Articles | Volume 20, issue 18
https://doi.org/10.5194/bg-20-3895-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-20-3895-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
27 Sep 2023
Research article |
| 27 Sep 2023
| 27 Sep 2023
Modeling coupled nitrification–denitrification in soil with an organic hotspot
Department of Agroecology, iClimate, Aarhus University, Tjele, Denmark
Elisabeth Larsen Kolstad
Department of Agroecology, iClimate, Aarhus University, Tjele, Denmark
Wenxin Zhang
Department of Physical Geography and Ecosystem Science, Lund
University, Lund, Sweden
Iris Vogeler
Department of Agroecology, iClimate, Aarhus University, Tjele, Denmark
Søren O. Petersen
Department of Agroecology, iClimate, Aarhus University, Tjele, Denmark
Related authors
Jie Zhang, Wenxin Zhang, Per-Erik Jansson, and Søren O. Petersen
Biogeosciences, 19, 4811–4832, https://doi.org/10.5194/bg-19-4811-2022, https://doi.org/10.5194/bg-19-4811-2022, 2022
Short summary
Short summary
In this study, we relied on a properly controlled laboratory experiment to test the model’s capability of simulating the dominant microbial processes and the emissions of one greenhouse gas (nitrous oxide, N2O) from agricultural soils. This study reveals important processes and parameters that regulate N2O emissions in the investigated model framework and also suggests future steps of model development, which have implications on the broader communities of ecosystem modelers.
Yong Yang, Huaiwei Sun, Jingfeng Wang, Wenxin Zhang, Gang Zhao, Weiguang Wang, Lei Cheng, Lu Chen, Hui Qin, and Zhanzhang Cai
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-420, https://doi.org/10.5194/essd-2024-420, 2024
Preprint under review for ESSD
Short summary
Short summary
Traditional methods for estimating ocean heat flux often introduce large uncertainties due to complex parameterizations and reliance on wind speed. To tackle this issue, we developed a novel framework based on MEP theory. By incorporating heat storage effects and refining the Bowen ratio, we enhanced the MEP method’s accuracy. This research derives a new long-term global ocean latent heat flux dataset that offers high accuracy, enhancing our understanding of ocean energy dynamics.
Ana Maria Roxana Petrescu, Glen P. Peters, Richard Engelen, Sander Houweling, Dominik Brunner, Aki Tsuruta, Bradley Matthews, Prabir K. Patra, Dmitry Belikov, Rona L. Thompson, Lena Höglund-Isaksson, Wenxin Zhang, Arjo J. Segers, Giuseppe Etiope, Giancarlo Ciotoli, Philippe Peylin, Frédéric Chevallier, Tuula Aalto, Robbie M. Andrew, David Bastviken, Antoine Berchet, Grégoire Broquet, Giulia Conchedda, Stijn N. C. Dellaert, Hugo Denier van der Gon, Johannes Gütschow, Jean-Matthieu Haussaire, Ronny Lauerwald, Tiina Markkanen, Jacob C. A. van Peet, Isabelle Pison, Pierre Regnier, Espen Solum, Marko Scholze, Maria Tenkanen, Francesco N. Tubiello, Guido R. van der Werf, and John R. Worden
Earth Syst. Sci. Data, 16, 4325–4350, https://doi.org/10.5194/essd-16-4325-2024, https://doi.org/10.5194/essd-16-4325-2024, 2024
Short summary
Short summary
This study provides an overview of data availability from observation- and inventory-based CH4 emission estimates. It systematically compares them and provides recommendations for robust comparisons, aiming to steadily engage more parties in using observational methods to complement their UNFCCC submissions. Anticipating improvements in atmospheric modelling and observations, future developments need to resolve knowledge gaps in both approaches and to better quantify remaining uncertainty.
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
Preprint 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.
Mengge Lu, Huaiwei Sun, Yong Yang, Jie Xue, Hongbo Ling, Hong Zhang, and Wenxin Zhang
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-128, https://doi.org/10.5194/hess-2024-128, 2024
Preprint under review for HESS
Short summary
Short summary
Our study explores how ecosystems recover after flash droughts. Using vegetation and soil moisture data, we found that recovery takes about 37.5 days on average in China, longer in central and southern regions. Factors like post-drought radiation and temperature affect recovery, with extreme temperatures prolonging it. Herbaceous plants recover faster than forests. Our findings aid water resource management and drought monitoring on a large scale, offering insights into ecosystem resilience.
