Articles | Volume 13, issue 6
https://doi.org/10.5194/bg-13-1733-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/bg-13-1733-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
21 Mar 2016
Research article |
| 21 Mar 2016
Comparing models of microbial–substrate interactions and their response to warming
Debjani Sihi
CORRESPONDING AUTHOR
University of Florida, Soil and Water Science Department, Gainesville, Florida, USA
now at: Appalachian Laboratory, University of Maryland
Center for Environmental Science, Frostburg, Maryland, USA
Stefan Gerber
University of Florida, Soil and Water Science Department, Gainesville, Florida, USA
Patrick W. Inglett
University of Florida, Soil and Water Science Department, Gainesville, Florida, USA
Kanika Sharma Inglett
University of Florida, Soil and Water Science Department, Gainesville, Florida, USA
Related authors
No articles found.
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
Short summary
Short summary
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.
Y. Huang and S. Gerber
Biogeosciences, 12, 6405–6427, https://doi.org/10.5194/bg-12-6405-2015, https://doi.org/10.5194/bg-12-6405-2015, 2015
Short summary
Short summary
The prediction of the greenhouse gas N2O from natural soils globally is sensitive to the representation of soil water. Factors that regulate nitrogen retention and nitrogen limitation, including fire and biological nitrogen fixation are further influencing the N2O gas production. Responses to warming and CO2 increase are strongly controlled by tropical soils. Therefore extrapolation of mostly extra-tropical field studies the globe warrants caution.
Related subject area
Biogeochemistry: Modelling, Terrestrial
Effect of land-use legacy on the future carbon sink for the conterminous US
Peatlands and their carbon dynamics in northern high latitudes from 1990 to 2300: a process-based biogeochemistry model analysis
Improved representation of phosphorus exchange on soil mineral surfaces reduces estimates of phosphorus limitation in temperate forest ecosystems
A coupled ground heat flux–surface energy balance model of evaporation using thermal remote sensing observations
Modeling nitrous oxide emissions from agricultural soil incubation experiments using CoupModel
Local-scale evaluation of the simulated interactions between energy, water and vegetation in ISBA, ORCHIDEE and a diagnostic model
Implementation and initial calibration of carbon-13 soil organic matter decomposition in the Yasso model
The carbon budget of the managed grasslands of Great Britain – informed by earth observations
Accounting for non-rainfall moisture and temperature improves litter decay model performance in a fog-dominated dryland system
Ideas and perspectives: Allocation of carbon from net primary production in models is inconsistent with observations of the age of respired carbon
Towards an ensemble-based evaluation of land surface models in light of uncertain forcings and observations
Exploring the role of bedrock representation on plant transpiration response during dry periods at four forested sites in Europe
Effects of climate change in European croplands and grasslands: productivity, greenhouse gas balance and soil carbon storage
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
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
Benjamin S. Felzer
Biogeosciences, 20, 573–587, https://doi.org/10.5194/bg-20-573-2023, https://doi.org/10.5194/bg-20-573-2023, 2023
Short summary
Short summary
The future of the terrestrial carbon sink depends upon the legacy of past land use, which determines the stand age of the forest and nutrient levels in the soil, both of which affect vegetation growth. This study uses a modeling approach to determine the effects of land-use legacy in the conterminous US from 1750 to 2099. Not accounting for land legacy results in a low carbon sink and high biomass, while water variables are not as highly affected.
Bailu Zhao and Qianlai Zhuang
Biogeosciences, 20, 251–270, https://doi.org/10.5194/bg-20-251-2023, https://doi.org/10.5194/bg-20-251-2023, 2023
Short summary
Short summary
In this study, we use a process-based model to simulate the northern peatland's C dynamics in response to future climate change during 1990–2300. Northern peatlands are projected to be a C source under all climate scenarios except for the mildest one before 2100 and C sources under all scenarios afterwards.
We find northern peatlands are a C sink until pan-Arctic annual temperature reaches −2.09 to −2.89 °C. This study emphasizes the vulnerability of northern peatlands to climate change.
