Articles | Volume 16, issue 8
https://doi.org/10.5194/bg-16-1641-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-16-1641-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
18 Apr 2019
Research article |
| 18 Apr 2019
| 18 Apr 2019
Estimating the soil N2O emission intensity of croplands in northwest Europe
School of GeoSciences, University of Edinburgh, Edinburgh EH9 3JN, UK
Mathew Williams
School of GeoSciences, University of Edinburgh, Edinburgh EH9 3JN, UK
Robert M. Rees
Scotland's Rural College (SRUC), West Mains Road, Edinburgh EH9 3JG, UK
Cairistiona F. E. Topp
Scotland's Rural College (SRUC), West Mains Road, Edinburgh EH9 3JG, UK
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Stephanie K. Jones, Carole Helfter, Margaret Anderson, Mhairi Coyle, Claire Campbell, Daniela Famulari, Chiara Di Marco, Netty van Dijk, Y. Sim Tang, Cairistiona F. E. Topp, Ralf Kiese, Reimo Kindler, Jan Siemens, Marion Schrumpf, Klaus Kaiser, Eiko Nemitz, Peter E. Levy, Robert M. Rees, Mark A. Sutton, and Ute M. Skiba
Biogeosciences, 14, 2069–2088, https://doi.org/10.5194/bg-14-2069-2017, https://doi.org/10.5194/bg-14-2069-2017, 2017
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Rhys Whitley, Jason Beringer, Lindsay B. Hutley, Gab Abramowitz, Martin G. De Kauwe, Remko Duursma, Bradley Evans, Vanessa Haverd, Longhui Li, Youngryel Ryu, Benjamin Smith, Ying-Ping Wang, Mathew Williams, and Qiang Yu
Biogeosciences, 13, 3245–3265, https://doi.org/10.5194/bg-13-3245-2016, https://doi.org/10.5194/bg-13-3245-2016, 2016
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D. Fowler, C. E. Steadman, D. Stevenson, M. Coyle, R. M. Rees, U. M. Skiba, M. A. Sutton, J. N. Cape, A. J. Dore, M. Vieno, D. Simpson, S. Zaehle, B. D. Stocker, M. Rinaldi, M. C. Facchini, C. R. Flechard, E. Nemitz, M. Twigg, J. W. Erisman, K. Butterbach-Bahl, and J. N. Galloway
Atmos. Chem. Phys., 15, 13849–13893, https://doi.org/10.5194/acp-15-13849-2015, https://doi.org/10.5194/acp-15-13849-2015, 2015
C. Safta, D. M. Ricciuto, K. Sargsyan, B. Debusschere, H. N. Najm, M. Williams, and P. E. Thornton
Geosci. Model Dev., 8, 1899–1918, https://doi.org/10.5194/gmd-8-1899-2015, https://doi.org/10.5194/gmd-8-1899-2015, 2015
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In this paper we propose a probabilistic framework for an uncertainty quantification study of a carbon cycle model and focus on the comparison between steady-state and transient
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L. Rowland, A. Harper, B. O. Christoffersen, D. R. Galbraith, H. M. A. Imbuzeiro, T. L. Powell, C. Doughty, N. M. Levine, Y. Malhi, S. R. Saleska, P. R. Moorcroft, P. Meir, and M. Williams
Geosci. Model Dev., 8, 1097–1110, https://doi.org/10.5194/gmd-8-1097-2015, https://doi.org/10.5194/gmd-8-1097-2015, 2015
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This study evaluates the capability of five vegetation models to simulate the response of forest productivity to changes in temperature and drought, using data collected from an Amazonian forest. This study concludes that model consistencies in the responses of net canopy carbon production to temperature and precipitation change were the result of inconsistently modelled leaf-scale process responses and substantial variation in modelled leaf area responses.
A. A. Bloom and M. Williams
Biogeosciences, 12, 1299–1315, https://doi.org/10.5194/bg-12-1299-2015, https://doi.org/10.5194/bg-12-1299-2015, 2015
D. Slevin, S. F. B. Tett, and M. Williams
Geosci. Model Dev., 8, 295–316, https://doi.org/10.5194/gmd-8-295-2015, https://doi.org/10.5194/gmd-8-295-2015, 2015
G. B. Bonan, M. Williams, R. A. Fisher, and K. W. Oleson
Geosci. Model Dev., 7, 2193–2222, https://doi.org/10.5194/gmd-7-2193-2014, https://doi.org/10.5194/gmd-7-2193-2014, 2014
R. Q. Thomas and M. Williams
Geosci. Model Dev., 7, 2015–2037, https://doi.org/10.5194/gmd-7-2015-2014, https://doi.org/10.5194/gmd-7-2015-2014, 2014
G. Xenakis and M. Williams
Geosci. Model Dev., 7, 1519–1533, https://doi.org/10.5194/gmd-7-1519-2014, https://doi.org/10.5194/gmd-7-1519-2014, 2014
T. L. Smallman, M. Williams, and J. B. Moncrieff
Biogeosciences, 11, 735–747, https://doi.org/10.5194/bg-11-735-2014, https://doi.org/10.5194/bg-11-735-2014, 2014
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Climate change is causing an increase in extreme wildfires in Europe, but drivers of fire are not well understood, especially across different land cover types. We used statistical models with satellite data, climate data, and socioeconomic data to determine what affects burning in cropland and non-cropland 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
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This study investigates present-day carbon cycle variables in CMIP5 and CMIP6 simulations. Overall, CMIP6 models perform better but also show many remaining biases. A significant improvement in the simulation of photosynthesis in models with a nitrogen cycle is found, with only small differences between emission- and concentration-based simulations. Thus, we recommend using emission-driven simulations in CMIP7 by default and including the nitrogen cycle in all future carbon cycle models.
Sven Armin Westermann, Anke Hildebrandt, Souhail Bousetta, and Stephan Thober
Biogeosciences, 21, 5277–5303, https://doi.org/10.5194/bg-21-5277-2024, https://doi.org/10.5194/bg-21-5277-2024, 2024
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Plants at the land surface mediate between soil and the atmosphere regarding water and carbon transport. Since plant growth is a dynamic process, models need to consider these dynamics. Two models that predict water and carbon fluxes by considering plant temporal evolution were tested against observational data. Currently, dynamizing plants in these models did not enhance their representativeness, which is caused by a mismatch between implemented physical relations and observable connections.
Kamal Nyaupane, Umakant Mishra, Feng Tao, Kyongmin Yeo, William J. Riley, Forrest M. Hoffman, and Sagar Gautam
Biogeosciences, 21, 5173–5183, https://doi.org/10.5194/bg-21-5173-2024, https://doi.org/10.5194/bg-21-5173-2024, 2024
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Representing soil organic carbon (SOC) dynamics in Earth system models (ESMs) is a key source of uncertainty in predicting carbon–climate feedbacks. Using machine learning, we develop and compare predictive relationships in observations (Obs) and ESMs. We find different relationships between environmental factors and SOC stocks in Obs and ESMs. SOC prediction in ESMs may be improved by representing the functional relationships of environmental controllers in a way consistent with observations.
