Articles | Volume 17, issue 13
https://doi.org/10.5194/bg-17-3643-2020
© Author(s) 2020. 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-17-3643-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
13 Jul 2020
Research article |
| 13 Jul 2020
| 13 Jul 2020
Modeling biological nitrogen fixation in global natural terrestrial ecosystems
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
Related authors
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
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Revised manuscript under review for ESSD
Short summary
Short summary
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
Preprint archived
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Bailu Zhao and Qianlai Zhuang
Biogeosciences, 20, 251–270, https://doi.org/10.5194/bg-20-251-2023, https://doi.org/10.5194/bg-20-251-2023, 2023
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Related subject area
Biogeochemistry: Modelling, Terrestrial
Understanding and simulating cropland and non-cropland burning in Europe using the BASE (Burnt Area Simulator for Europe) model
Representation of the terrestrial carbon cycle in CMIP6
Does dynamically modeled leaf area improve predictions of land surface water and carbon fluxes? Insights into dynamic vegetation modules
Observational benchmarks inform representation of soil organic carbon dynamics in land surface models
X-BASE: the first terrestrial carbon and water flux products from an extended data-driven scaling framework, FLUXCOM-X
A 2001–2022 global gross primary productivity dataset using an ensemble model based on the random forest method
Future projections of Siberian wildfire and aerosol emissions
Mechanisms of soil organic carbon and nitrogen stabilization in mineral-associated organic matter – insights from modeling in phase space
Optimizing the terrestrial ecosystem gross primary productivity using carbonyl sulfide (COS) within a two-leaf modeling framework
Modeling integrated soil fertility management for maize production in Kenya using a Bayesian calibration of the DayCent model
Estimates of critical loads and exceedances of acidity and nutrient nitrogen for mineral soils in Canada for 2014–2016 average annual sulphur and nitrogen atmospheric deposition
When and why microbial-explicit soil organic carbon models can be unstable
The impacts of modelling prescribed vs. dynamic land cover in a high-CO2 future scenario – greening of the Arctic and Amazonian dieback
Climate-based prediction of carbon fluxes from deadwood in Australia
Integration of tree hydraulic processes and functional impairment to capture the drought resilience of a semiarid pine forest
The effect of temperature on photosystem II efficiency across plant functional types and climate
Modeling microbial carbon fluxes and stocks in global soils from 1901 to 2016
Elevated atmospheric CO2 concentration and vegetation structural changes contributed to gross primary productivity increase more than climate and forest cover changes in subtropical forests of China
Developing the DO3SE-crop model for Xiaoji, China
Non-steady-state stomatal conductance modeling and its implications: from leaf to ecosystem
Modelled forest ecosystem carbon–nitrogen dynamics with integrated mycorrhizal processes under elevated CO2
A chemical kinetics theory for interpreting the non-monotonic temperature dependence of enzymatic reactions
Using Free Air CO2 Enrichment data to constrain land surface model projections of the terrestrial carbon cycle
Multiscale assessment of North American terrestrial carbon balance
Simulating net ecosystem exchange under seasonal snow cover at an Arctic tundra site
Spatial biases reduce the ability of Earth system models to simulate soil heterotrophic respiration fluxes
Tropical dry forest response to nutrient fertilization: a model validation and sensitivity analysis
Connecting competitor, stress-tolerator and ruderal (CSR) theory and Lund Potsdam Jena managed Land 5 (LPJmL 5) to assess the role of environmental conditions, management and functional diversity for grassland ecosystem functions
A global fuel characteristic model and dataset for wildfire prediction
Can models adequately reflect how long-term nitrogen enrichment alters the forest soil carbon cycle?