Lin Yu, Silvia Caldararu, Bernhard Ahrens, Thomas Wutzler, Marion Schrumpf, Julian Helfenstein, Chiara Pistocchi, and Sönke Zaehle
Biogeosciences, 20, 57–73, https://doi.org/10.5194/bg-20-57-2023, https://doi.org/10.5194/bg-20-57-2023, 2023
Short summary
Short summary
In this study, we addressed a key weakness in current ecosystem models regarding the phosphorus exchange in the soil and developed a new scheme to describe this process. We showed that the new scheme improved the model performance for plant productivity, soil organic carbon, and soil phosphorus content at five beech forest sites in Germany. We claim that this new model could be used as a better tool to study ecosystems under future climate change, particularly phosphorus-limited systems.
Bimal K. Bhattacharya, Kaniska Mallick, Devansh Desai, Ganapati S. Bhat, Ross Morrison, Jamie R. Clevery, William Woodgate, Jason Beringer, Kerry Cawse-Nicholson, Siyan Ma, Joseph Verfaillie, and Dennis Baldocchi
Biogeosciences, 19, 5521–5551, https://doi.org/10.5194/bg-19-5521-2022, https://doi.org/10.5194/bg-19-5521-2022, 2022
Short summary
Short summary
Evaporation retrieval in heterogeneous ecosystems is challenging due to empirical estimation of ground heat flux and complex parameterizations of conductances. We developed a parameter-sparse coupled ground heat flux-evaporation model and tested it across different limits of water stress and vegetation fraction in the Northern/Southern Hemisphere. The model performed particularly well in the savannas and showed good potential for evaporative stress monitoring from thermal infrared satellites.
Jie Zhang, Wenxin Zhang, Per-Erik Jansson, and Søren O. Petersen
Biogeosciences, 19, 4811–4832, https://doi.org/10.5194/bg-19-4811-2022, https://doi.org/10.5194/bg-19-4811-2022, 2022
Short summary
Short summary
In this study, we relied on a properly controlled laboratory experiment to test the model’s capability of simulating the dominant microbial processes and the emissions of one greenhouse gas (nitrous oxide, N2O) from agricultural soils. This study reveals important processes and parameters that regulate N2O emissions in the investigated model framework and also suggests future steps of model development, which have implications on the broader communities of ecosystem modelers.
Jan De Pue, José Miguel Barrios, Liyang Liu, Philippe Ciais, Alirio Arboleda, Rafiq Hamdi, Manuela Balzarolo, Fabienne Maignan, and Françoise Gellens-Meulenberghs
Biogeosciences, 19, 4361–4386, https://doi.org/10.5194/bg-19-4361-2022, https://doi.org/10.5194/bg-19-4361-2022, 2022
Short summary
Short summary
The functioning of ecosystems involves numerous biophysical processes which interact with each other. Land surface models (LSMs) are used to describe these processes and form an essential component of climate models. In this paper, we evaluate the performance of three LSMs and their interactions with soil moisture and vegetation. Though we found room for improvement in the simulation of soil moisture and drought stress, the main cause of errors was related to the simulated growth of vegetation.
Jarmo Mäkelä, Laura Arppe, Hannu Fritze, Jussi Heinonsalo, Kristiina Karhu, Jari Liski, Markku Oinonen, Petra Straková, and Toni Viskari
Biogeosciences, 19, 4305–4313, https://doi.org/10.5194/bg-19-4305-2022, https://doi.org/10.5194/bg-19-4305-2022, 2022
Short summary
Short summary
Soils account for the largest share of carbon found in terrestrial ecosystems, and accurate depiction of soil carbon decomposition is essential in understanding how permanent these carbon storages are. We present a straightforward way to include carbon isotope concentrations into soil decomposition and carbon storages for the Yasso model, which enables the model to use 13C as a natural tracer to track changes in the underlying soil organic matter decomposition.
