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Volume 9, issue 10
Biogeosciences, 9, 3983–3998, 2012
https://doi.org/10.5194/bg-9-3983-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/bg-9-3983-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
Special issue: Nitrogen and global change
Biogeosciences, 9, 3983–3998, 2012
https://doi.org/10.5194/bg-9-3983-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/bg-9-3983-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
Research article 17 Oct 2012
Research article | 17 Oct 2012
Parameter-induced uncertainty quantification of soil N2O, NO and CO2 emission from Höglwald spruce forest (Germany) using the LandscapeDNDC model
K.-H. Rahn et al.
Related subject area
Biogeochemistry: Modelling, Terrestrial
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
Rainfall intensification increases the contribution of rewetting pulses to soil respiration
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
A Bayesian Approach to Evaluation of Soil Biogeochemical Models
Historical CO2 emissions from land-use and land-cover change and their uncertainty
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 habitat preference of two key Sphagnum species in a poor fen as controlled by capitulum water retention
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
Decadal fates and impacts of nitrogen additions on temperate forest carbon storage: a data–model comparison
Global NO and HONO emissions of biological soil crusts estimated by a process-based non-vascular vegetation model
Estimating the soil N2O emission intensity of croplands in northwest Europe
Unifying soil organic matter formation and persistence frameworks: the MEMS model
Evaluating the simulated mean soil carbon transit times by Earth system models using observations
Modeling anaerobic soil organic carbon decomposition in Arctic polygon tundra: insights into soil geochemical influences on carbon mineralization
Neglecting plant–microbe symbioses leads to underestimation of modeled climate impacts
A simple time-stepping scheme to simulate leaf area index, phenology, and gross primary production across deciduous broadleaf forests in the eastern United States
Quantifying global N2O emissions from natural ecosystem soils using trait-based biogeochemistry models
Optimal inverse estimation of ecosystem parameters from observations of carbon and energy fluxes
Emergent relationships with respect to burned area in global satellite observations and fire-enabled vegetation models
Evaluation of simulated ozone effects in forest ecosystems against biomass damage estimates from fumigation experiments
Leaf area index identified as a major source of variability in modeled CO2 fertilization
An improved parameterization of leaf area index (LAI) seasonality in the Canadian Land Surface Scheme (CLASS) and Canadian Terrestrial Ecosystem Model (CTEM) modelling framework
Ecosystem carbon transit versus turnover times in response to climate warming and rising atmospheric CO2 concentration
Linking big models to big data: efficient ecosystem model calibration through Bayesian model emulation
Controls of terrestrial ecosystem nitrogen loss on simulated productivity responses to elevated CO2
The impact of spatiotemporal variability in atmospheric CO2 concentration on global terrestrial carbon fluxes
Microbial decomposition processes and vulnerable arctic soil organic carbon in the 21st century
Diffusion limitations and Michaelis–Menten kinetics as drivers of combined temperature and moisture effects on carbon fluxes of mineral soils
An evaluation of SMOS L-band vegetation optical depth (L-VOD) data sets: high sensitivity of L-VOD to above-ground biomass in Africa
Global soil organic carbon removal by water erosion under climate change and land use change during AD 1850–2005
Inferring the effects of sink strength on plant carbon balance processes from experimental measurements
Technical Note: An efficient method for accelerating the spin-up process for process-based biogeochemistry models
Asymmetric responses of primary productivity to altered precipitation simulated by ecosystem models across three long-term grassland sites
A Bayesian ensemble data assimilation to constrain model parameters and land-use carbon emissions
Ages and transit times as important diagnostics of model performance for predicting carbon dynamics in terrestrial vegetation models
Influence of climate variability, fire and phosphorus limitation on vegetation structure and dynamics of the Amazon–Cerrado border
Evaluating the effect of nutrient redistribution by animals on the phosphorus cycle of lowland Amazonia
Evaluation and uncertainty analysis of regional-scale CLM4.5 net carbon flux estimates
Modelling the diurnal and seasonal dynamics of soil CO2 exchange in a semiarid ecosystem with high plant–interspace heterogeneity
Gross changes in forest area shape the future carbon balance of tropical forests
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.
