 2000.
Batjes, N. H.: Global data set of derived soil properties,
0.5-degree grid
(ISRIC-WISE), ORNL DAAC, 2000.
Bianconi, E., Piovesan, A., Facchin, F., Beraudi, A., Casadei,
R., Frabetti, F., and Perez-Amodio, S.: An estimation of
the number of cells in the
human body, Ann. Hum. Biol., 40, 463–471, 2013.
Biederbeck, V. O. and Campbell, C. A.: Soil microbial activity as
influenced by temperature trends and fluctuations, Can. J. Soil Sci., 53,
363–376, 1973.
Bouskill, N., Tang, J., Riley, W. J., and Brodie, E. L.: Trait-based
representation of biological nitrification: model development, testing, and
predicted community composition, Front. Microbiol., 3, 364, 2012.
Bouwman, A. F., Fung, I., Matthews, E., and John, J.: Global analysis of the
potential for N2O production in natural soils, Global. Biogeochem. Cy.,
7, 557–597, 1993.
Brochier-Armanet, C., Boussau, B., Gribaldo, S., and Forterre, P.:
Mesophilic
Crenarchaeota: proposal for a third archaeal phylum,
the Thaumarchaeota. Nat.
Rev. Microbiol., 6, 245–252, 2008.
Cabello, P., Roldan, M. D., and Moreno-Vivian, C.: Nitrate reduction and the
nitrogen cycle in archaea, Microbiology, 150, 3527–3546, 2004.
Castro, H. F., Classen, A. T., Austin, E. E., Norby, R. J., and Schadt, C.
W.: Soil microbial community responses to multiple experimental climate
change drivers, Appl. Environ. Microb., 76, 999–1007, 2010.
Ciais, P., Sabine, C., Bala, G., Bopp, L., Brovkin, V., Canadell, J., and
Jones, C.: Carbon and other biogeochemical cycles, in: Climate change
2013: the physical science basis, Contribution of Working Group I to the
Fifth Assessment Report of the Intergovernmental Panel on Climate Change,
465–570, Cambridge University Press, 2014.
Cosentino, V. R. N., Brutti, L. N., Civeira, G., and Taboada, M. Á.:
Contribution of biological nitrogen fixation to N2O emission from soil under
soybean, Ciencia del Suelo, 33, 313–321, 2015.
Davidson, E. A. and Kanter, D.: Inventories and scenarios of nitrous oxide
emissions, Environ. Res. Lett., 9, 105012, 2014.
Droop, M. R.: Some thoughts on nutrient limitation in algae 1, J.
Phycol., 9, 264–272, 1973.
Erguder, T. H., Boon, N., Wittebolle, L., Marzorati, M., and Verstraete, W.:
Environmental factors shaping the ecological niches of ammonia-oxidizing
archaea, FEMS Microbiol. Rev., 33, 855–869, 2009.
Estes, L. D., Bradley, B. A., Beukes, H., Hole, D. G., Lau, M., Oppenheimer,
M. G., and Turner, W. R.: Comparing mechanistic and empirical model
projections of crop suitability and productivity: implications for
ecological forecasting, Global Ecol. Biogeogr., 22, 1007–1018, 2013.
Falkowski, P. G., Fenchel, T., and Delong, E. F.: The
microbial engines that
drive Earth's biogeochemical cycles, Science, 320,
1034–1039, 2008.
Farrell, M., Prendergast-Miller, M., Jones, D. L., Hill, P. W., and Condron,
L. M.: Soil microbial organic nitrogen uptake is regulated by carbon
availability, Soil Biol. Biochem., 77, 261–267, 2014.
Flynn, B., Graham, A., Scott, N., Layzell, D. B., and Dong, Z.: Nitrogen
fixation, hydrogen production and N2O emissions, Can. J. Plant Sci., 94,
1037–1041, 2014.
Francis, C. A., Roberts, K. J., Beman, J. M., Santoro, A. E., and Oakley, B.
B.: Ubiquity and diversity of ammonia-oxidizing archaea in water columns and
sediments of the ocean, P. Natl. Acad Sci. USA, 102, 14683–14688, 2005.
Francis, C. A., Beman, J. M., and Kuypers, M. M.: New processes
and players
in the nitrogen cycle: the microbial ecology of anaerobic and
archaeal ammonia oxidation, The ISME J., 1, 19–27, 2007.
Guo, L. and Vanrolleghem, P. A.: Calibration and validation of an activated
sludge model for greenhouse gases no. 1 (ASMG1): prediction of
temperature-dependent N2O emission dynamics,Bioproc. Biosyst.