Temporal variability of observed and simulated gross primary productivity, modulated by vegetation state and hydrometeorological drivers
Empirical upscaling of OzFlux eddy covariance for high-resolution monitoring of terrestrial carbon uptake in Australia
A modeling approach to investigate drivers, variability and uncertainties in O2 fluxes and O2 : CO2 exchange ratios in a temperate forest
Modeling coupled nitrification–denitrification in soil with an organic hotspot
A new method for estimating carbon dioxide emissions from drained peatland forest soils for the greenhouse gas inventory of Finland
Enabling a process-oriented hydro-biogeochemical model to simulate soil erosion and nutrient losses
Potassium limitation of forest productivity – Part 1: A mechanistic model simulating the effects of potassium availability on canopy carbon and water fluxes in tropical eucalypt stands
Potassium limitation of forest productivity – Part 2: CASTANEA-MAESPA-K shows a reduction in photosynthesis rather than a stoichiometric limitation of tissue formation
Global evaluation of terrestrial biogeochemistry in the Energy Exascale Earth System Model (E3SM) and the role of the phosphorus cycle in the historical terrestrial carbon balance
Assessing carbon storage capacity and saturation across six central US grasslands using data–model integration
Optimizing the carbonic anhydrase temperature response and stomatal conductance of carbonyl sulfide leaf uptake in the Simple Biosphere model (SiB4)
Exploring environmental and physiological drivers of the annual carbon budget of biocrusts from various climatic zones with a mechanistic data-driven model
Improved process representation of leaf phenology significantly shifts climate sensitivity of ecosystem carbon balance
Mapping of ESA's Climate Change Initiative land cover data to plant functional types for use in the CLASSIC land model
Exploring the impacts of unprecedented climate extremes on forest ecosystems: hypotheses to guide modeling and experimental studies
Effect of droughts and climate change on future soil weathering rates in Sweden
Information content in time series of litter decomposition studies and the transit time of litter in arid lands
Long-term changes of nitrogen leaching and the contributions of terrestrial nutrient sources to lake eutrophication dynamics on the Yangtze Plain of China
Towards an ensemble-based evaluation of land surface models in light of uncertain forcings and observations
Effect of land-use legacy on the future carbon sink for the conterminous US
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
Biogeosciences, 21, 5539–5560, https://doi.org/10.5194/bg-21-5539-2024, https://doi.org/10.5194/bg-21-5539-2024, 2024
Short summary
Short summary
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 areas of Europe. We found different drivers of burning in cropland burning vs. non-cropland to the point that some variables, e.g. population density, had the complete opposite effects.
Bettina K. Gier, Manuel Schlund, Pierre Friedlingstein, Chris D. Jones, Colin Jones, Sönke Zaehle, and Veronika Eyring
Biogeosciences, 21, 5321–5360, https://doi.org/10.5194/bg-21-5321-2024, https://doi.org/10.5194/bg-21-5321-2024, 2024
Short summary
Short summary
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
Biogeosciences, 21, 5277–5303, https://doi.org/10.5194/bg-21-5277-2024, https://doi.org/10.5194/bg-21-5277-2024, 2024
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Cited articles
Adams, M. A. and Attiwill, P. M.: Role of Acacia spp. in nutrient balance and cycling
in regenerating Eucalyptus regnans F. Muell. forests, I. Temporal changes in
biomass and nutrient content, Aust. J. Bot., 32, 205–215, 1984.
Alexander, V. and Billington, M. M.: Nitrogen fixation in the Alaskan taiga, Forest
ecosystems in the Alaskan taiga, Springer, New York, NY, 112–120, 1986.
Baker, T. G., Oliver, G. R., and Hodgkiss, P. D.: Distribution and cycling of nutrients
in Pinus radiata as affected by past lupin growth and fertiliser, Forest
Ecol. Manage., 17, 169–187, 1986.
Barron, A. R., Purves, D. W., and Hedin, L. O.: Facultative nitrogen fixation by canopy
legumes in a lowland tropical forest, Oecologia, 165, 511–520, 2011.
Bate, G. C. and Gunton, C.: Nitrogen in the Burkea savanna, in: Ecology of
Tropical Savannas, edited by: Huntley, B. J. and Walker, B. H.,
Springer-Verlag, New York, 498–513, 1982.
Batjes, N. H.: Global Data Set of Derived Soil Properties, 0.5-Degree Grid (ISRIC-WISE), ORNL DAAC, Oak Ridge, Tennessee, USA, https://doi.org/10.3334/ORNLDAAC/546, 2000.
Belnap, J.: Nitrogen fixation in biological soil crusts from southeast Utah, USA, Biol. Fertil. Soils, 35, 128–135, 2002.
Blundon, D. J. and Dale, M. R. T.: Dinitrogen fixation (acetylene reduction) in
primary succession near Mount Robson, British Columbia, Canada, Arct.
Alp. Res., 22, 255–263, 1990.
Boote, K. J., Jones, J. W., and Hoogenboom, G.: Simulation of crop growth:
CROPGRO model, Agr. Syst. Model. Simul., 18, 651–692,
1998.
Boote, K. J., Hoogenboom, G., Jones, J. W., and Ingram, K. T.: Modeling nitrogen
fixation and its relationship to nitrogen uptake in the in the CROPGRO
model, in: Quantifying and
Understanding Plant Nitrogen Uptake for Systems Modeling, edited by: Ma, L., Ahuja, L. R., and Bruulsema, T. W., CRC Press,
Florence, USA, 13–46, 2008.
