Articles | Volume 11, issue 7
https://doi.org/10.5194/bg-11-2069-2014
© Author(s) 2014. 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-11-2069-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
11 Apr 2014
Research article |
| 11 Apr 2014
Monte Carlo-based calibration and uncertainty analysis of a coupled plant growth and hydrological model
T. Houska
Institute for Landscape Ecology and Resources Management, Research Centre for BioSystems, Land Use and Nutrition (IFZ), Justus Liebig University Giessen, Giessen, Germany
S. Multsch
Institute for Landscape Ecology and Resources Management, Research Centre for BioSystems, Land Use and Nutrition (IFZ), Justus Liebig University Giessen, Giessen, Germany
Institute for Landscape Ecology and Resources Management, Research Centre for BioSystems, Land Use and Nutrition (IFZ), Justus Liebig University Giessen, Giessen, Germany
H.-G. Frede
Institute for Landscape Ecology and Resources Management, Research Centre for BioSystems, Land Use and Nutrition (IFZ), Justus Liebig University Giessen, Giessen, Germany
L. Breuer
Institute for Landscape Ecology and Resources Management, Research Centre for BioSystems, Land Use and Nutrition (IFZ), Justus Liebig University Giessen, Giessen, Germany
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We compared soil model performance to data from a long-term nitrogen addition experiment in a forested ecosystem. We found that in order for soil carbon models to accurately predict future forest carbon sequestration, two key processes must respond dynamically to nitrogen availability: (1) plant allocation of carbon to wood versus roots and (2) rates of soil organic matter decomposition. Long-term experiments can help improve our predictions of the land carbon sink and its climate impact.
Jan De Pue, Sebastian Wieneke, Ana Bastos, José Miguel Barrios, Liyang Liu, Philippe Ciais, Alirio Arboleda, Rafiq Hamdi, Maral Maleki, Fabienne Maignan, Françoise Gellens-Meulenberghs, Ivan Janssens, and Manuela Balzarolo
Biogeosciences, 20, 4795–4818, https://doi.org/10.5194/bg-20-4795-2023, https://doi.org/10.5194/bg-20-4795-2023, 2023
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The gross primary production (GPP) of the terrestrial biosphere is a key source of variability in the global carbon cycle. To estimate this flux, models can rely on remote sensing data (RS-driven), meteorological data (meteo-driven) or a combination of both (hybrid). An intercomparison of 11 models demonstrated that RS-driven models lack the sensitivity to short-term anomalies. Conversely, the simulation of soil moisture dynamics and stress response remains a challenge in meteo-driven models.
Chad A. Burton, Luigi J. Renzullo, Sami W. Rifai, and Albert I. J. M. Van Dijk
Biogeosciences, 20, 4109–4134, https://doi.org/10.5194/bg-20-4109-2023, https://doi.org/10.5194/bg-20-4109-2023, 2023
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Australia's land-based ecosystems play a critical role in controlling the variability in the global land carbon sink. However, uncertainties in the methods used for quantifying carbon fluxes limit our understanding. We develop high-resolution estimates of Australia's land carbon fluxes using machine learning methods and find that Australia is, on average, a stronger carbon sink than previously thought and that the seasonal dynamics of the fluxes differ from those described by other methods.
Patrick Neri, Lianhong Gu, and Yang Song
Biogeosciences Discuss., https://doi.org/10.5194/bg-2023-163, https://doi.org/10.5194/bg-2023-163, 2023
Revised manuscript accepted for BG
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We made the first global-scale effort that modeled how plant functional types and habitat climatology regulated the temperature responses of the photosynthetic efficiency of adsorbed lights. We found that the more temperature-resilient plants were less temperature-tolerant and vice versa. Habitat climatology is more critical than plant types for regulating the temperature responses of plants with broad distributions or experiences of large temperature variability.