Stefano Manzoni, Arjun Chakrawal, Thomas Fischer, Joshua P. Schimel, Amilcare Porporato, and Giulia Vico
Biogeosciences Discuss., https://doi.org/10.5194/bg-2020-95, https://doi.org/10.5194/bg-2020-95, 2020
Revised manuscript accepted for BG
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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.
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.
Hua W. Xie, Adriana L. Romero-Olivares, Michele Guindani, and Steven D. Allison
Biogeosciences Discuss., https://doi.org/10.5194/bg-2020-23, https://doi.org/10.5194/bg-2020-23, 2020
Revised manuscript accepted for BG
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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 statistical metrics. Our results demonstrate that our approach is a viable one for continued development and refinement.
Thomas Gasser, Léa Crepin, Yann Quilcaille, Richard A. Houghton, Philippe Ciais, and Michael Obersteiner
Biogeosciences Discuss., https://doi.org/10.5194/bg-2020-33, https://doi.org/10.5194/bg-2020-33, 2020
Revised manuscript accepted for BG
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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 happened if these ecosystems had not been destroyed (mostly through deforestation). Over the last decade, this foregone carbon sink amounted to about 50 % of the actual emissions.
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.
Jinnan Gong, Nigel Roulet, Steve Frolking, Heli Peltola, Anna M. Laine, Nicola Kokkonen, and Eeva-Stiina Tuittila
Biogeosciences Discuss., https://doi.org/10.5194/bg-2019-366, https://doi.org/10.5194/bg-2019-366, 2019
Revised manuscript accepted for BG
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In this study, which combined field and lab experiment with modelling, we developed a process-based model for simulating dynamics within peatland moss communities. Model is useful because Sphagnum mosses are key engineers in peatlands; their response to changes in climate through 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.
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.
Susan J. Cheng, Peter G. Hess, William R. Wieder, R. Quinn Thomas, Knute J. Nadelhoffer, Julius Vira, Danica L. Lombardozzi, Per Gundersen, Ivan J. Fernandez, Patrick Schleppi, Marie-Cécile Gruselle, Filip Moldan, and Christine L. Goodale
Biogeosciences, 16, 2771–2793, https://doi.org/10.5194/bg-16-2771-2019, https://doi.org/10.5194/bg-16-2771-2019, 2019
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Nitrogen deposition and fertilizer can change how much carbon is stored in plants and soils. Understanding how much added nitrogen is recovered in plants or soils is critical to estimating the size of the future land carbon sink. We compared how nitrogen additions are recovered in modeled soil and plant stocks against data from long-term nitrogen addition experiments. We found that the model simulates recovery of added nitrogen into soils through a different process than found in the field.
Philipp Porada, Alexandra Tamm, Jose Raggio, Yafang Cheng, Axel Kleidon, Ulrich Pöschl, and Bettina Weber
Biogeosciences, 16, 2003–2031, https://doi.org/10.5194/bg-16-2003-2019, https://doi.org/10.5194/bg-16-2003-2019, 2019
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The trace gases NO and HONO are crucial for atmospheric chemistry. It has been suggested that biological soil crusts in drylands contribute substantially to global NO and HONO emissions, based on empirical upscaling of laboratory and field observations. Here we apply an alternative, process-based modeling approach to predict these emissions. We find that biological soil crusts emit globally significant amounts of NO and HONO, which also vary depending on the type of biological soil crust.
Vasileios Myrgiotis, Mathew Williams, Robert M. Rees, and Cairistiona F. E. Topp
Biogeosciences, 16, 1641–1655, https://doi.org/10.5194/bg-16-1641-2019, https://doi.org/10.5194/bg-16-1641-2019, 2019
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This study focuses on a northwestern European cropland region and shows that the type of crop growing on a soil has notable effects on the emission of nitrous oxide (N2O – a greenhouse gas) from that soil. It was found that N2O emissions from soils under oilseed cultivation are significantly higher than soils under cereal cultivation. This variation is mostly explained by the fact that oilseeds require more nitrogen (fertiliser) than cereals, especially at early crop growth stages.