Jie Zhang, Wenxin Zhang, Per-Erik Jansson, and Søren O. Petersen
Biogeosciences, 19, 4811–4832, https://doi.org/10.5194/bg-19-4811-2022, https://doi.org/10.5194/bg-19-4811-2022, 2022
Short summary
Short summary
In this study, we relied on a properly controlled laboratory experiment to test the model’s capability of simulating the dominant microbial processes and the emissions of one greenhouse gas (nitrous oxide, N2O) from agricultural soils. This study reveals important processes and parameters that regulate N2O emissions in the investigated model framework and also suggests future steps of model development, which have implications on the broader communities of ecosystem modelers.
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.
Arezoo Taghizadeh-Toosi, Lars Elsgaard, Tim J. Clough, Rodrigo Labouriau, Vibeke Ernstsen, and Søren O. Petersen
Biogeosciences, 16, 4555–4575, https://doi.org/10.5194/bg-16-4555-2019, https://doi.org/10.5194/bg-16-4555-2019, 2019
Short summary
Short summary
Organic soils drained for crop production or grazing land have high potential for nitrous oxide emissions. The present study investigated the regulation of N2O emissions in a raised bog area drained for agriculture. It seems that archaeal ammonia oxidation and either chemodenitrification or nitrifier denitrification were considered to be plausible pathways of N2O production in spring, whereas in the autumn heterotrophic denitrification may have been more important at arable sites.
Arezoo Taghizadeh-Toosi, Lars Elsgaard, Tim Clough, Rodrigo Labouriau, and Søren Ole Petersen
Biogeosciences Discuss., https://doi.org/10.5194/bg-2018-9, https://doi.org/10.5194/bg-2018-9, 2018
Revised manuscript not accepted
Short summary
Short summary
Organic soils are extensively under agricultural management which lead to high emissions of N2O. We searched for relationships between seasonal variation in N2O emissions and potential driving variables such as temperature, precipitation, water table depth, N availability, and possible decomposibility of peat. Reducing surplus N in the soil, for example by use of a plant cover, and stabilisation of water table depth during the year, appear to be keys to controlling N2O emissions.
Related subject area
Biogeochemistry: Modelling, Terrestrial
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
Understanding and simulating cropland and non-cropland burning in Europe using the BASE (Burnt Area Simulator for Europe) model
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
Representation of the Terrestrial Carbon Cycle in CMIP6
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
X-BASE: the first terrestrial carbon and water flux products from an extended data-driven scaling framework, FLUXCOM-X
Spatial biases reduce the ability of Earth system models to simulate soil heterotrophic respiration fluxes
Future methane fluxes of peatlands are controlled by management practices and fluctuations in hydrological conditions due to climatic variability
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
Does dynamically modelled leaf area improve predictions of land surface water and carbon fluxes? – Insights into dynamic vegetation modules
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
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
Observational benchmarks inform representation of soil organic carbon dynamics in land surface models
Effect of land-use legacy on the future carbon sink for the conterminous US
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.
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
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 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
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.
Bettina K. Gier, Manuel Schlund, Pierre Friedlingstein, Chris D. Jones, Colin Jones, Sönke Zaehle, and Veronika Eyring
EGUsphere, https://doi.org/10.5194/egusphere-2024-277, https://doi.org/10.5194/egusphere-2024-277, 2024
Short summary
Short summary
This study investigates present day carbon cycle variables in CMIP5 and CMIP6 simulations. A significant improvement in the simulation of photosynthesis in models with nitrogen cycle is found, as well as only small differences between emission and concentration based simulations. Thus, we recommend the use of emission driven simulations in CMIP7 as default setup, and to view the nitrogen cycle as a necessary part of all future carbon cycle models.
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.
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 Billdesbach, 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 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, Gharun Mana, 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
EGUsphere, https://doi.org/10.5194/egusphere-2024-165, https://doi.org/10.5194/egusphere-2024-165, 2024
Short summary
Short summary
The movement of water, carbon, and energy from the earth surface to the atmosphere, or flux, is an important process to understand that impacts all of our lives. Here we outline a method to estimate global water and CO2 fluxes based on direct measurements from site around the world called FLUXCOM-X. 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.
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.
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
Short summary
Short summary
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
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.