Yuan Yan, Anne Klosterhalfen, Fernando Moyano, Matthias Cuntz, Andrew C. Manning, and Alexander Knohl
Biogeosciences, 20, 4087–4107, https://doi.org/10.5194/bg-20-4087-2023, https://doi.org/10.5194/bg-20-4087-2023, 2023
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A better understanding of O2 fluxes, their exchange ratios with CO2 and their interrelations with environmental conditions would provide further insights into biogeochemical ecosystem processes. We, therefore, used the multilayer canopy model CANVEG to simulate and analyze the flux exchange for our forest study site for 2012–2016. Based on these simulations, we further successfully tested the application of various micrometeorological methods and the prospects of real O2 flux measurements.
Jie Zhang, Elisabeth Larsen Kolstad, Wenxin Zhang, Iris Vogeler, and Søren O. Petersen
Biogeosciences, 20, 3895–3917, https://doi.org/10.5194/bg-20-3895-2023, https://doi.org/10.5194/bg-20-3895-2023, 2023
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Manure application to agricultural land often results in large and variable N2O emissions. We propose a model with a parsimonious structure to investigate N transformations around such N2O hotspots. The model allows for new detailed insights into the interactions between transport and microbial activities regarding N2O emissions in heterogeneous soil environments. It highlights the importance of solute diffusion to N2O emissions from such hotspots which are often ignored by process-based models.
Jukka Alm, Antti Wall, Jukka-Pekka Myllykangas, Paavo Ojanen, Juha Heikkinen, Helena M. Henttonen, Raija Laiho, Kari Minkkinen, Tarja Tuomainen, and Juha Mikola
Biogeosciences, 20, 3827–3855, https://doi.org/10.5194/bg-20-3827-2023, https://doi.org/10.5194/bg-20-3827-2023, 2023
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In Finland peatlands cover one-third of land area. For half of those, with 4.3 Mha being drained for forestry, Finland reports sinks and sources of greenhouse gases in forest lands on organic soils following its UNFCCC commitment. We describe a new method for compiling soil CO2 balance that follows changes in tree volume, tree harvests and temperature. An increasing trend of emissions from 1.4 to 7.9 Mt CO2 was calculated for drained peatland forest soils in Finland for 1990–2021.
Daniel Nadal-Sala, Rüdiger Grote, David Kraus, Uri Hochberg, Tamir Klein, Yael Wagner, Fedor Tatarinov, Dan Yakir, and Nadine Katrin Ruehr
Biogeosciences Discuss., https://doi.org/10.5194/bg-2023-142, https://doi.org/10.5194/bg-2023-142, 2023
Revised manuscript accepted for BG
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We present an integrative model approach that is based on plant water potential triggering stomatal closure, downregulation of photosynthesis, and sapwood as well as foliage senescence. This new model functionality that can be added to any physiologically based ecosystem model has been evaluated in an extremely dry Aleppo pine plantation. We were able to represent gas exchanges under varying soil water supply and atmospheric demand and the model responded realistically regarding leaf senescence.
Siqi Li, Bo Zhu, Xunhua Zheng, Pengcheng Hu, Shenghui Han, Jihui Fan, Tao Wang, Rui Wang, Kai Wang, Zhisheng Yao, Chunyan Liu, Wei Zhang, and Yong Li
Biogeosciences, 20, 3555–3572, https://doi.org/10.5194/bg-20-3555-2023, https://doi.org/10.5194/bg-20-3555-2023, 2023
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Physical soil erosion and particulate carbon, nitrogen and phosphorus loss modules were incorporated into the process-oriented hydro-biogeochemical model CNMM-DNDC to realize the accurate simulation of water-induced erosion and subsequent particulate nutrient losses at high spatiotemporal resolution.
Ivan Cornut, Nicolas Delpierre, Jean-Paul Laclau, Joannès Guillemot, Yann Nouvellon, Otavio Campoe, Jose Luiz Stape, Vitoria Fernanda Santos, and Guerric le Maire
Biogeosciences, 20, 3093–3117, https://doi.org/10.5194/bg-20-3093-2023, https://doi.org/10.5194/bg-20-3093-2023, 2023
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Potassium is an essential element for living organisms. Trees are dependent upon this element for certain functions that allow them to build their trunks using carbon dioxide. Using data from experiments in eucalypt plantations in Brazil and a simplified computer model of the plantations, we were able to investigate the effect that a lack of potassium can have on the production of wood. Understanding nutrient cycles is useful to understand the response of forests to environmental change.
