Articles | Volume 8, issue 10
https://doi.org/10.5194/gmd-8-3441-2015
© Author(s) 2015. 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-8-3441-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model description paper
| 
28 Oct 2015
Model description paper |
| 28 Oct 2015
SHIMMER (1.0): a novel mathematical model for microbial and biogeochemical dynamics in glacier forefield ecosystems
Bristol Glaciology Centre, School of Geographical Sciences, University of Bristol, Bristol, BS8 1SS, UK
BRIDGE, School of Geographical Sciences, University of Bristol, Bristol, BS8 1SS, UK
A. M. Anesio
Bristol Glaciology Centre, School of Geographical Sciences, University of Bristol, Bristol, BS8 1SS, UK
J. S. Singarayer
Department of Meteorology, University of Reading, Reading, RG6 6BB, UK
M. R. Heath
Department of Mathematics and Statistics, University of Strathclyde, Glasgow, G1 1XH, UK
BRIDGE, School of Geographical Sciences, University of Bristol, Bristol, BS8 1SS, UK
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EGUsphere, https://doi.org/10.5194/egusphere-2024-350, https://doi.org/10.5194/egusphere-2024-350, 2024
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Young Arctic sediments, uncovered by retreating glaciers, are in continuous development, shaped by how water infiltrates and is stored in the near subsurface. Harsh weather conditions at high latitudes make direct observation of these environments extremely difficult. To address this, we deployed two automated sensor installations in Aug 21 on a glacier forefield in Svalbard. These recorded continuously for one year revealing unprecedented images of the ground’s freeze-thaw transition.
James A. Bradley, Sandra Arndt, Marie Šabacká, Liane G. Benning, Gary L. Barker, Joshua J. Blacker, Marian L. Yallop, Katherine E. Wright, Christopher M. Bellas, Jonathan Telling, Martyn Tranter, and Alexandre M. Anesio
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Soil development following glacier retreat was characterized using a novel integrated field, laboratory and modelling approach in Svalbard. We found community shifts in bacteria, which were responsible for driving cycles in carbon and nutrients. Allochthonous inputs were also important in sustaining bacterial production. This study shows how an integrated model–data approach can improve understanding and obtain a more holistic picture of soil development in an increasingly ice-free future world.
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Young Arctic sediments, uncovered by retreating glaciers, are in continuous development, shaped by how water infiltrates and is stored in the near subsurface. Harsh weather conditions at high latitudes make direct observation of these environments extremely difficult. To address this, we deployed two automated sensor installations in Aug 21 on a glacier forefield in Svalbard. These recorded continuously for one year revealing unprecedented images of the ground’s freeze-thaw transition.
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Computer simulations of the geological past are an important tool to improve our understanding of climate change. We present results from two simulations using the latest version of the UK's climate model, the mid-Holocene (6000 years ago) and Last Interglacial (127 000 years ago). The simulations reproduce temperatures consistent with the pattern of incoming radiation. Model–data comparisons indicate that some regions (and some seasons) produce better matches to the data than others.
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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
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.
Dongyu Zheng, Andrew Merdith, Yves Goddéris, Yannick Donnadieu, Khushboo Gurung, and Benjamin J. W. Mills
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-230, https://doi.org/10.5194/gmd-2023-230, 2024
Revised manuscript accepted for GMD
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This study uses a deep learning method to enhance the time resolution of paleoclimate simulations to 1 million years. This improved resolution allows a climate-biogeochemical model for more accurate predictions of climate shifts. The method may be critical in developing new fully-continuous methods that are able to translate over a moving continental surface in deep time with high-resolution at a reasonable computational expense.
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.
Jorn Bruggeman, Karsten Bolding, Lars Nerger, Anna Teruzzi, Simone Spada, Jozef Skákala, and Stefano Ciavatta
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-238, https://doi.org/10.5194/gmd-2023-238, 2023
Revised manuscript accepted for GMD
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To understand and predict the ocean’s capacity for carbon sequestration, its ability to supply food, and its response to climate change, we need the best possible estimate of its physical and biogeochemical properties. This is obtained through “data assimilation”, which blends numerical models and observations. Here, we present EAT, a flexible and efficient testbed that allows any scientist to explore and further develop the state-of-the-art in data assimilation.
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.
Jacquelyn K. Shuman, Rosie A. Fisher, Charles D. Koven, Ryan G. Knox, Lara M. Kueppers, and Chonggang Xu
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-191, https://doi.org/10.5194/gmd-2023-191, 2023
Revised manuscript accepted for GMD
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We adapt a fire-behavior and effects module for use in a size-structured vegetation demographic model to test how climate, fire regime and fire-tolerance plant traits interact to determine the distribution of tropical forests and grasslands. Our model captures the connection between fire disturbance and plant fire-tolerance strategies in determining plant distribution and provides a useful tool for understanding the vulnerability of these areas under changing conditions across the tropics.
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.