Andy D. Robertson, Keith Paustian, Stephen Ogle, Matthew D. Wallenstein, Emanuele Lugato, and M. Francesca Cotrufo
Biogeosciences, 16, 1225–1248, https://doi.org/10.5194/bg-16-1225-2019, https://doi.org/10.5194/bg-16-1225-2019, 2019
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Predicting how soils respond to varying environmental conditions or land-use change is essential if we aim to promote sustainable management practices and help mitigate climate change. Here, we present a new ecosystem-scale soil model (MEMS v1) that is built upon recent, novel findings and can be run using very few inputs. The model accurately predicted soil carbon stocks for more than 8000 sites across Europe, ranging from cold, wet forests in sandy soils to hot, dry grasslands in clays.
Jing Wang, Jianyang Xia, Xuhui Zhou, Kun Huang, Jian Zhou, Yuanyuan Huang, Lifen Jiang, Xia Xu, Junyi Liang, Ying-Ping Wang, Xiaoli Cheng, and Yiqi Luo
Biogeosciences, 16, 917–926, https://doi.org/10.5194/bg-16-917-2019, https://doi.org/10.5194/bg-16-917-2019, 2019
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Soil is critical in mitigating climate change mainly because soil carbon turns over much slower in soils than vegetation and the atmosphere. However, Earth system models (ESMs) have large uncertainty in simulating carbon dynamics due to their biased estimation of soil carbon transit time (τsoil). Here, the τsoil estimates from 12 ESMs that participated in CMIP5 were evaluated by a database of measured τsoil. We detected a large spatial variation in measured τsoil across the globe.
Jianqiu Zheng, Peter E. Thornton, Scott L. Painter, Baohua Gu, Stan D. Wullschleger, and David E. Graham
Biogeosciences, 16, 663–680, https://doi.org/10.5194/bg-16-663-2019, https://doi.org/10.5194/bg-16-663-2019, 2019
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Arctic warming exposes soil carbon to increased degradation, increasing CO2 and CH4 emissions. Models underrepresent anaerobic decomposition that predominates wet soils. We simulated microbial growth, pH regulation, and anaerobic carbon decomposition in a new model, parameterized and validated with prior soil incubation data. The model accurately simulated CO2 production and strong influences of water content, pH, methanogen biomass, and competing electron acceptors on CH4 production.
Mingjie Shi, Joshua B. Fisher, Richard P. Phillips, and Edward R. Brzostek
Biogeosciences, 16, 457–465, https://doi.org/10.5194/bg-16-457-2019, https://doi.org/10.5194/bg-16-457-2019, 2019
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The ability of plants to slow climate change by taking up carbon hinges in part on there being ample soil nitrogen. We used a model that accounts for the carbon cost to plants of supporting nitrogen-acquiring microbes to explore how nitrogen limitation affects climate. Our model predicted that nitrogen limitation will enhance temperature and decrease precipitation; thus, our results suggest that carbon spent to support nitrogen-acquiring microbes is a critical component of the Earth's climate.
Qinchuan Xin, Yongjiu Dai, and Xiaoping Liu
Biogeosciences, 16, 467–484, https://doi.org/10.5194/bg-16-467-2019, https://doi.org/10.5194/bg-16-467-2019, 2019
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Terrestrial biosphere models that simulate both leaf dynamics and canopy photosynthesis are required to understand vegetation–climate interactions. A time-stepping scheme is proposed to simulate leaf area index, phenology, and gross primary production via climate variables. The method performs well on simulating deciduous broadleaf forests across the eastern United States; it provides a simplified and improved version of the growing production day model for use in land surface modeling.
Tong Yu and Qianlai Zhuang
Biogeosciences, 16, 207–222, https://doi.org/10.5194/bg-16-207-2019, https://doi.org/10.5194/bg-16-207-2019, 2019
Debsunder Dutta, David S. Schimel, Ying Sun, Christiaan van der Tol, and Christian Frankenberg
Biogeosciences, 16, 77–103, https://doi.org/10.5194/bg-16-77-2019, https://doi.org/10.5194/bg-16-77-2019, 2019
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Canopy structural and leaf photosynthesis parameterizations are often fixed over time in Earth system models and represent large sources of uncertainty in predictions of carbon and water fluxes. We develop a moving window nonlinear optimal parameter inversion framework using constraining flux and satellite reflectance observations. The results demonstrate the applicability of the approach for error reduction and capturing the seasonal variability of key ecosystem parameters.