Ivan Cornut, Guerric le Maire, Jean-Paul Laclau, Joannès Guillemot, Yann Nouvellon, and Nicolas Delpierre
Biogeosciences, 20, 3119–3135, https://doi.org/10.5194/bg-20-3119-2023, https://doi.org/10.5194/bg-20-3119-2023, 2023
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After simulating the effects of low levels of potassium on the canopy of trees and the uptake of carbon dioxide from the atmosphere by leaves in Part 1, here we tried to simulate the way the trees use the carbon they have acquired and the interaction with the potassium cycle in the tree. We show that the effect of low potassium on the efficiency of the trees in acquiring carbon is enough to explain why they produce less wood when they are in soils with low levels of potassium.
Xiaojuan Yang, Peter Thornton, Daniel Ricciuto, Yilong Wang, and Forrest Hoffman
Biogeosciences, 20, 2813–2836, https://doi.org/10.5194/bg-20-2813-2023, https://doi.org/10.5194/bg-20-2813-2023, 2023
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We evaluated the performance of a land surface model (ELMv1-CNP) that includes both nitrogen (N) and phosphorus (P) limitation on carbon cycle processes. We show that ELMv1-CNP produces realistic estimates of present-day carbon pools and fluxes. We show that global C sources and sinks are significantly affected by P limitation. Our study suggests that introduction of P limitation in land surface models is likely to have substantial consequences for projections of future carbon uptake.
Kevin R. Wilcox, Scott L. Collins, Alan K. Knapp, William Pockman, Zheng Shi, Melinda D. Smith, and Yiqi Luo
Biogeosciences, 20, 2707–2725, https://doi.org/10.5194/bg-20-2707-2023, https://doi.org/10.5194/bg-20-2707-2023, 2023
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The capacity for carbon storage (C capacity) is an attribute that determines how ecosystems store carbon in the future. Here, we employ novel data–model integration techniques to identify the carbon capacity of six grassland sites spanning the US Great Plains. Hot and dry sites had low C capacity due to less plant growth and high turnover of soil C, so they may be a C source in the future. Alternately, cooler and wetter ecosystems had high C capacity, so these systems may be a future C sink.
Ara Cho, Linda M. J. Kooijmans, Kukka-Maaria Kohonen, Richard Wehr, and Maarten C. Krol
Biogeosciences, 20, 2573–2594, https://doi.org/10.5194/bg-20-2573-2023, https://doi.org/10.5194/bg-20-2573-2023, 2023
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Carbonyl sulfide (COS) is a useful constraint for estimating photosynthesis. To simulate COS leaf flux better in the SiB4 model, we propose a novel temperature function for enzyme carbonic anhydrase (CA) activity and optimize conductances using observations. The optimal activity of CA occurs below 40 °C, and Ball–Woodrow–Berry parameters are slightly changed. These reduce/increase uptakes in the tropics/higher latitudes and contribute to resolving discrepancies in the COS global budget.
Yunyao Ma, Bettina Weber, Alexandra Kratz, José Raggio, Claudia Colesie, Maik Veste, Maaike Y. Bader, and Philipp Porada
Biogeosciences, 20, 2553–2572, https://doi.org/10.5194/bg-20-2553-2023, https://doi.org/10.5194/bg-20-2553-2023, 2023
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We found that the modelled annual carbon balance of biocrusts is strongly affected by both the environment (mostly air temperature and CO2 concentration) and physiology, such as temperature response of respiration. However, the relative impacts of these drivers vary across regions with different climates. Uncertainty in driving factors may lead to unrealistic carbon balance estimates, particularly in temperate climates, and may be explained by seasonal variation of physiology due to acclimation.