Boris Ťupek, Aleksi Lehtonen, Alla Yurova, Rose Abramoff, Stefano Manzoni, Bertrand Guenet, Elisa Bruni, Samuli Launiainen, Mikko Peltoniemi, Shoji Hashimoto, Xianglin Tian, Juha Heikkinen, Kari Minkkinen, and Raisa Mäkipää
EGUsphere, https://doi.org/10.5194/egusphere-2023-1523, https://doi.org/10.5194/egusphere-2023-1523, 2023
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Improving representation of peatlands in Earth system models (ESMs) (e.g., in Yasso soil C model coupled with JSBACH model) is rare. We updated Yasso07 moisture dependency for applications on both the mineral soils and peatlands of boreal forest. Our moisture function improved the simulated peatland C stocks and CO2 dynamics. However, due to nature of the measurements used for Bayesian MCMC data assimilation, it contrasts with functions in other ESMs (see graphical abstract).
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.
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).
Rui Ying, Fanny M. Monteiro, Jamie D. Wilson, and Daniela N. Schmidt
Geosci. Model Dev., 16, 813–832, https://doi.org/10.5194/gmd-16-813-2023, https://doi.org/10.5194/gmd-16-813-2023, 2023
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Planktic foraminifera are marine-calcifying zooplankton; their shells are widely used to measure past temperature and productivity. We developed ForamEcoGEnIE 2.0 to simulate the four subgroups of this organism. We found that the relative abundance distribution agrees with marine sediment core-top data and that carbon export and biomass are close to sediment trap and plankton net observations respectively. This model provides the opportunity to study foraminiferal ecology in any geological era.
Onur Kerimoglu, Markus Pahlow, Prima Anugerahanti, and Sherwood Lan Smith
Geosci. Model Dev., 16, 95–108, https://doi.org/10.5194/gmd-16-95-2023, https://doi.org/10.5194/gmd-16-95-2023, 2023
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In classical models that track the changes in the elemental composition of phytoplankton, additional state variables are required for each element resolved. In this study, we show how the behavior of such an explicit model can be approximated using an
instantaneous acclimationapproach, in which the elemental composition of the phytoplankton is assumed to adjust to an optimal value instantaneously. Through rigorous tests, we evaluate the consistency of this scheme.
Yuan Zhang, Devaraju Narayanappa, Philippe Ciais, Wei Li, Daniel Goll, Nicolas Vuichard, Martin G. De Kauwe, Laurent Li, and Fabienne Maignan
Geosci. Model Dev., 15, 9111–9125, https://doi.org/10.5194/gmd-15-9111-2022, https://doi.org/10.5194/gmd-15-9111-2022, 2022
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There are a few studies to examine if current models correctly represented the complex processes of transpiration. Here, we use a coefficient Ω, which indicates if transpiration is mainly controlled by vegetation processes or by turbulence, to evaluate the ORCHIDEE model. We found a good performance of ORCHIDEE, but due to compensation of biases in different processes, we also identified how different factors control Ω and where the model is wrong. Our method is generic to evaluate other models.
Thomas Neumann, Hagen Radtke, Bronwyn Cahill, Martin Schmidt, and Gregor Rehder
Geosci. Model Dev., 15, 8473–8540, https://doi.org/10.5194/gmd-15-8473-2022, https://doi.org/10.5194/gmd-15-8473-2022, 2022
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Marine ecosystem models are usually constrained by the elements nitrogen and phosphorus and consider carbon in organic matter in a fixed ratio. Recent observations show a substantial deviation from the simulated carbon cycle variables. In this study, we present a marine ecosystem model for the Baltic Sea which allows for a flexible uptake ratio for carbon, nitrogen, and phosphorus. With this extension, the model reflects much more reasonable variables of the marine carbon cycle.
Arsène Druel, Simon Munier, Anthony Mucia, Clément Albergel, and Jean-Christophe Calvet
Geosci. Model Dev., 15, 8453–8471, https://doi.org/10.5194/gmd-15-8453-2022, https://doi.org/10.5194/gmd-15-8453-2022, 2022
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Crop phenology and irrigation is implemented into a land surface model able to work at a global scale. A case study is presented over Nebraska (USA). Simulations with and without the new scheme are compared to different satellite-based observations. The model is able to produce a realistic yearly irrigation water amount. The irrigation scheme improves the simulated leaf area index, gross primary productivity, evapotransipiration, and land surface temperature.
Thomas Wutzler, Lin Yu, Marion Schrumpf, and Sönke Zaehle
Geosci. Model Dev., 15, 8377–8393, https://doi.org/10.5194/gmd-15-8377-2022, https://doi.org/10.5194/gmd-15-8377-2022, 2022
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Soil microbes process soil organic matter and affect carbon storage and plant nutrition at the ecosystem scale. We hypothesized that decadal dynamics is constrained by the ratios of elements in litter inputs, microbes, and matter and that microbial community optimizes growth. This allowed the SESAM model to descibe decadal-term carbon sequestration in soils and other biogeochemical processes explicitly accounting for microbial processes but without its problematic fine-scale parameterization.
Ensheng Weng, Igor Aleinov, Ram Singh, Michael J. Puma, Sonali S. McDermid, Nancy Y. Kiang, Maxwell Kelley, Kevin Wilcox, Ray Dybzinski, Caroline E. Farrior, Stephen W. Pacala, and Benjamin I. Cook
Geosci. Model Dev., 15, 8153–8180, https://doi.org/10.5194/gmd-15-8153-2022, https://doi.org/10.5194/gmd-15-8153-2022, 2022
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We develop a demographic vegetation model to improve the representation of terrestrial vegetation dynamics and ecosystem biogeochemical cycles in the Goddard Institute for Space Studies ModelE. The individual-based competition for light and soil resources makes the modeling of eco-evolutionary optimality possible. This model will enable ModelE to simulate long-term biogeophysical and biogeochemical feedbacks between the climate system and land ecosystems at decadal to centurial temporal scales.