Jacob A. Nelson, Sophia Walther, Fabian Gans, Basil Kraft, Ulrich Weber, Kimberly Novick, Nina Buchmann, Mirco Migliavacca, Georg Wohlfahrt, Ladislav Šigut, Andreas Ibrom, Dario Papale, Mathias Göckede, Gregory Duveiller, Alexander Knohl, Lukas Hörtnagl, Russell L. Scott, Weijie Zhang, Zayd Mahmoud Hamdi, Markus Reichstein, Sergio Aranda-Barranco, Jonas Ardö, Maarten Op de Beeck, Dave Billesbach, David Bowling, Rosvel Bracho, Christian Brümmer, Gustau Camps-Valls, Shiping Chen, Jamie Rose Cleverly, Ankur Desai, Gang Dong, Tarek S. El-Madany, Eugenie Susanne Euskirchen, Iris Feigenwinter, Marta Galvagno, Giacomo A. Gerosa, Bert Gielen, Ignacio Goded, Sarah Goslee, Christopher Michael Gough, Bernard Heinesch, Kazuhito Ichii, Marcin Antoni Jackowicz-Korczynski, Anne Klosterhalfen, Sara Knox, Hideki Kobayashi, Kukka-Maaria Kohonen, Mika Korkiakoski, Ivan Mammarella, Mana Gharun, Riccardo Marzuoli, Roser Matamala, Stefan Metzger, Leonardo Montagnani, Giacomo Nicolini, Thomas O'Halloran, Jean-Marc Ourcival, Matthias Peichl, Elise Pendall, Borja Ruiz Reverter, Marilyn Roland, Simone Sabbatini, Torsten Sachs, Marius Schmidt, Christopher R. Schwalm, Ankit Shekhar, Richard Silberstein, Maria Lucia Silveira, Donatella Spano, Torbern Tagesson, Gianluca Tramontana, Carlo Trotta, Fabio Turco, Timo Vesala, Caroline Vincke, Domenico Vitale, Enrique R. Vivoni, Yi Wang, William Woodgate, Enrico A. Yepez, Junhui Zhang, Donatella Zona, and Martin Jung
Biogeosciences, 21, 5079–5115, https://doi.org/10.5194/bg-21-5079-2024, https://doi.org/10.5194/bg-21-5079-2024, 2024
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The movement of water, carbon, and energy from the Earth's surface to the atmosphere, or flux, is an important process to understand because it impacts our lives. Here, we outline a method called FLUXCOM-X to estimate global water and CO2 fluxes based on direct measurements from sites around the world. We go on to demonstrate how these new estimates of net CO2 uptake/loss, gross CO2 uptake, total water evaporation, and transpiration from plants compare to previous and independent estimates.
Xin Chen, Tiexi Chen, Xiaodong Li, Yuanfang Chai, Shengjie Zhou, Renjie Guo, and Jie Dai
Biogeosciences, 21, 4285–4300, https://doi.org/10.5194/bg-21-4285-2024, https://doi.org/10.5194/bg-21-4285-2024, 2024
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We provide an ensemble-model-based GPP dataset (ERF_GPP) that explains 85.1 % of the monthly variation in GPP across 170 sites, which is higher than other GPP estimate models. In addition, ERF_GPP improves the phenomenon of “high-value underestimation and low-value overestimation” in GPP estimation to some extent. Overall, ERF_GPP provides a more reliable estimate of global GPP and will facilitate further development of carbon cycle research.
Reza Kusuma Nurrohman, Tomomichi Kato, Hideki Ninomiya, Lea Végh, Nicolas Delbart, Tatsuya Miyauchi, Hisashi Sato, Tomohiro Shiraishi, and Ryuichi Hirata
Biogeosciences, 21, 4195–4227, https://doi.org/10.5194/bg-21-4195-2024, https://doi.org/10.5194/bg-21-4195-2024, 2024
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SPITFIRE (SPread and InTensity of FIRE) was integrated into a spatially explicit individual-based dynamic global vegetation model to improve the accuracy of depicting Siberian forest fire frequency, intensity, and extent. Fires showed increased greenhouse gas and aerosol emissions in 2006–2100 for Representative Concentration Pathways. This study contributes to understanding fire dynamics, land ecosystem–climate interactions, and global material cycles under the threat of escalating fires.
Stefano Manzoni and M. Francesca Cotrufo
Biogeosciences, 21, 4077–4098, https://doi.org/10.5194/bg-21-4077-2024, https://doi.org/10.5194/bg-21-4077-2024, 2024
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Organic carbon and nitrogen are stabilized in soils via microbial assimilation and stabilization of necromass (in vivo pathway) or via adsorption of the products of extracellular decomposition (ex vivo pathway). Here we use a diagnostic model to quantify which stabilization pathway is prevalent using data on residue-derived carbon and nitrogen incorporation in mineral-associated organic matter. We find that the in vivo pathway is dominant in fine-textured soils with low organic matter content.
Huajie Zhu, Xiuli Xing, Mousong Wu, Weimin Ju, and Fei Jiang
Biogeosciences, 21, 3735–3760, https://doi.org/10.5194/bg-21-3735-2024, https://doi.org/10.5194/bg-21-3735-2024, 2024
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Ecosystem carbonyl sulfide (COS) fluxes were employed to optimize GPP estimation across ecosystems with the Biosphere-atmosphere Exchange Process Simulator (BEPS), which was developed for simulating the canopy COS uptake under its state-of-the-art two-leaf modeling framework. Our results showcased the efficacy of COS in improving model prediction and reducing prediction uncertainty of GPP and enhanced insights into the sensitivity, identifiability, and interactions of parameters related to COS.
Moritz Laub, Magdalena Necpalova, Marijn Van de Broek, Marc Corbeels, Samuel Mathu Ndungu, Monicah Wanjiku Mucheru-Muna, Daniel Mugendi, Rebecca Yegon, Wycliffe Waswa, Bernard Vanlauwe, and Johan Six
Biogeosciences, 21, 3691–3716, https://doi.org/10.5194/bg-21-3691-2024, https://doi.org/10.5194/bg-21-3691-2024, 2024
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We used the DayCent model to assess the potential impact of integrated soil fertility management (ISFM) on maize production, soil fertility, and greenhouse gas emission in Kenya. After adjustments, DayCent represented measured mean yields and soil carbon stock changes well and N2O emissions acceptably. Our results showed that soil fertility losses could be reduced but not completely eliminated with ISFM and that, while N2O emissions increased with ISFM, emissions per kilogram yield decreased.
Hazel Cathcart, Julian Aherne, Michael D. Moran, Verica Savic-Jovcic, Paul A. Makar, and Amanda Cole
EGUsphere, https://doi.org/10.5194/egusphere-2024-2371, https://doi.org/10.5194/egusphere-2024-2371, 2024
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Deposition from sulfur and nitrogen pollution can harm ecosystems, and recovery from this type of pollution can take decades or longer. To identify risk to Canadian soils, we created maps showing sensitivity to sulfur and nitrogen pollution. Results show that some ecosystems are at risk from acid and nutrient nitrogen deposition; 10 % of protected areas are receiving acid deposition beyond their damage threshold and 70 % may be receiving nitrogen deposition that could cause biodiversity loss.
