Articles | Volume 6, issue 1
https://doi.org/10.5194/gmd-6-29-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-6-29-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Development and technical paper
| 
08 Jan 2013
Development and technical paper |
| 08 Jan 2013
Sensitivity analysis and calibration of a soil carbon model (SoilGen2) in two contrasting loess forest soils
Y. Y. Yu
Key Laboratory of Cenozoic Geology and Environment, Institute of Geology and Geophysics, Chinese Academy of Science, 100029, Beijing, China
P. A. Finke
Department of Geology and Soil Science, University of Ghent, Krijgslaan 281, 9000 Ghent, Belgium
H. B. Wu
Key Laboratory of Cenozoic Geology and Environment, Institute of Geology and Geophysics, Chinese Academy of Science, 100029, Beijing, China
Z. T. Guo
Key Laboratory of Cenozoic Geology and Environment, Institute of Geology and Geophysics, Chinese Academy of Science, 100029, Beijing, China
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Earth Surf. Dynam., 12, 163–180, https://doi.org/10.5194/esurf-12-163-2024, https://doi.org/10.5194/esurf-12-163-2024, 2024
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The Wei River catchment, one of the centers of the agricultural revolution in China, has experienced intense land use changes since 6000 BCE. This makes it an ideal place to study the response of river systems to anthropogenic land use change. Modeling results show the sensitivity of discharge and sediment yield to climate change increased abruptly when the agricultural land area exceeded a threshold at around 1000 BCE. This regime shift in the fluvial catchment led to a large sediment pulse.
Haoyue Zuo, Yonggang Liu, Gaojun Li, Zhifang Xu, Liang Zhao, Zhengtang Guo, and Yongyun Hu
Geosci. Model Dev., 17, 3949–3974, https://doi.org/10.5194/gmd-17-3949-2024, https://doi.org/10.5194/gmd-17-3949-2024, 2024
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Compared to the silicate weathering fluxes measured at large river basins, the current models tend to systematically overestimate the fluxes over the tropical region, which leads to an overestimation of the global total weathering flux. The most possible cause of such bias is found to be the overestimation of tropical surface erosion, which indicates that the tropical vegetation likely slows down physical erosion significantly. We propose a way of taking this effect into account in models.
Hao Chen, Xianyan Wang, Yanyan Yu, Huayu Lu, and Ronald Van Balen
Earth Surf. Dynam., 12, 163–180, https://doi.org/10.5194/esurf-12-163-2024, https://doi.org/10.5194/esurf-12-163-2024, 2024
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The Wei River catchment, one of the centers of the agricultural revolution in China, has experienced intense land use changes since 6000 BCE. This makes it an ideal place to study the response of river systems to anthropogenic land use change. Modeling results show the sensitivity of discharge and sediment yield to climate change increased abruptly when the agricultural land area exceeded a threshold at around 1000 BCE. This regime shift in the fluvial catchment led to a large sediment pulse.
Lauren M. Gillespie, Nathalie Y. Triches, Diego Abalos, Peter Finke, Sophie Zechmeister-Boltenstern, Stephan Glatzel, and Eugenio Díaz-Pinés
SOIL, 9, 517–531, https://doi.org/10.5194/soil-9-517-2023, https://doi.org/10.5194/soil-9-517-2023, 2023
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Forest soil is potentially an important source or sink of greenhouse gases (CO2, N2O, and CH4), but this is affected by soil conditions. We studied how land inclination and soil/litter properties influence the flux of these gases. CO2 and N2O were more affected by inclination than CH4; all were affected by soil/litter properties. This study underlines the importance of inclination and soil/litter properties in predicting greenhouse gas fluxes from forest soil and potential source–sink balance.
Sastrika Anindita, Peter Finke, and Steven Sleutel
SOIL, 9, 443–459, https://doi.org/10.5194/soil-9-443-2023, https://doi.org/10.5194/soil-9-443-2023, 2023
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This study investigated how land use, through its impact on soil geochemistry, might indirectly control soil organic carbon (SOC) content in tropical volcanic soils in Indonesia. We analyzed SOC fractions, substrate-specific mineralization, and net priming of SOC. Our results indicated that the enhanced formation of aluminum (hydr)oxides promoted aggregation and physical occlusion of OC, which is consistent with the lesser degradability of SOC in agricultural soils.
Vanesa García-Gamero, Tom Vanwalleghem, Adolfo Peña, Andrea Román-Sánchez, and Peter A. Finke
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Short-scale soil variability has received much less attention than at the regional scale. The chemical depletion fraction (CDF), a proxy for chemical weathering, was measured and simulated with SoilGen along two opposite slopes in southern Spain. The results show that differences in CDF could not be explained by topography alone but by hydrological parameters. The model sensitivity test shows the maximum CDF value for intermediate precipitation has similar findings to other soil properties.
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Clim. Past Discuss., https://doi.org/10.5194/cp-2020-38, https://doi.org/10.5194/cp-2020-38, 2020
Manuscript not accepted for further review
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Whether an ice sheet once grew over Northeast Siberia-Beringia has been debated for decades. By comparing climate modelling with paleoclimate and glacial records from around the North Pacific, this study shows that the Laurentide-Eurasia-only ice sheet configuration fails in explaining these records, while a scenario involving the ice sheet over Northeast Siberia-Beringia succeeds. It highlights the complexity in glacial climates and urges new investigations across Northeast Siberia-Beringia.
Ning Tan, Camille Contoux, Gilles Ramstein, Yong Sun, Christophe Dumas, Pierre Sepulchre, and Zhengtang Guo
Clim. Past, 16, 1–16, https://doi.org/10.5194/cp-16-1-2020, https://doi.org/10.5194/cp-16-1-2020, 2020
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To understand the warm climate during the late Pliocene (~3.205 Ma), modeling experiments with the new boundary conditions are launched and analyzed based on the Institut Pierre Simon Laplace (IPSL) atmosphere–ocean coupled general circulation model (AOGCM). Our results show that the warming in mid- to high latitudes enhanced due to the modifications of the land–sea mask and land–ice configuration. The pCO2 uncertainties within the records can produce asymmetrical warming patterns.
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Clim. Past, 15, 1223–1249, https://doi.org/10.5194/cp-15-1223-2019, https://doi.org/10.5194/cp-15-1223-2019, 2019
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The mid-Holocene has been an excellent target for comparing models and data. This work shows that, over China, all the ocean–atmosphere general circulation models involved in PMIP3 show a very large discrepancy with pollen data reconstruction when comparing annual and seasonal temperature. It demonstrates that to reconcile models and data and to capture the signature of seasonal thermal response, it is necessary to integrate non-linear processes, particularly those related to vegetation changes.
