Articles | Volume 19, issue 12
Biogeosciences, 19, 3021–3050, 2022
https://doi.org/10.5194/bg-19-3021-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Biogeosciences, 19, 3021–3050, 2022
https://doi.org/10.5194/bg-19-3021-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| Highlight paper
22 Jun 2022
Research article
| Highlight paper
| 22 Jun 2022
Effects of climate change in European croplands and grasslands: productivity, greenhouse gas balance and soil carbon storage
Marco Carozzi et al.
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Arthur Nicolaus Fendrich, Philippe Ciais, Emanuele Lugato, Marco Carozzi, Bertrand Guenet, Pasquale Borrelli, Victoria Naipal, Matthew McGrath, Philippe Martin, and Panos Panagos
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-121, https://doi.org/10.5194/gmd-2022-121, 2022
Preprint under review for GMD
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Currently, spatially explicit models for soil carbon stock can simulate the impacts of several changes. However, they do not incorporate the erosion, lateral transport and deposition (ETD) of soil material. The present work: i) developed ETD formulation; ii) illustrated model calibration and validation for Europe; iii) presented the results for a depositional site. We expect that our work advances ETD models' description and facilitates its reproduction and incorporation in land surface models.
Benjamin Loubet, Marco Carozzi, Polina Voylokov, Jean-Pierre Cohan, Robert Trochard, and Sophie Génermont
Biogeosciences, 15, 3439–3460, https://doi.org/10.5194/bg-15-3439-2018, https://doi.org/10.5194/bg-15-3439-2018, 2018
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Tropospheric ammonia is mainly emitted by agriculture. It constitutes a loss for the farmers and a threat to human health and the environment. It is therefore crucial to improve agricultural practices to reduce ammonia losses following fertilisation. In this study we propose an inverse dispersion modelling method to simultaneously quantify ammonia volatilisation from multiple small agronomic plots. The method was evaluated to be suitable (though slightly biased) based on a theoretical study.
Arthur Nicolaus Fendrich, Philippe Ciais, Emanuele Lugato, Marco Carozzi, Bertrand Guenet, Pasquale Borrelli, Victoria Naipal, Matthew McGrath, Philippe Martin, and Panos Panagos
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-121, https://doi.org/10.5194/gmd-2022-121, 2022
Preprint under review for GMD
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Currently, spatially explicit models for soil carbon stock can simulate the impacts of several changes. However, they do not incorporate the erosion, lateral transport and deposition (ETD) of soil material. The present work: i) developed ETD formulation; ii) illustrated model calibration and validation for Europe; iii) presented the results for a depositional site. We expect that our work advances ETD models' description and facilitates its reproduction and incorporation in land surface models.
Raia Silvia Massad, Juliette Lathière, Susanna Strada, Mathieu Perrin, Erwan Personne, Marc Stéfanon, Patrick Stella, Sophie Szopa, and Nathalie de Noblet-Ducoudré
Biogeosciences, 16, 2369–2408, https://doi.org/10.5194/bg-16-2369-2019, https://doi.org/10.5194/bg-16-2369-2019, 2019
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Human activities strongly interfere in the land–atmosphere interactions through changes in land use and land cover changes and land management. The objectives of this review are to synthesize the existing experimental and modelling works that investigate physical, chemical, and biogeochemical interactions between land surface and the atmosphere. Greater consideration of atmospheric chemistry, through land–atmosphere interactions, as a decision parameter for land management is essential.
Benjamin Loubet, Marco Carozzi, Polina Voylokov, Jean-Pierre Cohan, Robert Trochard, and Sophie Génermont
Biogeosciences, 15, 3439–3460, https://doi.org/10.5194/bg-15-3439-2018, https://doi.org/10.5194/bg-15-3439-2018, 2018
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Tropospheric ammonia is mainly emitted by agriculture. It constitutes a loss for the farmers and a threat to human health and the environment. It is therefore crucial to improve agricultural practices to reduce ammonia losses following fertilisation. In this study we propose an inverse dispersion modelling method to simultaneously quantify ammonia volatilisation from multiple small agronomic plots. The method was evaluated to be suitable (though slightly biased) based on a theoretical study.
C. R. Flechard, R.-S. Massad, B. Loubet, E. Personne, D. Simpson, J. O. Bash, E. J. Cooter, E. Nemitz, and M. A. Sutton
Biogeosciences, 10, 5183–5225, https://doi.org/10.5194/bg-10-5183-2013, https://doi.org/10.5194/bg-10-5183-2013, 2013
Related subject area
Biogeochemistry: Modelling, Terrestrial
Assimilation of passive microwave vegetation optical depth in LDAS-Monde: a case study over the continental USA
Global modelling of soil carbonyl sulfide exchanges
Assessing the impacts of agricultural managements on soil carbon stocks, nitrogen loss, and crop production – a modelling study in eastern Africa
The effects of varying drought-heat signatures on terrestrial carbon dynamics and vegetation composition
Accounting for non-rainfall moisture and temperature improves litter decay model performance in a fog-dominated dryland system
Resolving temperature limitation on spring productivity in an evergreen conifer forest using a model–data fusion framework
A robust initialization method for accurate soil organic carbon simulations
Evaluation of carbonyl sulfide biosphere exchange in the Simple Biosphere Model (SiB4)
Model simulations of arctic biogeochemistry and permafrost extent are highly sensitive to the implemented snow scheme in LPJ-GUESS
Theoretical insights from upscaling Michaelis–Menten microbial dynamics in biogeochemical models: a dimensionless approach
Estimated effect of the permafrost carbon feedback on the zero emissions commitment to climate change
An improved process-oriented hydro-biogeochemical model for simulating dynamic fluxes of methane and nitrous oxide in alpine ecosystems with seasonally frozen soils
A novel representation of biological nitrogen fixation and competitive dynamics between nitrogen-fixing and non-fixing plants in a land model (GFDL LM4.1-BNF)
Organic phosphorus cycling may control grassland responses to nitrogen deposition: a long-term field manipulation and modelling study
A triple tree-ring constraint for tree growth and physiology in a global land surface model
Simulating shrubs and their energy and carbon dioxide fluxes in Canada's Low Arctic with the Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC)
Competing effects of nitrogen deposition and ozone exposure on northern hemispheric terrestrial carbon uptake and storage, 1850–2099
Carbonyl sulfide: comparing a mechanistic representation of the vegetation uptake in a land surface model and the leaf relative uptake approach
Optimal model complexity for terrestrial carbon cycle prediction
CO2 physiological effect can cause rainfall decrease as strong as large-scale deforestation in the Amazon
Plant phenology evaluation of CRESCENDO land surface models – Part 1: Start and end of the growing season
Understanding the effect of fire on vegetation composition and gross primary production in a semi-arid shrubland ecosystem using the Ecosystem Demography (EDv2.2) model
Impacts of fertilization on grassland productivity and water quality across the European Alps under current and warming climate: insights from a mechanistic model
The climate benefit of carbon sequestration
Extending a land-surface model with Sphagnum moss to simulate responses of a northern temperate bog to whole ecosystem warming and elevated CO2
Improving the representation of high-latitude vegetation distribution in dynamic global vegetation models
Robust processing of airborne laser scans to plant area density profiles
Investigating the sensitivity of soil heterotrophic respiration to recent snow cover changes in Alaska using a satellite-based permafrost carbon model
Hysteretic temperature sensitivity of wetland CH4 fluxes explained by substrate availability and microbial activity
Modelling the habitat preference of two key Sphagnum species in a poor fen as controlled by capitulum water content
Evaluating two soil carbon models within the global land surface model JSBACH using surface and spaceborne observations of atmospheric CO2
Assessing impacts of selective logging on water, energy, and carbon budgets and ecosystem dynamics in Amazon forests using the Functionally Assembled Terrestrial Ecosystem Simulator
Microbial dormancy and its impacts on northern temperate and boreal terrestrial ecosystem carbon budget
Historical CO2 emissions from land use and land cover change and their uncertainty
A Bayesian approach to evaluation of soil biogeochemical models
Rainfall intensification increases the contribution of rewetting pulses to soil heterotrophic respiration
Wide discrepancies in the magnitude and direction of modeled solar-induced chlorophyll fluorescence in response to light conditions
Modeling biological nitrogen fixation in global natural terrestrial ecosystems
The impact of a simple representation of non-structural carbohydrates on the simulated response of tropical forests to drought
Benchmarking and parameter sensitivity of physiological and vegetation dynamics using the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) at Barro Colorado Island, Panama
Modelling nitrification inhibitor effects on N2O emissions after fall- and spring-applied slurry by reducing nitrifier NH4+ oxidation rate
DRIFTS band areas as measured pool size proxy to reduce parameter uncertainty in soil organic matter models
Wintertime grassland dynamics may influence belowground biomass under climate change: a model analysis
Low sensitivity of gross primary production to elevated CO2 in a mature eucalypt woodland
Metabolic tradeoffs and heterogeneity in microbial responses to temperature determine the fate of litter carbon in simulations of a warmer world
Competition alters predicted forest carbon cycle responses to nitrogen availability and elevated CO2: simulations using an explicitly competitive, game-theoretic vegetation demographic model
The importance of physiological, structural and trait responses to drought stress in driving spatial and temporal variation in GPP across Amazon forests
Modelling the response of net primary productivity of the Zambezi teak forests to climate change along a rainfall gradient in Zambia
Three decades of simulated global terrestrial carbon fluxes from a data assimilation system confronted with different periods of observations
Using a modified DNDC biogeochemical model to optimize field management of a multi-crop (cotton, wheat, and maize) system: a site-scale case study in northern China
Anthony Mucia, Bertrand Bonan, Clément Albergel, Yongjun Zheng, and Jean-Christophe Calvet
Biogeosciences, 19, 2557–2581, https://doi.org/10.5194/bg-19-2557-2022, https://doi.org/10.5194/bg-19-2557-2022, 2022
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For the first time, microwave vegetation optical depth data are assimilated in a land surface model in order to analyze leaf area index and root zone soil moisture. The advantage of microwave products is the higher observation frequency. A large variety of independent datasets are used to verify the added value of the assimilation. It is shown that the assimilation is able to improve the representation of soil moisture, vegetation conditions, and terrestrial water and carbon fluxes.
Camille Abadie, Fabienne Maignan, Marine Remaud, Jérôme Ogée, J. Elliott Campbell, Mary E. Whelan, Florian Kitz, Felix M. Spielmann, Georg Wohlfahrt, Richard Wehr, Wu Sun, Nina Raoult, Ulli Seibt, Didier Hauglustaine, Sinikka T. Lennartz, Sauveur Belviso, David Montagne, and Philippe Peylin
Biogeosciences, 19, 2427–2463, https://doi.org/10.5194/bg-19-2427-2022, https://doi.org/10.5194/bg-19-2427-2022, 2022
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A better constraint of the components of the carbonyl sulfide (COS) global budget is needed to exploit its potential as a proxy of gross primary productivity. In this study, we compare two representations of oxic soil COS fluxes, and we develop an approach to represent anoxic soil COS fluxes in a land surface model. We show the importance of atmospheric COS concentration variations on oxic soil COS fluxes and provide new estimates for oxic and anoxic soil contributions to the COS global budget.
Jianyong Ma, Sam S. Rabin, Peter Anthoni, Anita D. Bayer, Sylvia S. Nyawira, Stefan Olin, Longlong Xia, and Almut Arneth
Biogeosciences, 19, 2145–2169, https://doi.org/10.5194/bg-19-2145-2022, https://doi.org/10.5194/bg-19-2145-2022, 2022
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Improved agricultural management plays a vital role in protecting soils from degradation in eastern Africa. We simulated the impacts of seven management practices on soil carbon pools, nitrogen loss, and crop yield under different climate scenarios in this region. This study highlights the possibilities of conservation agriculture when targeting long-term environmental sustainability and food security in crop ecosystems, particularly for those with poor soil conditions in tropical climates.
Elisabeth Tschumi, Sebastian Lienert, Karin van der Wiel, Fortunat Joos, and Jakob Zscheischler
Biogeosciences, 19, 1979–1993, https://doi.org/10.5194/bg-19-1979-2022, https://doi.org/10.5194/bg-19-1979-2022, 2022
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Droughts and heatwaves are expected to occur more often in the future, but their effects on land vegetation and the carbon cycle are poorly understood. We use six climate scenarios with differing extreme occurrences and a vegetation model to analyse these effects. Tree coverage and associated plant productivity increase under a climate with no extremes. Frequent co-occurring droughts and heatwaves decrease plant productivity more than the combined effects of single droughts or heatwaves.