Vasileios Myrgiotis, Thomas Luke Smallman, and Mathew Williams
Biogeosciences, 19, 4147–4170, https://doi.org/10.5194/bg-19-4147-2022, https://doi.org/10.5194/bg-19-4147-2022, 2022
Short summary
Short summary
This study shows that livestock grazing and grass cutting can determine whether a grassland is adding (source) or removing (sink) carbon (C) to/from the atmosphere. The annual C balance of 1855 managed grassland fields in Great Britain was quantified for 2017–2018 using process modelling and earth observation data. The examined fields were, on average, small C sinks, but the summer drought of 2018 led to a 9-fold increase in the number of fields that became C sources in 2018 compared to 2017.
J. Robert Logan, Kathe E. Todd-Brown, Kathryn M. Jacobson, Peter J. Jacobson, Roland Vogt, and Sarah E. Evans
Biogeosciences, 19, 4129–4146, https://doi.org/10.5194/bg-19-4129-2022, https://doi.org/10.5194/bg-19-4129-2022, 2022
Short summary
Short summary
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 not in deserts. 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 and/or dew.
Carlos A. Sierra, Verónika Ceballos-Núñez, Henrik Hartmann, David Herrera-Ramírez, and Holger Metzler
Biogeosciences, 19, 3727–3738, https://doi.org/10.5194/bg-19-3727-2022, https://doi.org/10.5194/bg-19-3727-2022, 2022
Short summary
Short summary
Empirical work that estimates the age of respired CO2 from vegetation tissue shows that it may take from years to decades to respire previously produced photosynthates. However, many ecosystem models represent respiration processes in a form that cannot reproduce these observations. In this contribution, we attempt to provide compelling evidence, based on recent research, with the aim to promote a change in the predominant paradigm implemented in ecosystem models.
Vivek K. Arora, Christian Seiler, Libo Wang, and Sian Kou-Giesbrecht
EGUsphere, https://doi.org/10.5194/egusphere-2022-641, https://doi.org/10.5194/egusphere-2022-641, 2022
Short summary
Short summary
The behaviour of natural systems is now very often represented through mathematical models. These models represent our understanding of how the nature works. Of course, the nature doesn't care about our understanding. Since our understanding is not perfect, evaluating models is challenging and there are uncertainties. This manuscript illustrates this uncertainty for land models and argues that evaluating models in the light of uncertainty in various components provides useful information.
César Dionisio Jiménez-Rodríguez, Mauro Sulis, and Stanislaus Schymanski
Biogeosciences, 19, 3395–3423, https://doi.org/10.5194/bg-19-3395-2022, https://doi.org/10.5194/bg-19-3395-2022, 2022
Short summary
Short summary
Vegetation relies on soil water reservoirs during dry periods. However, when this source is depleted, the plants may access water stored deeper in the rocks. This rock moisture contribution is usually omitted in large-scale models, which affects modeled plant water use during dry periods. Our study illustrates that including this additional source of water in the Community Land Model improves the model's ability to reproduce observed plant water use at seasonally dry sites.
Marco Carozzi, Raphaël Martin, Katja Klumpp, and Raia Silvia Massad
Biogeosciences, 19, 3021–3050, https://doi.org/10.5194/bg-19-3021-2022, https://doi.org/10.5194/bg-19-3021-2022, 2022
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
This study incorporated microbial dormancy into a detailed microbe-based biogeochemistry model to examine the fate of Arctic carbon budgets under changing climate conditions. Compared with the model without microbial dormancy, the new model estimated a much higher carbon accumulation in the region during the last and current century. This study highlights the importance of the representation of microbial dormancy in earth system models to adequately quantify the carbon dynamics in the Arctic.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
Biological nitrogen fixation (BNF) plays an important role in the global nitrogen cycle. However, the fixation rate has usually been measured or estimated at a particular observational site. This study develops a BNF model considering the symbiotic relationship between legume plants and bacteria. The model is extensively calibrated with site-level observational data and then extrapolated to the global terrestrial ecosystems to quantify the fixation rate in the 1990s.