Chenxi Xu, Masaki Sano, Ashok Priyadarshan Dimri, Rengaswamy Ramesh, Takeshi Nakatsuka, Feng Shi, and Zhengtang Guo
Clim. Past, 14, 653–664, https://doi.org/10.5194/cp-14-653-2018, https://doi.org/10.5194/cp-14-653-2018, 2018
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We have constructed a regional tree ring cellulose oxygen isotope record using a total of five chronologies obtained from the Himalaya. Centennial changes in the regional tree ring record indicate a trend of weakened Indian summer monsoon (ISM) intensity since 1820. Decreasing ISM activity is also observed in various high-resolution ISM records from southwest China and Southeast Asia, and may be the result of reduced land–ocean thermal contrasts since 1820.
Feng Shi, Sen Zhao, Zhengtang Guo, Hugues Goosse, and Qiuzhen Yin
Clim. Past, 13, 1919–1938, https://doi.org/10.5194/cp-13-1919-2017, https://doi.org/10.5194/cp-13-1919-2017, 2017
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We reconstructed the multi-proxy precipitation field for China over the past 500 years, which includes three leading modes (a monopole, a dipole, and a triple) of precipitation variability. The dipole mode may be controlled by the El Niño–Southern Oscillation variability. Such reconstruction is an essential source of information to document the climate variability over decadal to centennial timescales and can be used to assess the ability of climate models to simulate past climate change.
E. Opolot and P. A. Finke
Biogeosciences, 12, 6791–6808, https://doi.org/10.5194/bg-12-6791-2015, https://doi.org/10.5194/bg-12-6791-2015, 2015
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This study evaluated the sensitivity of silicate mineral dissolution rates to intrinsic and extrinsic factors using a soil evolution model, SoilGen2.25. Modelling results showed a dominant role of pH and a direct effect of soil texture on dissolution rates. Clay migration and plant nutrient recycling influenced the pH and thus the dissolution rates. These results demonstrate the need to couple different soil processes in order to explain differences between lab and field dissolution rates.
P. X. Wang, B. Wang, H. Cheng, J. Fasullo, Z. T. Guo, T. Kiefer, and Z. Y. Liu
Clim. Past, 10, 2007–2052, https://doi.org/10.5194/cp-10-2007-2014, https://doi.org/10.5194/cp-10-2007-2014, 2014
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All regional monsoons belong to a cohesive global monsoon circulation system, albeit thateach regional subsystem has its own indigenous features. A comprehensive review of global monsoon variability reveals that regional monsoons can vary coherently across a range of timescales, from interannual up to orbital and tectonic. Study of monsoon variability from both global and regional perspectives is imperative and advantageous for integrated understanding of the modern and paleo-monsoon dynamics.
Q. Z. Yin, U. K. Singh, A. Berger, Z. T. Guo, and M. Crucifix
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H. Wu, C. Peng, T. R. Moore, D. Hua, C. Li, Q. Zhu, M. Peichl, M. A. Arain, and Z. Guo
Geosci. Model Dev., 7, 867–881, https://doi.org/10.5194/gmd-7-867-2014, https://doi.org/10.5194/gmd-7-867-2014, 2014
H. Wu, C. Peng, M. Lucotte, N. Soumis, Y. Gélinas, É. Duchemin, J.-B. Plouhinec, A. Ouellet, and Z. Guo
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmdd-6-3509-2013, https://doi.org/10.5194/gmdd-6-3509-2013, 2013
Revised manuscript not accepted
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We use computer models to predict how the land surface will respond to climate change. However, these complex models do not always simulate what we observe in real life, limiting their effectiveness. To improve their accuracy, we use sophisticated statistical and computational techniques. We test a technique called history matching against more common approaches. This method adapts well to these models, helping us better understand how they work and therefore how to make them more realistic.
Jorn Bruggeman, Karsten Bolding, Lars Nerger, Anna Teruzzi, Simone Spada, Jozef Skákala, and Stefano Ciavatta
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Dongyu Zheng, Andrew S. Merdith, Yves Goddéris, Yannick Donnadieu, Khushboo Gurung, and Benjamin J. W. Mills
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Boris Ťupek, Aleksi Lehtonen, Alla Yurova, Rose Abramoff, Bertrand Guenet, Elisa Bruni, Samuli Launiainen, Mikko Peltoniemi, Shoji Hashimoto, Xianglin Tian, Juha Heikkinen, Kari Minkkinen, and Raisa Mäkipää
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Updating the Yasso07 soil C model's dependency on decomposition with a hump-shaped Ricker moisture function improved modelled soil organic C (SOC) stocks in a catena of mineral and organic soils in boreal forest. The Ricker function, set to peak at a rate of 1 and calibrated against SOC and CO2 data using a Bayesian approach, showed a maximum in well-drained soils. Using SOC and CO2 data together with the moisture only from the topsoil humus was crucial for accurate model estimates.
Jacquelyn K. Shuman, Rosie A. Fisher, Charles Koven, Ryan Knox, Lara Kueppers, and Chonggang Xu
Geosci. Model Dev., 17, 4643–4671, https://doi.org/10.5194/gmd-17-4643-2024, https://doi.org/10.5194/gmd-17-4643-2024, 2024
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Yoshiki Kanzaki, Isabella Chiaravalloti, Shuang Zhang, Noah J. Planavsky, and Christopher T. Reinhard
Geosci. Model Dev., 17, 4515–4532, https://doi.org/10.5194/gmd-17-4515-2024, https://doi.org/10.5194/gmd-17-4515-2024, 2024
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Soil pH is one of the most commonly measured agronomical and biogeochemical indices, mostly reflecting exchangeable acidity. Explicit simulation of both porewater and bulk soil pH is thus crucial to the accurate evaluation of alkalinity required to counteract soil acidification and the resulting capture of anthropogenic carbon dioxide through the enhanced weathering technique. This has been enabled by the updated reactive–transport SCEPTER code and newly developed framework to simulate soil pH.
David Sandoval, Iain Colin Prentice, and Rodolfo L. B. Nóbrega
Geosci. Model Dev., 17, 4229–4309, https://doi.org/10.5194/gmd-17-4229-2024, https://doi.org/10.5194/gmd-17-4229-2024, 2024
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Numerous estimates of water and energy balances depend on empirical equations requiring site-specific calibration, posing risks of "the right answers for the wrong reasons". We introduce novel first-principles formulations to calculate key quantities without requiring local calibration, matching predictions from complex land surface models.
Oliver Perkins, Matthew Kasoar, Apostolos Voulgarakis, Cathy Smith, Jay Mistry, and James D. A. Millington
Geosci. Model Dev., 17, 3993–4016, https://doi.org/10.5194/gmd-17-3993-2024, https://doi.org/10.5194/gmd-17-3993-2024, 2024
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Wildfire is often presented in the media as a danger to human life. Yet globally, millions of people’s livelihoods depend on using fire as a tool. So, patterns of fire emerge from interactions between humans, land use, and climate. This complexity means scientists cannot yet reliably say how fire will be impacted by climate change. So, we developed a new model that represents globally how people use and manage fire. The model reveals the extent and diversity of how humans live with and use fire.