J. Robert Logan, Kathe E. Todd-Brown, Kathryn M. Jacobson, Peter J. Jacobson, Roland Vogt, and Sarah E. Evans
Biogeosciences Discuss., https://doi.org/10.5194/bg-2022-16, https://doi.org/10.5194/bg-2022-16, 2022
Revised manuscript accepted for BG
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Understanding how plants decompose is important for understanding where the atmospheric CO2 they absorb ends up after they die. In forests, decomposition is controlled by rain but in deserts, it’s a different story. We performed a 2.5-year study in one of the driest places on Earth (the Namib Desert in southern Africa) and found that fog and dew, not rainfall, closely controlled how quickly plants decompose. We also created a model to help predict decomposition in drylands with lots of fog/dew.
Stephanie G. Stettz, Nicholas C. Parazoo, A. Anthony Bloom, Peter D. Blanken, David R. Bowling, Sean P. Burns, Cédric Bacour, Fabienne Maignan, Brett Raczka, Alexander J. Norton, Ian Baker, Mathew Williams, Mingjie Shi, Yongguang Zhang, and Bo Qiu
Biogeosciences, 19, 541–558, https://doi.org/10.5194/bg-19-541-2022, https://doi.org/10.5194/bg-19-541-2022, 2022
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Uncertainty in the response of photosynthesis to temperature poses a major challenge to predicting the response of forests to climate change. In this paper, we study how photosynthesis in a mountainous evergreen forest is limited by temperature. This study highlights that cold temperature is a key factor that controls spring photosynthesis. Including the cold-temperature limitation in an ecosystem model improved its ability to simulate spring photosynthesis.
Eva Kanari, Lauric Cécillon, François Baudin, Hugues Clivot, Fabien Ferchaud, Sabine Houot, Florent Levavasseur, Bruno Mary, Laure Soucémarianadin, Claire Chenu, and Pierre Barré
Biogeosciences, 19, 375–387, https://doi.org/10.5194/bg-19-375-2022, https://doi.org/10.5194/bg-19-375-2022, 2022
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Soil organic carbon (SOC) is crucial for climate regulation, soil quality, and food security. Predicting its evolution over the next decades is key for appropriate land management policies. However, SOC projections lack accuracy. Here we show for the first time that PARTYSOC, an approach combining thermal analysis and machine learning optimizes the accuracy of SOC model simulations at independent sites. This method can be applied at large scales, improving SOC projections on a continental scale.
Linda M. J. Kooijmans, Ara Cho, Jin Ma, Aleya Kaushik, Katherine D. Haynes, Ian Baker, Ingrid T. Luijkx, Mathijs Groenink, Wouter Peters, John B. Miller, Joseph A. Berry, Jerome Ogée, Laura K. Meredith, Wu Sun, Kukka-Maaria Kohonen, Timo Vesala, Ivan Mammarella, Huilin Chen, Felix M. Spielmann, Georg Wohlfahrt, Max Berkelhammer, Mary E. Whelan, Kadmiel Maseyk, Ulli Seibt, Roisin Commane, Richard Wehr, and Maarten Krol
Biogeosciences, 18, 6547–6565, https://doi.org/10.5194/bg-18-6547-2021, https://doi.org/10.5194/bg-18-6547-2021, 2021
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The gas carbonyl sulfide (COS) can be used to estimate photosynthesis. To adopt this approach on regional and global scales, we need biosphere models that can simulate COS exchange. So far, such models have not been evaluated against observations. We evaluate the COS biosphere exchange of the SiB4 model against COS flux observations. We find that the model is capable of simulating key processes in COS biosphere exchange. Still, we give recommendations for further improvement of the model.
Alexandra Pongracz, David Wårlind, Paul A. Miller, and Frans-Jan W. Parmentier
Biogeosciences, 18, 5767–5787, https://doi.org/10.5194/bg-18-5767-2021, https://doi.org/10.5194/bg-18-5767-2021, 2021
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This study shows that the introduction of a multi-layer snow scheme in the LPJ-GUESS DGVM improved simulations of high-latitude soil temperature dynamics and permafrost extent compared to observations. In addition, these improvements led to shifts in carbon fluxes that contrasted within and outside of the permafrost region. Our results show that a realistic snow scheme is essential to accurately simulate snow–soil–vegetation relationships and carbon–climate feedbacks.
Chris H. Wilson and Stefan Gerber
Biogeosciences, 18, 5669–5679, https://doi.org/10.5194/bg-18-5669-2021, https://doi.org/10.5194/bg-18-5669-2021, 2021
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To better mitigate against climate change, it is imperative that ecosystem scientists understand how microbes decompose organic carbon in the soil and thereby release it as carbon dioxide into the atmosphere. A major challenge is the high variability across ecosystems in microbial biomass and in the environmental factors like temperature that drive their activity. In this paper, we use math to better understand how this variability impacts carbon dioxide release over large scales.
Andrew H. MacDougall
Biogeosciences, 18, 4937–4952, https://doi.org/10.5194/bg-18-4937-2021, https://doi.org/10.5194/bg-18-4937-2021, 2021
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Permafrost soils hold about twice as much carbon as the atmosphere. As the Earth warms the organic matter in these soils will decay, releasing CO2 and CH4. It is expected that these soils will continue to release carbon to the atmosphere long after man-made emissions of greenhouse gases cease. Here we use a method employing hundreds of slightly varying model versions to estimate how much warming permafrost carbon will cause after human emissions of CO2 end.
Wei Zhang, Zhisheng Yao, Siqi Li, Xunhua Zheng, Han Zhang, Lei Ma, Kai Wang, Rui Wang, Chunyan Liu, Shenghui Han, Jia Deng, and Yong Li
Biogeosciences, 18, 4211–4225, https://doi.org/10.5194/bg-18-4211-2021, https://doi.org/10.5194/bg-18-4211-2021, 2021
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The hydro-biogeochemical model Catchment Nutrient Management Model – DeNitrification-DeComposition (CNMM-DNDC) is improved by incorporating a soil thermal module to simulate the soil thermal regime in the presence of freeze–thaw cycles. The modified model is validated at a seasonally frozen catchment with typical alpine ecosystems (wetland, meadow and forest). The simulated aggregate emissions of methane and nitrous oxide are highest for the wetland, which is dominated by the methane emissions.
Sian Kou-Giesbrecht, Sergey Malyshev, Isabel Martínez Cano, Stephen W. Pacala, Elena Shevliakova, Thomas A. Bytnerowicz, and Duncan N. L. Menge
Biogeosciences, 18, 4143–4183, https://doi.org/10.5194/bg-18-4143-2021, https://doi.org/10.5194/bg-18-4143-2021, 2021
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Representing biological nitrogen fixation (BNF) is an important challenge for land models. We present a novel representation of BNF and updated nitrogen cycling in a land model. It includes a representation of asymbiotic BNF by soil microbes and the competitive dynamics between nitrogen-fixing and non-fixing plants. It improves estimations of major carbon and nitrogen pools and fluxes and their temporal dynamics in comparison to previous representations of BNF in land models.
Christopher R. Taylor, Victoria Janes-Bassett, Gareth K. Phoenix, Ben Keane, Iain P. Hartley, and Jessica A. C. Davies
Biogeosciences, 18, 4021–4037, https://doi.org/10.5194/bg-18-4021-2021, https://doi.org/10.5194/bg-18-4021-2021, 2021
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We used experimental data to model two phosphorus-limited grasslands and investigated their response to nitrogen (N) deposition. Greater uptake of organic P facilitated a positive response to N deposition, stimulating growth and soil carbon storage. Where organic P access was less, N deposition exacerbated P demand and reduced plant C input to the soil. This caused more C to be released into the atmosphere than is taken in, reducing the climate-mitigation capacity of the modelled grassland.
Jonathan Barichivich, Philippe Peylin, Thomas Launois, Valerie Daux, Camille Risi, Jina Jeong, and Sebastiaan Luyssaert
Biogeosciences, 18, 3781–3803, https://doi.org/10.5194/bg-18-3781-2021, https://doi.org/10.5194/bg-18-3781-2021, 2021
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The width and the chemical signals of tree rings have the potential to test and improve the physiological responses simulated by global land surface models, which are at the core of future climate projections. Here, we demonstrate the novel use of tree-ring width and carbon and oxygen stable isotopes to evaluate the representation of tree growth and physiology in a global land surface model at temporal scales beyond experimentation and direct observation.
Gesa Meyer, Elyn R. Humphreys, Joe R. Melton, Alex J. Cannon, and Peter M. Lafleur
Biogeosciences, 18, 3263–3283, https://doi.org/10.5194/bg-18-3263-2021, https://doi.org/10.5194/bg-18-3263-2021, 2021
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Shrub and sedge plant functional types (PFTs) were incorporated in the land surface component of the Canadian Earth System Model to improve representation of Arctic tundra ecosystems. Evaluated against 14 years of non-winter measurements, the magnitude and seasonality of carbon dioxide and energy fluxes at a Canadian dwarf-shrub tundra site were better captured by the shrub PFTs than by previously used grass and tree PFTs. Model simulations showed the tundra site to be an annual net CO2 source.
Martina Franz and Sönke Zaehle
Biogeosciences, 18, 3219–3241, https://doi.org/10.5194/bg-18-3219-2021, https://doi.org/10.5194/bg-18-3219-2021, 2021
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The combined effects of ozone and nitrogen deposition on the terrestrial carbon uptake and storage has been unclear. Our simulations, from 1850 to 2099, show that ozone-related damage considerably reduced gross primary production and carbon storage in the past. The growth-stimulating effect induced by nitrogen deposition is offset until the 2050s. Accounting for nitrogen deposition without considering ozone effects might lead to an overestimation of terrestrial carbon uptake and storage.
Fabienne Maignan, Camille Abadie, Marine Remaud, Linda M. J. Kooijmans, Kukka-Maaria Kohonen, Róisín Commane, Richard Wehr, J. Elliott Campbell, Sauveur Belviso, Stephen A. Montzka, Nina Raoult, Ulli Seibt, Yoichi P. Shiga, Nicolas Vuichard, Mary E. Whelan, and Philippe Peylin
Biogeosciences, 18, 2917–2955, https://doi.org/10.5194/bg-18-2917-2021, https://doi.org/10.5194/bg-18-2917-2021, 2021
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The assimilation of carbonyl sulfide (COS) by continental vegetation has been proposed as a proxy for gross primary production (GPP). Using a land surface and a transport model, we compare a mechanistic representation of the plant COS uptake (Berry et al., 2013) to the classical leaf relative uptake (LRU) approach linking GPP and vegetation COS fluxes. We show that at high temporal resolutions a mechanistic approach is mandatory, but at large scales the LRU approach compares similarly.
Caroline A. Famiglietti, T. Luke Smallman, Paul A. Levine, Sophie Flack-Prain, Gregory R. Quetin, Victoria Meyer, Nicholas C. Parazoo, Stephanie G. Stettz, Yan Yang, Damien Bonal, A. Anthony Bloom, Mathew Williams, and Alexandra G. Konings
Biogeosciences, 18, 2727–2754, https://doi.org/10.5194/bg-18-2727-2021, https://doi.org/10.5194/bg-18-2727-2021, 2021
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Model uncertainty dominates the spread in terrestrial carbon cycle predictions. Efforts to reduce it typically involve adding processes, thereby increasing model complexity. However, if and how model performance scales with complexity is unclear. Using a suite of 16 structurally distinct carbon cycle models, we find that increased complexity only improves skill if parameters are adequately informed. Otherwise, it can degrade skill, and an intermediate-complexity model is optimal.
Gilvan Sampaio, Marília H. Shimizu, Carlos A. Guimarães-Júnior, Felipe Alexandre, Marcelo Guatura, Manoel Cardoso, Tomas F. Domingues, Anja Rammig, Celso von Randow, Luiz F. C. Rezende, and David M. Lapola
Biogeosciences, 18, 2511–2525, https://doi.org/10.5194/bg-18-2511-2021, https://doi.org/10.5194/bg-18-2511-2021, 2021
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The impact of large-scale deforestation and the physiological effects of elevated atmospheric CO2 on Amazon rainfall are systematically compared in this study. Our results are remarkable in showing that the two disturbances cause equivalent rainfall decrease, though through different causal mechanisms. These results highlight the importance of not only curbing regional deforestation but also reducing global CO2 emissions to avoid climatic changes in the Amazon.
Daniele Peano, Deborah Hemming, Stefano Materia, Christine Delire, Yuanchao Fan, Emilie Joetzjer, Hanna Lee, Julia E. M. S. Nabel, Taejin Park, Philippe Peylin, David Wårlind, Andy Wiltshire, and Sönke Zaehle
Biogeosciences, 18, 2405–2428, https://doi.org/10.5194/bg-18-2405-2021, https://doi.org/10.5194/bg-18-2405-2021, 2021
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Global climate models are the scientist’s tools used for studying past, present, and future climate conditions. This work examines the ability of a group of our tools in reproducing and capturing the right timing and length of the season when plants show their green leaves. This season, indeed, is fundamental for CO2 exchanges between land, atmosphere, and climate. This work shows that discrepancies compared to observations remain, demanding further polishing of these tools.