Boring, L. R. and Swank, W. T.: The role of black locust (Robinia pseudo-acacia) in
forest succession, J. Ecol., 71, 749–766, 1984.
Bouniols, A., Cabelguenne, M., Jones, C. A., Chalamet, A., Charpenteau, J. L., and
Marty, J. R.: Simulation
of Soybean Nitrogen Nutrition for a Silty Clay Soil in Southern France,
Field Crops Res., 26, 19–34, 1991.
Bowman, W. D., Schardt, J. C., and Schmidt, S. K.: Symbiotic N 2-fixation in alpine
tundra: ecosystem input and variation in fixation rates among communities,
Oecologia, 108, 345–350, 1996.
Breitbarth, E., Oschlies, A., and LaRoche, J.: Physiological constraints on the global distribution of Trichodesmium – effect of temperature on diazotrophy, Biogeosciences, 4, 53–61, https://doi.org/10.5194/bg-4-53-2007, 2007.
Bruijnzeel, L. A.: Nutrient input–output budgets of tropical forest
ecosystems: a review, J. Trop. Ecol., 7, 1–24, 1991.
Bustamante, M. M. C., Medina, E., Asner, G. P., Nardoto, G. B., and Garcia-Montiel, D. C.: Nitrogen cycling in tropical and temperate savannas. Biogeochemistry, 79, 209–237, 2006.
Cabelguenne, M., Debaeke, P., and Bouniols, A.: EPICphase, A Version of the
EPIC Model Simulating the Effects of Water and Nitrogen Stress on Biomass
and Yield, Taking Account of Developmental Stages: Validation on Maize,
Sunflower, Sorghum, Soybean, and Winter Wheat, Agric. Syst., 60, 175–196,
1999.
Cannell, M. G. R. and Thornley, J. H. M.: Modelling the components of plant
respiration: some guiding principles, Ann. Bot.-Lond., 85, 45–54, 2000.
Cech, P. G., Kuster, T., Edwards, P. J., and Olde Venterink, H.: Effects of herbivory, fire and N
2-fixation on nutrient limitation in a humid African savanna, Ecosystems,
11, 991–1004, 2008.
Chapin, D., Bliss, I. C., and Bledsoe, I. J:. Environmental regulation of nitrogen
fixation in a high arctic lowland ecosystem, Can J. Bot., 69, 2744–2755,
1991.
Chen, M. and Zhuang, Q.: Modelling temperature acclimation effects on the carbon dynamics of forest ecosystems in the conterminous United States, Tellus B, 65, 19156, https://doi.org/10.3402/tellusb.v65i0.19156, 2013.
Christie, P.: Nitrogen in two contrasting Antarctic bryophyte communities, J.
Ecol., 75, 73–93, 1987
Clayton, J. L. and Kennedy, D. A.: Nutrient Losses from Timber Harvest in the Idaho
Batholith 1, Soil. Sci. Soc. Am. J., 49, 1041–1049, 1985.
Cleveland, C. C., Townsend, A. R., Schimel, D. S., Fisher, H., Howarth, R. W., Hedin, L. O., Perakis, S. S., Latty, E. F., Von Fischer, J. C., Elseroad, A., and Wasson, M. F.: Global patterns of
terrestrial biological nitrogen (N2) fixation in natural ecosystems, Global
Biogeochem. Cy., 13, 623–645, 1999.
Cleveland, C. C., Houlton, B. Z., Neill, C., Reed, S. C., Townsend, A. R., and Wang, Y.: Using indirect methods to constrain symbiotic nitrogen fixation rates: a case study from an Amazonian rain forest, Biogeochemistry, 99, 1–13, 2010.
Cleveland, C. C., Houlton, B. Z., Smith, W. K., Marklein, A. R., Reed, S., Parton, W. J., Del Grosso, S., and Runing, S. W.: Patterns of new versus
recycled primary production in the terrestrial biosphere, P. Natl. Acad. Sci. USA,
110, 12733–12737, 2013.
Corre-Hellou, G., Brisson, N., Launay, M., Fustec, J., and Crozat, Y.: Effect of root depth penetration
on soil nitrogen competitive interactions and dry matter production in
pea–barley intercrops given different soil nitrogen supplies, Field Crop.
Res., 103, 76–85, 2007.
Corre-Hellou, G., Faure, M., Launay, M., Brisson, N., and Crozat, Y.: Adaptation of the STICS intercrop
model to simulate crop growth and N accumulation in pea–barley intercrops,
Field Crop. Res., 113, 72–81, 2009.