Amos P. K. Tai, David H. Y. Yung, and Timothy Lam
Geosci. Model Dev., 17, 3733–3764, https://doi.org/10.5194/gmd-17-3733-2024, https://doi.org/10.5194/gmd-17-3733-2024, 2024
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We have developed the Terrestrial Ecosystem Model in R (TEMIR), which simulates plant carbon and pollutant uptake and predicts their response to varying atmospheric conditions. This model is designed to couple with an atmospheric chemistry model so that questions related to plant–atmosphere interactions, such as the effects of climate change, rising CO2, and ozone pollution on forest carbon uptake, can be addressed. The model has been well validated with both ground and satellite observations.
Fabian Stenzel, Johanna Braun, Jannes Breier, Karlheinz Erb, Dieter Gerten, Jens Heinke, Sarah Matej, Sebastian Ostberg, Sibyll Schaphoff, and Wolfgang Lucht
Geosci. Model Dev., 17, 3235–3258, https://doi.org/10.5194/gmd-17-3235-2024, https://doi.org/10.5194/gmd-17-3235-2024, 2024
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We provide an R package to compute two biosphere integrity metrics that can be applied to simulations of vegetation growth from the dynamic global vegetation model LPJmL. The pressure metric BioCol indicates that we humans modify and extract > 20 % of the potential preindustrial natural biomass production. The ecosystems state metric EcoRisk shows a high risk of ecosystem destabilization in many regions as a result of climate change and land, water, and fertilizer use.
Elin Ristorp Aas, Heleen A. de Wit, and Terje K. Berntsen
Geosci. Model Dev., 17, 2929–2959, https://doi.org/10.5194/gmd-17-2929-2024, https://doi.org/10.5194/gmd-17-2929-2024, 2024
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By including microbial processes in soil models, we learn how the soil system interacts with its environment and responds to climate change. We present a soil process model, MIMICS+, which is able to reproduce carbon stocks found in boreal forest soils better than a conventional land model. With the model we also find that when adding nitrogen, the relationship between soil microbes changes notably. Coupling the model to a vegetation model will allow for further study of these mechanisms.
Katarína Merganičová, Ján Merganič, Laura Dobor, Roland Hollós, Zoltán Barcza, Dóra Hidy, Zuzana Sitková, Pavel Pavlenda, Hrvoje Marjanovic, Daniel Kurjak, Michal Bošeľa, Doroteja Bitunjac, Masa Zorana Ostrogovic Sever, Jiří Novák, Peter Fleischer, and Tomáš Hlásny
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-45, https://doi.org/10.5194/gmd-2024-45, 2024
Revised manuscript accepted for GMD
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We developed a multi-objective calibration approach leading to robust parameter values, aiming to strike a balance between their local precision and broad applicability. Using Biome-BGCMuSo model, we tested the calibrated parameter sets for simulating European beech forest dynamics across large environmental gradients. Leveraging data from 87 plots and five European countries, the results demonstrated reasonable local accuracy and plausible large-scale productivity responses.
Thomas Wutzler, Christian Reimers, Bernhard Ahrens, and Marion Schrumpf
Geosci. Model Dev., 17, 2705–2725, https://doi.org/10.5194/gmd-17-2705-2024, https://doi.org/10.5194/gmd-17-2705-2024, 2024
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Soil microbes provide a strong link for elemental fluxes in the earth system. The SESAM model applies an optimality assumption to model those linkages and their adaptation. We found that a previous heuristic description was a special case of a newly developed more rigorous description. The finding of new behaviour at low microbial biomass led us to formulate the constrained enzyme hypothesis. We now can better describe how microbially mediated linkages of elemental fluxes adapt across decades.
Salvatore R. Curasi, Joe R. Melton, Elyn R. Humphreys, Txomin Hermosilla, and Michael A. Wulder
Geosci. Model Dev., 17, 2683–2704, https://doi.org/10.5194/gmd-17-2683-2024, https://doi.org/10.5194/gmd-17-2683-2024, 2024
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Canadian forests are responding to fire, harvest, and climate change. Models need to quantify these processes and their carbon and energy cycling impacts. We develop a scheme that, based on satellite records, represents fire, harvest, and the sparsely vegetated areas that these processes generate. We evaluate model performance and demonstrate the impacts of disturbance on carbon and energy cycling. This work has implications for land surface modeling and assessing Canada’s terrestrial C cycle.
Yannek Käber, Florian Hartig, and Harald Bugmann
Geosci. Model Dev., 17, 2727–2753, https://doi.org/10.5194/gmd-17-2727-2024, https://doi.org/10.5194/gmd-17-2727-2024, 2024
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Many forest models include detailed mechanisms of forest growth and mortality, but regeneration is often simplified. Testing and improving forest regeneration models is challenging. We address this issue by exploring how forest inventories from unmanaged European forests can be used to improve such models. We find that competition for light among trees is captured by the model, unknown model components can be informed by forest inventory data, and climatic effects are challenging to capture.
Jalisha T. Kallingal, Johan Lindström, Paul A. Miller, Janne Rinne, Maarit Raivonen, and Marko Scholze
Geosci. Model Dev., 17, 2299–2324, https://doi.org/10.5194/gmd-17-2299-2024, https://doi.org/10.5194/gmd-17-2299-2024, 2024
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By unlocking the mysteries of CH4 emissions from wetlands, our work improved the accuracy of the LPJ-GUESS vegetation model using Bayesian statistics. Via assimilation of long-term real data from a wetland, we significantly enhanced CH4 emission predictions. This advancement helps us better understand wetland contributions to atmospheric CH4, which are crucial for addressing climate change. Our method offers a promising tool for refining global climate models and guiding conservation efforts
Thi Lan Anh Dinh, Daniel Goll, Philippe Ciais, and Ronny Lauerwald
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-42, https://doi.org/10.5194/gmd-2024-42, 2024
Revised manuscript accepted for GMD
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The study assesses the performance of the dynamic global vegetation model (DGVM), ORCHIDEE, in capturing the impact of land-use change on carbon stocks across Europe. Comparisons with observations reveal that the model accurately represents carbon fluxes and stocks. Despite the underestimations in certain land-use conversions, the model describes general trends in soil carbon response to land-use change, aligning with the site observations.