Sven Armin Westermann, Anke Hildebrandt, Souhail Bousetta, and Stephan Thober
EGUsphere, https://doi.org/10.5194/egusphere-2023-2101, https://doi.org/10.5194/egusphere-2023-2101, 2023
Short summary
Short summary
Plants at the land surface mediates between soil and atmosphere regarding water and carbon transport. Since plant growth is a dynamic process, models need to care for this dynamics. Here, two models which 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.
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.
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.
Kamal Nyaupane, Umakant Mishra, Feng Tao, Kyongmin Yeo, William J. Riley, Forrest M. Hoffman, and Sagar Gautam
Biogeosciences Discuss., https://doi.org/10.5194/bg-2023-50, https://doi.org/10.5194/bg-2023-50, 2023
Revised manuscript accepted for BG
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. We used machine learning to develop and compare predictive relationships in observations and ESMs. We found different relationships between environmental factors and SOC stocks in observations and ESMs. SOC predictions in ESMs may be improved by representing the functional relationships of environmental controllers consistent with observations.
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
Abeling, U. and Seyfried, C. F.: Anaerobic-aerobic treatment of high-strength ammonium wastewater – nitrogen removal via nitrite, Water Sci. Technol., 26, 1007–1015, https://doi.org/10.2166/wst.1992.0542, 1992.
Barbarika, A., Sikora, L. J., and Colacicco, D.: Factors affecting the
mineralization of nitrogen in sewage sludge applied to soils, Soil Sci. Soc.
Am. J., 49, 1403–1406, https://doi.org/10.2136/sssaj1985.03615995004900060014x, 1985.
Brilli, L., Bechini, L., Bindi, M., Carozzi, M., Cavalli, D., Conant, R.,
Dorich, C. D., Doro, L., Ehrhardt, F., Farina, R., Ferrise, R., Fitton, N.,
Francaviglia, R., Grace, P., Iocola, I., Klumpp, K., Léonard, J., Martin, R., Massad, R. S., Recous, S., Seddaiu, G., Sharp, J., Smith, P., Smith, W. N., Soussana, J.-F., and Bellocchi, G.: Review and analysis of strengths and weaknesses of agro-ecosystem models for simulating C and N fluxes, Sci. Total Environ., 598, 445–470, https://doi.org/10.1016/j.scitotenv.2017.03.208, 2017.
Brisson, N., Gary, C., Justes, E., Roche, R., Mary, B., Ripoche, D., Zimmer,
D., Sierra, J., Bertuzzi, P., Burger, P., Bussière, F., Cabidoche, Y. M., Cellier, P., Debaeke, P., Gaudillère, J. P., Hénault, C., Maraux, F., Seguin, B., and Sinoquet, H.: An overview of the crop model STICS, Eur. J. Agron., 18, 309–332, https://doi.org/10.1016/S1161-0301(02)00110-7, 2003.
Butterbach-Bahl, K., Baggs, E. M., Dannenmann, M., Kiese, R., and
Zechmeister-Boltenstern, S.: Nitrous oxide emissions from soils: how well do
we understand the processes and their controls?, Philos. T. Roy. Soc. B, 368, 20130122, https://doi.org/10.1098/rstb.2013.0122, 2013.
Chang, B., Yan, Z., Ju, X., Song, X., Li, Y., Li, S., Fu, P., and Zhu-Barker,
X.: Quantifying biological processes producing nitrous oxide in soil using a
mechanistic model, Biogeochemistry, 159, 1–14, https://doi.org/10.1007/s10533-022-00912-0, 2022.
Charles, A., Rochette, P., Whalen, J. K., Angers, D. A., Chantigny, M. H., and Bertrand, N.: Global nitrous oxide emission factors from agricultural soils after addition of organic amendments: a meta-analysis, Agr. Ecosyst.
Environ., 236, 88–98, https://doi.org/10.1016/j.agee.2016.11.021, 2017.
Chen, X., Ni, B. J., and Sin, G.: Nitrous oxide production in autotrophic
nitrogen removal granular sludge: a modeling study, Biotechnol. Bioeng., 116, 1280–1291, https://doi.org/10.1002/bit.26937, 2019.
Cheng, C. T., Ou, C. P., and Chau, K. W.: Combining a fuzzy optimal model with a genetic algorithm to solve multi-objective rainfall–runoff model calibration, J. Hydrol., 268, 72–86, https://doi.org/10.1016/S0022-1694(02)00122-1, 2002.