Cited articles
Allison, S. D.: Cheaters, diffusion and nutrients constrain decomposition by
microbial enzymes in spatially structured environments, Ecol. Lett., 8,
626–635, https://doi.org/10.1111/j.1461-0248.2005.00756.x, 2005.
Allison, S. D.: Soil minerals and humic acids alter enzyme stability:
implications for ecosystem processes, Biogeochemistry, 81, 361–373,
https://doi.org/10.1007/s10533-006-9046-2, 2006.
Allison, S. D.: Modeling adaptation of carbon use efficiency in microbial
communities, Frontiers in Microbiology, 5, 571,
https://doi.org/10.3389/fmicb.2014.00571, 2014.
Allison, S. D., Wallenstein, M. D., and Bradford, M. A.: Soil-carbon
response to warming dependent on microbial physiology, Nature Geosci., 3,
336–340, https://doi.org/10.1038/ngeo846, 2010.
Arora, V.: Modeling vegetation as a dynamic component in
soil-vegetation-atmosphere transfer schemes and hydrological models, Rev.
Geophys., 40, 3-1–3-26, https://doi.org/10.1029/2001RG000103, 2002.
Beeftink, H. H., van der Heijden, R. T. J. M., and Heijnen, J. J.:
Maintenance requirements: energy supply from simultaneous endogenous
respiration and substrate consumption, FEMS Microbiol. Ecol., 6, 203–209,
https://doi.org/10.1111/j.1574-6968.1990.tb03942.x, 1990.
Benbi, D. K., Boparai, A. K., and Brar, K.: Decomposition of particulate
organic matter is more sensitive to temperature than the mineral associated
organic matter, Soil Biol. Biochem., 70, 183–192,
https://doi.org/10.1016/j.soilbio.2013.12.032, 2014.
Cannell, M. G. R. and Thornley, J. H. M.: Modelling the components of plant
respiration: some guiding principles, Ann. Bot.-London, 85, 45–54,
https://doi.org/10.1006/anbo.1999.0996, 2000.
Chapman, S. J. and Gray, T. R. G.: Importance of cryptic growth, yield
factors and maintenance energy in models of microbial growth in soil, Soil
Boil. Biochem., 18, 1–4, https://doi.org/10.1016/0038-0717(86)90095-7, 1986.
Chertov, O. and Komarov, A.: SOMM: A model of soil organic matter dynamics,
Ecol. Model., 94, 177–189, https://doi.org/10.1016/S0304-3800(96)00017-8, 1997.
Conant, R. T., Ryan, M. G., Ågren, G. I., Birge, H. E., Davidson, E. A.,
Eliasson, P. E., Evans, S. E., Frey, S. D., Giardina, C. P., and Hopkins, F.
M.: Temperature and soil organic matter decomposition rates–synthesis of
current knowledge and a way forward, Glob. Change Biol., 17, 3392–3404,
https://doi.org/10.1111/j.1365-2486.2011.02496.x, 2011.
Coleman, K. and Jenkinson, D. S.: RothC-26.3 – A model for the turnover of
carbon in soil, in: Evaluation
of Soil Organic Matter Models Using Existing Long-Term Datasets, edited by: Powlson, D. S., Smith, P., and Smith, J.
U.,
Springer-Verlag, Heidelberg, 237–246, 1996.
Cooney, C. L.: Strategies for optimizing microbial growth and product
formation, Foundations of biochemical engineering, Foundations of
Biochemical Engineering, 207, 179–198, 2009.
Cotrufo, M. F., Wallenstein, M. D., Boot, C. M., Denef, K., and Paul, E.:
The Microbial Efficiency-Matrix Stabilization (MEMS) framework integrates
plant litter decomposition with soil organic matter stabilization: do labile
plant inputs form stable soil organic matter?, Glob. Change Biol., 19,
988–995, https://doi.org/10.1111/gcb.12113, 2013.