Guohua Liu, Mirco Migliavacca, Christian Reimers, Basil Kraft, Markus Reichstein, Andrew Richardson, Lisa Wingate, Nicolas Delpierre, Hui Yang, and Alexander Winkler
EGUsphere, https://doi.org/10.5194/egusphere-2024-464, https://doi.org/10.5194/egusphere-2024-464, 2024
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Our study employs Long Short-Term Memory (LSTM) networks to model canopy greenness and phenology, integrating meteorological memory effects. LSTM model outperforms traditional methods, enhancing accuracy in predicting greenness dynamics and phenological transitions across plant functional types. Highlighting the importance of multi-variate meteorological memory effects, our research pioneers unlocking the secrets of vegetation phenology responses to climate change with deep learning techniques.
Stephen Björn Wirth, Johanna Braun, Jens Heinke, Sebastian Ostberg, Susanne Rolinski, Sibyll Schaphoff, Fabian Stenzel, Werner von Bloh, and Christoph Müller
EGUsphere, https://doi.org/10.5194/egusphere-2023-2946, https://doi.org/10.5194/egusphere-2023-2946, 2024
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We present a new approach to model biological nitrogen fixation (BNF) in the Lund Potsdam Jena managed Land dynamic global vegetation model. While in the original approach BNF depended on actual evapotranspiration, the new approach considers soil water content and temperature, the nitrogen (N) deficit and carbon (C) costs. The new approach improved global sums and spatial patterns of BNF compared to the scientific literature and the models’ ability to project future C and N cycle dynamics.
Benjamin Post, Esteban Acevedo-Trejos, Andrew D. Barton, and Agostino Merico
Geosci. Model Dev., 17, 1175–1195, https://doi.org/10.5194/gmd-17-1175-2024, https://doi.org/10.5194/gmd-17-1175-2024, 2024
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Creating computational models of how phytoplankton grows in the ocean is a technical challenge. We developed a new tool set (Xarray-simlab-ODE) for building such models using the programming language Python. We demonstrate the tool set in a library of plankton models (Phydra). Our goal was to allow scientists to develop models quickly, while also allowing the model structures to be changed easily. This allows us to test many different structures of our models to find the most appropriate one.
Taeken Wijmer, Ahmad Al Bitar, Ludovic Arnaud, Remy Fieuzal, and Eric Ceschia
Geosci. Model Dev., 17, 997–1021, https://doi.org/10.5194/gmd-17-997-2024, https://doi.org/10.5194/gmd-17-997-2024, 2024
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Quantification of carbon fluxes of crops is an essential building block for the construction of a monitoring, reporting, and verification approach. We developed an end-to-end platform (AgriCarbon-EO) that assimilates, through a Bayesian approach, high-resolution (10 m) optical remote sensing data into radiative transfer and crop modelling at regional scale (100 x 100 km). Large-scale estimates of carbon flux are validated against in situ flux towers and yield maps and analysed at regional scale.
Moritz Laub, Sergey Blagodatsky, Marijn Van de Broek, Samuel Schlichenmaier, Benjapon Kunlanit, Johan Six, Patma Vityakon, and Georg Cadisch
Geosci. Model Dev., 17, 931–956, https://doi.org/10.5194/gmd-17-931-2024, https://doi.org/10.5194/gmd-17-931-2024, 2024
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To manage soil organic matter (SOM) sustainably, we need a better understanding of the role that soil microbes play in aggregate protection. Here, we propose the SAMM model, which connects soil aggregate formation to microbial growth. We tested it against data from a tropical long-term experiment and show that SAMM effectively represents the microbial growth, SOM, and aggregate dynamics and that it can be used to explore the importance of aggregate formation in SOM stabilization.
Jianhong Lin, Daniel Berveiller, Christophe François, Heikki Hänninen, Alexandre Morfin, Gaëlle Vincent, Rui Zhang, Cyrille Rathgeber, and Nicolas Delpierre
Geosci. Model Dev., 17, 865–879, https://doi.org/10.5194/gmd-17-865-2024, https://doi.org/10.5194/gmd-17-865-2024, 2024
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Currently, the high variability of budburst between individual trees is overlooked. The consequences of this neglect when projecting the dynamics and functioning of tree communities are unknown. Here we develop the first process-oriented model to describe the difference in budburst dates between individual trees in plant populations. Beyond budburst, the model framework provides a basis for studying the dynamics of phenological traits under climate change, from the individual to the community.
Skyler Kern, Mary E. McGuinn, Katherine M. Smith, Nadia Pinardi, Kyle E. Niemeyer, Nicole S. Lovenduski, and Peter E. Hamlington
Geosci. Model Dev., 17, 621–649, https://doi.org/10.5194/gmd-17-621-2024, https://doi.org/10.5194/gmd-17-621-2024, 2024
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Computational models are used to simulate the behavior of marine ecosystems. The models often have unknown parameters that need to be calibrated to accurately represent observational data. Here, we propose a novel approach to simultaneously determine a large set of parameters for a one-dimensional model of a marine ecosystem in the surface ocean at two contrasting sites. By utilizing global and local optimization techniques, we estimate many parameters in a computationally efficient manner.
Shuaitao Wang, Vincent Thieu, Gilles Billen, Josette Garnier, Marie Silvestre, Audrey Marescaux, Xingcheng Yan, and Nicolas Flipo
Geosci. Model Dev., 17, 449–476, https://doi.org/10.5194/gmd-17-449-2024, https://doi.org/10.5194/gmd-17-449-2024, 2024
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This paper presents unified RIVE v1.0, a unified version of the freshwater biogeochemistry model RIVE. It harmonizes different RIVE implementations, providing the referenced formalisms for microorganism activities to describe full biogeochemical cycles in the water column (e.g., carbon, nutrients, oxygen). Implemented as open-source projects in Python 3 (pyRIVE 1.0) and ANSI C (C-RIVE 0.32), unified RIVE v1.0 promotes and enhances collaboration among research teams and public services.
Sam S. Rabin, William J. Sacks, Danica L. Lombardozzi, Lili Xia, and Alan Robock
Geosci. Model Dev., 16, 7253–7273, https://doi.org/10.5194/gmd-16-7253-2023, https://doi.org/10.5194/gmd-16-7253-2023, 2023
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Climate models can help us simulate how the agricultural system will be affected by and respond to environmental change, but to be trustworthy they must realistically reproduce historical patterns. When farmers plant their crops and what varieties they choose will be important aspects of future adaptation. Here, we improve the crop component of a global model to better simulate observed growing seasons and examine the impacts on simulated crop yields and irrigation demand.
Weihang Liu, Tao Ye, Christoph Müller, Jonas Jägermeyr, James A. Franke, Haynes Stephens, and Shuo Chen
Geosci. Model Dev., 16, 7203–7221, https://doi.org/10.5194/gmd-16-7203-2023, https://doi.org/10.5194/gmd-16-7203-2023, 2023
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We develop a machine-learning-based crop model emulator with the inputs and outputs of multiple global gridded crop model ensemble simulations to capture the year-to-year variation of crop yield under future climate change. The emulator can reproduce the year-to-year variation of simulated yield given by the crop models under CO2, temperature, water, and nitrogen perturbations. Developing this emulator can provide a tool to project future climate change impact in a simple way.