Erik Schwarz, Samia Ghersheen, Salim Belyazid, and Stefano Manzoni
Biogeosciences, 21, 3441–3461, https://doi.org/10.5194/bg-21-3441-2024, https://doi.org/10.5194/bg-21-3441-2024, 2024
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The occurrence of unstable equilibrium points (EPs) could impede the applicability of microbial-explicit soil organic carbon models. For archetypal model versions we identify when instability can occur and describe mathematical conditions to avoid such unstable EPs. We discuss implications for further model development, highlighting the important role of considering basic ecological principles to ensure biologically meaningful models.
Sian Kou-Giesbrecht, Vivek K. Arora, Christian Seiler, and Libo Wang
Biogeosciences, 21, 3339–3371, https://doi.org/10.5194/bg-21-3339-2024, https://doi.org/10.5194/bg-21-3339-2024, 2024
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Terrestrial biosphere models can either prescribe the geographical distribution of biomes or simulate them dynamically, capturing climate-change-driven biome shifts. We isolate and examine the differences between these different land cover implementations. We find that the simulated terrestrial carbon sink at the end of the 21st century is twice as large in simulations with dynamic land cover than in simulations with prescribed land cover due to important range shifts in the Arctic and Amazon.
Elizabeth S. Duan, Luciana Chavez Rodriguez, Nicole Hemming-Schroeder, Baptiste Wijas, Habacuc Flores-Moreno, Alexander W. Cheesman, Lucas A. Cernusak, Michael J. Liddell, Paul Eggleton, Amy E. Zanne, and Steven D. Allison
Biogeosciences, 21, 3321–3338, https://doi.org/10.5194/bg-21-3321-2024, https://doi.org/10.5194/bg-21-3321-2024, 2024
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Understanding the link between climate and carbon fluxes is crucial for predicting how climate change will impact carbon sinks. We estimated carbon dioxide (CO2) fluxes from deadwood in tropical Australia using wood moisture content and temperature. Our model predicted that the majority of deadwood carbon is released as CO2, except when termite activity is detected. Future models should also incorporate wood traits, like species and chemical composition, to better predict fluxes.
Daniel Nadal-Sala, Rüdiger Grote, David Kraus, Uri Hochberg, Tamir Klein, Yael Wagner, Fedor Tatarinov, Dan Yakir, and Nadine K. Ruehr
Biogeosciences, 21, 2973–2994, https://doi.org/10.5194/bg-21-2973-2024, https://doi.org/10.5194/bg-21-2973-2024, 2024
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A hydraulic model approach is presented that can be added to any physiologically based ecosystem model. Simulated plant water potential triggers stomatal closure, photosynthesis decline, root–soil resistance increases, and sapwood and foliage senescence. The model has been evaluated at an extremely dry site stocked with Aleppo pine and was able to represent gas exchange, soil water content, and plant water potential. The model also responded realistically regarding leaf senescence.
Patrick Neri, Lianhong Gu, and Yang Song
Biogeosciences, 21, 2731–2758, https://doi.org/10.5194/bg-21-2731-2024, https://doi.org/10.5194/bg-21-2731-2024, 2024
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A first-of-its-kind global-scale model of temperature resilience and tolerance of photosystem II maximum quantum yield informs how plants maintain their efficiency of converting light energy to chemical energy for photosynthesis under temperature changes. Our finding explores this variation across plant functional types and habitat climatology, highlighting diverse temperature response strategies and a method to improve global-scale photosynthesis modeling under climate change.
Liyuan He, Jorge L. Mazza Rodrigues, Melanie A. Mayes, Chun-Ta Lai, David A. Lipson, and Xiaofeng Xu
Biogeosciences, 21, 2313–2333, https://doi.org/10.5194/bg-21-2313-2024, https://doi.org/10.5194/bg-21-2313-2024, 2024
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Soil microbes are the driving engine for biogeochemical cycles of carbon and nutrients. This study applies a microbial-explicit model to quantify bacteria and fungal biomass carbon in soils from 1901 to 2016. Results showed substantial increases in bacterial and fungal biomass carbon over the past century, jointly influenced by vegetation growth and soil temperature and moisture. This pioneering century-long estimation offers crucial insights into soil microbial roles in global carbon cycling.
Tao Chen, Félicien Meunier, Marc Peaucelle, Guoping Tang, Ye Yuan, and Hans Verbeeck
Biogeosciences, 21, 2253–2272, https://doi.org/10.5194/bg-21-2253-2024, https://doi.org/10.5194/bg-21-2253-2024, 2024
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Chinese subtropical forest ecosystems are an extremely important component of global forest ecosystems and hence crucial for the global carbon cycle and regional climate change. However, there is still great uncertainty in the relationship between subtropical forest carbon sequestration and its drivers. We provide first quantitative estimates of the individual and interactive effects of different drivers on the gross primary productivity changes of various subtropical forest types in China.
Ke Liu, Yujie Wang, Troy S. Magney, and Christian Frankenberg
Biogeosciences, 21, 1501–1516, https://doi.org/10.5194/bg-21-1501-2024, https://doi.org/10.5194/bg-21-1501-2024, 2024
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Stomata are pores on leaves that regulate gas exchange between plants and the atmosphere. Existing land models unrealistically assume stomata can jump between steady states when the environment changes. We implemented dynamic modeling to predict gradual stomatal responses at different scales. Results suggested that considering this effect on plant behavior patterns in diurnal cycles was important. Our framework also simplified simulations and can contribute to further efficiency improvements.
Melanie A. Thurner, Silvia Caldararu, Jan Engel, Anja Rammig, and Sönke Zaehle
Biogeosciences, 21, 1391–1410, https://doi.org/10.5194/bg-21-1391-2024, https://doi.org/10.5194/bg-21-1391-2024, 2024
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Due to their crucial role in terrestrial ecosystems, we implemented mycorrhizal fungi into the QUINCY terrestrial biosphere model. Fungi interact with mineral and organic soil to support plant N uptake and, thus, plant growth. Our results suggest that the effect of mycorrhizal interactions on simulated ecosystem dynamics is minor under constant environmental conditions but necessary to reproduce and understand observed patterns under changing conditions, such as rising atmospheric CO2.
Jinyun Tang and William J. Riley
Biogeosciences, 21, 1061–1070, https://doi.org/10.5194/bg-21-1061-2024, https://doi.org/10.5194/bg-21-1061-2024, 2024
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A chemical kinetics theory is proposed to explain the non-monotonic relationship between temperature and biochemical rates. It incorporates the observed thermally reversible enzyme denaturation that is ensured by the ceaseless thermal motion of molecules and ions in an enzyme solution and three well-established theories: (1) law of mass action, (2) diffusion-limited chemical reaction theory, and (3) transition state theory.
Nina Raoult, Louis-Axel Edouard-Rambaut, Nicolas Vuichard, Vladislav Bastrikov, Anne Sofie Lansø, Bertrand Guenet, and Philippe Peylin
Biogeosciences, 21, 1017–1036, https://doi.org/10.5194/bg-21-1017-2024, https://doi.org/10.5194/bg-21-1017-2024, 2024
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Observations are used to reduce uncertainty in land surface models (LSMs) by optimising poorly constraining parameters. However, optimising against current conditions does not necessarily ensure that the parameters treated as invariant will be robust in a changing climate. Manipulation experiments offer us a unique chance to optimise our models under different (here atmospheric CO2) conditions. By using these data in optimisations, we gain confidence in the future projections of LSMs.