Eng., 37, 151–163, 2014.
Holmes, W. E., Zak, D. R., Pregitzer, K. S., and King, J. S.: Elevated
CO2 and O3 alter soil nitrogen transformations beneath trembling aspen, paper
birch, and sugar maple, Ecosystems, 9, 1354–1363, 2006.
Huang, Y. and Gerber, S.: Global soil nitrous oxide emissions in a dynamic
carbon-nitrogen model, Biogeosciences, 12,
6405–6427, https://doi.org/10.5194/bg-12-6405-2015, 2015.
Janssen, P. H. M., Heuberger, P. S. C., and Sanders, R.: UNCSAM: a tool for
automating sensitivity and uncertainty analysis, Environ. Softw., 9,
1–11, 1994.
Kandeler, E., Deiglmayr, K., Tscherko, D., Bru, D., and Philippot, L.:
Abundance of narG, nirS, nirK, and nosZ genes of denitrifying bacteria during
primary successions of a glacier foreland, Appl. Environ. Microb., 72,
5957–5962, 2006.
Klemedtsson, L., Svensson, B. H., and Rosswall, T.: Relationships between
soil moisture content and nitrous oxide production during nitrification and
denitrification, Biol. Fert. Soils, 6, 106–111, 1988.
Koper, T. E., Stark, J. M., Habteselassie, M. Y., and Norton, J. M.:
Nitrification exhibits Haldane kinetics in an agricultural soil treated with
ammonium sulfate or dairy-waste compost, FEMS Microbiol. Ecol., 74,
316–322, 2010.
Kowalchuk, G. A. and Stephen, J. R.: Ammonia-oxidizing bacteria: a model
for molecular microbial ecology, Annu. Rev Microbiol., 55, 485–529, 2001.
Kreileman, G. J. J. and Bouwman, A. F.: Computing land use emissions of
greenhouse gases, Water Air. Soil Pollut., 76, 231–258, 1994.
Kroeze, C., Mosier, A., and Bouwman, L.: Closing the global N2O budget: a
retrospective analysis 1500–1994, Global Biogeochem. Cy., 13, 1–8, 1999.
Leininger, S., Urich, T., Schloter, M., Schwark, L., Qi, J., Nicol, G. W.,
and Schleper, C.: Archaea predominate among ammonia-oxidizing prokaryotes in
soils, Nature, 442, 806–809, 2006.
Li, C., Frolking, S., and Frolking, T. A.: A model of nitrous oxide
evolution from soil driven by rainfall events: 1. Model structure and
sensitivity, J. Geophys. Res.-Atmos., 97, 9759–9776, 1992.
Li, C. S.: Modeling trace gas emissions from agricultural ecosystems,
in: Methane Emissions from Major Rice Ecosystems in Asia, 259–276,
Springer, Dordrecht, 2000.
Liu, Y.: Modeling the emissions of nitrous oxide (N2O) and methane (CH4)
from the terrestrial biosphere to the atmosphere, Doctoral dissertation,
Massachusetts Institute of Technology, 1996.
Mäkelä, A., Landsberg, J., Ek, A. R., Burk, T. E., Ter-Mikaelian,
M., Ågren, G. I., and Puttonen, P.: Process-based models for forest
ecosystem management: current state of the art and challenges for practical
implementation, Tree Physiol., 20, 289–298, 2000.
McGuire, A. D., Melillo, J. M., Joyce, L. A., Kicklighter, D. W., Grace, A. L.,
Moore III, B., and Vorosmarty, C. J.: Interactions between carbon and
nitrogen dynamics in estimating net primary productivity for potential
vegetation in North America, Global Biogeochem. Cy., 6, 101–124,
https://doi.org/10.1029/92GB00219, 1992.
McGuire, A. D., Sitch, S., Clein, J. S., Dargaville, R., Esser, G., Foley,
J., and Meier, R. A.: Carbon balance of the terrestrial biosphere in the
twentieth century: Analyses of CO2, climate and land use effects with four
process-ecosystem models, Global Biogeochem. Cy., 15, 183–206,
2001.
Melillo, J. M., McGuire, A. D., Kicklighter, D. W., Moore III, B.,
Vorosmarty, C. J., and Schloss, A. L.: Global climate change and terrestrial
net primary production, Nature, 363, 234–240, https://doi.org/10.1038/363234a0, 1993.
Mosier, A., Kroeze, C., Nevison, C., Oenema, O., Seitzinger, S., and Van
Cleemput, O.: Closing the global N2O budget: nitrous oxide emissions
through the agricultural nitrogen cycle, Nutr. Cycl. Agroecosys., 52,
225–248, 1998.