Alexander J. Norton, A. Anthony Bloom, Nicholas C. Parazoo, Paul A. Levine, Shuang Ma, Renato K. Braghiere, and T. Luke Smallman
Biogeosciences, 20, 2455–2484, https://doi.org/10.5194/bg-20-2455-2023, https://doi.org/10.5194/bg-20-2455-2023, 2023
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This study explores how the representation of leaf phenology affects our ability to predict changes to the carbon balance of land ecosystems. We calibrate a new leaf phenology model against a diverse range of observations at six forest sites, showing that it improves the predictive capability of the processes underlying the ecosystem carbon balance. We then show how changes in temperature and rainfall affect the ecosystem carbon balance with this new model.
Libo Wang, Vivek K. Arora, Paul Bartlett, Ed Chan, and Salvatore R. Curasi
Biogeosciences, 20, 2265–2282, https://doi.org/10.5194/bg-20-2265-2023, https://doi.org/10.5194/bg-20-2265-2023, 2023
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Plant functional types (PFTs) are groups of plant species used to represent vegetation distribution in land surface models. There are large uncertainties associated with existing methods for mapping land cover datasets to PFTs. This study demonstrates how fine-resolution tree cover fraction and land cover datasets can be used to inform the PFT mapping process and reduce the uncertainties. The proposed largely objective method makes it easier to implement new land cover products in models.
Jennifer A. Holm, David M. Medvigy, Benjamin Smith, Jeffrey S. Dukes, Claus Beier, Mikhail Mishurov, Xiangtao Xu, Jeremy W. Lichstein, Craig D. Allen, Klaus S. Larsen, Yiqi Luo, Cari Ficken, William T. Pockman, William R. L. Anderegg, and Anja Rammig
Biogeosciences, 20, 2117–2142, https://doi.org/10.5194/bg-20-2117-2023, https://doi.org/10.5194/bg-20-2117-2023, 2023
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Unprecedented climate extremes (UCEs) are expected to have dramatic impacts on ecosystems. We present a road map of how dynamic vegetation models can explore extreme drought and climate change and assess ecological processes to measure and reduce model uncertainties. The models predict strong nonlinear responses to UCEs. Due to different model representations, the models differ in magnitude and trajectory of forest loss. Therefore, we explore specific plant responses that reflect knowledge gaps.
Veronika Kronnäs, Klas Lucander, Giuliana Zanchi, Nadja Stadlinger, Salim Belyazid, and Cecilia Akselsson
Biogeosciences, 20, 1879–1899, https://doi.org/10.5194/bg-20-1879-2023, https://doi.org/10.5194/bg-20-1879-2023, 2023
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In a future climate, extreme droughts might become more common. Climate change and droughts can have negative effects on soil weathering and plant health.
In this study, climate change effects on weathering were studied on sites in Sweden using the model ForSAFE, a climate change scenario and an extreme drought scenario. The modelling shows that weathering is higher during summer and increases with global warming but that weathering during drought summers can become as low as winter weathering.
Agustín Sarquis and Carlos A. Sierra
Biogeosciences, 20, 1759–1771, https://doi.org/10.5194/bg-20-1759-2023, https://doi.org/10.5194/bg-20-1759-2023, 2023
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Although plant litter is chemically and physically heterogenous and undergoes multiple transformations, models that represent litter dynamics often ignore this complexity. We used a multi-model inference framework to include information content in litter decomposition datasets and studied the time it takes for litter to decompose as measured by the transit time. In arid lands, the median transit time of litter is about 3 years and has a negative correlation with mean annual temperature.
Qi Guan, Jing Tang, Lian Feng, Stefan Olin, and Guy Schurgers
Biogeosciences, 20, 1635–1648, https://doi.org/10.5194/bg-20-1635-2023, https://doi.org/10.5194/bg-20-1635-2023, 2023
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Understanding terrestrial sources of nitrogen is vital to examine lake eutrophication changes. Combining process-based ecosystem modeling and satellite observations, we found that land-leached nitrogen in the Yangtze Plain significantly increased from 1979 to 2018, and terrestrial nutrient sources were positively correlated with eutrophication trends observed in most lakes, demonstrating the necessity of sustainable nitrogen management to control eutrophication.