Crews, T. E.: The presence of nitrogen fixing legumes in terrestrial
communities: Evolutionary vs ecological considerations, New Perspectives on
Nitrogen Cycling in the Temperate and Tropical Americas, Springer,
Dordrecht, 233–246, 1999.
Crisp, M., Cook, L., and Steane, D.: Radiation of the Australian flora: what can
comparisons of molecular phylogenies across multiple taxa tell us about the
evolution of diversity in present–day communities?, Philos. T. R. Soc.
B, 359, 1551–1571, 2004.
DeLuca, T., Zackrisson, O., Nilsson, M., and Sellstedt, A.: Quantifying nitrogen-fixation in feather moss carpets of boreal forests, Nature, 419, 917–920, 2002.
Doherty, R. M., Hulme, M., and Jones, C. G.: A gridded reconstruction of land and ocean precipitation for the extended tropics from 1974 to 1994, Int. J. Climatol., 19, 119–142, 1999.
DuBois, J. D. and Kapustka, L. A.: Biological nitrogen influx in an Ohio relict
prairie, Am. J. Bot., 70, 8–16, 1983.
Eckersten, H., Geijersstam, L. A., and Torssell, B.: Modelling nitrogen
fixation of pea (Pisum sativum L.), Acta. Agr. Scand. B.-S. P., 56, 129–137,
2006.
Eisele, L., Schimel, D. S., Kapustka, L. A., and Parton, W. J.: Effects of
available P and N:P ratios on non-symbiotic dinitrogen fixation in
tallgrass prairie soils, Oecologia, 79, 471–474, 1989.
Elbert, W., Weber, B., Burrows, S., Steinkamp, J., Büdel, B., Andreae,
M. O., and Pöschl, U.: Contribution of cryptogamic covers to the global
cycles of carbon and nitrogen, Nat. Geosci., 5, 459–462, 2012.
Fahey, T. J., Yavitt, J. B., Pearson, J. A., and Knight, D. H.: The nitrogen cycle in lodgepole
pine forests, southeastern Wyoming, Biogeochemistry, 1, 257–275, 1985.
Fahey, T. J., Yavitt, J. B., and Joyce, G.: Precipitation and throughfall chemistry in Pinus contorta spp. latifolia ecosystems, southeastern Wyoming, Can. J. Forest Res., 18, 337–345, 1988.
Fisher, J. B., Sitch, S., Malhi, Y., Fisher, R. A., Huntingford, C., and Tan, S.-Y.: Carbon cost of plant nitrogen
acquisition: A mechanistic, globally applicable model of plant nitrogen
uptake, retranslocation, and fixation, Global Biogeochem. Cy., 24, GB1014, https://doi.org/10.1029/2009GB003621, 2010.
Galloway, J. N., Schlesinger, W. H., Levy, H., Michaels, A., and Schnoor, J. L.: Nitrogen fixation:
Anthropogenic enhancement-environmental response, Global Biogeochem. Cy.,
9, 235–252, 1995.
Galloway, J. N., Cowling, E. B., Seitzinger, S. P., and Socolow, R. H.: Reactive nitrogen: too
much of a good thing?, AMBIO: A Journal of the Human Environment, 31,
60–64, 2002.
Galloway, J. N., Dentener, F. J., Capone, D. G., Boyer, E. W., Howarth, R. W., Seitzinger, S. P., Asner, G. P., Cleveland, C. C., Green, P. A., Holland, E. A., Karl, D. M., Michaels, A. F., Porter, J. H., Townsend, A. R., and Vorosmarty, C. J: Nitrogen cycles: past,
present, and future, Biogeochemistry, 70, 153–226, 2004.
Gerber, S., Hedin, L. O., Oppenheimer, M., Pacala, S. W., and Shevliakova, E.: Nitrogen cycling and feedbacks in
a global dynamic land model, Global Biochemical. Cy., 24, GB1001, https://doi.org/10.1029/2008GB00333, 2010.
Goosem, S. and Lamb, D.: Measurements of phylloshpere nitrogen fixation in a
tropical and two sub-tropical rainforests, J. Trop. Ecol., 2,
373–376, 1986.
Granhall, U., and Lid-Torsvik, V.: Nitrogen fixation by bacteria and free-living blue-green algae in tundra areas, in: Fennoscandian Tundra Ecosystems, edited by: Wielgolaski, F. E., Part I, Plants and Microorganisms, Spring-Verlag, New York, 305–315, 1975.