Davidson, E. A. and Janssens, I. A.: Temperature sensitivity of soil carbon
decomposition and feedbacks to climate change, Nature, 440, 165–173,
https://doi.org/10.1038/nature04514, 2006.
Davidson, E. A., Samanta, S., Caramori, S. S., and Savage, K. E.: The Dual
Arrhenius and Michaelis–Menten kinetics model for decomposition of soil
organic matter at hourly to seasonal time scales, Glob. Change Biol., 18,
371–384, https://doi.org/10.1111/j.1365-2486.2011.02546.x, 2012.
Davidson, E. A., Savage, K. E., and Finzi, A. C.: A big-microsite framework for
soil carbon modeling, Glob. Change Biol., 20, 3610–3620,
https://doi.org/10.1111/gcb.12718, 2014.
Foley, J. A., Prentice, I. C., Ramankutty, N., Levis, S., Pollard, D.,
Sitch, S., and Haxeltine, A.: An integrated biosphere model of land surface
processes, terrestrial carbon balance, and vegetation dynamics, Global
Biogeochem. Cy., 10, 603–628, https://doi.org/10.1029/96GB02692, 1996.
Fontaine, S. and Barot, S.: Size and functional diversity of microbe
populations control plant persistence and long-term soil carbon
accumulation, Ecol. Lett., 8, 1075–1087,
https://doi.org/10.1111/j.1461-0248.2005.00813.x, 2005.
Franklin, O., Högberg, P., Ekblad, A., and Ågren, G. I.: Pine forest
floor carbon accumulation in response to N and PK additions: bomb 14C
modelling and respiration studies, Ecosystems, 6, 644–658, https://doi.org/10.1007/s10021-002-0149-x, 2003.
Frantz, J. M., Cometti, N. N., and Bugbee, B.: Night temperature has a
minimal effect on respiration and growth in rapidly growing plants, Ann.
Bot.-London, 94, 155–166, https://doi.org/10.1093/aob/mch122, 2004.
Frey, S. D., Lee, J., Melillo, J. M., and Six, J.: The temperature response
of soil microbial efficiency and its feedback to climate, Nature Clim.
Change, 3, 395–398, https://doi.org/10.1038/nclimate1796, 2013.
Frost, P. C., Evans-White, M. A., Finkel, Z. V., Jensen, T. C., and Matzek,
V.: Are you what you eat? Physiological constraints on organismal
stoichiometry in an elementally imbalanced world, Oikos, 109, 18–28,
https://doi.org/10.1111/j.0030-1299.2005.14049.x, 2005.
Gerber, S., Hedin, L. O., Oppenheimer, M., Pacala, S. W., and Shevliakova,
E.: Nitrogen cycling and feedbacks in a global dynamic land model, Global
Biogeochem. Cy., 24, GB1001, https://doi.org/10.1029/2008GB003336, 2010.
German, D. P., Marcelo, K. R. B., Stone, M. M., and Allison, S. D.: The
Michaelis-Menton kinetics of soil extracellular enzyme in response to
temperature: a cross-latitudinal study, Glob. Change Biol., 18, 1468–1479,
https://doi.org/10.1111/j.1365-2486.2011.02615.x, 2012.
Gillabel, J., Cebrian-Lopez, B., Six, J., and Merckx, R.: Experimental
evidence for the attenuating effect of SOM protection on temperature
sensitivity of SOM decomposition, Glob. Change Biol., 16, 2789–2798,
https://doi.org/10.1111/j.1365-2486.2009.02132.x, 2010.
Hararuk, O., Smith, M. J., and Luo, Y.: Microbial models with data-driven
parameters predict stronger soil carbon responses to climate change, Glob.
Change Biol., 21, 2439–2453, https://doi.org/10.1111/gcb.12827, 2015.
Kivlin, S. N., Waring, B. G., Averill, C., and Hawkes, C. V.: Tradeoffs in
microbial carbon allocation may mediate soil carbon storage in future
climates, Front. Microbiol., 4, 261, https://doi.org/10.3389/fmicb.2013.00261,
2013.