Kelsey T. Foster, Wu Sun, Yoichi P. Shiga, Jiafu Mao, and Anna M. Michalak
Biogeosciences, 21, 869–891, https://doi.org/10.5194/bg-21-869-2024, https://doi.org/10.5194/bg-21-869-2024, 2024
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Assessing agreement between bottom-up and top-down methods across spatial scales can provide insights into the relationship between ensemble spread (difference across models) and model accuracy (difference between model estimates and reality). We find that ensemble spread is unlikely to be a good indicator of actual uncertainty in the North American carbon balance. However, models that are consistent with atmospheric constraints show stronger agreement between top-down and bottom-up estimates.
Victoria R. Dutch, Nick Rutter, Leanne Wake, Oliver Sonnentag, Gabriel Hould Gosselin, Melody Sandells, Chris Derksen, Branden Walker, Gesa Meyer, Richard Essery, Richard Kelly, Phillip Marsh, Julia Boike, and Matteo Detto
Biogeosciences, 21, 825–841, https://doi.org/10.5194/bg-21-825-2024, https://doi.org/10.5194/bg-21-825-2024, 2024
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We undertake a sensitivity study of three different parameters on the simulation of net ecosystem exchange (NEE) during the snow-covered non-growing season at an Arctic tundra site. Simulations are compared to eddy covariance measurements, with near-zero NEE simulated despite observed CO2 release. We then consider how to parameterise the model better in Arctic tundra environments on both sub-seasonal timescales and cumulatively throughout the snow-covered non-growing season.
Bertrand Guenet, Jérémie Orliac, Lauric Cécillon, Olivier Torres, Laura Sereni, Philip A. Martin, Pierre Barré, and Laurent Bopp
Biogeosciences, 21, 657–669, https://doi.org/10.5194/bg-21-657-2024, https://doi.org/10.5194/bg-21-657-2024, 2024
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Heterotrophic respiration fluxes are a major flux between surfaces and the atmosphere, but Earth system models do not yet represent them correctly. Here we benchmarked Earth system models against observation-based products, and we identified the important mechanisms that need to be improved in the next-generation Earth system models.
Shuyue Li, Bonnie Waring, Jennifer Powers, and David Medvigy
Biogeosciences, 21, 455–471, https://doi.org/10.5194/bg-21-455-2024, https://doi.org/10.5194/bg-21-455-2024, 2024
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We used an ecosystem model to simulate primary production of a tropical forest subjected to 3 years of nutrient fertilization. Simulations parameterized such that relative allocation to fine roots increased with increasing soil phosphorus had leaf, wood, and fine root production consistent with observations. However, these simulations seemed to over-allocate to fine roots on multidecadal timescales, affecting aboveground biomass. Additional observations across timescales would benefit models.
Stephen Björn Wirth, Arne Poyda, Friedhelm Taube, Britta Tietjen, Christoph Müller, Kirsten Thonicke, Anja Linstädter, Kai Behn, Sibyll Schaphoff, Werner von Bloh, and Susanne Rolinski
Biogeosciences, 21, 381–410, https://doi.org/10.5194/bg-21-381-2024, https://doi.org/10.5194/bg-21-381-2024, 2024
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In dynamic global vegetation models (DGVMs), the role of functional diversity in forage supply and soil organic carbon storage of grasslands is not explicitly taken into account. We introduced functional diversity into the Lund Potsdam Jena managed Land (LPJmL) DGVM using CSR theory. The new model reproduced well-known trade-offs between plant traits and can be used to quantify the role of functional diversity in climate change mitigation using different functional diversity scenarios.
Joe R. McNorton and Francesca Di Giuseppe
Biogeosciences, 21, 279–300, https://doi.org/10.5194/bg-21-279-2024, https://doi.org/10.5194/bg-21-279-2024, 2024
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Wildfires have wide-ranging consequences for local communities, air quality and ecosystems. Vegetation amount and moisture state are key components to forecast wildfires. We developed a combined model and satellite framework to characterise vegetation, including the type of fuel, whether it is alive or dead, and its moisture content. The daily data is at high resolution globally (~9 km). Our characteristics correlate with active fire data and can inform fire danger and spread modelling efforts.
Brooke A. Eastman, William R. Wieder, Melannie D. Hartman, Edward R. Brzostek, and William T. Peterjohn
Biogeosciences, 21, 201–221, https://doi.org/10.5194/bg-21-201-2024, https://doi.org/10.5194/bg-21-201-2024, 2024
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We compared soil model performance to data from a long-term nitrogen addition experiment in a forested ecosystem. We found that in order for soil carbon models to accurately predict future forest carbon sequestration, two key processes must respond dynamically to nitrogen availability: (1) plant allocation of carbon to wood versus roots and (2) rates of soil organic matter decomposition. Long-term experiments can help improve our predictions of the land carbon sink and its climate impact.
Jan De Pue, Sebastian Wieneke, Ana Bastos, José Miguel Barrios, Liyang Liu, Philippe Ciais, Alirio Arboleda, Rafiq Hamdi, Maral Maleki, Fabienne Maignan, Françoise Gellens-Meulenberghs, Ivan Janssens, and Manuela Balzarolo
Biogeosciences, 20, 4795–4818, https://doi.org/10.5194/bg-20-4795-2023, https://doi.org/10.5194/bg-20-4795-2023, 2023
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The gross primary production (GPP) of the terrestrial biosphere is a key source of variability in the global carbon cycle. To estimate this flux, models can rely on remote sensing data (RS-driven), meteorological data (meteo-driven) or a combination of both (hybrid). An intercomparison of 11 models demonstrated that RS-driven models lack the sensitivity to short-term anomalies. Conversely, the simulation of soil moisture dynamics and stress response remains a challenge in meteo-driven models.
Chad A. Burton, Luigi J. Renzullo, Sami W. Rifai, and Albert I. J. M. Van Dijk
Biogeosciences, 20, 4109–4134, https://doi.org/10.5194/bg-20-4109-2023, https://doi.org/10.5194/bg-20-4109-2023, 2023
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Australia's land-based ecosystems play a critical role in controlling the variability in the global land carbon sink. However, uncertainties in the methods used for quantifying carbon fluxes limit our understanding. We develop high-resolution estimates of Australia's land carbon fluxes using machine learning methods and find that Australia is, on average, a stronger carbon sink than previously thought and that the seasonal dynamics of the fluxes differ from those described by other methods.
Yuan Yan, Anne Klosterhalfen, Fernando Moyano, Matthias Cuntz, Andrew C. Manning, and Alexander Knohl
Biogeosciences, 20, 4087–4107, https://doi.org/10.5194/bg-20-4087-2023, https://doi.org/10.5194/bg-20-4087-2023, 2023
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A better understanding of O2 fluxes, their exchange ratios with CO2 and their interrelations with environmental conditions would provide further insights into biogeochemical ecosystem processes. We, therefore, used the multilayer canopy model CANVEG to simulate and analyze the flux exchange for our forest study site for 2012–2016. Based on these simulations, we further successfully tested the application of various micrometeorological methods and the prospects of real O2 flux measurements.