Yitong Yao, Emilie Joetzjer, Philippe Ciais, Nicolas Viovy, Fabio Cresto Aleina, Jerome Chave, Lawren Sack, Megan Bartlett, Patrick Meir, Rosie Fisher, and Sebastiaan Luyssaert
Geosci. Model Dev., 15, 7809–7833, https://doi.org/10.5194/gmd-15-7809-2022, https://doi.org/10.5194/gmd-15-7809-2022, 2022
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To facilitate more mechanistic modeling of drought effects on forest dynamics, our study implements a hydraulic module to simulate the vertical water flow, change in water storage and percentage loss of stem conductance (PLC). With the relationship between PLC and tree mortality, our model can successfully reproduce the large biomass drop observed under throughfall exclusion. Our hydraulic module provides promising avenues benefiting the prediction for mortality under future drought events.
Arthur Nicolaus Fendrich, Philippe Ciais, Emanuele Lugato, Marco Carozzi, Bertrand Guenet, Pasquale Borrelli, Victoria Naipal, Matthew McGrath, Philippe Martin, and Panos Panagos
Geosci. Model Dev., 15, 7835–7857, https://doi.org/10.5194/gmd-15-7835-2022, https://doi.org/10.5194/gmd-15-7835-2022, 2022
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Currently, spatially explicit models for soil carbon stock can simulate the impacts of several changes. However, they do not incorporate the erosion, lateral transport, and deposition (ETD) of soil material. The present work developed ETD formulation, illustrated model calibration and validation for Europe, and presented the results for a depositional site. We expect that our work advances ETD models' description and facilitates their reproduction and incorporation in land surface models.
Kazumi Ozaki, Devon B. Cole, Christopher T. Reinhard, and Eiichi Tajika
Geosci. Model Dev., 15, 7593–7639, https://doi.org/10.5194/gmd-15-7593-2022, https://doi.org/10.5194/gmd-15-7593-2022, 2022
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A new biogeochemical model (CANOPS-GRB v1.0) for assessing the redox stability and dynamics of the ocean–atmosphere system on geologic timescales has been developed. In this paper, we present a full description of the model and its performance. CANOPS-GRB is a useful tool for understanding the factors regulating atmospheric O2 level and has the potential to greatly refine our current understanding of Earth's oxygenation history.
Cited articles
Achuff, P. L. and Coen, G. M.: Subalpine Cryosolic Soils in Banff and Jasper National-Parks, Can. J. Soil Sci., 60, 579–581, 1980.
ACIA: Arctic Climate Impacts Assessment, Cambridge University Press, Cambridge, 2005.
Allison, S. D.: Cheaters, diffusion and nutrients constrain decomposition by microbial enzymes in spatially structured environments, Ecol. Lett., 8, 626–635, 2005.
Anderson, S. P., Drever, J. I., Frost, C. D., and Holden, P.:. Chemical weathering in the foreland of a retreating glacier, Geochim. Cosmochim. Ac., 64, 1173–1189, 2000.
Anderson, T. H. and Domsch, K. H.: Maintenance Carbon Requirements of Actively-Metabolizing Microbial-Populations under Insitu Conditions, Soil Biol. Biochem., 17, 197–203, 1985.
Anesio, A. M., Hodson, A. J., Fritz, A., Psenner, R., and Sattler, B.: High microbial activity on glaciers: importance to the global carbon cycle, Global Change Biol., 15, 955–960, 2009.
Arndt, S., Jorgensen, B. B., Larowe, D. E., Middelburg, J. J., Pancost, R. D., and Regnier, P.: Quantifying the degradation of organic matter in marine sediments: A review and synthesis, Earth-Sci. Rev., 123, 53–86, 2013.
Bernasconi, S. M., Bauder, A., Bourdon, B., Brunner, I., Bunemann, E., Christl, I., Derungs, N., Edwards, P., Farinotti, D., Frey, B., Frossard, E., Furrer, G., Gierga, M., Goransson, H., Gulland, K., Hagedorn, F., Hajdas, I., Hindshaw, R., Ivy-Ochs, S., Jansa, J., Jonas, T., Kiczka, M., Kretzschmar, R., Lemarchand, E., Luster, J., Magnusson, J., Mitchell, E. A. D., Venterink, H. O., Plotze, M., Reynolds, B., Smittenberg, R. H., Stahli, M., Tamburini, F., Tipper, E. T., Wacker, L., Welc, M., Wiederhold, J. G., Zeyer, J., Zimmermann, S., and Zumsteg, A.: Chemical and Biological Gradients along the Damma Glacier Soil Chronosequence, Switzerland, Vadose Zone J., 10, 867–883, 2011.
Berner, R. A., Lasaga, A. C., and Garrels, R. M.:. The Carbonate-Silicate Geochemical Cycle and Its Effect on Atmospheric Carbon-Dioxide over the Past 100 Million Years, Am. J. Sci., 283, 641–683, 1983.