Lawrence, C. R., Neff, J. C., and Schimel, J. P.: Does adding microbial
mechanisms of decomposition improve soil organic matter models? A comparison
of four models using data from a pulsed rewetting experiment, Soil Biol.
Biochem., 41, 1923–1934, https://doi.org/10.1016/j.soilbio.2009.06.016, 2009.
Li, C.: The DNDC model, in: Evaluation of Soil Organic Matter Models, edited by: Powlson, D. S., Smith, P., and Smith, J. U.,
Springer, Berlin, 263–268, 1996.
Li, J., Wang, G., Allison, S. D., Mayes, M. A., and Luo, Y.: Soil carbon
sensitivity to temperature and carbon use efficiency compared across
microbial-ecosystem models of varying complexity, Biogeochemistry, 119,
67–84, 2014.
Manzoni, S., Taylor, P., Richter, A., Porporato, A., and Ågren, G. I.:
Environmental and stoichiometric controls on microbial carbon-use efficiency
in soils, New Phytol., 196, 79–91, https://doi.org/10.1111/j.1469-8137.2012.04225.x,
2012.
Merchant, S. S. and Helmann, J. D.: Elemental economy: microbial strategies for
optimizing growth in the face of nutrient limitation, Adv. Microb. Physiol.,
60, 91–210, https://doi.org/10.1016/B978-0-12-398264-3.00002-4, 2012.
Menge, D. N. L., Pacala, S. W., and Hedin, L. O.: Emergence and
maintenance of nutrient Limitation over multiple timescales in terrestrial
ecosystems, The American Naturalist, 173, 164–175, 2009.
Molina, J. A. E., Hadas, A., and Clapp, C. E.: Computer simulation of
nitrogen turnover in soil and priming effect, Soil Biol. Biochem., 22,
349–353, https://doi.org/10.1016/0038-0717(90)90112-D, 1990.
Moorhead, D. L., Lashermes, G., and Sinsabaugh, R. L.: A theoretical model
of C-and N-acquiring exoenzyme activities, which balances microbial demands
during decomposition, Soil Biol. Biochem., 53, 133–141,
https://doi.org/10.1016/j.soilbio.2012.05.011, 2012.
Moorcroft, P. R., Hurtt, G. C., and Pacala, S. W.: A method for scaling
vegetation dynamics: The Ecosystem Demography Model (ED), Ecological
Monographs, 71, 557–586, 2001.
Parton, W. J., Schimel, D. S., Cole, C. V., and Ojima, D. S.: Analysis of
factors controlling soil organic matter levels in Great Plains grasslands,
Soil Sci. Soc. Am. J., 51, 1173–1179,
https://doi.org/10.2136/sssaj1987.03615995005100050015x, 1987.
Pretzsch, H., Biber, P., Schütze, G., Uhl, E., and Rötzer, T.:
Forest stand growth dynamics in Central Europe have accelerated since 1870,
Nat. Commun., 5, 1–10, https://doi.org/10.1038/ncomms5967, 2014.
Russell, J. B. and Cook, G. M.: Energetics of bacterial growth: balance of
anabolic and catabolic reactions, Microbiol. Rev., 59, 48–62, 1995.
Schmidt, M. W. I., Torn, M. S., Abiven, S., Dittmar, T., Guggenberger, G.,
Janssens, I. A., Kleber, M., Kögel-Knabner, I., Lehmann, J., Manning, D.
A. C., Nannipieri, P., Rasse, D. P., Weiner, S., and Trumbore, S. E.:
Persistence of soil organic matter as an ecosystem property, Nature, 478,
49–56, https://doi.org/10.1038/nature10386, 2011.
Schmidt, S. K., Costello, E. K., Nemergut, D. R., Cleveland, C. C., Reed, S.