Neira, J., Ortiz, M., Morales, L., and Acevedo, E.: Oxygen diffusion in
soils: Understanding the factors and processes needed for modeling, Chil. J
Agr. Res., 75, 35–44, 2015.
Olivier, J. G. J., Bouwman, A. F., Van der Hoek, K. W., and Berdowski, J. J.
M.: Global air emission inventories for anthropogenic sources of NOx,
NH3 and N2O in 1990, in: Nitrogen, the Confer-Ns, 135–148, 1998.
Painter, H. A.: A review of literature on inorganic nitrogen metabolism in
microorganisms, Water Res., 4, 393–450, 1970.
Pietikäinen, J., Pettersson, M., and Bååth, E.: Comparison of
temperature effects on soil respiration and bacterial and fungal growth
rates, FEMS Microbiol. Ecol., 52, 49–58, 2005.
Potter, C. S., Matson, P. A., Vitousek, P. M., and Davidson, E. A.: Process
modeling of controls on nitrogen trace gas emissions from soils
worldwide, J. Geophys. Res.-Atmos., 101, 1361–1377, 1996.
Prentice, I. C., Spahni, R., and Niu, H. S.: Modelling terrestrial nitrous
oxide emissions and implications for climate feedback, New Phytol., 196,
472–488, 2012.
Priemé, A., Braker, G., and Tiedje, J. M.: Diversity of nitrite
reductase (nirK and nirS) gene fragments in forested upland and wetland soils,
Appl. Environ. Microb., 68, 1893–1900, 2002.
Prinn, R., Cunnold, D., Rasmussen, R., Simmonds, P., Alyea, F., Crawford, A.,
and Rosen, R.: Atmospheric emissions and trends of nitrous oxide deduced
from 10 years of ALE-GAGE data, J. Geophys. Res.-Atmos., 95, 18369–18385, 1990.
Prosser, J. I. and Nicol, G. W.: Relative contributions of archaea and
bacteria to aerobic ammonia oxidation in the environment, Environ.
Microbiol., 10, 2931–2941, 2008.
Prosser, J. I.: Soil nitrifiers and nitrification, in: Nitrification,
347–383, American Society of Microbiology, 2011.
Qin, Z., Zhuang, Q., and Zhu, X.: Carbon and nitrogen dynamics in bioenergy
ecosystems: 1. Model development, validation and sensitivity analysis, GCB
bioenergy, 6, 740–755, 2014.
Rochette, P. and Janzen, H. H.: Towards a revised coefficient for
estimating N2O emissions from legumes, Nutr. Cycl. Agroecosys., 73,
171–179, 2005.
Saikawa, E., Schlosser, C. A., and Prinn, R. G.: Global modeling of
soil nitrous oxide emissions from natural processes, Global Biogeochem. Cy.,
27, 972–989, 2013.
Schindlbacher, A., Zechmeister-Boltenstern, S., and Butterbach-Bahl, K.:
Effects of soil moisture and temperature on NO, NO2, and N2O emissions from
European forest soils, J. Geophys. Res.-Atmos., 109, D17302, https://doi.org/10.1029/2004JD004590, 2004.
Shah, A.: Determination of Biological Nitrogen Fixation Induced N2O
Emission from Arable Soil by Using a Closed Chamber Technique, Appl.
Environ. Soil Sci., 685168, https://doi.org/10.1155/2014/685168, 2014.
Shoun, H., Fushinobu, S., Jiang, L., Kim, S. W., and Wakagi, T.: Fungal
denitrification and nitric oxide reductase cytochrome P450nor, Phil. Trans.
R. Soc. B, 367, 1186–1194, 2012.
Stanford, G., Dzienia, S., and Vander Pol, R. A.: Effect of
Temperature on Denitrification Rate in Soils 1, Soil Sci.
Soc. Am. J., 39, 867–870, 1975.
Stark, J. M. and Firestone, M. K.: Mechanisms for soil moisture effects on
activity of nitrifying bacteria, Appl. Environ. Microb., 61, 218–221,
1995.
Stehfest, E. and Bouwman, L.: N2O and NO emission from
agricultural fields
and soils under natural vegetation: summarizing available measurement
data and modeling of global annual emissions, Nutr. Cycl. Agroecosys,
74, 207–228, 2006.
Tian, H., Chen, G., Lu, C., Xu, X., Ren, W., Zhang, B., and Zhang, C.:
Global methane and nitrous oxide emissions from terrestrial ecosystems due
to multiple environmental changes, Ecosyst. Health Sustain., 1, 1–20,
2015.