Blagodatsky, S. A. and Richter, O.: Microbial growth in soil and nitrogen turnover: A theoretical model considering the activity state of microorganisms, Soil Biol. Biochem., 30, 1743–1755, 1998.
Blagodatsky, S. A., Yevdokimov, I. V., Larionova, A. A., and Richter, J.: Microbial growth in soil and nitrogen turnover: Model calibration with laboratory data, Soil Biol. Biochem., 30, 1757–1764, 1998.
Bottomley, P. and Myrold, D.: Biological N Inputs, in: Soil microbiology, ecology and biochemistry, edited by: Paul, E., Elsevier, USA, 365–388, 2007.
Boudreau, B. P.: A theoretical investigation of the organic carbon-microbial biomass relation in muddy sediments, Aquat. Microb. Ecol., 17, 181–189, 1999.
Bradley, J. A., Singarayer, J. S., and Anesio, A. M.: Microbial community dynamics in the forefield of glaciers, Proceedings, Biological sciences/The Royal Society, 281, 2793–2802, https://doi.org/10.1098/rspb.2014.0882, 2014.
Brankatschk, R., Towe, S., Kleineidam, K., Schloter, M., and Zeyer, J.: Abundances and potential activities of nitrogen cycling microbial communities along a chronosequence of a glacier forefield, Isme J., 5, 1025–1037, 2011.
Breitbarth, E., Wohlers, J., Klas, J., Laroche, J., and Peeken, I.: Nitrogen fixation and growth rates of Trichodesmium IMS-101 as a function of light intensity, Mar. Ecol. Prog. Ser., 359, 25–36, 2008.
Brooks, P. D. and Williams, M. W.: Snowpack controls on nitrogen cycling and export in seasonally snow-covered catchments, Hydrol. Process., 13, 2177–2190, 1999.
Brown, S. P. and Jumpponen, A.: Contrasting primary successional trajectories of fungi and bacteria in retreating glacier soils, Mol. Ecol., 23, 481–497, 2014.
Cannell, M. G. R. and Thornley, J. H. M.: Modelling the components of plant respiration: Some guiding principles, Ann. Bot.-London, 85, 45–54, 2000.
Cowan, A. E., Olivastro, E. M., Koppel, D. E., Loshon, C. A., Setlow, B., and Setlow, P.: Lipids in the inner membrane of dormant spores of Bacillus species are largely immobile, P. Natl. Acad. Sci. USA, 101, 7733-7738, 2004.
Darrah, P. R.: Models of the Rhizosphere .1. Microbial-Population Dynamics around a Root Releasing Soluble and Insoluble Carbon, Plant Soil, 133, 187–199, 1991.
Dessert, C., Dupre, B., Gaillardet, J., Francois, L. M., and Allegre, C. J.: Basalt weathering laws and the impact of basalt weathering on the global carbon cycle, Chem. Geol., 202, 257–273, 2003.
Duc, L., Noll, M., Meier, B. E., Burgmann, H., and Zeyer, J.: High Diversity of Diazotrophs in the Forefield of a Receding Alpine Glacier, Microbial Ecol., 57, 179–190, 2009.
Ensign, K. L., Webb, E. A., and Longstaffe, F. J.: Microenvironmental and seasonal variations in soil water content of the unsaturated zone of a sand dune system at Pinery Provincial Park, Ontario, Canada, Geoderma, 136, 788–802, 2006.
Erhagen, B., Ilstedt, U., and Nilsson, M. B.: Temperature sensitivity of heterotrophic soil CO2 production increases with increasing carbon substrate uptake rate, Soil Biol. Biochem., 80, 45–52, https://doi.org/10.1016/j.soilbio.2014.09.021, 2015.
Esperschütz, J., Pérez-de-Mora, A., Schreiner, K., Welzl, G., Buegger, F., Zeyer, J., Hagedorn, F., Munch, J. C., and Schloter, M.: Microbial food web dynamics along a soil chronosequence of a glacier forefield, Biogeosciences, 8, 3283–3294, https://doi.org/10.5194/bg-8-3283-2011, 2011.
Filippelli, G. M.: The global phosphorus cycle, Rev. Mineral Geochem., 48, 391–425, 2002.
Foereid, B. and Yearsley, J. M.: Modelling the impact of microbial grazers on soluble rhizodeposit turnover, Plant Soil, 267, 329–342, 2004.
Follmi, K. B., Hosein, R., Arn, K., and Steinmann, P.: Weathering and the mobility of phosphorus in the catchments and forefields of the Rhone and Oberaar glaciers, central Switzerland: Implications for the global phosphorus cycle on glacial-interglacial timescales, Geochim. Cosmochim. Ac., 73, 2252–2282, 2009.
Fountain, A. G., Nylen, T. H., Tranter, M., and Bagshaw, E.: Temporal variations in physical and chemical features of cryoconite holes on Canada Glacier, McMurdo Dry Valleys, Antarctica, J. Geophys. Res.-Biogeo., 113, G01S92, https://doi.org/10.1029/2007JG000430, 2008.
Frey, B., Rieder, S. R., Brunner, I., Plotze, M., Koetzsch, S., Lapanje, A., Brandl, H., and Furrer, G.: Weathering-Associated Bacteria from the Damma Glacier Forefield: Physiological Capabilities and Impact on Granite Dissolution, Appl. Environ. Microb., 76, 4788–4796, 2010.