Jurjen Rooze, Heewon Jung, and Hagen Radtke
Geosci. Model Dev., 16, 7107–7121, https://doi.org/10.5194/gmd-16-7107-2023, https://doi.org/10.5194/gmd-16-7107-2023, 2023
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Chemical particles in nature have properties such as age or reactivity. Distributions can describe the properties of chemical concentrations. In nature, they are affected by mixing processes, such as chemical diffusion, burrowing animals, and bottom trawling. We derive equations for simulating the effect of mixing on central moments that describe the distributions. We then demonstrate applications in which these equations are used to model continua in disturbed natural environments.
Esteban Acevedo-Trejos, Jean Braun, Katherine Kravitz, N. Alexia Raharinirina, and Benoît Bovy
Geosci. Model Dev., 16, 6921–6941, https://doi.org/10.5194/gmd-16-6921-2023, https://doi.org/10.5194/gmd-16-6921-2023, 2023
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The interplay of tectonics and climate influences the evolution of life and the patterns of biodiversity we observe on earth's surface. Here we present an adaptive speciation component coupled with a landscape evolution model that captures the essential earth-surface, ecological, and evolutionary processes that lead to the diversification of taxa. We can illustrate with our tool how life and landforms co-evolve to produce distinct biodiversity patterns on geological timescales.
Veli Çağlar Yumruktepe, Erik Askov Mousing, Jerry Tjiputra, and Annette Samuelsen
Geosci. Model Dev., 16, 6875–6897, https://doi.org/10.5194/gmd-16-6875-2023, https://doi.org/10.5194/gmd-16-6875-2023, 2023
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We present an along BGC-Argo track 1D modelling framework. The model physics is constrained by the BGC-Argo temperature and salinity profiles to reduce the uncertainties related to mixed layer dynamics, allowing the evaluation of the biogeochemical formulation and parameterization. We objectively analyse the model with BGC-Argo and satellite data and improve the model biogeochemical dynamics. We present the framework, example cases and routines for model improvement and implementations.
Tanya J. R. Lippmann, Ype van der Velde, Monique M. P. D. Heijmans, Han Dolman, Dimmie M. D. Hendriks, and Ko van Huissteden
Geosci. Model Dev., 16, 6773–6804, https://doi.org/10.5194/gmd-16-6773-2023, https://doi.org/10.5194/gmd-16-6773-2023, 2023
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Vegetation is a critical component of carbon storage in peatlands but an often-overlooked concept in many peatland models. We developed a new model capable of simulating the response of vegetation to changing environments and management regimes. We evaluated the model against observed chamber data collected at two peatland sites. We found that daily air temperature, water level, harvest frequency and height, and vegetation composition drive methane and carbon dioxide emissions.
Chonggang Xu, Bradley Christoffersen, Zachary Robbins, Ryan Knox, Rosie A. Fisher, Rutuja Chitra-Tarak, Martijn Slot, Kurt Solander, Lara Kueppers, Charles Koven, and Nate McDowell
Geosci. Model Dev., 16, 6267–6283, https://doi.org/10.5194/gmd-16-6267-2023, https://doi.org/10.5194/gmd-16-6267-2023, 2023
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We introduce a plant hydrodynamic model for the U.S. Department of Energy (DOE)-sponsored model, the Functionally Assembled Terrestrial Ecosystem Simulator (FATES). To better understand this new model system and its functionality in tropical forest ecosystems, we conducted a global parameter sensitivity analysis at Barro Colorado Island, Panama. We identified the key parameters that affect the simulated plant hydrodynamics to guide both modeling and field campaign studies.
Jianghui Du
Geosci. Model Dev., 16, 5865–5894, https://doi.org/10.5194/gmd-16-5865-2023, https://doi.org/10.5194/gmd-16-5865-2023, 2023
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Trace elements and isotopes (TEIs) are important tools to study the changes in the ocean environment both today and in the past. However, the behaviors of TEIs in marine sediments are poorly known, limiting our ability to use them in oceanography. Here we present a modeling framework that can be used to generate and run models of the sedimentary cycling of TEIs assisted with advanced numerical tools in the Julia language, lowering the coding barrier for the general user to study marine TEIs.
Siyu Zhu, Peipei Wu, Siyi Zhang, Oliver Jahn, Shu Li, and Yanxu Zhang
Geosci. Model Dev., 16, 5915–5929, https://doi.org/10.5194/gmd-16-5915-2023, https://doi.org/10.5194/gmd-16-5915-2023, 2023
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In this study, we estimate the global biogeochemical cycling of Hg in a state-of-the-art physical-ecosystem ocean model (high-resolution-MITgcm/Hg), providing a more accurate portrayal of surface Hg concentrations in estuarine and coastal areas, strong western boundary flow and upwelling areas, and concentration diffusion as vortex shapes. The high-resolution model can help us better predict the transport and fate of Hg in the ocean and its impact on the global Hg cycle.
Maria Val Martin, Elena Blanc-Betes, Ka Ming Fung, Euripides P. Kantzas, Ilsa B. Kantola, Isabella Chiaravalloti, Lyla L. Taylor, Louisa K. Emmons, William R. Wieder, Noah J. Planavsky, Michael D. Masters, Evan H. DeLucia, Amos P. K. Tai, and David J. Beerling
Geosci. Model Dev., 16, 5783–5801, https://doi.org/10.5194/gmd-16-5783-2023, https://doi.org/10.5194/gmd-16-5783-2023, 2023
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Enhanced rock weathering (ERW) is a CO2 removal strategy that involves applying crushed rocks (e.g., basalt) to agricultural soils. However, unintended processes within the N cycle due to soil pH changes may affect the climate benefits of C sequestration. ERW could drive changes in soil emissions of non-CO2 GHGs (N2O) and trace gases (NO and NH3) that may affect air quality. We present a new improved N cycling scheme for the land model (CLM5) to evaluate ERW effects on soil gas N emissions.
Özgür Gürses, Laurent Oziel, Onur Karakuş, Dmitry Sidorenko, Christoph Völker, Ying Ye, Moritz Zeising, Martin Butzin, and Judith Hauck
Geosci. Model Dev., 16, 4883–4936, https://doi.org/10.5194/gmd-16-4883-2023, https://doi.org/10.5194/gmd-16-4883-2023, 2023
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This paper assesses the biogeochemical model REcoM3 coupled to the ocean–sea ice model FESOM2.1. The model can be used to simulate the carbon uptake or release of the ocean on timescales of several hundred years. A detailed analysis of the nutrients, ocean productivity, and ecosystem is followed by the carbon cycle. The main conclusion is that the model performs well when simulating the observed mean biogeochemical state and variability and is comparable to other ocean–biogeochemical models.