Jie Zhang, Elisabeth Larsen Kolstad, Wenxin Zhang, Iris Vogeler, and Søren O. Petersen
Biogeosciences, 20, 3895–3917, https://doi.org/10.5194/bg-20-3895-2023, https://doi.org/10.5194/bg-20-3895-2023, 2023
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Manure application to agricultural land often results in large and variable N2O emissions. We propose a model with a parsimonious structure to investigate N transformations around such N2O hotspots. The model allows for new detailed insights into the interactions between transport and microbial activities regarding N2O emissions in heterogeneous soil environments. It highlights the importance of solute diffusion to N2O emissions from such hotspots which are often ignored by process-based models.
Jukka Alm, Antti Wall, Jukka-Pekka Myllykangas, Paavo Ojanen, Juha Heikkinen, Helena M. Henttonen, Raija Laiho, Kari Minkkinen, Tarja Tuomainen, and Juha Mikola
Biogeosciences, 20, 3827–3855, https://doi.org/10.5194/bg-20-3827-2023, https://doi.org/10.5194/bg-20-3827-2023, 2023
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In Finland peatlands cover one-third of land area. For half of those, with 4.3 Mha being drained for forestry, Finland reports sinks and sources of greenhouse gases in forest lands on organic soils following its UNFCCC commitment. We describe a new method for compiling soil CO2 balance that follows changes in tree volume, tree harvests and temperature. An increasing trend of emissions from 1.4 to 7.9 Mt CO2 was calculated for drained peatland forest soils in Finland for 1990–2021.
Siqi Li, Bo Zhu, Xunhua Zheng, Pengcheng Hu, Shenghui Han, Jihui Fan, Tao Wang, Rui Wang, Kai Wang, Zhisheng Yao, Chunyan Liu, Wei Zhang, and Yong Li
Biogeosciences, 20, 3555–3572, https://doi.org/10.5194/bg-20-3555-2023, https://doi.org/10.5194/bg-20-3555-2023, 2023
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Physical soil erosion and particulate carbon, nitrogen and phosphorus loss modules were incorporated into the process-oriented hydro-biogeochemical model CNMM-DNDC to realize the accurate simulation of water-induced erosion and subsequent particulate nutrient losses at high spatiotemporal resolution.
Ivan Cornut, Nicolas Delpierre, Jean-Paul Laclau, Joannès Guillemot, Yann Nouvellon, Otavio Campoe, Jose Luiz Stape, Vitoria Fernanda Santos, and Guerric le Maire
Biogeosciences, 20, 3093–3117, https://doi.org/10.5194/bg-20-3093-2023, https://doi.org/10.5194/bg-20-3093-2023, 2023
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Potassium is an essential element for living organisms. Trees are dependent upon this element for certain functions that allow them to build their trunks using carbon dioxide. Using data from experiments in eucalypt plantations in Brazil and a simplified computer model of the plantations, we were able to investigate the effect that a lack of potassium can have on the production of wood. Understanding nutrient cycles is useful to understand the response of forests to environmental change.
Ivan Cornut, Guerric le Maire, Jean-Paul Laclau, Joannès Guillemot, Yann Nouvellon, and Nicolas Delpierre
Biogeosciences, 20, 3119–3135, https://doi.org/10.5194/bg-20-3119-2023, https://doi.org/10.5194/bg-20-3119-2023, 2023
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After simulating the effects of low levels of potassium on the canopy of trees and the uptake of carbon dioxide from the atmosphere by leaves in Part 1, here we tried to simulate the way the trees use the carbon they have acquired and the interaction with the potassium cycle in the tree. We show that the effect of low potassium on the efficiency of the trees in acquiring carbon is enough to explain why they produce less wood when they are in soils with low levels of potassium.
Xiaojuan Yang, Peter Thornton, Daniel Ricciuto, Yilong Wang, and Forrest Hoffman
Biogeosciences, 20, 2813–2836, https://doi.org/10.5194/bg-20-2813-2023, https://doi.org/10.5194/bg-20-2813-2023, 2023
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We evaluated the performance of a land surface model (ELMv1-CNP) that includes both nitrogen (N) and phosphorus (P) limitation on carbon cycle processes. We show that ELMv1-CNP produces realistic estimates of present-day carbon pools and fluxes. We show that global C sources and sinks are significantly affected by P limitation. Our study suggests that introduction of P limitation in land surface models is likely to have substantial consequences for projections of future carbon uptake.
Kevin R. Wilcox, Scott L. Collins, Alan K. Knapp, William Pockman, Zheng Shi, Melinda D. Smith, and Yiqi Luo
Biogeosciences, 20, 2707–2725, https://doi.org/10.5194/bg-20-2707-2023, https://doi.org/10.5194/bg-20-2707-2023, 2023
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The capacity for carbon storage (C capacity) is an attribute that determines how ecosystems store carbon in the future. Here, we employ novel data–model integration techniques to identify the carbon capacity of six grassland sites spanning the US Great Plains. Hot and dry sites had low C capacity due to less plant growth and high turnover of soil C, so they may be a C source in the future. Alternately, cooler and wetter ecosystems had high C capacity, so these systems may be a future C sink.
Ara Cho, Linda M. J. Kooijmans, Kukka-Maaria Kohonen, Richard Wehr, and Maarten C. Krol
Biogeosciences, 20, 2573–2594, https://doi.org/10.5194/bg-20-2573-2023, https://doi.org/10.5194/bg-20-2573-2023, 2023
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Carbonyl sulfide (COS) is a useful constraint for estimating photosynthesis. To simulate COS leaf flux better in the SiB4 model, we propose a novel temperature function for enzyme carbonic anhydrase (CA) activity and optimize conductances using observations. The optimal activity of CA occurs below 40 °C, and Ball–Woodrow–Berry parameters are slightly changed. These reduce/increase uptakes in the tropics/higher latitudes and contribute to resolving discrepancies in the COS global budget.
Yunyao Ma, Bettina Weber, Alexandra Kratz, José Raggio, Claudia Colesie, Maik Veste, Maaike Y. Bader, and Philipp Porada
Biogeosciences, 20, 2553–2572, https://doi.org/10.5194/bg-20-2553-2023, https://doi.org/10.5194/bg-20-2553-2023, 2023
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We found that the modelled annual carbon balance of biocrusts is strongly affected by both the environment (mostly air temperature and CO2 concentration) and physiology, such as temperature response of respiration. However, the relative impacts of these drivers vary across regions with different climates. Uncertainty in driving factors may lead to unrealistic carbon balance estimates, particularly in temperate climates, and may be explained by seasonal variation of physiology due to acclimation.
Alexander J. Norton, A. Anthony Bloom, Nicholas C. Parazoo, Paul A. Levine, Shuang Ma, Renato K. Braghiere, and T. Luke Smallman
Biogeosciences, 20, 2455–2484, https://doi.org/10.5194/bg-20-2455-2023, https://doi.org/10.5194/bg-20-2455-2023, 2023
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This study explores how the representation of leaf phenology affects our ability to predict changes to the carbon balance of land ecosystems. We calibrate a new leaf phenology model against a diverse range of observations at six forest sites, showing that it improves the predictive capability of the processes underlying the ecosystem carbon balance. We then show how changes in temperature and rainfall affect the ecosystem carbon balance with this new model.