Frey, B., Buhler, L., Schmutz, S., Zumsteg, A., and Furrer, G.: Molecular characterization of phototrophic microorganisms in the forefield of a receding glacier in the Swiss Alps, Environ. Res. Lett., 8, 015033, https://doi.org/10.1088/1748-9326/8/1/015033, 2013.
Garnier, P., Neel, C., Mary, B., and Lafolie, F.: Evaluation of a nitrogen transport and transformation model in a bare soil, Eur. J. Soil. Sci., 52, 253–268, 2001.
German, D. P., Marcelo, K. R. B., Stone, M. M., and Allison, S. D.: The Michaelis-Menten kinetics of soil extracellular enzymes in response to temperature: a cross-latitudinal study, Global Change Biol., 18, 1468–1479, 2012.
Goebel, N. L., Edwards, C. A., Carter, B. J., Achilles, K. M., and Zehr, J. P.: Growth and carbon content of three different-sized diazotrophic cyanobacteria observed in the subtropical North Pacific, J. Phycol., 44, 1212–1220, 2008.
Göransson, H., Venterink, H. O., and Baath, E.:. Soil bacterial growth and nutrient limitation along a chronosequence from a glacier forefield, Soil Biol. Biochem., 43, 1333–1340, 2011.
Göransson, H., Edwards, P., Perreijn, K., Smittenberg, R. H., and Venterink, H. O.: Rocks create nitrogen hotspots and N:P heterogeneity by funnelling rain, Biogeochemistry, 121, 329–338, https://doi.org/10.1007/s10533-014-0031-x, 2014.
Grant, R. F., Juma, N. G., and McGill, W. B.: Simulation of Carbon and Nitrogen Transformations in Soil – Mineralization, Soil Biol. Biochem., 25, 1317–1329, 1993.
Graversen, R. G., Mauritsen, T., Tjernstrom, M., Kallen, E., and Svensson, G.: Vertical structure of recent Arctic warming, Nature, 451, 53–56, https://doi.org/10.1038/nature06502, 2008.
Greenfell, T. C. and Maykut, G. A.: The optical properties of ice and snow in the Arctic basin, J Glaciol., 18, 455–463, 1977.
Guelland, K., Esperschutz, J., Bornhauser, D., Bernasconi, S. M., Kretzschmar, R., and Hagedorn, F.: Mineralisation and leaching of C from C-13 labelled plant litter along an initial soil chronosequence of a glacier forefield, Soil Biol. Biochem., 57, 237–247, 2013a.
Guelland, K., Hagedorn, F., Smittenberg, R. H., Goransson, H., Bernasconi, S. M., Hajdas, I., and Kretzschmar, R.: Evolution of carbon fluxes during initial soil formation along the forefield of Damma glacier, Switzerland, Biogeochemistry, 113, 545–561, 2013b.
Hahn, A. S. and Quideau, S. A.: Shifts in soil microbial community biomass and resource utilization along a Canadian glacier chronosequence, Can. J. Soil Sci., 93, 305–318, 2013.
Hellweger, F. L. and Bucci, V.: A bunch of tiny individuals-Individual-based modeling for microbes, Ecol. Model., 220, 8–22, 2009.
Hinsinger, P.: Bioavailability of soil inorganic P in the rhizosphere as affected by root-induced chemical changes: a review, Plant Soil, 237, 173–195, 2001.
Holl, C. M. and Montoya, J. P.: Interactions between nitrate uptake and nitrogen fixation in continuous cultures of the marine diazotroph Trichodesmium (Cyanobacteria), J. Phycol., 41, 1178–1183, 2005.
Ingwersen, J., Poll, C., Streck, T., and Kandeler, E.: Micro-scale modelling of carbon turnover driven by microbial succession at a biogeochemical interface, Soil Biol. Biochem., 40, 864–878, 2008.
Insam, H. and Haselwandter, K.: Metabolic Quotient of the Soil Microflora in Relation to Plant Succession, Oecologia, 79, 174–178, 1989.
Kaitala, V., Ylikarjula, J., and Heino, M.: Dynamic complexities in host-parasitoid interaction, J. Theor. Biol., 197, 331–341, 1999.
Kastovska, K., Elster, J., Stibal, M., and Santruckova, H.: Microbial assemblages in soil microbial succession after glacial retreat in Svalbard (high Arctic), Microbial Ecol., 50, 396–407, 2005.
King, A. J., Meyer, A. F., and Schmidt, S. K.: High levels of microbial biomass and activity in unvegetated tropical and temperate alpine soils, Soil Biol. Biochem., 40, 2605–2610, 2008.
Kirschke, S., Bousquet, P., Ciais, P., Saunois, M., Canadell, J. G., Dlugokencky, E. J., Bergamaschi, P., Bergmann, D., Blake, D. R., Bruhwiler, L., Cameron-Smith, P., Castaldi, S., Chevallier, F., Feng, L., Fraser, A., Heimann, M., Hodson, E. L., Houweling, S., Josse, B., Fraser, P. J., Krummel, P. B., Lamarque, J. F., Langenfelds, R. L., Le Quere, C., Naik, V., O'Doherty, S., Palmer, P. I., Pison, I., Plummer, D., Poulter, B., Prinn, R. G., Rigby, M., Ringeval, B., Santini, M., Schmidt, M., Shindell, D. T., Simpson, I. J., Spahni, R., Steele, L. P., Strode, S. A., Sudo, K., Szopa, S., van der Werf, G. R., Voulgarakis, A., van Weele, M., Weiss, R. F., Williams, J. E., and Zeng, G.: Three decades of global methane sources and sinks, Nat. Geosci., 6, 813–823, 2013.