Karun Pandit, Hamid Dashti, Andrew T. Hudak, Nancy F. Glenn, Alejandro N. Flores, and Douglas J. Shinneman
Biogeosciences, 18, 2027–2045, https://doi.org/10.5194/bg-18-2027-2021, https://doi.org/10.5194/bg-18-2027-2021, 2021
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A dynamic global vegetation model, Ecosystem Demography (EDv2.2), is used to understand spatiotemporal dynamics of a semi-arid shrub ecosystem under alternative fire regimes. Multi-decadal point simulations suggest shrub dominance for a non-fire scenario and a contrasting phase of shrub and C3 grass growth for a fire scenario. Regional gross primary productivity (GPP) simulations indicate moderate agreement with MODIS GPP and a GPP reduction in fire-affected areas before showing some recovery.
Martina Botter, Matthias Zeeman, Paolo Burlando, and Simone Fatichi
Biogeosciences, 18, 1917–1939, https://doi.org/10.5194/bg-18-1917-2021, https://doi.org/10.5194/bg-18-1917-2021, 2021
Carlos A. Sierra, Susan E. Crow, Martin Heimann, Holger Metzler, and Ernst-Detlef Schulze
Biogeosciences, 18, 1029–1048, https://doi.org/10.5194/bg-18-1029-2021, https://doi.org/10.5194/bg-18-1029-2021, 2021
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The climate benefit of carbon sequestration (CBS) is a metric developed to quantify avoided warming by two separate processes: the amount of carbon drawdown from the atmosphere and the time this carbon is stored in a reservoir. This metric can be useful for quantifying the role of forests and soils for climate change mitigation and to better quantify the benefits of carbon removals by sinks.
Xiaoying Shi, Daniel M. Ricciuto, Peter E. Thornton, Xiaofeng Xu, Fengming Yuan, Richard J. Norby, Anthony P. Walker, Jeffrey M. Warren, Jiafu Mao, Paul J. Hanson, Lin Meng, David Weston, and Natalie A. Griffiths
Biogeosciences, 18, 467–486, https://doi.org/10.5194/bg-18-467-2021, https://doi.org/10.5194/bg-18-467-2021, 2021
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The Sphagnum mosses are the important species of a wetland ecosystem. To better represent the peatland ecosystem, we introduced the moss species to the land model component (ELM) of the Energy Exascale Earth System Model (E3SM) by developing water content dynamics and nonvascular photosynthetic processes for moss. We tested the model against field observations and used the model to make projections of the site's carbon cycle under warming and atmospheric CO2 concentration scenarios.
Peter Horvath, Hui Tang, Rune Halvorsen, Frode Stordal, Lena Merete Tallaksen, Terje Koren Berntsen, and Anders Bryn
Biogeosciences, 18, 95–112, https://doi.org/10.5194/bg-18-95-2021, https://doi.org/10.5194/bg-18-95-2021, 2021
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We evaluated the performance of three methods for representing vegetation cover. Remote sensing provided the best match to a reference dataset, closely followed by distribution modelling (DM), whereas the dynamic global vegetation model (DGVM) in CLM4.5BGCDV deviated strongly from the reference. Sensitivity tests show that use of threshold values for predictors identified by DM may improve DGVM performance. The results highlight the potential of using DM in the development of DGVMs.
Johan Arnqvist, Julia Freier, and Ebba Dellwik
Biogeosciences, 17, 5939–5952, https://doi.org/10.5194/bg-17-5939-2020, https://doi.org/10.5194/bg-17-5939-2020, 2020
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Data generated by airborne laser scans enable the characterization of surface vegetation for any application that might need it, such as forest management, modeling for numerical weather prediction, or wind energy estimation. In this work we present a new algorithm for calculating the vegetation density using data from airborne laser scans. The new routine is more robust than earlier methods, and an implementation in popular programming languages accompanies the article to support new users.
Yonghong Yi, John S. Kimball, Jennifer D. Watts, Susan M. Natali, Donatella Zona, Junjie Liu, Masahito Ueyama, Hideki Kobayashi, Walter Oechel, and Charles E. Miller
Biogeosciences, 17, 5861–5882, https://doi.org/10.5194/bg-17-5861-2020, https://doi.org/10.5194/bg-17-5861-2020, 2020
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We developed a 1 km satellite-data-driven permafrost carbon model to evaluate soil respiration sensitivity to recent snow cover changes in Alaska. Results show earlier snowmelt enhances growing-season soil respiration and reduces annual carbon uptake, while early cold-season soil respiration is linked to the number of snow-free days after the land surface freezes. Our results also show nonnegligible influences of subgrid variability in surface conditions on model-simulated CO2 seasonal cycles.
Kuang-Yu Chang, William J. Riley, Patrick M. Crill, Robert F. Grant, and Scott R. Saleska
Biogeosciences, 17, 5849–5860, https://doi.org/10.5194/bg-17-5849-2020, https://doi.org/10.5194/bg-17-5849-2020, 2020
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Methane (CH4) is a strong greenhouse gas that can accelerate climate change and offset mitigation efforts. A key assumption embedded in many large-scale climate models is that ecosystem CH4 emissions can be estimated by fixed temperature relations. Here, we demonstrate that CH4 emissions cannot be parameterized by emergent temperature response alone due to variability driven by microbial and abiotic interactions. We also provide mechanistic understanding for observed CH4 emission hysteresis.
Jinnan Gong, Nigel Roulet, Steve Frolking, Heli Peltola, Anna M. Laine, Nicola Kokkonen, and Eeva-Stiina Tuittila
Biogeosciences, 17, 5693–5719, https://doi.org/10.5194/bg-17-5693-2020, https://doi.org/10.5194/bg-17-5693-2020, 2020
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In this study, which combined a field and lab experiment with modelling, we developed a process-based model for simulating dynamics within peatland moss communities. The model is useful because Sphagnum mosses are key engineers in peatlands; their response to changes in climate via altered hydrology controls the feedback of peatland biogeochemistry to climate. Our work showed that moss capitulum traits related to water retention are the mechanism controlling moss layer dynamics in peatlands.
Tea Thum, Julia E. M. S. Nabel, Aki Tsuruta, Tuula Aalto, Edward J. Dlugokencky, Jari Liski, Ingrid T. Luijkx, Tiina Markkanen, Julia Pongratz, Yukio Yoshida, and Sönke Zaehle
Biogeosciences, 17, 5721–5743, https://doi.org/10.5194/bg-17-5721-2020, https://doi.org/10.5194/bg-17-5721-2020, 2020
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Global vegetation models are important tools in estimating the impacts of global climate change. The fate of soil carbon is of the upmost importance as its emissions will enhance the atmospheric carbon dioxide concentration. To evaluate the skill of global vegetation models to model the soil carbon and its responses to environmental factors, it is important to use different data sources. We evaluated two different soil carbon models by using atmospheric carbon dioxide concentrations.
Maoyi Huang, Yi Xu, Marcos Longo, Michael Keller, Ryan G. Knox, Charles D. Koven, and Rosie A. Fisher
Biogeosciences, 17, 4999–5023, https://doi.org/10.5194/bg-17-4999-2020, https://doi.org/10.5194/bg-17-4999-2020, 2020
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The Functionally Assembled Terrestrial Ecosystem Simulator (FATES) is enhanced to mimic the ecological, biophysical, and biogeochemical processes following a logging event. The model can specify the timing and aerial extent of logging events; determine the survivorship of cohorts in the disturbed forest; and modifying the biomass, coarse woody debris, and litter pools. This study lays the foundation to simulate land use change and forest degradation in FATES as part of an Earth system model.
Junrong Zha and Qianla Zhuang
Biogeosciences, 17, 4591–4610, https://doi.org/10.5194/bg-17-4591-2020, https://doi.org/10.5194/bg-17-4591-2020, 2020
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This study incorporated microbial dormancy into a detailed microbe-based biogeochemistry model to examine the fate of Arctic carbon budgets under changing climate conditions. Compared with the model without microbial dormancy, the new model estimated a much higher carbon accumulation in the region during the last and current century. This study highlights the importance of the representation of microbial dormancy in earth system models to adequately quantify the carbon dynamics in the Arctic.
Thomas Gasser, Léa Crepin, Yann Quilcaille, Richard A. Houghton, Philippe Ciais, and Michael Obersteiner
Biogeosciences, 17, 4075–4101, https://doi.org/10.5194/bg-17-4075-2020, https://doi.org/10.5194/bg-17-4075-2020, 2020
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We combine several lines of evidence to provide a robust estimate of historical CO2 emissions from land use change. Our novel approach leads to reduced uncertainty and identifies key remaining sources of uncertainty and discrepancy.
We also quantify the carbon removal by natural ecosystems that would have occurred if these ecosystems had not been destroyed (mostly via deforestation). Over the last decade, this foregone carbon sink amounted to about 50 % of the actual emissions.
Hua W. Xie, Adriana L. Romero-Olivares, Michele Guindani, and Steven D. Allison
Biogeosciences, 17, 4043–4057, https://doi.org/10.5194/bg-17-4043-2020, https://doi.org/10.5194/bg-17-4043-2020, 2020
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Soil biogeochemical models (SBMs) are needed to predict future soil CO2 emissions levels, but we presently lack statistically rigorous frameworks for assessing the predictive utility of SBMs. In this study, we demonstrate one possible approach to evaluating SBMs by comparing the fits of two models to soil CO2 respiration data with recently developed Bayesian statistical goodness-of-fit metrics. Our results demonstrate that our approach is a viable one for continued development and refinement.
Stefano Manzoni, Arjun Chakrawal, Thomas Fischer, Joshua P. Schimel, Amilcare Porporato, and Giulia Vico
Biogeosciences, 17, 4007–4023, https://doi.org/10.5194/bg-17-4007-2020, https://doi.org/10.5194/bg-17-4007-2020, 2020
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Carbon dioxide is produced by soil microbes through respiration, which is particularly fast when soils are moistened by rain. Will respiration increase with future more intense rains and longer dry spells? With a mathematical model, we show that wetter conditions increase respiration. In contrast, if rainfall totals stay the same, but rain comes all at once after long dry spells, the average respiration will not change, but the contribution of the respiration bursts after rain will increase.
Nicholas C. Parazoo, Troy Magney, Alex Norton, Brett Raczka, Cédric Bacour, Fabienne Maignan, Ian Baker, Yongguang Zhang, Bo Qiu, Mingjie Shi, Natasha MacBean, Dave R. Bowling, Sean P. Burns, Peter D. Blanken, Jochen Stutz, Katja Grossmann, and Christian Frankenberg
Biogeosciences, 17, 3733–3755, https://doi.org/10.5194/bg-17-3733-2020, https://doi.org/10.5194/bg-17-3733-2020, 2020
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Satellite measurements of solar-induced chlorophyll fluorescence (SIF) provide a global measure of photosynthetic change. This enables scientists to better track carbon cycle responses to environmental change and tune biochemical processes in vegetation models for an improved simulation of future change. We use tower-instrumented SIF measurements and controlled model experiments to assess the state of the art in terrestrial biosphere SIF modeling and find a wide range of sensitivities to light.
Tong Yu and Qianlai Zhuang
Biogeosciences, 17, 3643–3657, https://doi.org/10.5194/bg-17-3643-2020, https://doi.org/10.5194/bg-17-3643-2020, 2020
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Biological nitrogen fixation (BNF) plays an important role in the global nitrogen cycle. However, the fixation rate has usually been measured or estimated at a particular observational site. This study develops a BNF model considering the symbiotic relationship between legume plants and bacteria. The model is extensively calibrated with site-level observational data and then extrapolated to the global terrestrial ecosystems to quantify the fixation rate in the 1990s.
Simon Jones, Lucy Rowland, Peter Cox, Deborah Hemming, Andy Wiltshire, Karina Williams, Nicholas C. Parazoo, Junjie Liu, Antonio C. L. da Costa, Patrick Meir, Maurizio Mencuccini, and Anna B. Harper
Biogeosciences, 17, 3589–3612, https://doi.org/10.5194/bg-17-3589-2020, https://doi.org/10.5194/bg-17-3589-2020, 2020
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Non-structural carbohydrates (NSCs) are an important set of molecules that help plants to grow and respire when photosynthesis is restricted by extreme climate events. In this paper we present a simple model of NSC storage and assess the effect that it has on simulations of vegetation at the ecosystem scale. Our model has the potential to significantly change predictions of plant behaviour in global vegetation models, which would have large implications for predictions of the future climate.