Christensen, S., Simkins, S., and Tiedje, J. M.: Spatial variation in
denitrification: dependency of activity centers on the soil environment,
Soil Sci. Soc. Am. J., 54, 1608–1613, https://doi.org/10.2136/SSSAJ1990.03615995005400060016X, 1990a.
Christensen, S., Simkins, S., and Tiedje, J. M.: Temporal patterns of soil
denitrification: their stability and causes, Soil Sci. Soc. Am. J., 54,
1614–1618, https://doi.org/10.2136/SSSAJ1990.03615995005400060017X, 1990b.
Conen, F., Dobbie, K. E., and Smith, K. A.: Predicting N2O emissions
from agricultural land through related soil parameters, Global Change Biol.,
6, 417–426, https://doi.org/10.1046/j.1365-2486.2000.00319.x, 2000.
Davidson, E. A.: The contribution of manure and fertilizer nitrogen to
atmospheric nitrous oxide since 1860, Nat. Geosci., 2, 659–662,
https://doi.org/10.1038/ngeo608, 2009.
Davidson, E. A., Samanta, S., Caramori, S. S., and Savage, K.: The Dual
Arrhenius and Michaelis – Menten kinetics model for decomposition of soil
organic matter at hourly to seasonal time scales, Global Change Biol., 18,
371–384, https://doi.org/10.1111/j.1365-2486.2011.02546.x, 2012.
Francis, C. W. and Mankin, J. B.: High nitrate denitrification in continuous
flow-stirred reactors, Water Res., 11, 289–294,
https://doi.org/10.1016/0043-1354(77)90061-6, 1977.
Gjettermann, B., Styczen, M., Hansen, H. C. B., Vinther, F. P., and Hansen, S.: Challenges in modelling dissolved organic matter dynamics in
agricultural soil using DAISY, Soil Biol. Biochem., 40, 1506–1518,
https://doi.org/10.1016/J.SOILBIO.2008.01.005, 2008.
Glass, C., Silverstein, J., and Oh, J.: Inhibition of denitrification in
activated sludge by nitrite, Water Environ. Res., 69, 1086–1093,
https://doi.org/10.2175/106143097X125803, 1997.
Groffman, P. M., Butterbach-Bahl, K., Fulweiler, R. W., Gold, A. J., Morse,
J. L., Stander, E. K., Tague, C., Tonitto, C., and Vidon, P.: Challenges to
incorporating spatially and temporally explicit phenomena (hotspots and hot
moments) in denitrification models, Biogeochemistry, 93, 49–77,
https://doi.org/10.1007/s10533-008-9277-5, 2009.
Grosz, B., Well, R., Dechow, R., Köster, J. R., Khalil, M. I., Merl, S.,
Rode, A., Ziehmer, B., Matson, A., and He, H.: Evaluation of denitrification
and decomposition from three biogeochemical models using laboratory
measurements of N2, N2O and CO2, Biogeosciences, 18,
5681–5697, https://doi.org/10.5194/bg-18-5681-2021, 2021.
Hansen, S., Abrahamsen, P., Petersen, C. T., and Styczen, M.: Daisy: model
use, calibration, and validation, T. ASABE, 55, 1317–1335,
https://doi.org/10.13031/2013.42244, 2012.
Holzworth, D. P., Huth, N. I., deVoil, P. G., Zurcher, E. J., Herrmann, N. I., McLean, G., Chenu, K., van Oosterom, E. J., Snow, V., Murphy, C., Moore, A. D., Brown, H., Whish, J. P. M., Verrall, S., Fainges, J., Bell, L. W.,
Peake, A. S., Poulton, P. L., Hochman, Z., Thorburn, P. J., Gaydon, D. S.,
Dalgliesh, N. P., Rodriguez, D., Cox, H., Chapman, S., Doherty, A., Teixeira, E., Sharp, J., Cichota, R., Vogeler, I., Li, F. Y., Wang, E., Hammer, G. L., Robertson, M. J., Dimes, J. P., Whitbread, A. M., Hunt, J., van Rees, H., McClelland, T., Carberry, P. S., Hargreaves, J. N. G., MacLeod, N., McDonald, C., Harsdorf, J., Wedgwood, S., and Keating, B. A.: APSIM – Evolution towards a new generation of agricultural systems simulation, Environ. Model. Softw., 62, 327–350, https://doi.org/10.1016/J.ENVSOFT.2014.07.009, 2014.