Grove, T. S. and Malajczuk, N.: Nodule production and nitrogen fixation (acetylene
reduction) by an understorey legume (Bossiaea laidlawiana) in Eucalyptus
forest, J. Ecol., 80, 303–314, 1992.
Gruber, N. and Galloway, J. N.: An Earth System Perspective of the
Global Nitrogen Cycle, Nature, 451, 293–296, 2008.
Gundale, M. J., Nilsson, M., Bansal, S., and Jaderlund, A.: The interactive effects of
temperature and light on biological nitrogen fixation in boreal forests, New
Phytol., 194, 453–463, 2012.
Hardy, R. W. F., Holsten, R. D., Jackson, E. K., and Burns, R. C.: The acetylene-ethylene assay
for N2 fixation: laboratory and field evaluation, Plant Physiol.,
43, 1185–1207, 1968.
Hardy, R. W. F., Burns, R. C., and Holsten, R. D.: Applications of the acetylene-ethylene
assay for measurement of nitrogen fixation, Soil Biol. Biochem., 5,
47–81, 1973.
Harvey, A. E., Larsen, M. J., Jurgensen, M. F., and Jones, E. A.: Nitrogenase activity
associated with decayed wood of living northern Idaho conifers, Mycologia,
81, 765–771, 1989.
Heath, B., Sollins, P., Perry, D. A., and Cromack Jr., K.: Asymbiotic
nitrogen fixation in litter from Pacific Northwest forests, Can J. Forest
Res., 18, 68–74, 1988.
Hendrickson, O. Q.: Asymbiotic nitrogen fixation and soil metabolism in three
Ontario forests, Soil Biol. Biochem., 22, 967–971, 1990.
Hendrickson, O. Q. and Burgess, D.: Nitrogen-fixing plants in a cut-over lodgepole pine stand of southern British Columbia, Can J. Forest Res., 19, 936–939, 1989.
Holzworth, D. P., Huth, N. I., deVoil, P. G., Zurcher, E. J., Herrmann, N.
I., McLean, G., and Moore, A. D.: APSIM–evolution towards a new
generation of agricultural systems simulation, Environ. Modell. Softw., 62,
327–350, 2014.
Houlton, B. Z., Morford, S. L., and Dahlgren, R. A.: Convergent evidence for
widespread rock nitrogen sources in Earth's surface environment, Science,
360, 58–62, 2018.
Huss-Danell, K.: Nitrogen fixation by Stereocaulon paschale under field
conditions, Can J. Botany, 55, 585–592, 1977.
Jarrell, W. M. and Virginia, R. A.: Soil cation accumulation in a mesquite
woodland: sustained production and long-term estimates of water use and
nitrogen fixation, J. Arid Environ., 18, 51–58, 1990.
Johnson, H. B. and Mayeux, H. S.: Prosopis glandulosa and the nitrogen
balance of rangelands: extent and occurrence of nodulation, Oecologia,
84, 176–185, 1990.
Jones, P. D., Lister, D. H., Osborn, T. J., Harpham, C., Salmon, M., and Morice, C. P.: Hemispheric and large-scale land surface air temperature variations: an extensive revision and an update to 2010, J. Geophys. Res., 117, D05127, https://doi.org/10.1029/2011JD017139, 2012.
Jordan, C. W., Caskey, W., Escalante, G., Herrera, R., Montagnini, E.,
Todd, R., and Uhl, C.: The nitrogen cycle in a Terra Eirme rain forest on Oxisol in the Amazon Territory of Venezuela, Plant Soil, 67, 325–332, 1983.
Kapustka, L. A. and DuBois, J. D.: Dinitrogen fixation by cyanobacteria and
associative rhizosphere bacteria in the Arapaho Prairie in the Sand Hills of
Nebraska, Am. J. Bot., 74, 107–113, 1987.
Kou-Giesbrecht, S. and Menge, D.: Nitrogen-fixing trees could exacerbate climate change under elevated nitrogen deposition, Nat. Commun., 10, 1493, https://doi.org/10.1038/s41467-019-09424-2, 2019.
Layzell, D. B., Rainbird R. M., Atkins, C. A., and Pate, J. S.: Economy of photosynthate use in N-fixing legume modules: observations on two contracting symbioses, Plant Physiol., 64, 888–891, 1979.
LeBauer, D. S. and Treseder, K. K.: Nitrogen limitation of net primary
productivity in terrestrial ecosystems is globally distributed, Ecology,
89, 371–379, 2008.
Lee, Y. Y. and Son, Y.: Diurnal and seasonal patterns of nitrogen fixation
in analnus hirsuta plantation of central Korea, J. Plant Biol., 48,
332–337, 2005.