Charles D. Koven, Ryan G. Knox, Rosie A. Fisher, Jeffrey Q. Chambers, Bradley O. Christoffersen, Stuart J. Davies, Matteo Detto, Michael C. Dietze, Boris Faybishenko, Jennifer Holm, Maoyi Huang, Marlies Kovenock, Lara M. Kueppers, Gregory Lemieux, Elias Massoud, Nathan G. McDowell, Helene C. Muller-Landau, Jessica F. Needham, Richard J. Norby, Thomas Powell, Alistair Rogers, Shawn P. Serbin, Jacquelyn K. Shuman, Abigail L. S. Swann, Charuleka Varadharajan, Anthony P. Walker, S. Joseph Wright, and Chonggang Xu
Biogeosciences, 17, 3017–3044, https://doi.org/10.5194/bg-17-3017-2020, https://doi.org/10.5194/bg-17-3017-2020, 2020
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Tropical forests play a crucial role in governing climate feedbacks, and are incredibly diverse ecosystems, yet most Earth system models do not take into account the diversity of plant traits in these forests and how this diversity may govern feedbacks. We present an approach to represent diverse competing plant types within Earth system models, test this approach at a tropical forest site, and explore how the representation of disturbance and competition governs traits of the forest community.
Robert F. Grant, Sisi Lin, and Guillermo Hernandez-Ramirez
Biogeosciences, 17, 2021–2039, https://doi.org/10.5194/bg-17-2021-2020, https://doi.org/10.5194/bg-17-2021-2020, 2020
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Nitrification inhibitors (NI) have been shown to reduce emissions of nitrous oxide (N20), a potent greenhouse gas, from fertilizer and manure applied to agricultural fields. However difficulties in measuring N20 emissions limit our ability to estimate these reductions. Here we propose and test a mathematical model that may allow us to estimate these reductions under diverse site conditions. These estimates will be useful in determining emission factors for NI-amended fertilizer and manure.
Moritz Laub, Michael Scott Demyan, Yvonne Funkuin Nkwain, Sergey Blagodatsky, Thomas Kätterer, Hans-Peter Piepho, and Georg Cadisch
Biogeosciences, 17, 1393–1413, https://doi.org/10.5194/bg-17-1393-2020, https://doi.org/10.5194/bg-17-1393-2020, 2020
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Loss of soil carbon to the atmosphere represents a global challenge. We tested an innovative way to reduce the high uncertainty related to turnover of carbon stored in soils. With the use of infrared spectra of soils from model bare fallow systems, we were able to better assess the current state of soil carbon and predict its behavior in overdecadal time spans. In agreement with recent studies, carbon turnover seems faster than earlier assumed, with potential for high loss under mismanagement.
Genki Katata, Rüdiger Grote, Matthias Mauder, Matthias J. Zeeman, and Masakazu Ota
Biogeosciences, 17, 1071–1085, https://doi.org/10.5194/bg-17-1071-2020, https://doi.org/10.5194/bg-17-1071-2020, 2020
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In this paper, we demonstrate that high physiological activity levels during the extremely warm winter are allocated into the below-ground biomass and only to a minor extent used for additional plant growth during early spring. This process is so far largely unaccounted for in scenario analysis using global terrestrial biosphere models, and it may lead to carbon accumulation in the soil and/or carbon loss from the soil as a response to global warming.
Jinyan Yang, Belinda E. Medlyn, Martin G. De Kauwe, Remko A. Duursma, Mingkai Jiang, Dushan Kumarathunge, Kristine Y. Crous, Teresa E. Gimeno, Agnieszka Wujeska-Klause, and David S. Ellsworth
Biogeosciences, 17, 265–279, https://doi.org/10.5194/bg-17-265-2020, https://doi.org/10.5194/bg-17-265-2020, 2020
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This study addressed a major knowledge gap in the response of forest productivity to elevated CO2. We first quantified forest productivity of an evergreen forest under both ambient and elevated CO2, using a model constrained by in situ measurements. The simulation showed the canopy productivity response to elevated CO2 to be smaller than that at the leaf scale due to different limiting processes. This finding provides a key reference for the understanding of CO2 impacts on forest ecosystems.
Grace Pold, Seeta A. Sistla, and Kristen M. DeAngelis
Biogeosciences, 16, 4875–4888, https://doi.org/10.5194/bg-16-4875-2019, https://doi.org/10.5194/bg-16-4875-2019, 2019
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The litter decomposition model DEMENT was run under ambient temperatures and with 5 °C; of warming. We found that the loss of litter carbon to the atmosphere as CO2 was exacerbated by warming when the microbes in the model differed in their temperature responses, compared to when all microbes responded identically to warming. Our results therefore indicate that predicted changes in litter carbon stocks are sensitive to heterogeneity in key parameters of soil decomposer physiology.
Ensheng Weng, Ray Dybzinski, Caroline E. Farrior, and Stephen W. Pacala
Biogeosciences, 16, 4577–4599, https://doi.org/10.5194/bg-16-4577-2019, https://doi.org/10.5194/bg-16-4577-2019, 2019
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Our study illustrates that the competition processes for light and soil resources in a game-theoretic vegetation demographic model can substantially change the prediction of the contribution of ecosystems to the global carbon cycle. The model that tracks the competitive allocation strategies can generate significantly different ecosystem-level predictions than those with fixed allocation strategies.
Sophie Flack-Prain, Patrick Meir, Yadvinder Malhi, Thomas Luke Smallman, and Mathew Williams
Biogeosciences, 16, 4463–4484, https://doi.org/10.5194/bg-16-4463-2019, https://doi.org/10.5194/bg-16-4463-2019, 2019
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Across the Amazon rainforest, trees take in carbon through photosynthesis. However, photosynthesis across the basin is threatened by predicted shifts in rainfall patterns. To unpick how changes in rainfall affect photosynthesis, we use a model which combines climate data with our knowledge of photosynthesis and other plant processes. We find that stomatal constraints are less important, and instead shifts in leaf surface area and leaf properties drive changes in photosynthesis with rainfall.
Justine Ngoma, Maarten C. Braakhekke, Bart Kruijt, Eddy Moors, Iwan Supit, James H. Speer, Royd Vinya, and Rik Leemans
Biogeosciences, 16, 3853–3867, https://doi.org/10.5194/bg-16-3853-2019, https://doi.org/10.5194/bg-16-3853-2019, 2019
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The Zambezi teak forests are a source of raw material for the timber industry. Through application of the LPJ-GUESS vegetation model, we determined the forests' response to climate change at the wetter Kabompo, drier Sesheke, and intermediate Namwala sites in Zambia. While increased CO2 concentration enhances forests' productivity at Kabompo and Namwala, the decreased rainfall will reduce forests' productivity at Sesheke by the year 2099, resulting in reduced raw material for saw millers.
Karel Castro-Morales, Gregor Schürmann, Christoph Köstler, Christian Rödenbeck, Martin Heimann, and Sönke Zaehle
Biogeosciences, 16, 3009–3032, https://doi.org/10.5194/bg-16-3009-2019, https://doi.org/10.5194/bg-16-3009-2019, 2019
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To obtain nearly 30 years of global terrestrial carbon fluxes, we simultaneously incorporated in a land surface model three different time periods of two observational data sets: absorbed photosynthetic active radiation and atmospheric CO2 concentrations. One decade of data is enough to improve the modeled long-term trends and seasonal amplitudes of the assimilated variables, particularly in boreal regions. This model has the potential to provide short-term predictions of land carbon fluxes.
Wei Zhang, Chunyan Liu, Xunhua Zheng, Kai Wang, Feng Cui, Rui Wang, Siqi Li, Zhisheng Yao, and Jiang Zhu
Biogeosciences, 16, 2905–2922, https://doi.org/10.5194/bg-16-2905-2019, https://doi.org/10.5194/bg-16-2905-2019, 2019
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A biogeochemical process model-based approach for screening the best management practices (BMPs) of a three-crop system was proposed. The BMPs are the management alternatives with the lowest negative impact potentials that still satisfy all given constraints. Three BMP alternatives with overlapping uncertainties of simulated NIPs were screened from 6000 scenarios using the modified DNDC95 model, which could sustain crop yields, enlarge SOC stock, mitigate GHG, and reduce other nitrogen losses.
Cited articles
Aguilera, E., Lassaletta, L., Sanz Cobeña, A., Garnier, J., and Vallejo
Garcia, A.: The potential of organic fertilizers and water management to
reduce N2O emissions in Mediterranean climate cropping systems, Agr.
Ecosyst. Environ., 164, 32–52,
https://doi.org/10.1016/j.agee.2012.09.006, 2013.
Ammann, C., Neftel, A., Jocher, M., Fuhrer, J., and Leifeld, J.: Effect of
management and weather variations on the greenhouse gas budget of two
grasslands during a 10-year experiment, Agr. Ecosyst. Environ., 292, 106814,
https://doi.org/10.1016/j.agee.2019.106814, 2020.
Amundson, R. and Biardeau, L.: Opinion: Soil carbon sequestration is an
elusive climate mitigation tool, P. Natl. Acad. Sci. USA, 115,
11652–11656, https://doi.org/10.1073/pnas.1815901115, 2018.
Asseng, S., Ewert, F., Martre, P., Rötter, R. P., Lobell, D. B.,
Cammarano, D., Kimball, B. A., Ottman, M. J., Wall, G. W., White, J. W., and
Reynolds, M. P.: Rising temperatures reduce global wheat production, Nat. Clim.
Change, 5, 143–147, https://doi.org/10.1038/nclimate2470,
2015.
Bahn, M., Rodeghiero, M., Anderson-Dunn, M., Dore, S., Gimeno, C.,
Drösler, M., Williams, M., Ammann, C., Berninger, F., Flechard, C., and
Jones, S.: Soil respiration in European grasslands in relation to climate
and assimilate supply, Ecosystems, 11, 1352–1367, https://doi.org/10.1007/s10021-008-9198-0, 2008.
Balkovič, J., van der Velde, M., Schmid, E., Skalský, 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, https://doi.org/10.1016/j.agsy.2013.05.008, 2013.
Bassu, S., Brisson, N., Durand, J.-L., Boote, K., Lizaso, J., Jones, J.W.,
Rosenzweig, C., Ruane, A. C., Adam, M., Baron, C., Basso, B., Biernath, C.,
Boogaard, H., Conijn, S., Corbeels, M., Deryng, D., De Sanctis, G., Gayler,
S., Grassini, P., Hatfield, J.L., Hoek, S., Izaurralde, C., Jongschaap, R.,
Kemanian, A.R., Kersebaum, K.C., Kim, S.-H., Kumar, N.S., Makowski, D.,
Müller, C., Nendel, C., Priesack, E., Pravia, M.V., Sau, F., Shcherbak,
I., Tao, F., Teixeira, E., Timlin, D., and Waha, K.: How do various maize
crop models vary in their responses to climate change factors?, Glob. Change
Biol., 20, 2301–2320, https://doi.org/10.1111/gcb.12520,
2014.
Blanke, J., Boke-Olén, N., Olin, S., Chang, J., Sahlin, U., Lindeskog,
M., and Lehsten, V.: Implications of accounting for management intensity on
carbon and nitrogen balances of European grasslands, PLoS One, 13,
e0201058, https://doi.org/10.1371/journal.pone.0201058, 2018.
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.
Britz, W. and Witzke, H.: CAPRI Model Documentation 2008: Version 2,
Institute for Food and Resource Economics, University of Bonn, Germany,
http://www.capri-model.org/docs/capri_documentation.pdf (last access: last access: 17 June 2022), 2008.
Buysse, P., Bodson, B., Debacq, A., De Ligne, A., Heinesch, B., Manise, T.,
Moureaux, C., and Aubinet, M.: Carbon budget measurement over 12 years at a
crop production site in the silty-loam region in Belgium, Agr. Forest
Meteorol., 246, 241–255, https://doi.org/10.1016/j.agrformet.2017.07.004, 2017.
Calanca, P., Vuichard, N., Campbell, C., Viovy, N., Cozic, A., Fuhrer, J.,
and Soussana, J. F.: Simulating the fluxes of CO2 and N2O in European
grasslands with the Pasture Simulation Model (PaSim), Agr. Ecosyst.
Environ., 121, 164–174, https://doi.org/10.1016/j.agee.2006.12.010, 2007.