Knapp, E. B., Elliott, L. F., and Campbell, G. S.:. Carbon, Nitrogen and Microbial Biomass Interrelationships during the Decomposition of Wheat Straw – a Mechanistic Simulation-Model, Soil Biol. Biochem., 15, 455–461, 1983.
Knelman, J. E., Legg, T. M., O'Neill, S. P., Washenberger, C. L., Gonzalez, A., Cleveland, C. C., and Nemergut, D. R.: Bacterial community structure and function change in association with colonizer plants during early primary succession in a glacier forefield, Soil Biol. Biochem., 46, 172–180, 2012.
Kravchenko, L. V., Strigul, N. S., and Shvytov, I. A.: Mathematical simulation of the dynamics of interacting populations of rhizosphere microorganisms, Microbiology+, 73, 189–195, 2004.
Kuijper, L. D. J., Berg, M. P., Morrien, E., Kooi, B. W., and Verhoef, H. A.: Global change effects on a mechanistic decomposer food web model, Global Change Biol., 11, 249–265, 2005.
Lancelot, C., Spitz, Y., Gypens, N., Ruddick, K., Becquevort, S., Rousseau, V., Lacroix, G., and Billen, G.: Modelling diatom and Phaeocystis blooms and nutrient cycles in the Southern Bight of the North Sea: the MIRO model, Mar. Ecol. Prog. Ser., 289, 63–78, 2005.
LaRoche, J. and Breitbarth, E.: Importance of the diazotrophs as a source of new nitrogen in the ocean, J. Sea Res., 53, 67–91, 2005.
Lazzaro, A., Abegg, C., and Zeyer, J.: Bacterial community structure of glacier forefields on siliceous and calcareous bedrock, Eur. J. Soil. Sci., 60, 860–870, 2009.
Lazzaro, A., Brankatschk, R., and Zeyer, J.: Seasonal dynamics of nutrients and bacterial communities in unvegetated alpine glacier forefields, Appl. Soil Ecol., 53, 10–22, 2012.
Leffelaar, P. A. and Wessel, W. W.: Denitrification in a Homogeneous, Closed System – Experiment and Simulation, Soil Sci., 146, 335–349, 1988.
Lennon, J. T. and Jones, S. E.: Microbial seed banks: the ecological and evolutionary implications of dormancy, Nat. Rev. Microbiol., 9, 119–130, 2011.
Levin, P. S.: The significance of variable and density-independent post-recruitment mortality in local populations of reef fishes, Aust. J. Ecol., 23, 246–251, 1998.
Liu, G. X., Hu, P., Zhang, W., Wu, X. K., Yang, X., Chen, T., Zhang, M. X., and Li, S. W.: Variations in soil culturable bacteria communities and biochemical characteristics in the Dongkemadi glacier forefield along a chronosequence, Folia Microbiol., 57, 485–494, 2012.
Liu, Y. Y., Wu, L. H., Baddeley, J. A., and Watson, C. A.: Models of biological nitrogen fixation of legumes. A review, Agron. Sustain. Dev., 31, 155–172, 2011.
Long, T. and Or, D.: Aquatic habitats and diffusion constraints affecting microbial coexistence in unsaturated porous media, Water Resour. Res., 41, W08408, https://doi.org/10.1029/2004WR003796, 2005.
Maggi, F. and Porporato, A.: Coupled moisture and microbial dynamics in unsaturated soils, Water Resour. Res., 43, W07444, https://doi.org/10.1029/2006WR005367, 2007.
Manzoni, S., Taylor, P., Richter, A., Porporato, A., and Agren, G. I.: Environmental and stoichiometric controls on microbial carbon-use efficiency in soils, New Phytol., 196, 79–91, 2012.
McGill, W.: Review and classification of ten soil organic matter (SOM) models, in: Evaluation of Soil Organic Matter Models, edited by: Powlson, D. S., Smith, P., and Smith, J. U., Springer, Berlin, 111–132, 1996.
McGill, W.: The physiology and biochemistry of soil organisms, in: Soil microbiology, ecology and biochemistry, edited by: Paul, E., 3 ed., Elsevier, USA, 2007.
Meola, M., Lazzaro, A., and Zeyer, J.: Diversity, resistance, and resilience of the bacterial communities at two alpine glacier forefields after a reciprocal soil transplantation, Environ. Microbiol., 16, 1918–1934, https://doi.org/10.1111/1462-2920.12435, 2014.
Mindl, B., Anesio, A. M., Meirer, K., Hodson, A. J., Laybourn-Parry, J., Sommaruga, R., and Sattler, B.: Factors influencing bacterial dynamics along a transect from supraglacial runoff to proglacial lakes of a high Arctic glacieri (vol 7, p. 307, 2007), Fems. Microbiol. Ecol., 59, 762–762, 2007.