Lepper, M. G. and Fleschner, M.: Nitrogen fixation by Cercocarpus
ledifolius (Rosaceae) in pioneer habitats, Oecologia, 27, 333–338, 1977.
Lett, S. and Michelsen, A.: Seasonal variation in nitrogen fixation and
effects of climate change in a subarctic heath, Plant Soil, 379,
193–204, 2014.
Levy, H., Moxim, W. J., and Kasibhatla, P. S.: A global three–dimensional
time–dependent lightning source of tropospheric NOx, J. Geophys. Res.-Atmos.,
101, 22911–22922, 1996.
Ley, R. E. and D'Antonio, C. M.: Exotic grass invasion alters potential rates of
N fixation in Hawaiian woodlands, Oecologia, 113, 179–187, 1998.
Lindemann, W. C. and Glover, C. R.: Nitrogen fixation by legumes. New Mexico State University, Cooperative Extension Service, New Mexico State University, College of Agricultural, Consumer, and Environmental Sciences 2003.
Luken, J. O. and Fonda, R. W.: Nitrogen accumulation in a chronosequence of
red alder communities along the Hoh River, Olympic National Park,
Washington, Can. J. Forest Res., 13, 1228–1237, 1983.
Maheswaran, J. and Gunatilleke, I. A. U. N.: Nitrogenase activity in soil
and litter of a tropical lowland rain forest and an adjacent fernland in Sri
Lanka, J. Trop. Ecol., 6, 281–289, 1990.
Marino, D., Frendo, P., Ladrera, R., Zabalza, A., Puppo, A., Arrese-Igor,
C., and González, E. M.: Nitrogen fixation control under drought stress.
Localized or systemic?, Plant Physiol., 143, 1968–1974, 2007.
May, D. E. and Webber, P. J.: Spatial and temporal variation of vegetation and
its productivity on Niwot Ridge, Colorado, in: Ecological Studies in the
Colorado Alpine, a Festschrift for John W. Mart, edited by: Halfpenny, H.,
35–62, Institute for Arctic and Alpine Research, Univ. of Colorado, Boulder,
Colorado, 1982.
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.
Mitchell, T. D. and Jones, P. D.: An improved method of constructing a
database of monthly climate observations and associated high–resolution
grids, Int. J. Climatol., 25, 693–712, 2005.
Montanez, A., Danso, S. K. A., and Hardarson, G.: The effect of
temperature on nodulation and nitrogen fixation by five Bradyrhizobium
japonicum strains, Appl. Soil Ecol., 2, 165–174, 1995.
Morford, S. L., Houlton, B. Z., and Dahlgren, R. A.: Increased forest
ecosystem carbon and nitrogen storage from nitrogen rich bedrock, Nature,
477, 78–81, https://doi.org/10.1038/nature10415, 2011.
Mus, F., Crook, M. B., Garcia, K., Costas, A. G., Geddes, B. A., Kouri, E.
D., and Udvardi, M. K.: Symbiotic nitrogen fixation and the challenges
to its extension to nonlegumes, Appl. Environ. Microbiol., 82,
3698–3710, 2016.
Nohrstedt, H. Ö.: Biological activity in soil from forest stands in Central
Sweden, as related to site properties, Microb. Ecol., 11, 259–266, 1985.
O'Connel, A. M. and Grove, T. S.: Seasonal variation in C2H2 reduction
(N2-fixation) in the litter layer of eucalypt forests of south-western
Australia, Soil Biol. Biochem., 19, 135–142, 1987.
Permar, T. A. and Fisher, R. F.: Nitrogen fixation and accretion by wax
myrtle (Myrica cerifera) in slash pine (Pinus elliottii) plantations, Forest
Ecol. Manag., 5, 39–46, 1983.
Pons, T. L., Perreijn, K., Van Kessel, C., and Werger, M. J.: Symbiotic
nitrogen fixation in a tropical rainforest: 15N natural abundance
measurements supported by experimental isotopic enrichment, New Phytol.,
173, 154–167, 2007.
Reed, S. C., Cleveland, C. C., and Townsend, A. R. Functional ecology of
free-living nitrogen fixation: a contemporary perspective, Annu. Rev. Ecol.
Evol. S., 42, 489–512, 2011.
Robertson, G. P. and Rosswall, T.: Nitrogen in West Africa: The tropical cycle, Ecol. Monogr., 56, 43–72, 1986.
Rundel, P. W., Nilsen, E. T., Sharifi, M. R., Virginia, R. A., Jarrell, W.