Hocheol Seo and Yeonjoo Kim
Geosci. Model Dev., 16, 4699–4713, https://doi.org/10.5194/gmd-16-4699-2023, https://doi.org/10.5194/gmd-16-4699-2023, 2023
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Wildfire is a crucial factor in carbon and water fluxes on the Earth system. About 2.1 Pg of carbon is released into the atmosphere by wildfires annually. Because the fire processes are still limitedly represented in land surface models, we forced the daily GFED4 burned area into the land surface model over Alaska and Siberia. The results with the GFED4 burned area significantly improved the simulated carbon emissions and net ecosystem exchange compared to the default simulation.
Hideki Ninomiya, Tomomichi Kato, Lea Végh, and Lan Wu
Geosci. Model Dev., 16, 4155–4170, https://doi.org/10.5194/gmd-16-4155-2023, https://doi.org/10.5194/gmd-16-4155-2023, 2023
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Non-structural carbohydrates (NSCs) play a crucial role in plants to counteract the effects of climate change. We added a new NSC module into the SEIB-DGVM, an individual-based ecosystem model. The simulated NSC levels and their seasonal patterns show a strong agreement with observed NSC data at both point and global scales. The model can be used to simulate the biotic effects resulting from insufficient NSCs, which are otherwise difficult to measure in terrestrial ecosystems globally.
Guillaume Marie, Jina Jeong, Hervé Jactel, Gunnar Petter, Maxime Cailleret, Matthew McGrath, Vladislav Bastrikov, Josefine Ghattas, Bertrand Guenet, Anne-Sofie Lansø, Kim Naudts, Aude Valade, Chao Yue, and Sebastiaan Luyssaert
EGUsphere, https://doi.org/10.5194/egusphere-2023-1216, https://doi.org/10.5194/egusphere-2023-1216, 2023
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This research looks at how climate change influences forests, particularly how altered wind and insect activities could make forests emit, instead of absorb, carbon. We've updated a land surface model called ORCHIDEE to better examine the effect of bark beetles on forest health. Our findings suggest that sudden events, like insect outbreaks, can dramatically affect carbon storage, offering crucial insights for tackling climate change.
Miquel De Cáceres, Roberto Molowny-Horas, Antoine Cabon, Jordi Martínez-Vilalta, Maurizio Mencuccini, Raúl García-Valdés, Daniel Nadal-Sala, Santiago Sabaté, Nicolas Martin-StPaul, Xavier Morin, Francesco D'Adamo, Enric Batllori, and Aitor Améztegui
Geosci. Model Dev., 16, 3165–3201, https://doi.org/10.5194/gmd-16-3165-2023, https://doi.org/10.5194/gmd-16-3165-2023, 2023
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Regional-level applications of dynamic vegetation models are challenging because they need to accommodate the variation in plant functional diversity. This can be done by estimating parameters from available plant trait databases while adopting alternative solutions for missing data. Here we present the design, parameterization and evaluation of MEDFATE (version 2.9.3), a novel model of forest dynamics for its application over a region in the western Mediterranean Basin.
Jens Heinke, Susanne Rolinski, and Christoph Müller
Geosci. Model Dev., 16, 2455–2475, https://doi.org/10.5194/gmd-16-2455-2023, https://doi.org/10.5194/gmd-16-2455-2023, 2023
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We develop a livestock module for the global vegetation model LPJmL5.0 to simulate the impact of grazing dairy cattle on carbon and nitrogen cycles in grasslands. A novelty of the approach is that it accounts for the effect of feed quality on feed uptake and feed utilization by animals. The portioning of dietary nitrogen into milk, feces, and urine shows very good agreement with estimates obtained from animal trials.
Yimian Ma, Xu Yue, Stephen Sitch, Nadine Unger, Johan Uddling, Lina M. Mercado, Cheng Gong, Zhaozhong Feng, Huiyi Yang, Hao Zhou, Chenguang Tian, Yang Cao, Yadong Lei, Alexander W. Cheesman, Yansen Xu, and Maria Carolina Duran Rojas
Geosci. Model Dev., 16, 2261–2276, https://doi.org/10.5194/gmd-16-2261-2023, https://doi.org/10.5194/gmd-16-2261-2023, 2023
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Plants have been found to respond differently to O3, but the variations in the sensitivities have rarely been explained nor fully implemented in large-scale assessment. This study proposes a new O3 damage scheme with leaf mass per area to unify varied sensitivities for all plant species. Our assessment reveals an O3-induced reduction of 4.8 % in global GPP, with the highest reduction of >10 % for cropland, suggesting an emerging risk of crop yield loss under the threat of O3 pollution.
Winslow D. Hansen, Adrianna Foster, Benjamin Gaglioti, Rupert Seidl, and Werner Rammer
Geosci. Model Dev., 16, 2011–2036, https://doi.org/10.5194/gmd-16-2011-2023, https://doi.org/10.5194/gmd-16-2011-2023, 2023
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Permafrost and the thick soil-surface organic layers that insulate permafrost are important controls of boreal forest dynamics and carbon cycling. However, both are rarely included in process-based vegetation models used to simulate future ecosystem trajectories. To address this challenge, we developed a computationally efficient permafrost and soil organic layer module that operates at fine spatial (1 ha) and temporal (daily) resolutions.
Heewon Jung, Hyun-Seob Song, and Christof Meile
Geosci. Model Dev., 16, 1683–1696, https://doi.org/10.5194/gmd-16-1683-2023, https://doi.org/10.5194/gmd-16-1683-2023, 2023
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Microbial activity responsible for many chemical transformations depends on environmental conditions. These can vary locally, e.g., between poorly connected pores in porous media. We present a modeling framework that resolves such small spatial scales explicitly, accounts for feedback between transport and biogeochemical conditions, and can integrate state-of-the-art representations of microbes in a computationally efficient way, making it broadly applicable in science and engineering use cases.
Arthur Guignabert, Quentin Ponette, Frédéric André, Christian Messier, Philippe Nolet, and Mathieu Jonard
Geosci. Model Dev., 16, 1661–1682, https://doi.org/10.5194/gmd-16-1661-2023, https://doi.org/10.5194/gmd-16-1661-2023, 2023
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Spatially explicit and process-based models are useful to test innovative forestry practices under changing and uncertain conditions. However, their larger use is often limited by the restricted range of species and stand structures they can reliably account for. We therefore calibrated and evaluated such a model, HETEROFOR, for 23 species across southern Québec. Our results showed that the model is robust and can predict accurately both individual tree growth and stand dynamics in this region.