Hunt, H. W. and Adamsen, F. J.: Empirical representation of ammonium adsorption in two soils, Soil Sci., 139, 205–210,
https://doi.org/10.1097/00010694-198503000-00003, 1985.
Jansson, P.-E. and Moon, D. S.: A coupled model of water, heat and mass
transfer using object orientation to improve flexibility and functionality,
Environ. Model. Softw., 16, 37–46, https://doi.org/10.1016/S1364-8152(00)00062-1, 2001.
Jensen, J. L., Christensen, B. T., Schjønning, P., Watts, C. W., and Munkholm, L. J.: Converting loss-on-ignition to organic carbon content in
arable topsoil: pitfalls and proposed procedure, Eur. J. Soil Sci., 69,
604–612, https://doi.org/10.1111/EJSS.12558, 2018.
Jones, J. W., Tsuji, G. Y., Hoogenboom, G., Hunt, L. A., Thornton, P. K.,
Wilkens, P. W., Imamura, D. T., Bowen, W. T., and Singh, U.: Decision support
system for agrotechnology transfer: DSSAT v3, Springer, Dordrecht, 157–177,
https://doi.org/10.1007/978-94-017-3624-4, 1998.
Jost, D. I., Aschemann, M., Lebzien, P., Joergensen, R. G., and Sundrum, A.:
Microbial biomass in faeces of dairy cows affected by a nitrogen deficient
diet, Arch. Anim. Nutr., 67, 104–118, https://doi.org/10.1080/1745039X.2013.776326,
2013.
Kessler, A. J., Glud, R. N., Cardenas, M. B., and Cook, P. L. M.: Transport
zonation limits coupled nitrification-denitrification in permeable sediments, Environ. Sci. Technol., 47, 13404–13411, https://doi.org/10.1021/es403318x, 2013.
Khalil, K., Renault, P., Guerin, N., and Mary, B.: Modelling denitrification
including the dynamics of denitrifiers and their progressive ability to reduce nitrous oxide: comparison with batch experiments, Eur. J. Soil Sci.,
56, 491–504, https://doi.org/10.1111/j.1365-2389.2004.00681.x, 2005.
Kolstad, E., Well, R., Grosz, B., and Petersen, S. O.: Nitrogen dynamics and nitrous oxide emissions of a manure hotspot as influenced by bulk density and soil water potential, in preparation, 2023.
Konak, A., Coit, D. W., and Smith, A. E.: Multi-objective optimization using
genetic algorithms: a tutorial, Reliab. Eng. Syst. Safe., 91, 992–1007,
https://doi.org/10.1016/J.RESS.2005.11.018, 2006.
Kravchenko, A. N., Toosi, E. R., Guber, A. K., Ostrom, N. E., Yu, J., Azeem,
K., Rivers, M. L., and Robertson, G. P.: Hotspots of soil N2O emission
enhanced through water absorption by plant residue, Nat. Geosci., 10, 496–500, https://doi.org/10.1038/ngeo2963, 2017.
Kremen, A., Bear, J., Shavit, U., and Shaviv, A.: Model demonstrating the
potential for coupled nitrification denitrification in soil aggregates,
Environ. Sci. Technol., 39, 4180–4188, https://doi.org/10.1021/es048304z, 2005.
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, https://doi.org/10.1029/92JD00509, 1992.
Li, C., Aber, J., Stange, F., Butterbach-Bahl, K., and Papen, H.: A
process-oriented model of N2O and NO emissions from forest soils: 1. model development, J. Geophys. Res.-Atmos., 105, 4369–4384,
https://doi.org/10.1029/1999JD900949, 2000.
Li, X., Weller, D. E., and Jordan, T. E.: Watershed model calibration using
multi-objective optimization and multi-site averaging, J. Hydrol., 380,
277–288, https://doi.org/10.1016/J.JHYDROL.2009.11.003, 2010.
Li, Z. H., Alvarez, V. E., De Gaudenzi, J. G., Sant'Anna, C., Frasch, A. C.
C., Cazzulo, J. J., and Docampo, R.: Hyperosmotic stress induces
aquaporin-dependent cell shrinkage, polyphosphate synthesis, amino acid
accumulation, and global gene expression changes in Trypanosoma cruzi, J.