Moorhead, D. L. and Sinsabaugh, R. L.: A theoretical model of litter decay and microbial interaction, Ecol. Monogr., 76, 151–174, 2006.
Moreau, M., Mercier, D., Laffly, D., and Roussel, E.: Impacts of recent paraglacial dynamics on plant colonization: A case study on Midtre Lovenbreen foreland, Spitsbergen (79 degrees N), Geomorphology, 95, 48–60, 2008.
Mur, L., Skulberg, O., and Utkilen, H.: Cyanobacteria in the environment, in: Toxic Cyanobacteria in Water: A guide to their public health consequences, monitoring and management, edited by: Chorus, I. and Bartram, J., St Edmundsbury Press, Bury St Edmunds, Suffolk, UK, 1999.
Nemergut, D. R., Anderson, S. P., Cleveland, C. C., Martin, A. P., Miller, A. E., Seimon, A., and Schmidt, S. K.: Microbial community succession in an unvegetated, recently deglaciated soil, Microbial Ecol., 53, 110–122, 2007.
Ohtonen, R., Fritze, H., Pennanen, T., Jumpponen, A., and Trappe, J.: Ecosystem properties and microbial community changes in primary succession on a glacier forefront, Oecologia, 119, 239–246, 1999.
Panikov, N. S. and Sizova, M. V.: A kinetic method for estimating the biomass of microbial functional groups in soil, J. Microbiol. Meth., 24, 219–230, 1996.
Parton, W. J., Stewart, J. W. B., and Cole, C. V.: Dynamics of C, N, P and S in Grassland Soils – a Model, Biogeochemistry, 5, 109–131, 1988.
Paul, F., Frey, H., and Le Bris, R.: A new glacier inventory for the European Alps from Landsat TM scenes of 2003: challenges and results, Ann. Glaciol., 52, 144–152, 2011.
Phillips, D. A.: Efficiency of Symbiotic Nitrogen-Fixation in Legumes, Annu. Rev. Plant Phys., 31, 29–49, 1980.
Rabouille, S., Staal, M., Stal, L. J., and Soetaert, K.: Modeling the dynamic regulation of nitrogen fixation in the cyanobacterium Trichodesmium sp., Appl. Environ. Microb., 72, 3217–3227, 2006.
Rime, T., Hartmann, M., Brunner, I., Widmer, F., Zeyer, J., and Frey, B.: Vertical distribution of the soil microbiota along a successional gradient in a glacier forefield, Mol. Ecol., 24, 1091–1108, 2014.
Sattin, S. R., Cleveland, C. C., Hood, E., Reed, S. C., King, A. J., Schmidt, S. K., Robeson, M. S., Ascarrunz, N., and Nemergut, D. R.: Functional Shifts in Unvegetated, Perhumid, Recently-Deglaciated Soils Do Not Correlate with Shifts in Soil Bacterial Community Composition, J. Microbiol., 47, 673–681, 2009.
Schimel, J. P., Bilbrough, C., and Welker, J. A.: Increased snow depth affects microbial activity and nitrogen mineralization in two Arctic tundra communities, Soil Biol. Biochem., 36, 217–227, 2004.
Schipper, L. A., Hobbs, J. K., Rutledge, S., and Arcus, V. L.: Thermodynamic theory explains the temperature optima of soil microbial processes and high Q(10) values at low temperatures, Global Change Biol., 20, 3578–3586, 2014.
Schmidt, S. K., Reed, S. C., Nemergut, D. R., Grandy, A. S., Cleveland, C. C., Weintraub, M. N., Hill, A. W., Costello, E. K., Meyer, A. F., Neff, J. C., and Martin, A. M.: The earliest stages of ecosystem succession in high-elevation (5000 metres above sea level), recently deglaciated soils, P. Roy. Soc. B-Biol. Sci., 275, 2793–2802, 2008.
Schulz, S., Brankatschk, R., Dümig, A., Kögel-Knabner, I., Schloter, M., and Zeyer, J.: The role of microorganisms at different stages of ecosystem development for soil formation, Biogeosciences, 10, 3983–3996, https://doi.org/10.5194/bg-10-3983-2013, 2013.
Schutte, U. M. E., Abdo, Z., Bent, S. J., Williams, C. J., Schneider, G. M., Solheim, B., and Forney, L. J.: Bacterial succession in a glacier foreland of the High Arctic, Isme J., 3, 1258–1268, 2009.
Scott, E. M., Rattray, E. A. S., Prosser, J. I., Killham, K., Glover, L. A., Lynch, J. M., and Bazin, M. J.: A Mathematical-Model for Dispersal of Bacterial Inoculants Colonizing the Wheat Rhizosphere, Soil Biol. Biochem., 27, 1307–1318, 1995.
Sigler, W. V. and Zeyer, J.: Microbial diversity and activity along the forefields of two receding glaciers, Microbial Ecol., 43, 397–407, 2002.
Smittenberg, R. H., Gierga, M., Goransson, H., Christl, I., Farinotti, D., and Bernasconi, S. M.:. Climate-sensitive ecosystem carbon dynamics along the soil chronosequence of the Damma glacier forefield, Switzerland, Global Change Biol., 18, 1941–1955, 2012.
Soetaert, K. and Herman, P.: A Practical Guide to Ecological Modelling: Using R as a Simulation Platform, Springer, UK, 2009.