Cayuela, M. L., Aguilera, E., Sanz-Cobena, A., Adams, D.C., Abalos, D.,
Barton, L., Ryals, R., Silver, W. L., Alfaro, M. A., Pappa, V. A., Smith, P.,
Garnier, J., Billen, G., Bouwman, L., Bondeau, A., and Lassaletta, L.:
Direct nitrous oxide emissions in Mediterranean climate cropping systems:
emission factors based on a meta-analysis of available measurement data,
Agr. Ecosyst. Environ., 238, 25–35, https://doi.org/10.1016/j.agee.2016.10.006, 2017.
Ceschia, E., Beziat, P., Dejoux, J. F., and Aubinet, M.: Management effects on
net ecosystem carbon and GHG budgets at European crop sites, Agriculture,
139, 363–383 , 2010.
Chabbi, A., Lehmann, J., Ciais, P., Loescher, H. W., Cotrufo, M. F., Don,
A., SanClements, M., Schipper, L., Six, J., Smith, P., and Rumpel, C.:
Aligning agriculture and climate policy, Nat. Clim. Change, 7, 307–309,
https://doi.org/10.1038/nclimate3286, 2017.
Challinor, A. J., Ewert, F., Arnold, S., Simelton, E., and Fraser, E.: Crops
and climate change: progress, trends, and challenges in simulating impacts
and informing adaptation, J. Exp. Bot., 60, 2775–2789, https://doi.org/10.1093/jxb/erp062, 2009.
Challinor, A. J., Watson, J., Lobell, D. B., Howden, S. M., Smith, D. R., and
Chhetri, N.: A meta-analysis of crop yield under climate change and
adaptation, Nat. Clim. Change, 4, 287–291, https://doi.org/10.1038/nclimate2153, 2014.
Chang J., Ciais P., Viovy N., Soussana J.-F., Klumpp K., and Sultan B.:
Future productivity and phenology changes in European grasslands for
different warming levels: Implications for grassland management and carbon
balance, Carbon Balance Manag., 12, 1–21, https://doi.org/10.1186/s13021-017-0079-8, 2017.
Chang, J., Viovy, N., Vuichard, N., Ciais, P., Campioli, M., Klumpp, K.,
Martin, R., Leip, A., and Soussana, J.-F.: Modeled changes in potential
grassland productivity and in grass-fed ruminant livestock density in Europe
over 1961–2010, PLoS ONE, 10, e0127554, https://doi.org/10.1371/journal.pone.0127554, 2015.
Chaudhary, A., Gustafson, D., and Mathys, A.: Multi-indicator sustainability
assessment of global food systems, Nat. Commun. 9, 848, https://doi.org/10.1038/s41467-018-03308-7, 2018.
Collins, W. J., Bellouin, N., Doutriaux-Boucher, M., Gedney, N., Halloran,
P., Hinton, T., Hughes, J., Jones, C. D., Joshi, M., Liddicoat, S., Martin,
G., O'Connor, F., Rae, J., Senior, C., Sitch, S., Totterdell, I., Wiltshire,
A., and Woodward, S.: Development and evaluation of an Earth-System model –
HadGEM2, Geosci. Model Dev., 4, 1051–1075, https://doi.org/10.5194/gmd-4-1051-2011, 2011.
Conant, R. T., Cerri, C. E. P., Osborne, B. B., and Paustian, K.: Grassland
management impacts on soil carbon stocks: A new synthesis, Ecol. Appl., 27, 662–668, https://doi.org/10.1002/eap.1473, 2017.
Constantin, J., Raynal, H., Casellas, E., Hoffmann, H., Bindi, M., Doro, L.,
Eckersten, H., Gaiser, T., Grosz, B., Haas, E., Kersebaum, K.-C., Klatt, S.,
Kuhnert, M., Lewan, E., Maharjan, G.R., Moriondo, M., Nendel, C., Roggero,
P.P., Specka, X., Trombi, G., Villa, A., Wang, E., Weihermüller, L.,
Yeluripati, J., Zhao, Z., Ewert, F., and Bergez, J.-E.: Management and
spatial resolution effects on yield and water balance at regional scale in
crop models, Agr. Forest Meteorol., 275, 184–195, https://doi.org/10.1016/j.agrformet.2019.05.013, 2019.
Cowan, N. J., Levy, P. E., Famulari, D., Anderson, M., Drewer, J., Carozzi, M., Reay, D. S., and Skiba, U. M.: The influence of tillage on N2O fluxes from an intensively managed grazed grassland in Scotland, Biogeosciences, 13, 4811–4821, https://doi.org/10.5194/bg-13-4811-2016, 2016.
De Antoni Migliorati, M., Bell, M., Grace, P. R., Scheer, C., Rowlings, D. W.,
and Liu, S.: Legume pastures can reduce N2O emissions intensity in
subtropical cereal cropping systems, Agr. Ecosyst. Environ., 204, 27–39,
https://doi.org/10.1016/j.agee.2015.02.007, 2015.
de Souza, T. T., Silva Antolin, S. L., Bianchini, V., Pereira, R., Moura Silva,
E., and Marin, F.: Longer crop cycle lengths could offset the negative
effects of climate change on Brazilian maize, Bragantia, 78, 622–631,
https://doi.org/10.1590/1678-4499.20190085, 2019.
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, 2011.
Del Grosso, S. J., Ojima, D. S., Parton, W. J., Stehfest, E., Heistemann, M.,
DeAngelo, B., and Rose, S.: Global scale DAYCENT model analysis of greenhouse
gas emissions and mitigation strategies for cropped soils, Global Planet
Change, 67, 44–50, https://doi.org/10.1016/j.gloplacha.2008.12.006, 2009.
Dono, G., Cortignani, R., Dell'Unto, D., Deligios, P., Doro, L., Lacetera,
N., Mula, L., Pasqui, M., Quaresima, S., Vitali, A., and Roggero, P. P.: Winners
and losers from climate change in agriculture: insights from a case study in
the Mediterranean basin, Agr. Syst., 147, 65–75, https://doi.org/10.1016/j.agsy.2016.05.013, 2016.
Drouet J.-L., Capian N., Fiorelli J.-L., Blanfort V., Capitaine M., Duretz
S., Gabrielle B., Martin R., Lardy R., Cellier P., and Soussana J.-F.:
Sensitivity analysis for models of greenhouse gas emissions at farm level.
Case study of N2O emissions simulated by the CERES-EGC model, Environ.
Pollut., 159, 3156–3161, https://doi.org/10.1016/j.envpol.2011.01.019, 2011.
EC (European Commission): Communication from the commission to the European
parliament, the council, the European economic and social committee and the
committee of the regions Stepping up Europe's 2030 climate ambition
Investing in a climate-neutral future for the benefit of our people,
https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:52020DC0562&from=EN (last access: 17 June 2022), 2020.
EEA (European Environment Agency): Trends and projections in Europe 2020,
Tracking progress towards Europe's climate and energy targets, https://www.eea.europa.eu//publications/trends-and-projections-in-europe-2020 (last access: 17 June 2022),
2020.
Ehrhardt, F., Soussana, J.-F., Bellocchi, G., Grace, P., McAuliffe, R.,
Recous, S., Sándor, R., Smith, P., Snow, de Antoni Migliorati, Basso,
B., Bhatia, A., Brilli, L., Doltra, J., Dorich, C. D., Doro, L., Fitton, N.,
Giacomini, S. J., Grant, B., Harrison, M. T., Jones, S. K., Kirschbaum, M.
U. F., Klumpp, K., Laville, P., Léonard, J., Liebig, M., Lieffering,
Martin, R., Massad, R. S., Meier, E., Merbold, L., Moore, Myrgiotis, Newton,
Pattey, Rolinski, S., Sharp, J., Smith, Wu, L., and Zhang, Q.: Assessing
uncertainties in crop and pasture ensemble model simulations of productivity
and N2O emissions, Glob. Change Biol., 24, e603-e616, https://doi.org/10.1111/gcb.13965, 2018.
Emmel, C., Winkler, A., Hörtnagl, L., Revill, A., Ammann, C., D'Odorico,
P., Buchmann, N., and Eugster, W.: Integrated management of a Swiss cropland
is not sufficient to preserve its soil carbon pool in the long term,
Biogeosciences, 15, 5377–5393, https://doi.org/10.5194/bg-15-5377-2018, 2018.
Eurostat: Agri-environmental indicator – greenhouse gas emissions,
https://ec.europa.eu/eurostat/ (last access: 7 September 2021),
2017.
Eurostat: European Statistical Office database, https://ec.europa.eu/eurostat/data/database (last access: 17 June 2022), 2019a.
Eurostat: European Statistical Office database, Share of irrigable and
irrigated areas in utilised agricultural area (UAA) by NUTS 2 regions, http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=aei_ef_ir&lang=en (last access: 17 June 2022), 2019b.
Eurostat: Annual crop statistics handbook, 2020 Edn.,
https://ec.europa.eu/eurostat/cache/metadata/Annexes/apro_cp_esms_an1.pdf (last access: 17 June 2022), 2020.
Ewert, F., Van Ittersum, M. K., Heckelei, T., Therond, O., Bezlepkina, I., and
Andersen, E.: Scale changes and model linking methods for integrated
assessment of agri-environmental systems, Agr. Ecosyst. Environ., 142,
6–17, https://https://doi.org/10.1016/j.agee.2011.05.016, 2011.
Faivre, R., Leenhardt, D., Voltz, M., Benoit, M., Papy, F., Dedieu, G.,
and Wallach, D.: Spatialising crop models, Agronomie, 24, 205–217,
https://doi.org/10.1051/agro:2004016, 2004.
FAOSTAT (Food and Agriculture Organization of the United Nations): FAOSTAT Database, Rome, Italy, https://www.fao.org/faostat/en/#home, last access: 17 June 2022.
Ferrara, R. M., Carozzi, M., Decuq, C., Loubet, B., Finco, A., Marzuoli, R.,
Gerosa, G., Di Tommasi, P., Magliulo, V., and Rana, G.: Ammonia, nitrous oxide,
carbon dioxide, and water vapor fluxes after green manuring of faba bean
under Mediterranean climate, Agr. Ecosyst. Environ., 315, 107439,
https://doi.org/10.1016/j.agee.2021.107439, 2021.
Fischer, G., Shah, M., Tubiello, F. N., and von Velthuizen, H.:
Socio-economic and climate change impacts on agriculture: An integrated
assessment, 1990–2080, Philos. T. R. Soc. Lond. Ser. B, 360, 2067–2083,
https://doi.org/10.1098/rstb.2005.1744, 2005.
Fitton, N., Alexander, P., Arnell, N., Bajzelj, B., Calvin, K., Doelman, J.,
Gerber, J. S., Havlik, P., Hasegawa, T., Herrero, M., Krisztin, T., van
Meijl, H., Powell, T., Sands, R., Stehfest, E., West, P. C., and Smith, P.:
The vulnerabilities of agricultural land and food production to future water
scarcity, Glob. Environ. Change, 58, 101944, https://doi.org/10.1016/j.gloenvcha.2019.101944, 2019.
Folberth, C., Elliott, J., Müller, C., Balkovic, J.,
Chryssanthacopoulos, J., Izaurralde, R. C., Jones, C. D., Khabarov, N., Liu, W.,
Reddy, A., Schmid, E., Skalský, R., Yang, H., Arneth, A., Ciais, P., Deryng, D.,
Lawrence, P. J., Olin, S., Pugh, T. A. M., Ruane, A. C., and Wang, X.:
Parameterization-induced uncertainties and impacts of crop management
harmonization in a global gridded crop model ensemble, PLoS ONE, 14,
e0221862, https://doi.org/0.1371/journal.pone.0221862, 2019.
Fuss, S., Jones, C. D., Kraxner, F., Peters, G. P., Smith, P., Tavoni, M., Van
Vuuren, D. P., Canadell, J. G., Jackson, R. B., Milne, J., Moreira, J. R.,
Nakicenovic, N., Sharifi, A., and Yamagata, Y.: Research priorities for
negative emissions, Environ. Res. Lett., 11, 115007, https://doi.org/10.1088/1748-9326/11/11/115007, 2016.
Gabrielle, B., Da-Silveira, J., Houot, S., and Michelin, J.: Field-scale
modelling of carbon and nitrogen dynamics in soils amended with urban waste
composts, Agr. Ecosyst. Environ., 110, 289e299, https://doi.org/10.1016/j.agee.2005.04.015, 2005.
Goglio, P., Colnenne-David, C., Laville, P., Doré, T., and Gabrielle,
B.: 29 % N2O emission reduction from a modelled low-greenhouse gas
cropping system during 2009–2011, Environ. Chem. Lett., 11, 143–149,
https://doi.org/doi.org/10.1007/s10311-012-0389-8, 2013.