C., Weintraub, M. N., Meyer, A. F., and Martin, A. M.: Biogeochemical
consequences of rapid microbial turnover and seasonal succession in soil,
Ecology, 88, 1379–1385, https://doi.org/10.1890/06-0164, 2007.
Schimel, J. P. and Weintraub, M. N.: The implications of exoenzyme activity
on microbial carbon and nitrogen limitation in soil: a theoretical model,
Soil Biol. Biochem., 35, 549–563, https://doi.org/10.1016/S0038-0717(03)00015-4, 2003.
Sinsabaugh, R. L., Manzoni, S., Moorhead, D. L., and Richter, A.: Carbon use
efficiency of microbial communities: stoichiometry, methodology and
modelling, Ecol. Lett., 16, 930–939, https://doi.org/10.1111/ele.12113, 2013.
Sistla, S. A., Rastetter, E. B., and Schimel, J. P.: Responses of a tundra
system to warming using SCAMPS: a stoichiometrically coupled, acclimating
microbe-plant-soil model, Ecol. Monogr., 84, 151–170, https://doi.org/10.1890/12-2119.1, 2014.
Sitch, S., Smith, B., Prentice, I. C., Arneth, A., Bondeau, A., Cramer, W.,
Kaplan, J. O., Levis, S., Lucht, W., Sykes, M. T., Thonicke, K., and Venevsky,
S.: Evaluation of ecosystem dynamics, plant geography, and terrestrial
carbon cycling in the LPJ dynamic global vegetation model, Glob. Change
Biol., 9, 161–185, https://doi.org/10.1046/j.1365-2486.2003.00569.x, 2003.
Stark, J. M. and Hart, S. C.: High rates of nitrification and nitrate
turnover in undisturbed coniferous forests, Nature, 385, 61–64,
https://doi.org/10.1038/385061a0, 1997.
Stone, M. M., Weiss, M. S., Goodale, C. L., Adams, M. B., Fernandez, I. J.,
German, D. P., and Allison, S. D.: Temperature sensitivity of soil enzyme
kinetics under N-fertilization in two
temperate forests, Glob. Change Biol., 18, 1173–1184, 2012.
Tang, J. Y.: On the relationships between the Michaelis-Menten kinetics, reverse
Michaelis-Menten kinetics, equilibrium chemistry approximation kinetics, and
quadratic kinetics, Geosci. Model Dev., 8, 3823–3835, https://doi.org/10.5194/gmd-8-3823-2015, 2015.
Tang, J. Y. and Riley, W. J.: Weaker soil carbon-climate feedbacks resulting
from microbial and abiotic interactions, Nature Clim. Change, 5, 56–60,
https://doi.org/10.1038/nclimate2438, 2015.
Thornley, J. H. M.: Plant growth and respiration re-visited: maintenance
respiration defined–it is an emergent property of, not a separate process
within, the system–and why the respiration: photosynthesis ratio is
conservative, Ann. Bot.-London, 108, 1365–1380, https://doi.org/10.1093/aob/mcr238,
2011.
Todd-Brown, K. E. O., Hopkins, F. M., Kivlin, S. N., Talbot, J. M., and
Allison, S. D.: A framework for representing microbial decomposition in
coupled climate models, Biogeochemistry, 109, 19–33,
https://doi.org/10.1007/s10533-011-9635-6, 2012.
Todd-Brown, K. E. O., Randerson, J. T., Post, W. M., Hoffman, F. M., Tarnocai, C., Schuur, E. A. G., and Allison, S. D.:
Causes of variation in soil carbon simulations from CMIP5 Earth system
models and comparison with observations, Biogeosciences, 10, 1717–1736, https://doi.org/10.5194/bg-10-1717-2013, 2013.
Tucker, C. L., Bell, J., Pendall, E., and Ogle, K.: Does declining
carbon-use efficiency explain thermal acclimation of soil respiration with
warming?, Glob. Change Biol., 19, 252-263, https://doi.org/10.1111/gcb.12036, 2013.