M., Kohl, D. H., and Shearer, G. B.: Seasonal dynamics of nitrogen cycling
for a Prosopis woodland in the Sonoran Desert, in: Nitrogen Cycling in
Ecosystems of Latin America and the Caribbean, Springer,
Dordrecht, 343–353, 1982.
Rylr, G. J. A., Powell, C. E., and Gordon, A. J.: Th respiratory costs of nitrogen fixation in soybean, cowpea and white clover, I. Nitrogen fixation and the respiration of the nodulated root, J. Expt. Bot., 30, 145–153, 1979.
Sánchez-Diaz, M.: Adaptation of legumes to multiple stresses in
Mediterranean-type environments, Options Méditerranéennes, 45,
145–151, 2001.
Schlesinger, W. H., Gray, J. T., Gill, D. S., and Mahall, B. E.: Ceanothus
megacarpus chaparral: a synthesis of ecosystem processes during development
and annual growth, Bot. Rev., 48, 71–117, 1982.
Schrire, B. D., Lewis, G. P., and Lavin, M.: Biogeography of the Leguminosae,
Legumes of the world, 21–54, 2005.
Schwintzer, C. R.: Nonsymbiotic and symbiotic nitrogen fixation in a weakly
minerotrophic peatland, Am. J. Bot., 70, 1071–1078, 1983.
Sharpley, A. N. and Williams, J. R.: EPIC Erosion/Productivity Impact Calculator: 1. Model Documentation, USA Department of Agriculture Technical Bulletin No. 1768, USA Government Printing Office, Washington DC, 1990.
Shearer, G. and Kohl, D. H.: N2-fixation in field settings: estimations
based on natural 15N abundance, Funct. Plant Biol., 13, 699–756, 1986.
Sheridan, R. P.: Nitrogenase activity by Hapalosiphon flexuosus associated
with Sphagnum erythrocalyx mats in the cloud forest on the volcano La
Soufriere, Guadeloupe, French West Indies, Biotropica, 23, 134–140, 1991.
Skujinš, J., Tann, C. C., and Börjesson, I.: Dinitrogen fixation in
a montane forest sere determined by 15N2 assimilation and in situ
acetylene-reduction methods, Soil Biol. Biochem., 19, 465–471, 1987.
Sobota, D. J., Compton, J. E., and Harrison, J. A.: Reactive nitrogen inputs
to US lands and waterways: how certain are we about sources and fluxes?,
Front. Ecol. Environ., 11, 82–90, 2013.
Sonesson, M., Jonsson, S., Rosswall, T., and Rydén, B. E.: The Swedish
IBP/PT Tundra Biome Project Objectives-Planning-Site, Ecol. Bull., 30, 7–25,
1980.
Sprent, J. I.: The effects of water stress on nitrogen–fixing root nodules,
New Phytol., 71, 443–450, 1972.
Sprent, J. I., Ardley, J., and James, E. K.: Biogeography of nodulated
legumes and their nitrogen–fixing symbionts, New Phytol., 215, 40–56,
2017.
Srivastava, A. K. and Ambasht, R. S.: Soil moisture control of nitrogen
fixation activity in dry tropical Casuarina plantation forest, J. Environ.
Manage., 42, 49–54, 1994.
Stedman, D. H. and Shetter, R.: The global budget of atmosphere nitrogen
species, in: Trace Atmospheric Constituent: Properties, Transformations and
Fates, edited by: Schwartz, S. S., John Wiley, New York, 411–454, 1983.
Stewart, W. D. P., Sampaio, M. J., Isichei, A. O., and Sylvester-Bradley, R.:
Nitrogen fixation by soil algae of temperate and tropical soils, in:
Limitation and potentials for
biological nitrogen fixation in the tropics, edited by: Dobreiner, J., Burris, R. H., and Hollaender, A., Basic Life Sciences,
Plenum Press, New York,Vol. 10, 41–63, 1978.
Sutton, M. A., Mason, K. E., Sheppard, L. J., Sverdrup, H., Haeuber, R., and Hicks, W. K.: Nitrogen deposition, critical loads and biodiversity, Springer Science and Business Media, https://doi.org/10.1007/978-94-007-7939-6, 2014.
Sullivan, B. W., Smith, W. K., Townsend, A. R., Nasto, M. K., Reed, S. C.,
Chazdon, R. L., and Cleveland, C. C.: Spatially robust estimates of
biological nitrogen (N) fixation imply substantial human alteration of the
tropical N cycle, P. Natl. Acad. Sci. USA, 111, 8101–8106, 2014.