Matthias Forkel, Niels Andela, Sandy P. Harrison, Gitta Lasslop, Margreet van Marle, Emilio Chuvieco, Wouter Dorigo, Matthew Forrest, Stijn Hantson, Angelika Heil, Fang Li, Joe Melton, Stephen Sitch, Chao Yue, and Almut Arneth
Biogeosciences, 16, 57–76, https://doi.org/10.5194/bg-16-57-2019, https://doi.org/10.5194/bg-16-57-2019, 2019
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Weather, humans, and vegetation control the occurrence of fires. In this study we find that global fire–vegetation models underestimate the strong increase of burned area with higher previous-season plant productivity in comparison to satellite-derived relationships.
Martina Franz, Rocio Alonso, Almut Arneth, Patrick Büker, Susana Elvira, Giacomo Gerosa, Lisa Emberson, Zhaozhong Feng, Didier Le Thiec, Riccardo Marzuoli, Elina Oksanen, Johan Uddling, Matthew Wilkinson, and Sönke Zaehle
Biogeosciences, 15, 6941–6957, https://doi.org/10.5194/bg-15-6941-2018, https://doi.org/10.5194/bg-15-6941-2018, 2018
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Four published ozone damage functions previously used in terrestrial biosphere models were evaluated regarding their ability to simulate observed biomass dose–response relationships using the O-CN model. Neither damage function was able to reproduce the observed ozone-induced biomass reductions. Calibrating a plant-functional-type-specific relationship between accumulated ozone uptake and leaf-level photosynthesis did lead to a good agreement between observed and modelled ozone damage.
Qianyu Li, Xingjie Lu, Yingping Wang, Xin Huang, Peter M. Cox, and Yiqi Luo
Biogeosciences, 15, 6909–6925, https://doi.org/10.5194/bg-15-6909-2018, https://doi.org/10.5194/bg-15-6909-2018, 2018
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Land-surface models have been widely used to predict the responses of terrestrial ecosystems to climate change. A better understanding of model mechanisms that govern terrestrial ecosystem responses to rising atmosphere [CO2] is needed. Our study for the first time shows that the expansion of leaf area under rising [CO2] is the most important response for the stimulation of land carbon accumulation by a land-surface model: CABLE. Processes related to leaf area should be better calibrated.
Ali Asaadi, Vivek K. Arora, Joe R. Melton, and Paul Bartlett
Biogeosciences, 15, 6885–6907, https://doi.org/10.5194/bg-15-6885-2018, https://doi.org/10.5194/bg-15-6885-2018, 2018
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Non-structural carbohydrates (NSCs), which play a central role in a plant's life processes and its response to environmental conditions, are typically not included in terrestrial biogeochemistry models used in Earth system models (ESMs). In this study, we include NSC pools in the framework of the land component of the Canadian ESM and show how they help address the long-standing problem of delayed leaf phenology.
Xingjie Lu, Ying-Ping Wang, Yiqi Luo, and Lifen Jiang
Biogeosciences, 15, 6559–6572, https://doi.org/10.5194/bg-15-6559-2018, https://doi.org/10.5194/bg-15-6559-2018, 2018
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How long does C cycle through terrestrial ecosystems is a critical question for understanding land C sequestration capacity under future rising atmosphere [CO2] and climate warming. Under climate change, previous conventional concepts with a steady-state assumption will no longer be suitable for a non-steady state. Our results using the new concept, C transit time, suggest more significant responses in terrestrial C cycle under rising [CO2] and climate warming.