Libo Wang, Vivek K. Arora, Paul Bartlett, Ed Chan, and Salvatore R. Curasi
Biogeosciences, 20, 2265–2282, https://doi.org/10.5194/bg-20-2265-2023, https://doi.org/10.5194/bg-20-2265-2023, 2023
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Plant functional types (PFTs) are groups of plant species used to represent vegetation distribution in land surface models. There are large uncertainties associated with existing methods for mapping land cover datasets to PFTs. This study demonstrates how fine-resolution tree cover fraction and land cover datasets can be used to inform the PFT mapping process and reduce the uncertainties. The proposed largely objective method makes it easier to implement new land cover products in models.
Jennifer A. Holm, David M. Medvigy, Benjamin Smith, Jeffrey S. Dukes, Claus Beier, Mikhail Mishurov, Xiangtao Xu, Jeremy W. Lichstein, Craig D. Allen, Klaus S. Larsen, Yiqi Luo, Cari Ficken, William T. Pockman, William R. L. Anderegg, and Anja Rammig
Biogeosciences, 20, 2117–2142, https://doi.org/10.5194/bg-20-2117-2023, https://doi.org/10.5194/bg-20-2117-2023, 2023
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Unprecedented climate extremes (UCEs) are expected to have dramatic impacts on ecosystems. We present a road map of how dynamic vegetation models can explore extreme drought and climate change and assess ecological processes to measure and reduce model uncertainties. The models predict strong nonlinear responses to UCEs. Due to different model representations, the models differ in magnitude and trajectory of forest loss. Therefore, we explore specific plant responses that reflect knowledge gaps.
Veronika Kronnäs, Klas Lucander, Giuliana Zanchi, Nadja Stadlinger, Salim Belyazid, and Cecilia Akselsson
Biogeosciences, 20, 1879–1899, https://doi.org/10.5194/bg-20-1879-2023, https://doi.org/10.5194/bg-20-1879-2023, 2023
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In a future climate, extreme droughts might become more common. Climate change and droughts can have negative effects on soil weathering and plant health.
In this study, climate change effects on weathering were studied on sites in Sweden using the model ForSAFE, a climate change scenario and an extreme drought scenario. The modelling shows that weathering is higher during summer and increases with global warming but that weathering during drought summers can become as low as winter weathering.
Agustín Sarquis and Carlos A. Sierra
Biogeosciences, 20, 1759–1771, https://doi.org/10.5194/bg-20-1759-2023, https://doi.org/10.5194/bg-20-1759-2023, 2023
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Although plant litter is chemically and physically heterogenous and undergoes multiple transformations, models that represent litter dynamics often ignore this complexity. We used a multi-model inference framework to include information content in litter decomposition datasets and studied the time it takes for litter to decompose as measured by the transit time. In arid lands, the median transit time of litter is about 3 years and has a negative correlation with mean annual temperature.
Qi Guan, Jing Tang, Lian Feng, Stefan Olin, and Guy Schurgers
Biogeosciences, 20, 1635–1648, https://doi.org/10.5194/bg-20-1635-2023, https://doi.org/10.5194/bg-20-1635-2023, 2023
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Understanding terrestrial sources of nitrogen is vital to examine lake eutrophication changes. Combining process-based ecosystem modeling and satellite observations, we found that land-leached nitrogen in the Yangtze Plain significantly increased from 1979 to 2018, and terrestrial nutrient sources were positively correlated with eutrophication trends observed in most lakes, demonstrating the necessity of sustainable nitrogen management to control eutrophication.
Vivek K. Arora, Christian Seiler, Libo Wang, and Sian Kou-Giesbrecht
Biogeosciences, 20, 1313–1355, https://doi.org/10.5194/bg-20-1313-2023, https://doi.org/10.5194/bg-20-1313-2023, 2023
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The behaviour of natural systems is now very often represented through mathematical models. These models represent our understanding of how nature works. Of course, nature does not care about our understanding. Since our understanding is not perfect, evaluating models is challenging, and there are uncertainties. This paper illustrates this uncertainty for land models and argues that evaluating models in light of the uncertainty in various components provides useful information.
Cited articles
Baggs, E. M., Rees, R. M., and Smith, K. A.: Nitrous oxide emission from
soils
after incorporating crop residues, Soil Use Manage., 16, 82–87,
2000. a
Balkovia, J., van der Velde, M., Schmid, E., Skalsky, R., Khabarov, N.,
Obersteiner, M., Stürmer, B., and Xiong, W.: Pan-European crop modelling
with EPIC: Implementation, up-scaling and regional crop yield validation,
Agr. Syst., 120, 61–75, 2013. a
Baobao, P., Shu, K. L., Arvin, M., Yiqi, L., and Deli, C.: Ammonia
volatilization from synthetic fertilizers and its mitigation strategies: A
global synthesis, Agr. Ecosyst. Environ., 232, 283–289,
https://doi.org/10.1016/j.agee.2016.08.019, 2016. a
Batjes, N. H.: Harmonized soil property values for broad-scale modelling
(WISE30sec) with estimates of global soil carbon stocks, Geoderma, 269,
61–68, 2016. a
Bellocchi, G., Rivington, M., Matthews, K., and Acutis, M.: Deliberative
processes for comprehensive evaluation of agroecological models. A review,
Agron. Sustain. Dev., 35, 589–605, 2014. a
Bonsall, C., Macklin, M. G., Anderson, D. E., and Payton, R. W.: Climate
Change and the Adoption of Agriculture in North-West Europe, Eur.
J. Archaeol., 5, 9–23, https://doi.org/10.1177/1465712002005001168, 2002. a
Bouchet, A.-S., Laperche, A., Bissuel-Belaygue, C., Snowdon, R., Nesi, N.,
and
Stahl, A.: Nitrogen use efficiency in rapeseed. A review, Agron.
Sustain. Dev., 36, 1–20, https://doi.org/10.1007/s13593-016-0371-0, 2016. a
Cardenas, L. M., Gooday, R., Brown, L., Scholefield, D., Cuttle, S.,
Gilhespy,
S., Matthews, R., Misselbrook, T., Wang, J., Li, C. L., Hughes, G., and Lord,
E.: Towards an improved inventory of N2O from agriculture: Model evaluation
of N2O emission factors and N fraction leached from different sources in UK
agriculture, Atmos. Environ., 79, 340–348, 2013. a, b, c
Cowan, N. J., Famulari, D., Levy, P. E., Anderson, M., Bell, M. J., Rees,
R. M., Reay, D. S., and Skiba, U. M.: An improved method for measuring soil
N2O fluxes using a quantum cascade laser with a dynamic chamber, Eur.