Vivek K. Arora, Christian Seiler, Libo Wang, and Sian Kou-Giesbrecht
Biogeosciences, 20, 1313–1355, https://doi.org/10.5194/bg-20-1313-2023, https://doi.org/10.5194/bg-20-1313-2023, 2023
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The behaviour of natural systems is now very often represented through mathematical models. These models represent our understanding of how nature works. Of course, nature does not care about our understanding. Since our understanding is not perfect, evaluating models is challenging, and there are uncertainties. This paper illustrates this uncertainty for land models and argues that evaluating models in light of the uncertainty in various components provides useful information.
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
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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
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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
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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
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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
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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
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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
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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
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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
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Understanding how plants decompose is important for understanding where the atmospheric CO2 they absorb ends up after they die. In forests, decomposition is controlled by rain but 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
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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.
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
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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
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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
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For the first time, microwave vegetation optical depth data are assimilated in a land surface model in order to analyze leaf area index and root zone soil moisture. The advantage of microwave products is the higher observation frequency. A large variety of independent datasets are used to verify the added value of the assimilation. It is shown that the assimilation is able to improve the representation of soil moisture, vegetation conditions, and terrestrial water and carbon fluxes.
Camille Abadie, Fabienne Maignan, Marine Remaud, Jérôme Ogée, J. Elliott Campbell, Mary E. Whelan, Florian Kitz, Felix M. Spielmann, Georg Wohlfahrt, Richard Wehr, Wu Sun, Nina Raoult, Ulli Seibt, Didier Hauglustaine, Sinikka T. Lennartz, Sauveur Belviso, David Montagne, and Philippe Peylin
Biogeosciences, 19, 2427–2463, https://doi.org/10.5194/bg-19-2427-2022, https://doi.org/10.5194/bg-19-2427-2022, 2022
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A better constraint of the components of the carbonyl sulfide (COS) global budget is needed to exploit its potential as a proxy of gross primary productivity. In this study, we compare two representations of oxic soil COS fluxes, and we develop an approach to represent anoxic soil COS fluxes in a land surface model. We show the importance of atmospheric COS concentration variations on oxic soil COS fluxes and provide new estimates for oxic and anoxic soil contributions to the COS global budget.
Cited articles
Acevedo, E., Silva, P., and Silva, H.: Wheat growth and physiology, CURTIS, BC et al., Bread wheat. Rome, Italy: FAO Plant Production and Protection Series (FAO), 39–70, 2002.
Allen, R. G., Pereira, L. S., Raes, D., and Smith, M.: Crop evapotranspiration-Guidelines for computing crop water requirements-FAO Irrigation and drainage paper 56, FAO, Rome, 300, 6541, 1998.
Aurbacher, J., Parker, P. S., Calberto Sánchez, G. A., Steinbach, J., Reinmuth, E., Ingwersen, J., and Dabbert, S.: Influence of climate change on short term management of field crops – A modelling approach, Agr. Systems, 119, 44–57, 2013.
Besalatpour, A., Hajabbasi, M. A., Ayoubi, S., and Jalalian, A.: Identification and prioritization of critical sub-basins in a highly mountainous watershed using SWAT model, Euras. J. Soil Sci., 1, 58–63, 2012.
Beven, K.: A manifesto for the equifinality thesis, J. Hydrol., 320, 18–36, 2006.
Beven, K. and Binley, A.: The future of distributed models: Model calibration and uncertainty prediction, Hydrol. Proc., 6, 279–298, 1992.
Beven, K. and Freer, J.: Equifinality, data assimilation, and uncertainty estimation in mechanistic modelling of complex environmental systems using the GLUE methodology, Journal of Hydrology, 249, 11–29, 2001.
Calderini, D. F., Dreccer, M. F., and Slafer, G. A.: Consequences of breeding on biomass, radiation interception and radiation-use efficiency in wheat, Field Crops Res., 52, 271–281, 1997.