Istem Fer, Ryan Kelly, Paul R. Moorcroft, Andrew D. Richardson, Elizabeth M. Cowdery, and Michael C. Dietze
Biogeosciences, 15, 5801–5830, https://doi.org/10.5194/bg-15-5801-2018, https://doi.org/10.5194/bg-15-5801-2018, 2018
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The computer models we use to understand and forecast the ecosystem changes have multiple components that determine their outcomes. Due to our limited observation capacities, these components bear uncertainties that in return affect our predictions. While there are techniques for reducing these uncertainties, they are not applicable to every model due to computational and statistical barriers. This research presents a method that lowers those barriers and allows us to improve model predictions.
Johannes Meyerholt and Sönke Zaehle
Biogeosciences, 15, 5677–5698, https://doi.org/10.5194/bg-15-5677-2018, https://doi.org/10.5194/bg-15-5677-2018, 2018
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Terrestrial biosphere models employ various representations of ecosystem nitrogen loss, some based on soil N availability, some based on net N mineralization. We show in local and global simulations that this variety leads to pronounced uncertainty in the predicted magnitude and sign of ecosystem N loss change under elevated CO2. Suprisingly, this uncertainty barely affects predicted carbon storage responses to elevated CO2, illustrating the need for new benchmarks especially in the boreal zone.
Eunjee Lee, Fan-Wei Zeng, Randal D. Koster, Brad Weir, Lesley E. Ott, and Benjamin Poulter
Biogeosciences, 15, 5635–5652, https://doi.org/10.5194/bg-15-5635-2018, https://doi.org/10.5194/bg-15-5635-2018, 2018
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Land carbon fluxes are controlled in part by the responses of terrestrial ecosystems to atmospheric conditions near the Earth's surface. This study offers a comprehensive evaluation of the consequences of multiple facets of spatiotemporal variability in atmospheric CO2 for carbon cycle dynamics. Globally, consideration of the diurnal CO2 variability reduces the gross primary production and net land carbon uptake. The relative contributions of other variability vary regionally and seasonally.
Junrong Zha and Qianlai Zhuang
Biogeosciences, 15, 5621–5634, https://doi.org/10.5194/bg-15-5621-2018, https://doi.org/10.5194/bg-15-5621-2018, 2018
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This study used a detailed microbial-based soil decomposition biogeochemistry model to examine the fate of much arctic soil carbon under changing climate conditions. We found that the detailed microbial decomposition biogeochemistry model estimated a much lower carbon accumulation in the region during this century. The amount of soil carbon considered in the 21st-century simulations determines the regional carbon sink and source strengths, regardless of the complexity of models used.
Fernando Esteban Moyano, Nadezda Vasilyeva, and Lorenzo Menichetti
Biogeosciences, 15, 5031–5045, https://doi.org/10.5194/bg-15-5031-2018, https://doi.org/10.5194/bg-15-5031-2018, 2018
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Soils are complex systems storing large quantities of carbon in the form of organic matter. Understanding how climatic drivers such as temperature and moisture influence the decomposition and thus the turnover of this carbon is crucial for predicting feedbacks between climate and soils. This study aims at improving our mechanistic understanding of how these factors interact to drive decomposition and thus modify the capacity of soils to emit or capture atmospheric CO2.
Nemesio J. Rodríguez-Fernández, Arnaud Mialon, Stephane Mermoz, Alexandre Bouvet, Philippe Richaume, Ahmad Al Bitar, Amen Al-Yaari, Martin Brandt, Thomas Kaminski, Thuy Le Toan, Yann H. Kerr, and Jean-Pierre Wigneron
Biogeosciences, 15, 4627–4645, https://doi.org/10.5194/bg-15-4627-2018, https://doi.org/10.5194/bg-15-4627-2018, 2018
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Existing global scale above-ground biomass (AGB) maps are made at very high spatial resolution collecting data during several years. In this paper we discuss the use of a new data set from the SMOS satellite: the vegetation optical depth estimated from low microwave frequencies. It is shown that this new data set is highly sensitive to AGB. The spacial resolution of SMOS is coarse (40 km) but the new data set can be used to monitor AGB variations with time due to its high revisit frequency.