J. Soil Sci., 65, 643–652, 2014. a
Dechow, R. and Freibauer, A.: Assessment of German nitrous oxide emissions
using empirical modelling approaches, Nutr. Cycl. Agroecosys.,
91, 235–254, https://doi.org/10.1007/s10705-011-9458-9, 2011. a, b, c
DEFRA: Fertiliser Manual RB209, 9th Edn., Stationery Office, Norwich, UK,
2010. a
De Vries, W., Kros, J., Reinds, G. J., and Butterbach-Bahl, K.: Quantifying
impacts of nitrogen use in European agriculture on global warming potential,
Curr. Opin. Env. Sust., 3, 291–302, 2011a. a
De Vries, W., Leip, A., Reinds, G. J., Kros, J., Lesschen, J. P., and
Bouwman, A. F.: Comparison of land nitrogen budgets for European agriculture
by various modeling approaches, Environ. Pollut., 159, 3254–3268,
https://doi.org/10.1016/j.envpol.2011.03.038, 2011b. a
Dobbie, K. E., McTaggart, I. P., and Smith, K. A.: Nitrous oxide emissions
from intensive agricultural systems: Variations between crops and seasons,
key driving variables, and mean emission factors, J. Geophys.
Res.-Atmos., 104, 26891–26899, 1999. a
Edina AgCensus: Grid square agricultural census data for England, Scotland
and Wales, available at: http://agcensus.edina.ac.uk (last access: 1 March 2017), 2016. a
European Commission: European Union: Agri-food database, available at:
http://agridata.ec.europa.eu/extensions/DataPortal/home.html (last access: 1 June 2018),
2018. a
Eurostat: Farm structure statistics, available at:
https://ec.europa.eu/eurostat/web/agriculture/data/database (last
access: 1 October 2018),
2015. a
Fitton, N., Datta, A., Cloy, J. M., Rees, R. M., Topp, C. F. E., Bell, M. J.,
Cardenas, L. M., Williams, J., Smith, K., Thorman, R., Watson, C. J.,
McGeough, K. L., Kuhnert, M., Hastings, A., Anthony, S., Chadwick, D., and
Smith, P.: Modelling spatial and inter-annual variations of nitrous oxide
emissions from UK cropland and grasslands using DailyDayCent, Agr.
Ecosyst. Environ., 250, 1–11, https://doi.org/10.1016/j.agee.2017.08.032,
2017. a, b
Gabrielle, B., Laville, P., Duval, O., Nicoullaud, B., Germon, J. C., and
Henault, C.: Process-based modeling of nitrous oxide emissions from
wheat-cropped soils at the subregional scale, Global Biogeochem. Cy.,
20, GB4018, https://doi.org/10.1029/2006GB002686, 2006. a
Galloway, J. N., Leach, A. M., Bleeker, A., and Erisman, J. W.: A chronology
of human understanding of the nitrogen cycle, Philos. T.
R. Soc. B, 368, 20130120, https://doi.org/10.1098/rstb.2013.0120, 2013. a
Gilhespy, S. L., Anthony, S., Cardenas, L., Chadwick, D., del Prado, A., Li,
C., Misselbrook, T., Rees, R. M., Salas, W., Sanz-Cobena, A., Smith, P.,
Tilston, E. L., Topp, C. F. E., Vetter, S., and Yeluripati, J. B.: First 20
years of DNDC (DeNitrification DeComposition): Model evolution, Ecol.
Model., 292, 51–62, 2014. a, b
Haas, E., Klatt, S., Fröhlich, A., Kraft, P., Werner, C., Kiese, R.,
Grote,
R., Breuer, L., and Butterbach-Bahl, K.: LandscapeDNDC: a process model for
simulation of biosphere–atmosphere–hydrosphere
exchange processes at site and regional scale, Landscape Ecol., 28, 615–636, https://doi.org/10.1007/s10980-012-9772-x,
2012. a, b
Hay, R., Russell, G., and Edwards, T. W.: Crop Production in the East of
Scotland, Tech. rep., Scottish Agricultural Science Agency, Edinburgh, UK, 2000. a
Hengl, T., de Jesus, J. M., MacMillan, R. A., Batjes, N. H., Heuvelink, G.
B. M., Ribeiro, E., Samuel-Rosa, A., Kempen, B., Leenaars, J. G. B., Walsh,
M. G., and Gonzalez, M. R.: SoilGrids1km – Global Soil Information Based
on Automated Mapping, PLoS ONE, 9, e105992-17,
https://doi.org/10.1371/journal.pone.0105992, 2014. a
Hinton, N. J., Cloy, J. M., Bell, M. J., Chadwick, D. R., Topp, C. F. E., and
Rees, R. M.: Managing fertiliser nitrogen to reduce nitrous oxide emissions
and emission intensities from a cultivated Cambisol in Scotland, Geoderma Regional, 4, 55–65, 2015. a
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.: Evolution towards a new generation of agricultural systems simulation, Environ. Model. Softw., 62, 327–350, 2014. a
Jeuffroy, M. H., Baranger, E., Carrouée, B., de Chezelles, E., Gosme, M.,
Hénault, C., Schneider, A., and Cellier, P.: Nitrous oxide emissions from
crop rotations including wheat, oilseed rape and dry peas, Biogeosciences,
10, 1787–1797, https://doi.org/10.5194/bg-10-1787-2013, 2013. a
Kaiser, E. A. and Ruser, R.: Nitrous oxide emissions from arable soils in
Germany – An evaluation of six long-term field experiments,
J. Plant Nutr. Soil Sc., 163, 249–259, 2000. a
Klatt, S., Kraus, D., Rahn, K., Werner, C., Kiese, R., Butterbach-Bahl, K.,
and Haas, E.: Parameter-Induced Uncertainty Quantification of Regional
N2O Emissions and NO3 Leaching using the Biogeochemical Model
LandscapeDNDC, in: Synthesis and Modeling of Greenhouse Gas Emissions and
Carbon Storage in Agricultural and Forest Systems to Guide Mitigation and
Adaptation, edited by: Del Grosso, S., Ahuja, L., and Parton, W., Adv. Agric.
Syst. Model. 6. ASA, CSSA, and SSSA, Madison, WI, 149–172,
https://doi.org/10.2134/advagricsystmodel6.2013.0001, 2016. a
Kracher, D.: Modeling Nitrous Oxide Emissionsand Associated C and N Turnover
and Exchange Processes Between Atmosphere and Biosphere for Agricultural
Ecosystems Onsite and Regional Scale, PhD thesis,
Albert-Ludwigs-Universität, Freiburg im Breisgau, Germany, 2010. a
Lassaletta, L., Billen, G., Grizzetti, B., Anglade, J., and Garnier, J.: 50
year trends in nitrogen use efficiency of world cropping systems: the
relationship between yield and nitrogen input to cropland, Environ.
Res. Lett., 9, 105011, https://doi.org/10.1088/1748-9326/9/10/105011, 2014. a, b
Lesschen, J. P., Velthof, G. L., de Vries, W., and Kros, J.: Differentiation
of nitrous oxide emission factors for agricultural soils, Environ.