Maureen Beaudor, Nicolas Vuichard, Juliette Lathière, Nikolaos Evangeliou, Martin Van Damme, Lieven Clarisse, and Didier Hauglustaine
Geosci. Model Dev., 16, 1053–1081, https://doi.org/10.5194/gmd-16-1053-2023, https://doi.org/10.5194/gmd-16-1053-2023, 2023
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Ammonia mainly comes from the agricultural sector, and its volatilization relies on environmental variables. Our approach aims at benefiting from an Earth system model framework to estimate it. By doing so, we represent a consistent spatial distribution of the emissions' response to environmental changes.
We greatly improved the seasonal cycle of emissions compared with previous work. In addition, our model includes natural soil emissions (that are rarely represented in modeling approaches).
Cited articles
Berg, B. and McClaugherty, C. (Eds.): Plant Litter: decomposition, humus formation, carbon Sequestration, 2nd Edn., Springer-Verlag, Berlin-Heidelberg, Germany, 2008.
Campolongo, F., Kleijnen, J., and Andres, T.: Screening methods, in: Sensitivity analysis, edited by: Saltelli, A., Chan, K., and Scott, M., Wiley and Sons, Chichester, UK, 65–80, 2000.
Cao, Y., Zhao, Z., Qu, M., Cheng, X. Y., and Wang D. H.: Effects of Robinia pseudoacacia roots on deep soil moisture status, Chin. J. Appl. Ecol., 17, 765–768, 2006.
Coldwell, B. B. and DeLong, W. A.: Studies of the composition of deciduous forest tree leaves before and after partial decomposition, Sci. Agric., 30, 456–466, 1950.
Coleman, K. and Jenkinson, D. S.: RothC-26.3 a model for the turnover of carbon in soil, available at: http://www.rothamsted.bbsrc.ac.uk/aen/carbon/download.htm (last access: 10 June 2012), 2005.
Coleman, K., Jenkinson, D. S., Crocker, G. J., Grace, P. R., Klír, J., Körschens, M., Poulton, P. R., and Richter D. D.: Simulating trends in soil organic carbon in long-term experiments using RothC-26.3, Geoderma, 81, 29–44, 1997.
Cui, L. J., Liang, Z. S., Han, R. L., and Yang, J. W.: Biomass soil and root system distribution characteristics of Seabuckthorn × Poplar mixed forest, Sci. Silv. Sin., 39, 1–7, 2003.
Davis, B. A. S., Brewer, S., Stevenson, A. C., Guiot, J., and Data Contributors: The temperature of Europe during the Holocene reconstructed from pollen data, Quaternary Sci. Rev., 22, 1701–1716, 2003.
De Wit, H. A., Palosuo, T., Hylen, G., and Liski, J.: A carbon budget of forest biomass and soils in southeast Norway, Forest Ecol. Manag., 225, 15–26, 2006.
Doherty, J. (Ed.): PEST: model independent parameter estimation user manual, Fifth Edition, Watermark Numerical Computing, Brisbane, Australia, 2004.
Falkowski, P., Scholes, R. J., Boyle, E., Canadell, J., Canfield, D., Elser, J., Gruber, N., Hibbard, K., Högberg, P., Linder, S., Mackenzie, F. T., Moore III, B., Pedersen, T., Rosenthal, Y., Seitzinger, S., Smetacek, V., and Steffen, W.: The global carbon cycle: a test of our knowledge of earth as a system, Science, 290, 291–296, 2000.
Finke, P. A.: Modeling the genesis of Luvisols as a function of topographic position in loess parent material, Quaternary Int., 265, 3–17, 2012.
Finke, P. A. and Hutson, J.: Modelling soil genesis in calcareous loess, Geoderma, 145, 462–479, 2008.
Gobat, J. M., Aragno, M., and Matthey, W. (Eds): The Living Soil: Fundamentals of Soil Science and Soil Biology, Science Publishers Inc., NH, USA, 2004.
Gong, Z. T., Chen, Z. C., and Zhang, G. L.: World reference base for soil resources (WRB): Establishment and development, Soils, 35, 271–278, 2003.
Gower, J. C.: A general coefficient of similarity and some of its properties, Biometrics, 27, 623–637, 1971.
Grievank, A. and Walter, A. (Eds.): Evaluating derivatives, principles and techniques of algorithmic differentiation, SIAM, Philadelphia, USA, 2008.
Guo, Z. T., Ruddiman, W. F., Hao, Q. Z., Wu, H. B., Qiao, Y. S., Zhu, R. X., Peng, S. Z., Wei, J. J., Yuan, B. Y., and Liu, T. S.: Onset of Asian desertification by 22 Myr ago inferred from loess deposits in China, Nature, 416, 159–163, 2002.
Hu, X. N., Zhao, Z., Yuan, Z. F., Li, J., Guo, M. C., and Wang, D. H.: A model for fine root growth of Robinia pseudoacacia in the Loess Plateau, Sci. Silv. Sin., 46, 126–132, 2010.
IUSS Working Group WRB: World Reference Base for Soil Resources 2006, in: World Soil Resources Report No. 103, 2nd Edn., FAO, Rome, Italy, 2006.
Jenkinson, D. S.: The turnover of organic carbon and nitrogen in soil, Philos. T. R. Soc. Lond., 329, 361–368, 1990.
Jenkinson, D. S. and Coleman, K.: Calculating the annual input of organic matter to soil from measurements of total organic carbon and radiocarbon, Eur. J. Soil Sci., 45, 167–174, 1994.
Jenny, H.: Derivation of state factor equations of soils and ecosystems, Soil Sci. Soc. Am. Pro., 25, 385–388, 1961.
Jensen, L. S., Mueller, T., Nielsen, N. E., Hansen, S., Crocker, G. J., Grace, P. R., Klir, J., Korschens, M., and Poulton, P. R.: Simulating trends in soil organic carbon in long-term experiments using the soil-plant-atmosphere model DAISY, Geoderma, 81, 5–28, 1997.
Kelly, R. H., Parton W. J., Crocker, G. J., Graced, P. R., Klir, J., Korschens, M., Poulton, P. R., and Richter, D. D.: Simulating trends in soil organic carbon in long-term experiments using the century model, Geoderma, 81, 75–90, 1997.
Kirkby, M. J.: Soil development models as a component of slope models, Earth Surf. Proc. Landf., 2, 203–230, 1977.
Kononova, M. M.: Humus of virgin and cultivated soils, in: Soil components. I. Organic Components, edited by: Gieseling, J. E., Springer, Berlin, Germany, 475–526, 1975.
Kukla, G. J.: Correlation of Chinese, European and American loess series with deep-sea sediments, in: Aspects of loess research, edited by: Liu, T. S., China Ocean Press, Beijing, China, 27–38, 1987.
Lal, R.: Soil Carbon sequestration impacts on global climate change and food security, Science, 304, 1623–1627, 2004.
Lambers, H., Chapin, F. S., and Pons, T. L. (Eds.): Plant Physiological Ecology, Springer-Verlag New York Inc, New York, USA, 1998.