Candela, A., Noto, L. V., and Aronica, G.: Influence of surface roughness in hydrological response of semiarid catchments, J. Hydrol., 313, 119–131, 2005.
Christiaens, K. and Feyen, J.: Constraining soil hydraulic parameter and output uncertainty of the distributed hydrological MIKE SHE model using the GLUE framework, Hydrol. Proc., 16, 373–391, 2002.
De Vries, P., Balema, A., Jansen, D. M., and Ten Berge, H. F. M.: Simulation of ecophysiological process of growth in several annual crops, Center for agriculture publishing and documentation (Pudoc), Wageningen, 1989.
Feddes, R. A., Kowalik, P. J., and Zaradny, H.: Simulation of field water use and crop yield, Wageningen: Centre for Agricultural Publishing and Documentation, 1978.
Feddes, R. A., Hoff, H., Bruen, M., Dawson, T., Rosnay, P. de, Dirmeyer, P., Jackson, R. B., Kabat, P., Kleidon, A., and Lilly, A.: Modeling root water uptake in hydrological and climate models., Bulletin of the American Meteorological Society, 82, 2797–2809, 2001.
Freer, J., Beven, K., and Ambroise, B.: Bayesian Estimation of Uncertainty in Runoff Prediction and the Value of Data: An Application of the GLUE Approach, Water Resour. Res., 32, 2161–2173, 1996.
Garnier, P., Néel, C., Mary, B., and Lafolie, F.: Evaluation of a nitrogen transport and transformation model in a bare soil, Europ. J. Soil Sci., 52, 253–268, 2001.
Genuchten, V. and T., M.: A Closed-form Equation for Predicting the Hydraulic Conductivity of Unsaturated Soils, Soil Sci. Soc. Am. J., 44, 892–898, 1980.
He, J., Jones, J. W., Graham, W. D., and Dukes, M. D.: Influence of likelihood function choice for estimating crop model parameters using the generalized likelihood uncertainty estimation method, Agr. Systems, 103, 256–264, 2010.
Hopmans, J. W. and Bristow, K. L.: Current Capabilities and Future Needs of Root Water and Nutrient Uptake Modeling, in: Advances in Agronomy, edited by: Donald L., Sparks, 77, 103–183, 2002.
Iizumi, T., Yokozawa, M., and Nishimori, M.: Parameter estimation and uncertainty analysis of a large-scale crop model for paddy rice: Application of a Bayesian approach, Agr. Forest Meteorol., 149, 333–348, 2009.
Ippisch, O., Vogel, H.-J., and Bastian, P.: Validity limits for the van Genuchten–Mualem model and implications for parameter estimation and numerical simulation, Adv. Water Res., 29, 1780–1789, 2006.
Jakeman, A. J., Letcher, R. A., and Norton, J. P.: Ten iterative steps in development and evaluation of environmental models, Environ. Modell. Software, 21, 602–614, 2006.
Jégo, G., Pattey, E., Bourgeois, G., Morrison, M. J., Drury, C. F., Tremblay, N., and Tremblay, G.: Calibration and performance evaluation of soybean and spring wheat cultivars using the STICS crop model in Eastern Canada, Field Crops Res., 117, 183–196, 2010.
Jiménez-Martínez, J., Skaggs, T. H., van Genuchten, M. T., and Candela, L.: A root zone modelling approach to estimating groundwater recharge from irrigated areas, J. Hydrol., 367, 138–149, 2009.
Jin, X., Xu, C.-Y., Zhang, Q., and Singh, V. P.: Parameter and modeling uncertainty simulated by GLUE and a formal Bayesian method for a conceptual hydrological model, J. Hydrol., 383, 147–155, 2010.
Jones, J. W., Tsuji, G. Y., Hoogenboom, G., Hunt, L. A., Thornton, P. K., Wilkens, P. W., Imamura, D. T., Bowen, W. T., and Singh, U.: Decision support system for agrotechnology transfer: DSSAT v3, in: Understanding Options for Agricultural Production, edited by: G. Y. Tsuji, G. Hoogenboom, and P. K. Thornton, 157–177, 1998.