Tian, H., Yang, J., Lu, C., et al.: The
global N2O Model Intercomparison Project, B. Am.
Meteorol. Soc.,99, 1231–1251, 2018.
Tong, Y.: Quantifying the global N2O emissions from natural
ecosystems using a mechanistically-based biogeochemistry model, MS thesis,
available at: http://docs.lib.purdue.edu/dissertations/AAI10145857/ (last
access: January 2019), 2016.
Torregrosa-Crespo, J., Martínez-Espinosa, R. M., Esclapez, J.,
Bautista, V., Pire, C., Camacho, M., and Bonete, M. J.: Anaerobic
metabolism in Haloferax genus: Denitrification as case of study, in: Advances
in microbial physiology, Vol. 68, 41–85, Academic Press, 2016.
Treusch, A. H., Leininger, S., Kletzin, A., Schuster, S. C., Klenk, H. P.,
and Schleper, C.: Novel genes for nitrite reductase and Amo-related
proteins indicate a role of uncultivated mesophilic crenarchaeota in
nitrogen cycling, Environ. Microbiol., 7, 1985–1995, 2005.
Venter, J. C., Remington, K., Heidelberg, J. F., Halpern, A. L., Rusch, D.,
Eisen, J. A., and Fouts, D. E.: Environmental genome shotgun sequencing of
the Sargasso Sea, Science, 304, 66–74, 2004.
Vet, R., Artz, R. S., Carou, S., Shaw, M., Ro, C. U., Aas, W., and Hou,
A.: A global assessment of precipitation chemistry and deposition of sulfur,
nitrogen, sea salt, base cations, organic acids, acidity and pH, and
phosphorus, Atmos. Environ., 93, 3–100, 2014.
Whitehead, D. C.: Grassland nitrogen, CAB international, Wallingford,
UK, ISBN: 0851989152, 1995.
Winogradsky, S.: Recherches sur les organisms de la
nitrification, Ann. Inst.
Pasteur, 4, 213–231, 1890.
Xu, X., Tian, H., and Hui, D.: Convergence in the relationship of CO2 and
N2O exchanges between soil and atmosphere within terrestrial ecosystems,
Global Change Biol., 14, 1651–1660, 2008.
Xu, X., Thornton, P. E., and Potapov, P.: A Compilation of Global Soil
Microbial Biomass Carbon, Nitrogen, and Phosphorus Data, ORNL DAAC, 2015.
Xu, X., Thornton, P. E., and Post, W. M.: A Compilation of Global
Soil Microbial Biomass Carbon, Nitrogen, and Phosphorus Data,
Data set from Oak Ridge National Laboratory Distributed Active
Archive Center, Oak Ridge, Tennessee, USA,
available at: http://daac.ornl.gov (last access: May, 2017), 2014.
Zhao, S., Li, K., Zhou, W., Qiu, S., Huang, S., and He, P.: Changes in soil
microbial community, enzyme activities and organic matter fractions under
long-term straw return in north-central China, Agr. Ecosyst. Environ., 216,
82–88, 2016.
Zhong, Z., Lemke, R. L., and Nelson, L. M.: Nitrous oxide emissions
associated with nitrogen fixation by grain legumes, Soil Biol. Biochem.,
41, 2283–2291, 2009.
Zhu, Q., Riley, W. J., and Tang, J.: A new theory of plant–microbe nutrient
competition resolves inconsistencies between observations and model
predictions, Ecol. Appl., 27, 875–886, 2017.
Zhu, S. and Chen, S.: The impact of temperature on nitrification rate in
fixed film biofilters, Aquacult. Eng., 26, 221–237, 2002.
Zhuang, Q., McGuire, A. D., Melillo, J. M., Clein, J. S., Dargaville, R. J.,
Kicklighter, D. W., and Hobbie, J. E.: Carbon cycling in extratropical
terrestrial ecosystems of the Northern Hemisphere during the 20th century: a
modeling analysis of the influences of soil thermal dynamics, Tellus, 55,
751–776, 2003.
Zhuang, Q., McGuire, A. D., Melillo, J. M., Clein, J. S., Dargaville, R. J.,
Kicklighter, D. W., and Hobbie, J. E.: Carbon cycling in extratropical
terrestrial ecosystems of the Northern Hemisphere during the 20th century: a
modeling analysis of the influences of soil thermal dynamics, Tellus B, 55, 751–776, 2011.
Zhuang, Q., Lu, Y., and Chen, M.: An inventory of global N2O emissions from
the soils of natural terrestrial ecosystems, Atmos. Environ., 47, 66–75,
2012.
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