Gottschalk, P., Wattenbach, M., Neftel, A., Fuhrer, J., Jones, M., Lanigan, G.,
Davis, P., Campbell, C., Soussana, J.-F., and Smith, P.: The role of measurement
uncertainties for the simulation of grassland net ecosystem exchange (NEE)
in Europe, Agr. Ecosyst. Environ., 121, 175–185, https://doi.org/10.1016/j.agee.2006.12.026, 2007.
Haas, E., Carozzi, M., Massad, R. S, Scheer, C., and Butterbach-Bahl, K.:
Testing the performance of CERES-EGC and LandscapeDNDC to simulate effects
of residue management on soil N2O emissions, ResidueGas deliverable report
4.1,
https://projects.au.dk/fileadmin/projects/residuegas/D_reports/ResidueGas_D4.1.pdf (last access: 17 June 2022), 2021.
Haas, E., Carozzi, M., Massad, R. S., Butterbach-Bahl, K., and Scheer, C.:
Long term impact of residue management on soil organic carbon stocks and
nitrous oxide emissions from European croplands, Sci. Total Environ., 154932,
https://doi.org/10.1016/j.scitotenv.2022.154932, 2022.
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, 2013.
Hansen, J. W. and Jones, J. W.: Scaling-up crop models for climate variability
applications, Agr. Syst., 65, 43–72, https://doi.org/10.1016/S0308-521X(00)00025-1, 2000.
Hassink, J. and Whitmore, A. P.: A Model of the Physical Protection of
Organic Matter in Soils, Soil Sci. Soc. Am. J., 61, 131–139, https://doi.org/10.2136/sssaj1997.03615995006100010020x, 1997.
Hénault, C., Bizouard, F., Laville, P., Gabrielle, B., Nicoullaud, B.,
Germon, J. C., and Cellier, P.: Predicting in situ soil N2O emission using
NOE algorithm and soil database, Glob. Change Biol., 11, 115–127, https://doi.org/10.1111/j.1365-2486.2004.00879.x, 2005.
Hiederer, R.: Mapping Soil Properties for Europe – Spatial Representation of
Soil Database Attributes, Luxembourg, Publications Office of the European
Union – 2013, 47 pp., EUR26082EN Scientific and Technical Research series,
ISSN 1831–9424, https://doi.org/10.2788/94128, 2013.
Hoffmann, H., Zhao, G., Asseng, S., Bindi, M., Biernath, C., Constantin, J.,
Coucheney, E., Dechow, R., Doro, L., Eckersten, H., Gaiser, T., Grosz, B.,
Heinlein, F., Kassie, B., Kersebaum, K., Klein, C., Kuhnert, M., Lewan, E.,
Moriondo, M., Nendel, C., Priesack, E., Raynal, H., Roggero, P., Rötter, R.,
Siebert, S., Specka, X., Tao, F., Teixeira, E., Trombi, G., Wallach, D.,
Weihermüller, L., Yeluripati, J., and Ewert, F.: Impact of spatial soil and
climate input data aggregation on regional yield simulations, PloS One, 11,
e0151782, https://doi.org/10.1371/journal.pone.0151782, 2016.
Hörtnagl, L., Barthel, M., Buchmann, N., Eugster, W., Butterbach-Bahl,
K., Díaz-Pinés, E., Zeeman, M., Klumpp, K., Kiese, R., Bahn, M.,
Hammerle, A., Lu, H., Ladreiter-Knauss, T., Burri, S., and Merbold, L.:
Greenhouse gas fluxes over managed grasslands in Central Europe, Glob.
Change Biol., 24, 1843–1872, https://doi.org/10.1111/gcb.14079, 2018.
Howden, S. M., Soussana, J.-F., Tubiello, F. N., Chhetri, N., Dunlop, M., and
Meinke, H.: Adapting agriculture to climate change, P. Natl. Acad. Sci.
USA, 104, 19691–19696, https://doi.org/10.1073/pnas.0701890104,
2007.
Hsu, J. S., Powell, J., and Adler, P. B.: Sensitivity of mean annual primary
production to precipitation, Glob. Change Biol., 18, 2246–2255,
https://doi.org/10.1111/j.1365-2486.2012.02687.x, 2012.
IPCC: Climate Change 2013: The Physical Science Basis, Contribution of
Working Group I to the Fifth Assessment Report of the Intergovernmental
Panel on Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor,
M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley,
P. M., Cambridge University Press, Cambridge, United Kingdom and New
York, NY, USA, 1535, https://doi.org/10.1017/CBO9781107415324,
2013.
IPCC: Global warming of 1.5 ∘C. An IPCC Special Report on the
impacts of global warming of 1.5 ∘C above pre-industrial levels
and related global greenhouse gas emission pathways, in the context of
strengthening the global response to the threat of climate change,
sustainable development, and efforts to eradicate poverty, edited by:
Masson-Delmotte, V., Zhai, P., Pörtner, H. O., Roberts, D., Skea, J.,
Shukla, P. R., Pirani, A., Moufouma-Okia, W., Péan, C., Pidcock, R., Connors, S., Matthews, J.
B. R., Chen, Y., Zhou, X., Gomis, M. I., Lonnoy, E., Maycock, T.,
Tignor, M., and Waterfield, T., Cambridge University Press, https://doi.org/10.1017/9781009157940, 2018.
Jones, C. A. and Kiniry, J. R.: CERES-Maize: A simulation model of maize
growth and development, Texas A&M University Press, Temple, TX, USA, ISBN
08-909-62693, 1986.
Jones, C. D., Hughes, J. K., Bellouin, N., Hardiman, S. C., Jones, G. S.,
Knight, J., Liddicoat, S., O'Connor, F. M., Andres, R. J., Bell, C., Boo,
K.-O., Bozzo, A., Butchart, N., Cadule, P., Corbin, K. D.,
Doutriaux-Boucher, M., Friedlingstein, P., Gornall, J., Gray, L., Halloran,
P. R., Hurtt, G., Ingram, W. J., Lamarque, J.-F., Law, R. M., Meinshausen,
M., Osprey, S., Palin, E. J., Parsons Chini, L., Raddatz, T., Sanderson, M.
G., Sellar, A. A., Schurer, A., Valdes, P., Wood, N., Woodward, S.,
Yoshioka, M., and Zerroukat, M.: The HadGEM2-ES implementation of CMIP5
centennial simulations, Geosci. Model Dev., 4, 543–570, https://doi.org/10.5194/gmd-4-543-2011, 2011.
Jones, S. K., Helfter, C., Anderson, M., Coyle, M., Campbell, C., Famulari,
D., Di Marco, C., van Dijk, N., Tang, Y. S., Topp, C. F. E., Kiese, R.,
Kindler, R., Siemens, J., Schrumpf, M., Kaiser, K., Nemitz, E., Levy, P. E.,
Rees, R. M., Sutton, M. A., and Skiba, U. M.: The nitrogen, carbon and
greenhouse gas budget of a grazed, cut and fertilised temperate grassland,
Biogeosciences, 14, 2069–2088, https://doi.org/10.5194/bg-14-2069-2017, 2016.
Kanter, D., Zhang, X., Mauzerall, D., Malyshev, S., and Shevliakova, E.: The
importance of climate change and nitrogen use efficiency for future nitrous
oxide emissions from agriculture, Environ. Res. Lett., 11, 094003, https://doi.org/10.1088/1748-9326/11/9/094003, 2016.
Kirschbaum, M. U. F.: The temperature dependence of soil organic matter
decomposition, and the effect of global warming on soil organic C storage,
Soil Biol. Biochem., 27, 753–760, https://doi.org/10.1016/0038-0717(94)00242-s, 1995.
Kutsch, W. L., Aubinet, M., Buchmann, N., Smith, P., Osborne, B., Eugster,
W., Wattenbach, M., Schrumpf, M., Schulze, E. D., Tomelleri, E., Ceschia,
E., Bernhofer, C., Beziat, P., Carrara, A., Di Tommasi, P., Grünwald,
T., Jones, M., Magliulo, V., Marloie, O., Moureaux, C., Olioso, A., Sanz, M.
J., Saunders, M., Søgaard, H., and Ziegler, W.: The net biome production
of full crop rotations in Europe, Agr. Ecosyst. Environ., 139, 336–345,
https://doi.org/10.1016/j.agee.2010.07.016, 2010.
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.
Launay, C., Constantin, J., Chlebowski, F., Houot, S., Graux, A.I., Klumpp,
K., Martin, R., Mary, B., Pellerin, S., and Therond, O. Estimating the
carbon storage potential and greenhouse gas emissions of French arable
cropland using high-resolution modeling, Glob. Change Biol., 27,
1645–1661, https://doi.org/10.1111/gcb.15512, 2021.
Lawton, D., Leahy, P., Kiely, G., Byrne, K., and Calanca, P.: Modeling of net
ecosystem exchange and its components for a humid grassland ecosystem,
J. Geophys. Res.-Biogeo., 111, G04013, https://doi.org/10.1029/2006JG000160, 2006.
Lehmann, N., Finger, R., Klein, T., Calanca, P., and Walter, A.: Adapting crop
management practices to climate change: Modeling optimal solutions at the
field scale, Agr. Syst., 117, 55–65, https://doi.org/10.1016/j.agsy.2012.12.011, 2013.
Lehuger, S., Gabrielle, B., Laville, P., Lamboni, M., Loubet, B., and
Cellier, P.: Predicting and mitigating the net greenhouse gas emissions of
crop rotations in Western Europe, Agr. Forest Meteorol., 151,
1654–1671, https://doi.org/10.1016/j.agrformet.2011.07.002,
2011.
Lehuger, S., Gabrielle, B., Oijen, M. Van, Makowski, D., Germon, J., Morvan,
T., Hénault, C., Lehuger, S., Gabrielle, B., Oijen, M. Van, Makowski,
D., and Germon, J.: Bayesian calibration of the nitrous oxide emission
module of an agro-ecosystem model, Agr. Ecosyst. Environ., 133, 208–222,
https://doi.org/10.1016/j.agee.2009.04.022, 2009.
Lehuger, S., Gabrielle, B., Cellier, P., Loubet, B., Roche, R., Béziat,
P., Ceschia, E., and Wattenbach, M.: Predicting the net carbon exchanges of
crop rotations in Europe with an agro-ecosystem model, Agr. Ecosyst.
Environ., 139, 384–395, https://doi.org/10.1016/j.agee.2010.06.011, 2010.
Leip, A., Marchi, G., Koeble, R., Kempen, M., Britz, W., and Li, C.: Linking
an economic model for European agriculture with a mechanistic model to
estimate nitrogen and carbon losses from arable soils in Europe,
Biogeosciences, 5, 73–94, https://doi.org/10.5194/bg-5-73-2008,
2008.
Leip, A., Britz, W., Weiss, F., and de Vries, W.: Farm, land, and soil
nitrogen budgets for agriculture in Europe calculated with CAPRI, Environ.
Pollut., 159, 3243–3253, https://doi.org/10.1016/j.envpol.2011.01.040, 2011.
Lesschen, J. P., van den Berg, M., Westhoek, H. J., Witzke, H. P., and Oenema,
O.: Greenhouse gas emission profiles of European livestock sectors, Anim.
Feed Sci. Technol., 166/167, 16–28, https://doi.org/10.1016/j.anifeedsci.2011.04.058, 2011.
Li, X., Sørensen, P., Olesen, J. E., and Petersen, S. O.: Evidence for
denitrification as main source of N2O emission from residue-amended soil,
Soil Biol. Biochem., 92, 153–160, https://doi.org/10.1016/j.soilbio.2015.10.008, 2016.
Lobell, D. B. and Tebaldi, C.: Getting caught with our plants down: The
risks of a global crop yield slowdown from climate trends in the next two
decades, Environ. Res. Lett., 9, 074003, https://doi.org/10.1088/1748-9326/9/7/074003, 2014.
Lugato, E., Zuliani, M., Alberti, G., Vedove, G. D., Gioli, B., Miglietta,
F., and Peressotti, A.: Application of DNDC biogeochemistry model to
estimate greenhouse gas emissions from Italian agricultural areas at high
spatial resolution, Agr. Ecosyst. Environ., 139, 546–556, https://doi.org/10.1016/j.agee.2010.09.015, 2010.
Lugato, E., Bampa, F., Panagos, P., Montanarella, L., and Jones, A.:
Potential carbon sequestration of European arable soils estimated by
modelling a comprehensive set of management practices, Glob. Change Biol.,
20, 3557–3567, https://doi.org/10.1111/gcb.12551,
2014.
Lugato, E., Paniagua, L., Jones, A., de Vries, W., and Leip, A.: Complementing
the topsoil information of the Land Use/Land Cover Area Frame Survey (LUCAS)
with modelled N2O emissions, PLoS ONE, 12, e0176111, https://doi.org/10.1371/journal.pone.0176111, 2017.