Victoria Naipal, Philippe Ciais, Yilong Wang, Ronny Lauerwald, Bertrand Guenet, and Kristof Van Oost
Biogeosciences, 15, 4459–4480, https://doi.org/10.5194/bg-15-4459-2018, https://doi.org/10.5194/bg-15-4459-2018, 2018
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We seek to better understand the links between soil erosion by rainfall and the global carbon (C) cycle by coupling a soil erosion model to the C cycle of a land surface model. With this modeling approach we evaluate the effects of soil removal on soil C stocks in the presence of climate change and land use change. We find that accelerated soil erosion leads to a potential SOC removal flux of 74 ±18 Pg of C globally over the period AD 1850–2005, with significant impacts on the land C balance.
Kashif Mahmud, Belinda E. Medlyn, Remko A. Duursma, Courtney Campany, and Martin G. De Kauwe
Biogeosciences, 15, 4003–4018, https://doi.org/10.5194/bg-15-4003-2018, https://doi.org/10.5194/bg-15-4003-2018, 2018
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A major limitation of current terrestrial vegetation models is that we do not know how to model C balance processes under sink-limited conditions. To address this limitation, we applied data assimilation of a simple C balance model to a manipulative experiment in which sink limitation was induced with low rooting volume. Our analysis framework allowed us to infer that, in addition to a feedback on photosynthetic rates, the reduction in growth was effected by other C balance processes.
Yang Qu, Shamil Maksyutov, and Qianlai Zhuang
Biogeosciences, 15, 3967–3973, https://doi.org/10.5194/bg-15-3967-2018, https://doi.org/10.5194/bg-15-3967-2018, 2018
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We developed an algorithm for a fast spin-up by finding the exact solution of a linearized system representing the cyclo-stationary state of a model and implemented it in a biogeochemistry model, the Terrestrial Ecosystem Model. For the test sites with five different plant functional types, the new method saves over 90 % of the original spin-up time in site-level simulations. The developed spin-up method will be used for future quantification of carbon dynamics at fine spatiotemporal scales.
Donghai Wu, Philippe Ciais, Nicolas Viovy, Alan K. Knapp, Kevin Wilcox, Michael Bahn, Melinda D. Smith, Sara Vicca, Simone Fatichi, Jakob Zscheischler, Yue He, Xiangyi Li, Akihiko Ito, Almut Arneth, Anna Harper, Anna Ukkola, Athanasios Paschalis, Benjamin Poulter, Changhui Peng, Daniel Ricciuto, David Reinthaler, Guangsheng Chen, Hanqin Tian, Hélène Genet, Jiafu Mao, Johannes Ingrisch, Julia E. S. M. Nabel, Julia Pongratz, Lena R. Boysen, Markus Kautz, Michael Schmitt, Patrick Meir, Qiuan Zhu, Roland Hasibeder, Sebastian Sippel, Shree R. S. Dangal, Stephen Sitch, Xiaoying Shi, Yingping Wang, Yiqi Luo, Yongwen Liu, and Shilong Piao
Biogeosciences, 15, 3421–3437, https://doi.org/10.5194/bg-15-3421-2018, https://doi.org/10.5194/bg-15-3421-2018, 2018
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Our results indicate that most ecosystem models do not capture the observed asymmetric responses under normal precipitation conditions, suggesting an overestimate of the drought effects and/or underestimate of the watering impacts on primary productivity, which may be the result of inadequate representation of key eco-hydrological processes. Collaboration between modelers and site investigators needs to be strengthened to improve the specific processes in ecosystem models in following studies.
Sebastian Lienert and Fortunat Joos
Biogeosciences, 15, 2909–2930, https://doi.org/10.5194/bg-15-2909-2018, https://doi.org/10.5194/bg-15-2909-2018, 2018
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Deforestation, shifting cultivation and wood harvesting cause large carbon emissions, altering climate. We apply a dynamic global vegetation model in a probabilistic framework. Diverse observations are assimilated to establish an optimally performing model and a large ensemble of model versions. Land-use carbon emissions are reported for individual countries, regions and the world. We find that parameter-related uncertainties are on the same order of magnitude as process-related effects.