Langohr, R. and Sanders, J.: The Belgian loess belt in the last 20,000 years: evolution of soils and relief in the Zoniën forest, in: Soils and Quaternary Landscape Evolution, edited by: Boardman, J., Wiley, Chichester, UK, 359–371, 1985.
Li, C. S., Frolking, S., Crocker, G. J., Grace, P. R., Klir, J., Korchens, M., and Poulton, P. R.: Simulating trends in soil organic carbon in long-term experiments using the DNDC model, Geoderma, 81, 45–60, 1997.
Liu, T. S. (Ed.): Loess and the Environment, Science Press, Beijing, China, 1985.
Liu, Y.: The relationship between community biomass and soil moisture, soil nutrient in ZIwuling typical forests, Master Degree thesis, Northwest Agriculture and Forest University, Yangling, China, 2007.
Mermut, A. R., Amundson, R., and Cerling, T. E.: The use of stable isotopes in studying carbonate dynamics in soils, in: Global Climate Change and Pedogenic Carbonates, edited by: Lal, R., Kimble, J. M., Eswaran, H., and Stewart, B. A. (Eds), CRC Press, Boca Raton, USA, 65–85, 2000.
Minasny, B. and McBratney, A. B.: A rudimentary mechanistic model for soil production and landscape development, Geoderma, 90, 3–21, 1999.
Minasny, B. and McBratney, A. B.: A rudimentary mechanistic model for soil production and landscape development II. A two-dimensional model incorporating chemical weathering, Geoderma, 103, 161–179, 2001.
Minasny, B., McBratney, A. B., and Salvador-Blanes, S.: Quantitative models for pedogenesis: a review, Geoderma, 144, 140–157, 2008.
Morris, M. D.: Factorial sampling plans for preliminary computational experiments, Technometrics, 33, 161–174, 1991.
Oakley, J. and O'Hagan, A.: Probabilistic sensitivity analysis of complex models: a Bayesian approach, J. Roy. Stat. Soc. B., 66, 751–769, 2004.
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, 1987.
Paul, K. I. and Polglase, P. J.: Calibration of the RothC model to turnover of soil carbon under eucalypts and pines, Aust. J. Soil Res., 42, 883–895, 2004.
Paul, K. I., Polglase, P. J., and Richards, G. P.: Sensitivity analysis of predicted change in soil carbon following afforestation, Ecol. Model., 164, 137–152, 2003.
Post, W. F., Peng, T. H., Emanuel, W. R., King, A. W., Dale, V. H., and DeAngelis, D. L.: The global carbon cycle, Am. Sci., 78, 310–326, 1990.
Quideau, S. A., Chadwick, O. A., Benesi, A., Graham, R. C., and Anderson, M. A.: A direct link between forest vegetation type and soil organic matter composition, Geoderma, 104, 41–60, 2001.
Raich, J. W. and Tufekcioglu, A.: Vegetation and soil respiration: correlations and controls, Biogeochemistry, 48, 71–90, 2000.
Saltelli, A., Chan, K., and Scott, M. (Eds.): Sensitivity analysis, Wiley and Sons, Chichester, UK, 2000.
Saltelli, A., Ratto, M., Tarantola, S., and Campolongo, F.: Sensitivity analysis for chemical models, Chem. Rev., 105, 2811–2827, 2005.
Salvador-Blanes, S., Minasny, B., and McBratney, A. B.: Modelling long-term in situ soil profile evolution: application to the genesis of soil profiles containing stone layers, Eur. J. Soil Sci., 58, 1535–1548, 2007.
Sauer, D., Finke, P. A., Sørensen, R., Sperstad, R., Schülli-Maurer, I., Høeg, H., and Stahr, K.: Testing a soil development model against southern Norway soil chronosequences, Quaternary. Int., 265, 18–31, 2012.
Schimel, D. S., Braswell, B. H., Holland, E. A., McKeown, R., Ojima, D. S., Painter, T. H., Parton, W. J., and Townsend, A. R.: Climatic, edaphic, and biotic controls over storage and turnover of carbon in soils, Global Biogeochem. Cy., 8, 279–293, 1994.
Schlesinger, W. H. and Andrews, J. A.: Soil respiration and the global carbon cycle, Biogeochemistry, 48, 7–20, 2000.
Shirato, Y., Hakamata, T., and Taniyama, I.: Modified Rothamsted carbon model for Andosols and its validation: changing humus decomposition rate constant with pyrophosphate-extractable Al, Soil Sci. Plant Nutr., 50, 149–158, 2004.
Skjemstad, J. O., Spouncer, L. R., Cowie, B., and Swift, R. S.: Calibration of the Rothamsted organic carbon turnover model (RothC ver.26.3), using measurable soil organic carbon pools, Aust. J. Soil Res., 42, 79–88, 2004.
Swift, R. S.: Sequestration of carbon by soil, Soil Sci., 166, 858–871, https://doi.org/10.1097/00010694-200111000-00010, 2001.
Todorovic, G. R., Stemmer, M., Tatzber, M., Katzlberger, C., Spiegel, H., Zehetner, F., and Gerzabek, M. H.: Soil-carbon turnover under different crop management: evaluation of RothC-model predictions under Pannonian climate conditions, J. Plant Nutr. Soil Sci., 173, 662–670, 2010.
Van Ranst, E.: Vorming and eigenschappen van lemige bosgronden in midden en hoog België, Ph.D. thesis, Ghent University, Ghent, Belgium, 1981.
Verbruggen, C., Denys, L., and Kiden, P.: Belgium, in: Palaeoecological Events During the Last 15000 Years. Regional Syntheses of Palaeoecological Studies of Lakes and Mires in Europe, edited by: Berglund, B. E., Birks, H. J. B., Ralska-Jasiewiczowa, M., Wright, H. E., Wiley, Chichester, 1996.
Vrugt, J. A., Braak C. J. F., Diks, C. G. H., Robinson, B. A., Hyman, J. M., and Higdon, D.: Accelerating Markov Chain Monte Carlo simulation by differential evolution with self-adaptive randomized subspace sampling, Int. J. Nonlin. Sci. Num., 10, 273–290, 2009.
Zhang, D. Q., Hui, D. F., Luo, Y. Q., and Zhou, G. Y.: Rates of litter decomposition in terrestrial ecosystems: global pattern and controlling factors, J. Plant Ecol., 1, 85–93, 2008.
Zhang, J., Wang, Y. K., and Wu, Q. X.: Comparison of litterfall and its process between some forest types in Loess Plateau, J. Soil Water Conserv., 15, 91–94, 2001.
Zhang, X. B. and Shangguan, Z. P.: The bio-cycle patterns of nutrient elements and stand biomass in forest communities in Hilly Loess Regions, Acta Ecol. Sin., 25, 527–537, 2005.