Biol. Chem., 286, 43959–43971, https://doi.org/10.1074/JBC.M111.311530, 2011.
Manzoni, S. and Katul, G.: Invariant soil water potential at zero microbial
respiration explained by hydrological discontinuity in dry soils, Geophys.
Res. Lett., 41, 7151–7158, https://doi.org/10.1002/2014GL061467, 2014.
Markfoged, R., Nielsen, L. P., Nyord, T., Ottosen, L. D. M., and Revsbech, N.
P.: Transient N2O accumulation and emission caused by O2 depletion
in soil after liquid manure injection, Eur. J. Soil Sci., 62, 541–550,
https://doi.org/10.1111/j.1365-2389.2010.01345.x, 2011.
Meyer, R. L., Kjaer, T., and Revsbech, N. P.: Nitrification and denitrification near a soil-manure interface studied with a nitrate-nitrite
biosensor, Soil Sci. Soc. Am. J., 66, 498–506, https://doi.org/10.2136/SSSAJ2002.4980,
2002.
Millington, R. J.: Gas diffusion in porous media, Science, 130, 100–102, https://doi.org/10.1126/science.130.3367.100.b, 1959.
Møller, H. B., Sommer, S. G., and Ahring, B. K.: Methane productivity of
manure, straw and solid fractions of manure, Biomass Bioenerg., 26, 485–495, https://doi.org/10.1016/j.biombioe.2003.08.008, 2004.
Nguyen, T. H., Nong, D., and Paustian, K.: Surrogate-based multi-objective
optimization of management options for agricultural landscapes using
artificial neural networks, Ecol. Model., 400, 1–13,
https://doi.org/10.1016/J.ECOLMODEL.2019.02.018, 2019.
Ni, B. J., Sheng, G. P., and Yu, H. Q.: Model-based characterization of
endogenous maintenance, cell death and predation processes of activated sludge in sequencing batch reactors, Chem. Eng. Sci., 66, 747–754,
https://doi.org/10.1016/J.CES.2010.11.033, 2011.
Nielsen, T. H. and Revsbech, N. P.: Diffusion chamber for nitrogen-15
determination of coupled nitrification-denitrification around soil-manure
interfaces, Soil Sci. Soc. Am. J., 58, 795–800,
https://doi.org/10.2136/sssaj1994.03615995005800030022x, 1994.
Nielsen, T. H., Nielsen, L. P., and Revsbech, N. P.: Nitrification and
coupled nitrification-denitrification associated with a soil-manure
interface, Soil Sci. Soc. Am. J., 60, 1829–1840,
https://doi.org/10.2136/sssaj1996.03615995006000060031x, 1996.
Oenema, O., Wrage, N., Velthof, G. L., Van Groenigen, J. W., Dolfing, J., and
Kuikman, P. J.: Trends in global nitrous oxide emissions from animal production systems, Nutr. Cycl. Agroecosyst., 72, 51–65,
https://doi.org/10.1007/s10705-004-7354-2, 2005.
Olesen, T., Griffiths, B. S., Henriksen, K., Moldrup, P., and Wheatley, R.:
Modeling diffusion and reaction in soils: V. Nitrogen transformations in
organic manure-amended soil, Soil Sci., 162, 157–168, 1997a.
Olesen, T., Moldrup, P., and Henriksen, K.: Modeling diffusion and reaction
in soils: VI. Ion diffusion and water characteristics in organic manure-amended soil, Soil Sci., 162, 399–409, 1997b.
Olesen, T., Moldrup, P., and Gamst, J.: Solute diffusion and adsorption in
six soils along a soil texture gradient, Soil Sci. Soc. Am. J., 63,
519–524, https://doi.org/10.2136/sssaj1999.03615995006300030014x, 1999.
Papendick, R. I. and Campbell, G. S.: Theory and measurement of water
potential, in: Water Potential Relations in Soil Microbiology, vol. 9,
Soil Science Society of America Special Publications, Madison, WI, 1–22, https://doi.org/10.2136/sssaspecpub9.c1, 2015.
Parton, W. J., Hartman, M., Ojima, D., and Schimel, D.: DAYCENT and its land
surface submodel: description and testing, Global Planet. Change, 19, 35–48,
https://doi.org/10.1016/S0921-8181(98)00040-X, 1998.