Pollut., 159, 3215–3222, https://doi.org/10.1016/j.envpol.2011.04.001, 2011. a
Li, C. L., 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.-Oceans, 97, 9759–9776, 1992. a
Li, X., Yeluripati, J., Jones, E. O., Uchida, Y., and Hatano, R.:
Hierarchical
Bayesian calibration of nitrous oxide (N2O) and nitrogen monoxide (NO) flux
module of an agro-ecosystem model: ECOSSE, Ecol. Model., 316,
14–27, 2015. a
Lilly, A., Ball, B. C., McTaggart, I. P., and Horne, P. L.: Spatial and
temporal scaling of nitrous oxide emissions from the field to the regional
scale in Scotland, Nutr. Cycl. Agroecosys., 66, 241–257, 2003. a
McTaggart, I. P. and Smith, K. A.: The effect of rate, form and timing of
fertilizer N on nitrogen uptake and grain N content in spring malting
barley, J. Agr. Sci., 125, 341–353, https://doi.org/10.1017/S0021859600084847, 1995. a
Monfreda, C., Ramankutty, N., and Foley, J. A.: Farming the planet: 2.
Geographic distribution of crop areas, yields, physiological types, and net
primary production in the year 2000, Global Biogeochem. Cy., 22, GB1022,
https://doi.org/10.1029/2007GB002947, 2008. a
Myrgiotis, V., Rees, R. M., Topp, C. F., and Williams, M.: A systematic
approach to identifying key parameters and processes in agroecosystem
models, Ecol. Model., 368, 344–356,
https://doi.org/10.1016/j.ecolmodel.2017.12.009, 2018a. a, b
Myrgiotis, V., Williams, M., Topp, C. F. E., and Rees, R. M.: Improving
model
prediction of soil N2O emissions through Bayesian calibration, Sci. Total Environ., 624, 1467–1477,
https://doi.org/10.1016/j.scitotenv.2017.12.202, 2018b. a, b, c
Necpálová, M., Anex, R. P., Fienen, M. N., Del Grosso, S. J.,
Castellano, M. J., Sawyer, J. E., Iqbal, J., Pantoja, J. L., and Barker,
D. W.: Understanding the DayCent model: Calibration, sensitivity, and identifiability
through inverse modeling, Environ. Modell.
Softw., 66, 110–130, 2015. a
Olesen, J. E., Trnka, M., Kersebaum, K. C., Skjelvaag, A. O., Seguin, B.,
Peltonen-Sainio, P., Rossi, F., Kozyra, J., and Micale, F.: Impacts and
adaptation of European crop production systems to climate change, Eur.
J. Agron., 34, 96–112, https://doi.org/10.1016/j.eja.2010.11.003, 2011. a
Pan, B., Lam, S. K., Mosier, A., Luo, Y., and Chen, D.: Ammonia
volatilization
from synthetic fertilizers and its mitigation strategies: A global
synthesis, Agr. Ecosyst. Environ., 232, 283–289,
https://doi.org/10.1016/j.agee.2016.08.019, 2016. a
Paustian, K., Lehmann, J., Ogle, S., Reay, D., Robertson, G. P., and Smith,
P.:
Climate-smart soils, Nature, 532, 49–57, 2016. a
Pogson, M. and Smith, P.: Effect of spatial data resolution on uncertainty,
Environ. Modell. Softw., 63, 87–96, 2015. a
Potter, P., Ramankutty, N., Bennett, E. M., and Donner, S. D.:
Characterizing
the Spatial Patterns of Global Fertilizer Application and Manure Production,
Earth Interact., 14, 1–22, https://doi.org/10.1175/2009EI288.1, 2010. a
Rathke, G., Behrens, T., and Diepenbrock, W.: Integrated nitrogen management
strategies to improve seed yield, oil content and nitrogen efficiency of
winter oilseed rape (Brassica napus L.): A review, Agr. Ecosyst. Environ., 117, 80–108, 2006. a
Ravishankara, A. R., Haag, D., and Portmann, R. W.: Nitrous Oxide
(N2O): The
Dominant Ozone-Depleting Substance Emitted in the 21st Century, Science,
326, 123–125, 2009. a
Reay, D. S., Davidson, E. A., Smith, K. A., Smith, P., Melillo, J. M.,
Dentener, F., and Crutzen, P. J.: Global agriculture and nitrous oxide
emissions, Nature Climate Change, 2, 410–416, 2012. a
Robinson, E., Blyth, E., Clark, D., Comyn-Platt, E., Finch, J., and Rudd, A.:
Climate hydrology and ecology research support system meteorology dataset
for Great Britain (1961–2015) [CHESS-met] v1.2. NERC Environmental
Information Data Centre, https://doi.org/10.5285/b745e7b1-626c-4ccc-ac27-56582e77b900,
2017. a, b
The Scottish Government: Results From the June 2013 Scottish Agricultural
Census, Edinburgh, UK, 1–49, 2013. a
Scottish Spatial Data Infrastructure: National Soil Inventory of Scotland,
available at:
https://www.spatialdata.gov.scot/geonetwork/srv/eng/catalog.search#/home
(last access: 9 April 2019),
2014. a
Smith, K. A.: Changing views of nitrous oxide emissions from agricultural
soil: key controlling processes and assessment at different spatial scales,
Eur. J. Soil Sci., 68, 137–155, https://doi.org/10.1111/ejss.12409,
2017. a
Stehfest, E. and Bouwman, L.: N2O and NO emission from agricultural
fields and
soils under natural vegetation: summarizing available measurement data and
modeling of global annual emissions, Nutr. Cycl. Agroecosys., 74,
207–228, https://doi.org/10.1007/s10705-006-9000-7, 2006. a, b
Stoate, C., Boatman, N. D., Borralho, R. J., Carvalho, C. R., Snoo, G. R. d.,
and Eden, P.: Ecological impacts of arable intensification in Europe,
J. Environ. Manage., 63, 337–365,
https://doi.org/10.1006/jema.2001.0473, 2001. a
Sylvester-Bradley, R., Thorman, R., Kindred, D. R., Wynn, S. C., Smith,
K. E.,
Rees, R. M., Topp, C. F. E., Pappa, V. A., Mortimer, N. D., Misselbrook,
T. H., Gilhespy, S., Cardenas, L. M., Chauhan, M., Bennet, G., Malkin, S.,
and Munro, D. G.: Minimising nitrous oxide intensities of arable crop
products (MIN-NO), Tech. rep., Kenilworth, UK, 2015. a, b
Toth, G., Montanarella, L., Stolbovoy, V., Mate, F., Bodis, K., Jones, A.,
Panagos, P., and van Liedekerke, M.: Soils of the European Union, Tech. rep.,
Institute for Environment and Sustainability, Luxembourg, 2008. a
Van Meter, K. J., Basu, N. B., Veenstra, J. J., and Burras, C. L.: The
nitrogen legacy: emerging evidence of nitrogen accumulation in anthropogenic
landscapes, Environ. Res. Lett., 11, 1–12, 2016. a
Wang, G. and Chen, S.: A review on parameterization and uncertainty in
modeling greenhouse gas emissions from soil, Geoderma, 170, 206–216, 2012. a
Short summary
This study focuses on a northwestern European cropland region and shows that the type of crop growing on a soil has notable effects on the emission of nitrous oxide (N2O – a greenhouse gas) from that soil. It was found that N2O emissions from soils under oilseed cultivation are significantly higher than soils under cereal cultivation. This variation is mostly explained by the fact that oilseeds require more nitrogen (fertiliser) than cereals, especially at early crop growth stages.
This study focuses on a northwestern European cropland region and shows that the type of crop...
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