Lugato, E., Leip, A., and Jones, A.: Mitigation potential of soil carbon
management overestimated by neglecting N2O emissions, Nat. Clim. Change, 8,
219–223, https://doi.org/10.1038/s41558-018-0087-z, 2018.
Ma, S., Lardy, R., Graux, A.-I., Ben Touhami, H., Klumpp, K., Martin, R.,
and Bellocchi, G.: Regional-scale analysis of carbon and water cycles on
managed grassland systems, Environ. Modell. Softw., 72, 356–371, https://doi.org/10.1016/j.envsoft.2015.03.007, 2015.
Maaz, T. M., Sapkota, T. B., Eagle, A. J., Kantar, M. B., Bruulsema, T. W.,
and Majumdar, K.: Meta-analysis of yield and nitrous oxide outcomes for
nitrogen management in agriculture, Glob. Change Biol., 27,
2343–2360, https://https://doi.org/10.1111/gcb.15588, 2021.
Martínez-López J., Bagstad K.J., Balbi S., Magrach A., Voigt B.,
Athanasiadis I., Pascual M., Willcock S., and Villa F.: Towards globally
customizable ecosystem service models, Sci. Total Environ., 650,
2325–2336, https://doi.org/10.1016/j.scitotenv.2018.09.371,
2019.
Martre, P., Wallach, D., Asseng, S., Ewert, F., Jones, J. W., Rötter,
R. P., Boote, K. J., Ruane, A. C., Thorburn, P. J., Cammarano, D., and Hatfield,
J. L.: Multimodel ensembles of wheat growth: many models are better than one,
Glob. Change Biol., 21, 911–925, https://doi.org/10.1111/gcb.12768, 2015.
Metzger, M. J., Bunce, R. G. H., Jongman, R. H. G., Mücher, C. A., and
Watkins, J. W.: A climatic stratification of the environment of Europe,
Glob. Ecol. Biogeogr., 14, 549–563,
https://doi.org/10.1111/j.1466-822X.2005.00190.x, 2005.
Minasny, B., Malone, B. P., McBratney, A. B., Angers, D. A., Arrouays, D.,
Chambers, A., Chaplot, V., Chen, Z.-S., Cheng, K., Das, B. S., Field, D. J.,
Gimona, A., Hedley, C. B., Hong, S. Y., Mandal, B., Marchant, B. P., Martin,
M., McConkey, B. G., Mulder, V. L., O'Rourke, S., Richer-de-Forges, A. C.,
Odeh, I., Padarian, J., Paustian, K., Pan, G., Poggio, L., Savin, I.,
Stolbovoy, V., Stockmann, U., Sulaeman, Y., Tsui, C.-C., Vågen, T.-G.,
van Wesemael, B., and Winowiecki, L.: Soil carbon 4 per mille, Geoderma,
292, 59–86, https://doi.org/10.1016/j.geoderma.2017.01.002,
2017.
Minoli, S., Müller, C., Elliott, J., Ruane, A.C., Jägermeyr, J.,
Zabel, F., Dury, M., Folberth, C., François, L., Hank, T. B., Jacquemin,
I., Liu, W., Olin, S., and Pugh, T. A.: Global response patterns of major
rainfed crops to adaptation by maintaining current growing periods and
irrigation, Earth's Future, 7, 1464–80, https://doi.org/10.1029/2018EF001130, 2019.
Molina, J. A. E., Clapp, C. E., Shaffer, M. J., Chichester, F. W., and Larson,
W. E.: NCSOIL, a model of nitrogen and carbon transformations in soil:
description, calibration, and behavior, Soil Sci. Soc. Am. J., 47, 85–91,
https://doi.org/10.2136/sssaj1983.03615995004700010017x,
1983.
Molina-Herrera, S., Haas, E., Klatt, S., Kraus, D., Augustin, J., Magliulo,
V., Tallec, T., Ceschia, E., Ammann, C., Loubet, B., Skiba, U., Jones, S.,
Brümmer, C., Butterbach-Bahl, K., and Kiese, R.: A modeling study on
mitigation of N2O emissions and NO3 leaching at different agricultural sites
across Europe using LandscapeDNDC, Sci. Total Environ., 553, 128–140,
https://doi.org/10.1016/j.scitotenv.2015.12.099, 2016.
Morais, T. G., Teixeira, R. F., and Domingos, T.: Detailed global modelling of
soil organic carbon in cropland, grassland and forest soils, PLoS ONE, 14,
e0222604, https://doi.org/10.1371/journal.pone.0222604, 2019.
Mueller, B., Hauser, M., Iles, C., Rimi, R. H., Zwiers, F. W., and Wan, H.:
Lengthening of the growing season in wheat and maize producing regions,
Weather Clim. Extrem., 9, 47–56, https://doi.org/10.1016/j.wace.2015.04.001, 2015.
Myrgiotis, V., Williams, M., Rees, R. M., and Topp, C. F. E.: Estimating the
soil N2O emission intensity of croplands in northwest Europe,
Biogeosciences, 16, 1641–1655, https://doi.org/10.5194/bg-16-1641-2019, 2019.
Nicolardot, B., Molina, J. A. E., and Allard, M. R.: C and N fluxes between
pools of soil organic matter: model calibration with long-term incubation
data, Soil Biol. Biochem., 26, 235–243, https://doi.org/10.1016/0038-0717(94)90163-5, 1994.
Niu, X., Easterling, W., Hays, C. J., Jacobs, A., and Mearns, L.: Reliability and
input-data induced uncertainty of EPIC model to estimate climate change
impact on sorghum yields in the U.S, Great Plains, Agr. Ecosyst. Environ.,
129, 268–276, https://doi.org/10.1016/j.agee.2008.09.012, 2009.
Olesen, J. E.: Climate change impacts on society: Section 5.3, Agriculture, in:
Climate change, impacts and vulnerability in Europe 2016: An indicator-based
report, European Environment Agency, 1, 223–244, 2017.
Olesen, J. E. and Bindi, M.: Consequences of climate change for European
agricultural productivity, land use and policy, Eur. J. Agron., 16, 239–262,
https://doi.org/10.1016/S1161-0301(02)00004-7, 2002.
Olesen, J. E., Trnka, M., Kersebaum, K. C., Skjelvåg, 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.
Olesen, J. E., Børgesen, C. D., Elsgaard, L., Palosuo, T., Rötter, R. P.,
Skjelvåg, A. O., Peltonen-Sainio, P., Börjesson, T., Trnka, M., Ewert, F.,
Siebert, S., Brisson, N., Eitzinger, J., van Asselt, E. D., Oberforster, M., and
van der Fels-Klerx, H. J.: Changes in time of sowing, flowering and maturity
of cereals in Europe under climate change, Food Addit. Conta.m Pt. A, 29,
1527–1542, https://doi.org/10.1080/19440049.2012.712060, 2012.
Parry, M., Rosenzweig, C., and Livermore, M.: Climate change, global food
supply and risk of hunger, Philos. T. R. Soc. B, 360, 2125–2138,
https://doi.org/10.1098/rstb.2005.1751, 2005.
Parton, W. J., Schimel, D. S., Ojima, D. S., and Cole, C. V.: A general model
for soil organic matter dynamics: sensitivity to litter chemistry, texture
and management, in:
Quantitative modeling of soil farming processes, edited by: Bryant, R. B. and Arnold, R. W., SSSA Special Publication
39, ASA, CSSA, and SSA, Madison, Wisconsin, USA, 147–167, https://doi.org/10.2136/sssaspecpub39.c9, 1994.
Ramirez-Villegas, J., Watson, J., and Challinor, A. J.: Identifying traits for
genotypic adaptation using crop models, J. Exp. Bot., 66, 3451–3462,
https://doi.org/10.1093/jxb/erv014, 2015.
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, Nat.
Clim. Change, 2, 410–416, https://doi.org/10.1038/NCLIMATE1458, 2012.
Reinds, G. J., Heuvelink, G. B. M., Hoogland, T., Kros, J., and de Vries, W.:
Estimating nitrogen fluxes at the European scale by upscaling INTEGRATOR
model outputs from selected sites, Biogeosciences, 9, 4527–4536, https://doi.org/10.5194/bg-9-4527-2012, 2012.
Reuter, H. I, Rodriguez Lado, L., Hengl, T., and Montanarella, L.:
Continental Scale Digital Soil Mapping using European Soil Profile Data:
soil pH, in: SAGA –
Seconds Out, edited by: Böhner, J., Blaschke, T., and Montanarella, L., Hamburger Beiträge zur Physischen Geographie und
Landschaftsökologie, Heft 19, Universität Hamburg, Institut für
Geographie, https://esdac.jrc.ec.europa.eu/public_path/shared_folder/dataset/10_soil_ph/soil_ph_in_europe_hbpl19_10.pdf (last access: 17 June 2022), 2008.
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.
Rosenzweig C., Jones J. W., Hatfield J. L., Ruane A. C., Boote K. J.,
Thorburn P., Antle J. M., Nelson G. C., Porter C., Janssen S., Asseng S.,
Basso B., Ewert F., Wallach D., Baigorria G., and Winter J. M.: The
Agricultural Model Intercomparison and Improvement Project (AgMIP):
Protocols and pilot studies, Agr. Forest Meteorol., 170, 166–172,
https://doi.org/10.1016/j.agrformet.2012.09.011, 2013.
Rumpel, C., Amiraslani, F., Chenu, C., Garcia Cardenas, M., Kaonga, M.,
Koutika, L. S., Ladha, J., Madari, B., Shirato, Y., Smith, P., Soudi, B.,
Soussana, J.-F., Whitehead, D., and Wollenberg, E.: The 4p1000 initiative:
Opportunities, limitations and challenges for implementing soil organic
carbon sequestration as a sustainable development strategy, Ambio, 1–11,
https://doi.org/10.1007/s13280-019-01165-2, 2019.
Sacks, W. J., Deryng, D., Foley, J. A., and Ramankutty, N.: Crop planting dates: An
analysis of global patterns, Glob. Ecol. Biogeogr., 19, 607–620, https://doi.org/10.1111/j.1466-8238.2010.00551.x, 2010.
Sándor, R., Barcza, Z., Hidy, D., Lellei-Kovács, E., Ma, S., and Bellocchi,
G.: Modelling of grassland fluxes in Europe: Evaluation of two
biogeochemical models, Agr. Ecosyst. Environ., 215, 1–19, https://doi.org/10.1016/j.agee.2015.09.001, 2016.
Sándor, R., Ehrhardt, F., Brilli, L., Carozzi, M., Recous, S., Smith, P., Snow,
V., Soussana, J.-F., Dorich, C. D., Fuchs, K., Fitton, N., Gongadze, K., Klumpp,
K., Liebig, M., Martin, R., Merbold, L., Newton, P. C. D., Rees, R. M., Rolinski, S.,
and Bellocchi, G.: The use of biogeochemical models to evaluate mitigation of
greenhouse gas emissions from managed grasslands, Sci. Total Environ.,
642, 292–306, https://doi.org/10.1016/j.scitotenv.2018.06.020, 2018.
Sansoulet, J., Pattey, E., Kröbel, R., Grant, B., Smith, W., Jégo,
G., Desjardins, R. L., Tremblay, N., and Tremblay, G.: Comparing the
performance of the STICS, DNDC, and DayCent models for predicting N uptake
and biomass of spring wheat in Eastern Canada, Field Crops Res., 156,
135–150, https://doi.org/10.1016/j.fcr.2013.11.010, 2014.
Scarlat, N., Fahl, F., Lugato, E., Monforti, F., and Dallemand, J.:
Integrated and spatially explicit assessment of sustainable crop residues
potential in Europe, Biomass Bioenerg., 122, 257–269, https://doi.org/10.1016/j.biombioe.2019.01.021, 2019.
Schmid, M., Neftel, A., Riedo, M., and Fuhrer, J.: Process-based modelling
of nitrous oxide emissions from different nitrogen sources in mown
grassland, Nutr. Cycl. Agroecosyst., 60, 177–187, https://doi.org/10.1023/A:1012694218748, 2001.
Shcherbak, I., Millar, N., and Robertson, G.P.: Global metaanalysis of the
nonlinear response of soil nitrous oxide (N2O) emissions to fertilizer
nitrogen, P. Natl. Acad. Sci. USA, 111, 9199–9204, https://doi.org/10.1073/pnas.1322434111, 2014.
Smit, H. J., Metzger, M. J., and Ewert, F.: Spatial distribution of grassland
productivity and land use in Europe, Agr. Syst., 98, 208–219,
https://doi.org/10.1016/j.agsy.2008.07.004, 2008.