Peng, L., Ni, B. J., Erler, D., Ye, L., and Yuan, Z.: The effect of dissolved
oxygen on N2O production by ammonia-oxidizing bacteria in an enriched
nitrifying sludge, Water Res., 66, 12–21, https://doi.org/10.1016/j.watres.2014.08.009, 2014.
Petersen, S. O. and Andersen, M. N.: Influence of soil water potential and
slurry type on denitrification activity, Soil Biol. Biochem., 28, 977–980,
https://doi.org/10.1016/0038-0717(96)00067-3, 1996.
Petersen, S. O., Henriksen, K., and Blackburn, T. H.: Coupled nitrification-denitrification associated with liquid manure in a
gel-stabilized model system, Biol. Fertil. Soils, 12, 19–27, 1991.
Petersen, S. O., Nielsen, A. L., Haarder, K., and Henriksen, K.: Factors
controlling nitrification and denitrification: a laboratory study with
gel-stabilized liquid cattle manure, Microb. Ecol., 23, 239–255,
https://doi.org/10.1007/BF00164099, 1992.
Petersen, S. O., Nielsen, T. H., Frostegård, Å., and Olesen, T.: O2 uptake, C metabolism and denitrification associated with manure
hot-spots, Soil Biol. Biochem., 28, 341–349,
https://doi.org/10.1016/0038-0717(95)00150-6, 1996.
Petersen, S. O., Nissen, H. H., Lund, I., and Ambus, P.: Redistribution of
slurry components as influenced by injection method, soil, and slurry
properties, J. Environ. Qual., 32, 2399–2409, https://doi.org/10.2134/jeq2003.2399,
2003.
Petersen, S. O., Olsen, A. B., Elsgaard, L., Triolo, J. M., and Sommer, S.
G.: Estimation of methane emissions from slurry pits below pig and cattle
confinements, PLoS One, 11, 1–16, https://doi.org/10.1371/journal.pone.0160968, 2016.
Recous, S., Mary, B., and Faurie, G.: Microbial immobilization of ammonium
and nitrate in cultivated soils, Soil Biol. Biochem., 22, 913–922,
https://doi.org/10.1016/0038-0717(90)90129-N, 1990.
Riedo, M., Grub, A., Rosset, M., and Fuhrer, J.: A pasture simulation model
for dry matter production, and fluxes of carbon, nitrogen, water and energy,
Ecol. Model., 105, 141–183, https://doi.org/10.1016/S0304-3800(97)00110-5, 1998.
Schlüter, S., Henjes, S., Zawallich, J., Bergaust, L., Horn, M., Ippisch, O., Vogel, H. J., and Dörsch, P.: Denitrification in soil aggregate analogues-effect of aggregate size and oxygen diffusion, Front. Environ. Sci., 6, 1–10, https://doi.org/10.3389/fenvs.2018.00017, 2018.
Sexstone, A. J., Parkin, T. B., and Tiedje, J. M.: Temporal response of soil
denitrification rates to rainfall and irrigation, Soil Sci. Soc. Am. J., 49,
99–103, https://doi.org/10.2136/SSSAJ1985.03615995004900010020X, 1985.
Sieczka, A. and Koda, E.: Kinetic and equilibrium studies of sorption of
ammonium in the soil-water environment in agricultural areas of central
poland, Appl. Sci., 6, 269, https://doi.org/10.3390/app6100269, 2016.
Smith, K. A.: A model of the extent of anaerobic zones in aggregated soils,
and its potential application to estimates of denitrification, J. Soil Sci.,
31, 263–277, https://doi.org/10.1111/j.1365-2389.1980.tb02080.x, 1980.
Sozanska, M., Skiba, U. and Metcalfe, S.: Developing an inventory of N2O emissions from British soils, Atmos. Environ., 36, 987–998,
https://doi.org/10.1016/S1352-2310(01)00441-1, 2002.
Syakila, A. and Kroeze, C.: The global nitrous oxide budget revisited,
Greenh. Gas Meas. Manage., 1, 17–26, https://doi.org/10.3763/GHGMM.2010.0007, 2011.
Taghizadeh-Toosi, A., Janz, B., Labouriau, R., Olesen, J. E., Butterbach-Bahl, K., and Petersen, S. O.: Nitrous oxide emissions from red
clover and winter wheat residues depend on interacting effects of
distribution, soil N availability and moisture level, Plant Soil, 466,
121–138, https://doi.org/10.1007/s11104-021-05030-8, 2021.