Sylvester-Bradley, R., Oloveira, L. A., Podesta Filho, J. A., and St John, T. V.: Nodulation of legumes, nitrogenase activity-fixing Azospirillum app. in representative soils of Central Amazonia, Proc. Int. Lupin Conf., 157–173, 1980.
Thornley, J. H. M.: Simulating grass-legume dynamics: a phenomenological
submodel, Ann. Bot.-Lond., 88, 905–913, 2001.
Vitousek, P. M.: Potential nitrogen fixation during primary succession in
Hawaii Volcanoes National Park, Biotropica, 26, 234–240, 1994.
Vitousek, P. M. and FIeld, C. B.: Ecosystem constraints to symbiotic nitrogen fixers: A simple model and its implications, Biogeochemistry, 46, 179–202, 1999.
Vitousek, P. M., Menge, D. N., Reed, S. C., and Cleveland, C. C.: Biological
nitrogen fixation: rates, patterns and ecological controls in terrestrial
ecosystems, Philos. T. R. Soc. B, 368, 20130119, https://doi.org/10.1098/rstb.2013.0119, 2013.
Voisin, A. S., Salon, C., Jeudy, C., and Warembourg, F. R.: Symbiotic N2
fixation activity in relation to C economy of Pisum sativum L. as a function
of plant phenology, J. Exp. Bot., 54, 2733–2744, 2003.
Voisin, A. S., Bourion, V., Duc, G., and Salon, C.: Using an
ecophysiological analysis to dissect genetic variability and to propose an
ideotype for nitrogen nutrition in pea, Ann. Bot.-Lond., 100, 1525–1536,
2007.
Weber, M. G. and Van Cleve, K.: Nitrogen dynamics in the forest floor of interior Alaska black spruce ecosystems, Can J. Forest Res., 11, 743–751, https://doi.org/10.1139/x81-106, 1981.
Wheatley, R. E. and Sprent, J. I.: Legume Nodulation: A Global Perspective, edited by: Sprent, J. I., Chichester, UK, Wiley-Blackwell, ISBN 97818405181754, 200 pp., 2009.
Williams, J. R. and Sharply, A. N.: EPIC-Erosion Productivity Impact Cacalator,
Model Documentation, US Department of Agriculture Technical Bulletin, 235 pp.,
1768.
Woodmansee, R. G. and Wallach, L. S.: Effects of fire regimes on
biogeochemical cycles, Terr. Nitr. Cy. Ecol. Bull.,
33, 649–669, 1981.
Wu, L. and McGechan, M. B.: Simulation of nitrogen uptake, fixation and
leaching in a grass/white clover mixture, Grass Forage Sci., 54, 30–41,
1999.
Xu, X., Thornton, P. E., and Potapov, P.: A Compilation of Global Soil Microbial Biomass Carbon, Nitrogen, and Phosphorus Data, ORNL DAAC, Oak Ridge, Tennessee, USA, https://doi.org/10.3334/ORNLDAAC/1264, 2014.
Xu-Ri and Prentice, I. C.: Modelling the demand for new nitrogen fixation by terrestrial ecosystems, Biogeosciences, 14, 2003–2017, https://doi.org/10.5194/bg-14-2003-2017, 2017.
Yu, T. and Zhuang, Q.: Quantifying global N2O emissions from natural ecosystem soils using trait-based biogeochemistry models, Biogeosciences, 16, 207–222, https://doi.org/10.5194/bg-16-207-2019, 2019.
Zhuang, Q., Romanovsky, V. E., and McGuire, A. D.: Incorporation of a
permafrost model into a large–scale ecosystem model: Evaluation of temporal
and spatial scaling issues in simulating soil thermal dynamics, J. Geophys.
Res.-Atmos., 106, 33649–33670, 2001.
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, 8147, https://doi.org/10.1029/2001JD001244,
2002.
Zhuang, Q., McGuire, A. D., Melillo, J. M., Clein, J. S., Dargaville, R. J., Kicklighter, D. W., Myneni, R. B., Dong, J., Romanovsky, V. E., Harden, J., 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, 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.
Zhuang, Q., Chen, M., Xu, K., Tang, J., Saikawa, E., Lu, Y., and
McGuire, A. D.: Response of global soil consumption of atmospheric
methane to changes in atmospheric climate and nitrogen deposition, Global
Biogeochem. Cy., 27, 650–663, 2013.
Short summary
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.
Biological nitrogen fixation (BNF) plays an important role in the global nitrogen cycle....
Altmetrics
Final-revised paper
Preprint