Smith, P.: Agricultural greenhouse gas mitigation potential globally, in:
Europe and in the UK: what have we learnt in the last 20 years?, Glob.
Change Biol., 18, 35–43, https://doi.org/10.1111/j.1365-2486.2011.02517.x, 2012.
Smith, P.: Soil carbon sequestration and biochar as negative emission
technologies, Glob. Change Biol., 22, 1315–1324, https://doi.org/10.1111/gcb.13178, 2016.
Smith, P., Martino, D., Cai, Z., Gwary, D., Janzen, H. H., Kumar, P., McCarl,
B., Ogle, S., O'Mara, F., Rice, C., Scholes, R. J., Sirotenko, O., Howden,
M., McAllister, T., Pan, G., Romanenkov, V., Schneider, U., Towprayoon, S.,
Wattenbach, M., and Smith, J. U.: Greenhouse gas mitigation in agriculture,
Philos. T. R. Soc. Lond. Ser. B, 27, 89–813, https://doi.org/10.1098/rstb.2007.2184, 2008.
Smith, P., Heberl, H., Popp, A., Erb, K.-H., Lauk, C., Harper, R., Tubiello,
F., De Pinto, A., Jafari, M., Sohi, S., Masera, O., Bottcher, H., Berndes,
G., Bustamante, M., Ahammad, H., Clark, H., Dong, H., Elsiddig, E., Mbow,
C., Ravindranath, N., Rice, C., Abad, C., Romanovskaya, A., Sperling, F.,
Herrero, M., House, J., and Rose, S.: How much land based greenhouse gas
mitigation can be achieved without compromising food security and
environmental goals?, Glob. Change Biol., 19, 2285–2302,
https://doi.org/10.1111/gcb.12160, 2013.
Soussana, J.-F., Tallec, T., and Blanfort, V.: Mitigating the greenhouse gas balance
of ruminant production systems through carbon sequestration in grasslands,
Animal, 4, 334–350, https://doi.org/10.1017/S1751731109990784,
2010.
Soussana, J. F., Allard, V., Pilegaard, K., Ambus, C., Campbell, C., Ceschia,
E., Clifton-Brown, J., Czobel, S., Domingues, R., Flechard, C., Fuhrer, J.,
Hensen, A., Horvath, L., Jones, M., Kasper, G., Martin, C., Nagy, Z.,
Neftel, A., Raschi, A., Baronti, S., Rees, R.M., Skiba, U., Stefani, P.,
Manca, G., Sutton, M., Tuba, Z., and Valentini, R.: Full accounting of the
greenhouse gas (CO2, N2O, CH4) budget of nine European grassland sites, Agr.
Ecosyst. Environ., 121, 121–134, https://doi.org/10.1016/j.agee.2006.12.022, 2007.
Stagge, J. H., Kingston, D. G., Tallaksen, L. M., and Hannah, D. M.: Observed
drought indices show increasing divergence across Europe. Sci. Rep., 7,
14045. https://doi.org/10.1038/s41598-017-14283-2, 2017.
Steduto, P., Hsiao, T. C., Fereres, E., and Raes, D.: Crop Yield
Response to Water, Irrigation and Drainage Paper 66, United Nations FAO,
Rome, ISBN 978-92-5-107274-5, 2012.
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. Agroecosyst., 74,
207–228, https://doi.org/10.1007/s10705-006-9000-7, 2006.
Stella, T., Mouratiadou, I., Gaiser, T., Berg-Mohnicke, M., Wallor, E.,
Ewert, F., and Nendel, C.: Estimating the contribution of crop residues to
soil organic carbon conservation, Environ. Res. Lett., 14, 094008, https://doi.org/10.1088/1748-9326/ab395c, 2019.
Sutton, M., Billen, G., Bleeker, A., Erisman, J. W., Grennfelt, P.,
Grinsven, H., Grizzetti, B., Howard, C., and Leip, A.: The European Nitrogen Assessment: Sources, Effects and Policy Perspectives, Cambridge University Press, https://doi.org/10.1017/CBO9780511976988, 2011.
Tao, F. and Zhang, Z.: Impacts of climate change as a function of global
mean temperature: maize productivity and water use in China, Climatic Change,
105, 409–432, https://doi.org/10.1007/s10584-010-9883-9, 2011.
Therond, O., Hengsdijk, H., Casellas, E., Wallach, D., Adam, M.,
Belhouchette, H., Oomen, R., Russell, G., Ewert, F., Bergez, J. E., and
Janssen, S.: Using a cropping system model at regional scale: Low-data
approaches for crop management information and model calibration, Agr.
Ecosyst. Environ., 142, 85–94, https://doi.org/10.1016/j.agee.2010.05.007, 2011.
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.
Tubiello, F. N., Soussana, J. F., Howden, M., and Easterling, W.: Crop and
pasture responses to climate change: fundamental processes, P. Natl.
Acad. Sci. USA., 104, 19686–19690, https://doi.org/10.1073/pnas.0701728104, 2007.
Tubiello, F. N. and Rosenzweig, C.: Developing climate change impact metrics
for agriculture, Integrat. Assess. J., 8, 165–184, 2008.
Turral, H., Burke, J., and Faurès, J.-M.: Climate change, water and food security, FAO Water Reports, 36, FAO, Rome, ISBN 978-9-25106-7-956, 2011.
UNEP: Drawing Down N2O to Protect Climate and the Ozone Layer. A UNEP Synthesis Report, United Nations Environment Programme (UNEP), Nairobi, Kenya, ISBN 978-92-807-3358-7, 2013.
USDA: Major World Crop Areas and Climatic Profiles. World Agricultural Outlook Board, U.S. Department of Agriculture, Agricultural Handbook No. 664, https://naldc.nal.usda.gov/download/CAT88895275/PDF (last access: 17 June 2022), 1994.
van der Velde, M., Bouraoui, F., and Aloe, A.: Pan-European regional-scale
modelling ofwater and N efficiencies of rapeseed cultivation for biodiesel
production, Glob. Change Biol., 15, 24–37, https://doi.org/10.1111/j.1365-2486.2008.01706.x, 2009.
Van Oijen, M., Balkovi, J., Beer, C., Cameron, D.R., Ciais, P., Cramer, W.,
Kato, T., Kuhnert, M., Martin, R., Myneni, R., and Rammig, A.: Impact of
droughts on the carbon cycle in European vegetation: a probabilistic risk
analysis using six vegetation models, Biogeosciences, 11, 6357–6375,
https://doi.org/10.5194/bg-11-6357-2014, 2014.
Voglmeier, K., Six, J., Jocher, M., and Ammann, C.: Grazing-related nitrous
oxide emissions: From patch scale to field scale, Biogeosciences, 16,
1685–1703, https://doi.org/10.5194/bg-16-1685-2019, 2019.
Vuichard, N., Ciais, P., Viovy, N., Calanca, P., and Soussana, J.-F.:
Estimating the greenhouse gas fluxes of European grasslands with a
process-based model: 2. Simulations at the continental level, Global
Biogeochem. Cy., 21, GB1005, https://doi.org/10.1029/2005gb002612,
2007.
Wada, Y., Wisser, D., Eisner, S., Flörke, M., Gerten, D., Haddeland, I.,
Hanasaki, N., Masaki, Y., Portmann, F. T., Stacke, T., Tessler, Z., and
Schewe, J.: Multimodel projections and uncertainties of irrigation water
demand under climate change, Geophys. Res. Lett., 40, 4626–4632, https://doi.org/10.1002/grl.50686, 2013.
Waha, K., Dietrich, J. P., Portmann, F. T., Siebert, S., Thornton, P. K.,
Bondeau, A., and Herrero, M.: Multiple cropping systems of the world and the
potential for increasing cropping intensity, Glob. Environ. Change, 64,
102131, https://doi.org/10.1016/j.gloenvcha.2020.102131, 2020.
Warszawski, L., Frieler, K., Huber, V., Piontek, F., Serdeczny, O., and
Schewe, J.: The Inter-Sectoral Impact Model Intercomparison Project
(ISI-MIP): project framework, P. Natl. Acad. Sci. USA, 111, 3228–3232,
https://doi.org/10.1073/pnas.1312330110, 2014.
Wattenbach, M., Sus, O., Vuichard, N., Lehuger, S., Gottschalk, P., Li, L.,
Leip, A., Williams, M., Tomelleri, E., Kutsch, W. L., Buchmann, N., Eugster,
W., Dietiker, D., Aubinet, M., Ceschia, E., Béziat, P., Grünwald,
T., Hastings, A., Osborne, B., Ciais, P., Celier, P., and Smith, P.: The
carbon balance of European croplands: A cross-site comparison of simulation
models, Agr. Ecosyst. Environ., 139, 419–453, https://doi.org/10.1016/j.agee.2010.08.004, 2010.
Wattenbach, M., Lüdtke, S., Redweik, R., Van Oijen, M., Balkovic, J.,
and Reinds, G.: A generic probability based model to derive regional patterns of
crops in time and space, Geophys. Res. Abstr.,
EGU2015–13153, EGU General Assembly 2015, Vienna, Austria, 2015.
Weitz, A. M., Linder, E., Frolking, S., Crill, P. M., and Keller, M.: N2O
emissions from humid tropical agricultural soils: Effects of soil moisture,
texture and nitrogen availability, Soil Biol. Biochem., 33, 1077–1093, https://doi.org/10.1016/S0038-0717(01)00013-X, 2001.
Wells, K. C., Millet, D. B., Bousserez, N., Henze, D. K., Griffis, T. J.,
Chaliyakunnel, S., Dlugokencky, E. J., Saikawa, E., Xiang, G., Prinn, R. G.,
O'Doherty, S., Young, D., Weiss, R. F., Dutton, G. S., Elkins, J. W.,
Krummel, P. B., Langenfelds, R., and Steele, L. P.: Top-down constraints on
global N2O emissions at optimal resolution: application of a new dimension
reduction technique, Atmos. Chem. Phys., 18, 735–756, https://doi.org/10.5194/acp-18-735-2018, 2018.
Wilkinson, J. M. and Lee, M. R. F.: Use of human-edible animal feeds by ruminant
livestock, Animal, 12, 1–9, https://doi.org/10.1017/S175173111700218X, 2017.
Wint, G. R. W. and Robinson, T. P.: Gridded livestock of the world 2007, Food and
Agriculture Organization of the United Nations (FAO), Rome, Italy, 131 pp. ISBN 978-9-2510-579,
2007.
World Bank: World Development Indicators: Trends in greenhouse gas
emissions, http://wdi.worldbank.org/table/3.9, last access: 7
September 2021.
Yang, C., Fraga, H., van Ieperen, W., Trindade, H., and Santos, J. A.: Effects of
climate change and adaptation options on winter wheat yield under rainfed
Mediterranean conditions in southern Portugal, Climatic Change, 154,
159–178, https://doi.org/10.1007/s10584-019-02419-4, 2019.
Yang, X., Chen, F., Lin, X., Liu, Z., Zhang, H., Zhao, J., Li, K., Ye, Q., Li, Y.,
Lv, S., and Yang, P.: Potential benefits of climate change for crop
productivity in China, Agr. Forest Meteorol., 208, 76–84, https://doi.org/10.1016/j.agrformet.2015.04.024, 2015.
Zhang, Q., Zhang, W., Li, T., Sun, W., Yu, Y., and Wang, G.: Projective
analysis of staple food crop productivity in adaptation to future climate
change in China, Int. J. Biometeorol., 61, 1445–1460, https://doi.org/10.1007/s00484-017-1322-4, 2017.
Zhao, C., Liu, B., Piao, S. L., Wang, X. H., Lobell, D. B., Huang, Y., Huang, M. T.,
Yao, Y. T., Bassu, S., Ciais, P., Durand, J. L., Elliott, J., Ewert, F., Janssens,
I. A., Li, T., Lin, E., Liu, Q., Martre, P., Muller, C., Peng, S. S., Penuelas, J.,
Ruane, A. C., Wallach, D., Wang, T., Wu, D. H., Liu, Z., Zhu, Y., Zhu, Z. C., and
Asseng, S.: Temperature increase reduces global yields of major crops in four
independent estimates, P. Natl. Acad. Sci. USA, 114, 9326–9331,
https://doi.org/10.1073/pnas.1701762114, 2017.
Short summary
Crop and grassland production indicates a strong reduction due to the shortening of the length of the growing cycle associated with rising temperatures. Greenhouse gas emissions will increase exponentially over the century, often exceeding the CO2 accumulation of agro-ecosystems. Water demand will double in the next few decades, whereas the benefits in terms of yield will not fill the gap of C losses due to climate perturbation. Climate change will have a regionally distributed effect in the EU.
Crop and grassland production indicates a strong reduction due to the shortening of the length...
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