Verónika Ceballos-Núñez, Andrew D. Richardson, and Carlos A. Sierra
Biogeosciences, 15, 1607–1625, https://doi.org/10.5194/bg-15-1607-2018, https://doi.org/10.5194/bg-15-1607-2018, 2018
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Will the terrestrial biosphere be a carbon source or sink in the future? Different model simulations cannot reach a consensus, so we need to diagnose the performance of these models. We implemented three models differing in their carbon allocation strategies and assessed their performance using three metrics. The most sensible metric was the distribution of carbon age and transit times. Thus, empirical measurements of these distributions could be key to reduce the model uncertainty.
Emily Ane Dionizio, Marcos Heil Costa, Andrea D. de Almeida Castanho, Gabrielle Ferreira Pires, Beatriz Schwantes Marimon, Ben Hur Marimon-Junior, Eddie Lenza, Fernando Martins Pimenta, Xiaojuan Yang, and Atul K. Jain
Biogeosciences, 15, 919–936, https://doi.org/10.5194/bg-15-919-2018, https://doi.org/10.5194/bg-15-919-2018, 2018
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Using a dynamic vegetation model, we demonstrate that fire occurrence is the main determinant factor of vegetation changes along the Amazon–Cerrado border, followed by nutrient limitation and interannual climate variability. Although we simulated more than 80 % of the variability of biomass in the transition zone, in many places the simulated biomass clearly does not match observations. The accurate representation of the transition is important for understanding the savannization of the Amazon.
Corina Buendía, Axel Kleidon, Stefano Manzoni, Björn Reu, and Amilcare Porporato
Biogeosciences, 15, 279–295, https://doi.org/10.5194/bg-15-279-2018, https://doi.org/10.5194/bg-15-279-2018, 2018
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Amazonia is highly biodiverse and of global importance for regulating the climate system. Because soils are highly weathered, phosphorus (P) is suggested to limit ecosystem productivity. Here, we evaluate the importance of P redistribution by animals using a simple mathematical model synthesizing the major processes of the Amazon P cycle. Our findings suggest that food web complexity plays an important role for sustaining the productivity of terra firme forests.
Hanna Post, Harrie-Jan Hendricks Franssen, Xujun Han, Roland Baatz, Carsten Montzka, Marius Schmidt, and Harry Vereecken
Biogeosciences, 15, 187–208, https://doi.org/10.5194/bg-15-187-2018, https://doi.org/10.5194/bg-15-187-2018, 2018
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Estimated values of selected key CLM4.5-BGC parameters obtained with the Markov chain Monte Carlo (MCMC) approach DREAM(zs) strongly altered catchment-scale NEE predictions in comparison to global default parameter values. The effect of perturbed meteorological input data on the uncertainty of the predicted carbon fluxes was notably higher for C3-grass and C3-crop than for coniferous and deciduous forest. A future distinction of different crop types including management is considered essential.
Jinnan Gong, Ben Wang, Xin Jia, Wei Feng, Tianshan Zha, Seppo Kellomäki, and Heli Peltola
Biogeosciences, 15, 115–136, https://doi.org/10.5194/bg-15-115-2018, https://doi.org/10.5194/bg-15-115-2018, 2018
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By modelling soil CO2 production, transport and surface exchange processes (e.g. biocrust photosynthesis, respiration and photodegradation), we simulated the large variation of soil CO2 emissions from sparsely vegetated dryland ecosystem. Based on the model, we studied the roles of different processes in regulating soil C emissions. The complexity of regulation processes implied possibly high non-linearity of C responses to climatic variation, climate change and extreme climate events.
Wei Li, Philippe Ciais, Chao Yue, Thomas Gasser, Shushi Peng, and Ana Bastos
Biogeosciences, 15, 91–103, https://doi.org/10.5194/bg-15-91-2018, https://doi.org/10.5194/bg-15-91-2018, 2018
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We compared the biomass recovery curves from a recent field-based study with those used in bookkeeping models and demonstrated the importance of considering gross forest changes rather than net forest changes. We also derived a critical gross-to-net forest area change ratio, beyond which the sign of carbon flux will be reversed. This critical ratio was further applied to the high-resolution satellite data in the Amazon to distinguish the sensitive regions.
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