Van Bodegom, P.: Microbial maintenance: a critical review on its
quantification, Microbial. Ecol., 53, 513–523,
https://doi.org/10.1007/s00248-006-9049-5, 2007.
Van Veen, J., Ladd, J., and Frissel, M.: Modelling C and N turnover through
the microbial biomass in soil, Plant Soil, 76, 257–274, 1984.
Vetter, Y. A., Deming, J. W., Jumars, P. A., and Krieger-Brockett, B. B.: A
predictive model of bacterial foraging by means of freely released
extracellular enzymes, Microbial Ecol., 36, 75–92, 1998.
Wagai, R., Kishimoto-Mo, A. W., Yonemura, S., Shirato, Y., Hiradate, S., and
Yagasaki, Y.: Linking temperature sensitivity of soil organic matter
decomposition to its molecular structure, accessibility, and microbial
physiology, Glob. Change Biol., 19, 1114–1125, https://doi.org/10.1111/gcb.12112, 2013.
Wang, G. and Post, W. M..: A note on the reverse Michaelis-Menten kinetics,
Soil Biol. Biochem., 57, 946–949, https://doi.org/10.1016/j.soilbio.2012.08.028, 2013.
Wang, G., Post, W. M., and Mayes, M. A.: Development of
microbial-enzyme-mediated decomposition model parameters through
steady-state and dynamic analyses, Ecol. Appl., 23, 255–272,
https://doi.org/10.1890/12-0681.1, 2013.
Wang, Y. P., Chen, B. C., Wieder, W. R., Leite, M., Medlyn, B. E., Rasmussen, M., Smith, M. J.,
Agusto, F. B., Hoffman, F., and Luo, Y. Q.: Oscillatory behavior of two nonlinear
microbial models of soil carbon decomposition, Biogeosciences, 11, 1817–1831, https://doi.org/10.5194/bg-11-1817-2014, 2014.
Wieder, W. R., Bonan, G. B., and Allison, S. D.: Global soil carbon
projections are improved by modelling microbial processes, Nature Clim.
Change, 3, 909–912, https://doi.org/10.1038/nclimate1951, 2013.
Wieder, W. R., Grandy, A. S., Kallenbach, C. M., and Bonan, G. B.:
Integrating microbial physiology and physio-chemical principles in soils with
the MIcrobial-MIneral Carbon Stabilization (MIMICS) model, Biogeosciences,
11, 3899–3917, https://doi.org/10.5194/bg-11-3899-2014, 2014a.
Wieder, W. R., Boehnert, J., and Bonan, G. B.: Evaluating soil
biogeochemistry parameterizations in Earth system models with observations,
Global Biogeochem. Cy., 28, 211–222, https://doi.org/10.1002/2013GB004665, 2014b.
Wieder, W. R., Allison, S. D., Davidson, E. A., Georgiou, K., Hararuk, O.,
He, Y., Hopkins, F., Luo, Y., Smith, M. J., Sulman, B., Todd-Brown, K., Wang, Y., Xia, J., and Xu, X.: Explicitly
representing soil microbial processes in Earth system models, Global
Biogeochem. Cy., 29, 1782–1800, 2015a.
Wieder, W. R., Grandy, A. S., Kallenbach, C. M., Taylor, P. G., and Bonan, G.
B.: Representing life in the Earth system with soil microbial functional
traits in the MIMICS model, Geosci. Model Dev., 8, 1789–1808,
https://doi.org/10.5194/gmd-8-1789-2015, 2015b.
Short summary
Simple microbial decomposition models show distinct responses to warming under different assumptions of how complex organic matter is broken down. If there are limitations other than microbial enzyme availability, the short-term respiration response is dampened and the decomposition dynamics resemble traditional first-order decay used in most biogeochemistry models. Further, microbial adjustment to respiratory cost for enzyme production reduces overall sensitivity to temperature.
Simple microbial decomposition models show distinct responses to warming under different...
Altmetrics
Final-revised paper
Preprint