Keesman, K. and Straten, G. van: Set Membership Approach to Identification and Prediction of Lake Eutrophication, Water Resour. Res., 26, 2643–2652, 1990.
Kersebaum, K. C., Hecker, J.-M., Mirschel, W., and Wegehenkel, M.: Modelling water and nutrient dynamics in soil–crop systems: a comparison of simulation models applied on common data sets, in: Modelling water and nutrient dynamics in soil–crop systems, edited by: K. C. Kersebaum, J.-M. Hecker, W. Mirschel, and M. Wegehenkel, Springer Netherlands, teh Netherlands, 1–17, 2007.
Kraft, P., Vaché, K. B., Frede, H.-G., and Breuer, L.: CMF: A Hydrological Programming Language Extension For Integrated Catchment Models, Environ. Modell. Software, 26, 828–830, 2011.
Li, L., Xia, J., Xu, C.-Y., and Singh, V. P.: Evaluation of the subjective factors of the GLUE method and comparison with the formal Bayesian method in uncertainty assessment of hydrological models, J. Hydrol., 390, 210–221, 2010.
Lindquist, J. L., Arkebauer, T. J., Walters, D. T., Cassman, K. G., and Dobermann, A.: Maize Radiation Use Efficiency under Optimal Growth Conditions, Agronomy J., 97, 72–78, 2005.
Ma, L., Ahuja, L. R., Saseendran, S. A., Malone, R. W., Green, T. R., Nolan, B. T., Bartling, P. N. S., Flerchinger, G. N., Boote, K. J., and Hoogenboom, G.: A Protocol for Parameterization and Calibration of RZWQM2 in Field Research, Methods of Introducing System Models into Agricultural Research, advancesinagric(methodsofintrod), 1–64, 2011.
McMaster, G. S. and Wilhelm, W. W.: Growing degree-days: one equation, two interpretations, Agr. Forest Meteorol., 87, 291–300, 1997.
Mirschel, W., Wenkel, K.-O., Wegehenkel, M., Kersebaum, K. C., Schindler, U., and Hecker, J.-M.: Müncheberg field trial data set for agro-ecosystem model validation, in: Modelling water and nutrient dynamics in soil–crop systems, edited by: Kersebaum, K. C., Hecker, J.-M., Mirschel, W., and Wegehenkel, M., Springer Netherlands, the Netherlands, 219–243, 2007.
Mo, X. and Beven, K.: Multi-objective parameter conditioning of a three-source wheat canopy model, Agr. Forest Meteorol., 122, 39–63, 2004.
Monteith, J. L.: Evaporation and environment, in: Symp. Soc. Exp. Biol, 19, p. 4., 1965.
Multsch, S., Kraft, P., Frede, H. G., and Breuer, L.: Development and application of the generic Plant growth Modeling Framework (PMF), in MODSIM2011 International Congress on Modelling and Simulation, Modelling and Simulation Society of Australia and New Zealand, 2011.
Nash, J. E. and Sutcliffe, J. V.: River flow forecasting through conceptual models part I – A discussion of principles, J. Hydrol., 10, 282–290, 1970.
Nassif, D. S. P., Marin, F. R., Pallone Filho, W. J., Resende, R. S., and Pellegrino, G. Q.: Parameterization and evaluation of the DSSAT/Canegro model for Brazilian sugarcane varieties, Pesquisa Agropecuária Brasileira, 47, 311–318, 2012.
Oliphant, T. E.: A Guide to NumPy, Trelgol Publishing USA, available at: http://ftp.sumy.volia.net/pub/FreeBSD/distfiles/numpybook.pdf, 2006.