Soetaert, K., Petzoldt, T., and Setzer, R. W.: Solving Differential Equations in R: Package deSolve, J. Stat. Softw., 33, 1–25, 2010.
Staines, K. E. H., Carrivick, J. L., Tweed, F. S., Evans, A. J., Russell, A. J., Jóhannesson, T., and Roberts, M.: A multi-dimensional analysis of pro-glacial landscape change at Sólheimajökull, southern Iceland, Earth Surf. Process. Landf., 40, 809–822, https://doi.org/10.1002/esp.3662, 2014.
Stapleton, L. M., Crout, N. M. J., Sawstrom, C., Marshall, W. A., Poulton, P. R., Tye, A. M., and Laybourn-Parry, J.: Microbial carbon dynamics in nitrogen amended Arctic tundra soil: Measurement and model testing, Soil Biol. Biochem., 37, 2088–2098, 2005.
Strauss, S. L., Garcia-pichel, F., and Day, T. A.: Soil microbial carbon and nitrogen transformations at a glacial foreland on Anvers Island, Antarctic Peninsula, Polar Biol., 35, 1459–1471, 2012.
Tamburini, F., Pfahler, V., Bunemann, E. K., Guelland, K., Bernasconi, S. M., and Frossard, E.: Oxygen Isotopes Unravel the Role of Microorganisms in Phosphate Cycling in Soils, Environ. Sci. Technol., 46, 5956–5962, 2012.
Toal, M. E., Yeomans, C., Killham, K., and Meharg, A. A.: A review of rhizosphere carbon flow modelling, Plant Soil, 222, 263–281, 2000.
Vandewerf, H. and Verstraete, W.: Estimation of Active Soil Microbial Biomass by Mathematical-Analysis of Respiration Curves – Calibration of the Test Procedure, Soil Biol. Biochem., 19, 261–265, 1987a.
Vandewerf, H. and Verstraete, W.: Estimation of Active Soil Microbial Biomass by Mathematical-Analysis of Respiration Curves – Development and Verification of the Model, Soil Biol. Biochem., 19, 253–260, 1987b.
Van Liere, L. and Walsby, A. E.: Interactions of Cyanobacteria with Light, in: The Biology of Cyanobacteria, edited by: Whitton, B. A. and Carr, N. G., 2 ed., Blackwell Scientific, Oxford, 1982.
Wieder, W. R., Bonan, G. B., and Allison, S. D.: Global soil carbon projections are improved by modelling microbial processes, Nat. Clim. Change, 3, 909-912, 2013.
Williams, M. W., Seibold, C., and Chowanski, K.: Storage and release of solutes from a subalpine seasonal snowpack: soil and stream water response, Niwot Ridge, Colorado, Biogeochemistry, 95, 77–94, 2009.
Xenakis, G., Ray, D., and Mencuccini, M.: Sensitivity and uncertainty analysis from a coupled 3-PG and soil organic matter decomposition model, Ecol. Model., 219, 1–16, 2008.
Yoshitake, S., Uchida, M., Koizumi, H., and Nakatsubo, T.: Carbon and nitrogen limitation of soil microbial respiration in a High Arctic successional glacier foreland near Ny-Ålesund, Svalbard, Polar Res., 26, 22–30, 2007.
Yoshitake, S., Uchida, M., Koizumi, H., Kanda, H., and Nakatsubo, T.: Production of biological soil crusts in the early stage of primary succession on a High Arctic glacier foreland, New Phytol., 186, 451–460, 2010.
Zelenev, V. V., van Bruggen, A. H. C., and Semenov, A. M.: "BACWAVE", a spatial–temporal model for traveling waves of bacterial populations in response to a moving carbon source in soil, Microbial Ecol., 40, 260–272, 2000.
Zumsteg, A., Bernasconi, S. M., Zeyer, J., and Frey, B.: Microbial community and activity shifts after soil transplantation in a glacier forefield, Appl. Geochem., 26, S326–S329, 2011.
Zumsteg, A., Luster, J., Goransson, H., Smittenberg, R. H., Brunner, I., Bernasconi, S. M., Zeyer, J., and Frey, B.: Bacterial, Archaeal and Fungal Succession in the Forefield of a Receding Glacier, Microbial Ecol., 63, 552–564, 2012.
Zumsteg, A., Baath, E., Stierli, B., Zeyer, J., and Frey, B.: Bacterial and fungal community responses to reciprocal soil transfer along a temperature and soil moisture gradient in a glacier forefield, Soil Biol. Biochem., 61, 121–132, 2013a.
Zumsteg, A., Schmutz, S., and Frey, B.: Identification of biomass utilizing bacteria in a carbon-depleted glacier forefield soil by the use of 13C DNA stable isotope probing, Env. Microbiol. Rep., 5, 424–437, 2013b.
Short summary
Recent climate warming causing ice retreat exposes new terrestrial ecosystems that have potentially significant yet largely unexplored roles on large-scale biogeochemical cycling and climate. SHIMMER (Soil biogeocHemIcal Model for Microbial Ecosystem Response) is a new numerical model designed to simulate microbial community establishment and elemental cycling (C, N and P) during initial soil formation in exposed glacier forefields. It is also transferable to other extreme ecosystem types.
Recent climate warming causing ice retreat exposes new terrestrial ecosystems that have...