Thompson, R. L., Lassaletta, L., Patra, P. K., Wilson, C., Wells, K. C.,
Gressent, A., Koffi, E. N., Chipperfield, M. P., Winiwarter, W., Davidson,
E. A., Tian, H., and Canadell, J. G.: Acceleration of global N2O
emissions seen from two decades of atmospheric inversion, Nat. Clim. Change,
9, 993–998, https://doi.org/10.1038/s41558-019-0613-7, 2019.
Tian, H., Xu, R., Canadell, J. G., Thompson, R. L., Winiwarter, W., Suntharalingam, P., Davidson, E. A., Ciais, P., Jackson, R. B., Janssens-Maenhout, G., Prather, M. J., Regnier, P., Pan, N., Pan, S., Peters, G. P., Shi, H., Tubiello, F. N., Zaehle, S., Zhou, F., Arneth, A., Battaglia, G., Berthet, S., Bopp, L., Bouwman, A. F., Buitenhuis, E. T., Chang, J., Chipperfield, M. P., Dangal, S. R. S., Dlugokencky, E., Elkins, J. W., Eyre, B. D., Fu, B., Hall, B., Ito, A., Joos, F., Krummel, P. B., Landolfi, A., Laruelle, G. G., Lauerwald, R., Li, W., Lienert, S., Maavara, T., MacLeod, M., Millet, D. B., Olin, S., Patra, P. K., Prinn, R. G., Raymond, P. A., Ruiz, D. J., van der Werf, G. R., Vuichard, N., Wang, J., Weiss, R. F., Wells, K. C., Wilson, C., Yang, J., and Yao, Y.: A comprehensive quantification of global nitrous oxide sources and sinks, Nature, 586, 248–256, https://doi.org/10.1038/s41586-020-2780-0, 2020.
Wagner-Riddle, C., Baggs, E. M., Clough, T. J., Fuchs, K., and Petersen, S.
O.: Mitigation of nitrous oxide emissions in the context of nitrogen loss
reduction from agroecosystems: managing hot spots and hot moments, Curr. Opin. Environ. Sustain., 47, 46–53, https://doi.org/10.1016/j.cosust.2020.08.002, 2020.
Webb, J., Sørensen, P., Velthof, G., Amon, B., Pinto, M., Rodhe, L.,
Salomon, E., Hutchings, N., Burczyk, P., and Reid, J.: An assessment of the
variation of manure nitrogen efficiency throughout Europe and an appraisal
of means to increase manure-N efficiency, Adv. Agron., 119, 371–442, https://doi.org/10.1016/B978-0-12-407247-3.00007-X, 2013.
World Meteorological Organization: WMO Greenhouse gas bulletin: the state of
greenhouse gases in the atmosphere based on global observations through 2020, https://library.wmo.int/index.php?lvl=notice_display&id=21975#.YgFFTrrMJaQ (last access: 7 February 2022), 2021.
Wrage, N., Velthof, G. L., van Beusichem, M. L., and Oenema, O.: Role of
nitrifier denitrification in the production of nitrous oxide, Soil Biol.
Biochem., 33, 1723–1732, https://doi.org/10.1016/S0038-0717(01)00096-7, 2001.
Zhang, J.: Source code of the N2O model, Zenodo [code], https://doi.org/10.5281/zenodo.8366778, 2023.
Zhu, K., Bruun, S., Larsen, M., Glud, R. N., and Jensen, L. S.: Heterogeneity
of O2 dynamics in soil amended with animal manure and implications for
greenhouse gas emissions, Soil Biol. Biochem., 84, 96–106,
https://doi.org/10.1016/J.SOILBIO.2015.02.012, 2015.
Zimmermann, J., Carolan, R., Forrestal, P., Harty, M., Lanigan, G., Richards, K. G., Roche, L., Whitfield, M. G., and Jones, M. B.: Assessing the performance of three frequently used biogeochemical models when simulating
N2O emissions from a range of soil types and fertiliser treatments,
Geoderma, 331, 53–69, https://doi.org/10.1016/j.geoderma.2018.06.004, 2018.
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.
Manure application to agricultural land often results in large and variable N2O emissions. We...
Altmetrics
Final-revised paper
Preprint