Palosuo, T., Kersebaum, K. C., Angulo, C., Hlavinka, P., Moriondo, M., Olesen, J. E., Patil, R. H., Ruget, F., Rumbaur, C., Takáč, J., Trnka, M., Bindi, M., Çaldağ, B., Ewert, F., Ferrise, R., Mirschel, W., Şaylan, L., Šiška, B., and Rötter, R.: Simulation of winter wheat yield and its variability in different climates of Europe: A comparison of eight crop growth models, Europ. J. Agr., 35, 103–114, 2011.
Pathak, T. B., Jones, J. W., Fraisse, C. W., Wright, D., and Hoogenboom, G.: Uncertainty Analysis and Parameter Estimation for the CSM-CROPGRO-Cotton Model, Agronomy J., 104, 1363, 2012.
Pauwels, V. R. N., Verhoest, N. E. C., De Lannoy, G. J. M., Guissard, V., Lucau, C., and Defourny, P.: Optimization of a coupled hydrology–crop growth model through the assimilation of observed soil moisture and leaf area index values using an ensemble Kalman filter, Water Resour. Res., 43, 2007.
Porter, J. R. and Gawith, M.: Temperatures and the growth and development of wheat: a review, Europ. J. Agr., 10, 23–36, 1999.
Priesack, E., Gayler, S., and Hartmann, H. P.: The impact of crop growth sub-model choice on simulated water and nitrogen balances, Nutr. Cycl. Agroecosyst., 75, 1–13, 2006.
Rankinen, K., Karvonen, T., and Butterfield, D.: An application of the GLUE methodology for estimating the parameters of the INCA-N model, Sci. Total Environ., 365, 123–139, 2006.
Scharnagl, B., Vrugt, J. A., Vereecken, H., and Herbst, M.: Bayesian inverse modelling of in situ soil water dynamics: using prior information about the soil hydraulic properties, Hydrol. Earth Syst. Sci. Discuss., 8, 2019–2063, 2011.
Sinclair, T. R. and Horie, T.: Leaf Nitrogen, Photosynthesis, and Crop Radiation Use Efficiency: A Review, Crop Science, 29, 90, https://doi.org/10.2135/cropsci1989.0011183X002900010023x, 1989.
Viola, F., Noto, L. V., Cannarozzo, M., and La Loggia, G.: Daily streamflow prediction with uncertainty in ephemeral catchments using the GLUE methodology, Physics and Chemistry of the Earth, Parts A/B/C, 34, 701–706, 2009.
Vogel, T., van Genuchten, M. T., and Cislerova, M.: Effect of the shape of the soil hydraulic functions near saturation on variably-saturated flow predictions, Adv. Water Resour., 24, 133–144, 2000.
Vrugt, J. A., Gupta, H. V., Bastidas, L. A., Bouten, W., and Sorooshian, S.: Effective and efficient algorithm for multiobjective optimization of hydrologic models, Water Resour. Res., 39, 1214, 2003.
Vrugt, J. A., Braak, C. J. F., Gupta, H. V., and Robinson, B. A.: Equifinality of formal (DREAM) and informal (GLUE) Bayesian approaches in hydrologic modeling?, Stochastic Environmental Research and Risk Assessment, 23, 1011–1026, 2008.
Wallach, D.: Working with Dynamic Crop Models: Evaluation, Analysis, Parameterization, and Applications, Elsevier, 2006.
Wang, X., He, X., Wiliams, J. R., Izaurralde, R. C., and Atwood, J. D.: Sensitivity and uncertainty analyses of crop yields and soil organic carbon simulated with EPIC, Transactions of the ASAE, 48, 1041–1054, 2005.
Wegehenkel, M.: Test of a modelling system for simulating water balances and plant growth using various different complex approaches, Ecol. Modell., 129, 39–64, 2000.
Wilmott, C. J.: On the validation of models, Phys. Geogr., 2, 184–194, 1981.
Windhorst, D., Kraft, P., Frede, H.-G., and Breuer, L.: Landscape Management Framework (LMF) – development and application of a new concept for a dynamic landscape management model, edited by: Seppelt, R., Voinov, A., Lange, S., and Bankamp, D., Leipzig, Germany, 2559–2565, 2012.
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