Articles | Volume 8, issue 11
https://doi.org/10.5194/gmd-8-3545-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/gmd-8-3545-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Development and technical paper
| Highlight paper
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05 Nov 2015
Development and technical paper | Highlight paper |
| 05 Nov 2015
Modelling Mediterranean agro-ecosystems by including agricultural trees in the LPJmL model
M. Fader
CORRESPONDING AUTHOR
Institut Méditerranéen de Biodiversité et d'Ecologie marine et continentale, Aix-Marseille Université, CNRS, IRD, Avignon Université, Technopôle Arbois-Méditerranée, Bâtiment Villemin, BP 80, 13545 Aix-en-Provence CEDEX 04, France
W. von Bloh
Potsdam Institute for Climate Impact Research, Telegraphenberg, 14473 Potsdam, Germany
S. Shi
Research Software Development Group, Research IT Services, University College London, Podium Building (1st Floor), Gower Street, London WC1E 6BT, UK
A. Bondeau
Institut Méditerranéen de Biodiversité et d'Ecologie marine et continentale, Aix-Marseille Université, CNRS, IRD, Avignon Université, Technopôle Arbois-Méditerranée, Bâtiment Villemin, BP 80, 13545 Aix-en-Provence CEDEX 04, France
W. Cramer
Institut Méditerranéen de Biodiversité et d'Ecologie marine et continentale, Aix-Marseille Université, CNRS, IRD, Avignon Université, Technopôle Arbois-Méditerranée, Bâtiment Villemin, BP 80, 13545 Aix-en-Provence CEDEX 04, France
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At present, the Mediterranean region could save 35 % of water by implementing more efficient irrigation and conveyance systems (EICS). By 2080–2090 the region may face an increase in gross irrigation requirements (IRs) of up to 74 % due to climate change and population growth. EICS may be able to compensate to some degree these increases. Most countries in the northern and eastern Mediterranean have a high risk of not being able to meet future IRs due to water scarcity.
C. Le Quéré, R. Moriarty, R. M. Andrew, J. G. Canadell, S. Sitch, J. I. Korsbakken, P. Friedlingstein, G. P. Peters, R. J. Andres, T. A. Boden, R. A. Houghton, J. I. House, R. F. Keeling, P. Tans, A. Arneth, D. C. E. Bakker, L. Barbero, L. Bopp, J. Chang, F. Chevallier, L. P. Chini, P. Ciais, M. Fader, R. A. Feely, T. Gkritzalis, I. Harris, J. Hauck, T. Ilyina, A. K. Jain, E. Kato, V. Kitidis, K. Klein Goldewijk, C. Koven, P. Landschützer, S. K. Lauvset, N. Lefèvre, A. Lenton, I. D. Lima, N. Metzl, F. Millero, D. R. Munro, A. Murata, J. E. M. S. Nabel, S. Nakaoka, Y. Nojiri, K. O'Brien, A. Olsen, T. Ono, F. F. Pérez, B. Pfeil, D. Pierrot, B. Poulter, G. Rehder, C. Rödenbeck, S. Saito, U. Schuster, J. Schwinger, R. Séférian, T. Steinhoff, B. D. Stocker, A. J. Sutton, T. Takahashi, B. Tilbrook, I. T. van der Laan-Luijkx, G. R. van der Werf, S. van Heuven, D. Vandemark, N. Viovy, A. Wiltshire, S. Zaehle, and N. Zeng
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Accurate assessment of anthropogenic carbon dioxide emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to understand the global carbon cycle, support the development of climate policies, and project future climate change. We describe data sets and a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on a range of data and models and their interpretation by a broad scientific community.
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Preprint withdrawn
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F. Langerwisch, A. Walz, A. Rammig, B. Tietjen, K. Thonicke, and W. Cramer
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M. Fader, S. Shi, W. von Bloh, A. Bondeau, and W. Cramer
Hydrol. Earth Syst. Sci., 20, 953–973, https://doi.org/10.5194/hess-20-953-2016, https://doi.org/10.5194/hess-20-953-2016, 2016
Short summary
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At present, the Mediterranean region could save 35 % of water by implementing more efficient irrigation and conveyance systems (EICS). By 2080–2090 the region may face an increase in gross irrigation requirements (IRs) of up to 74 % due to climate change and population growth. EICS may be able to compensate to some degree these increases. Most countries in the northern and eastern Mediterranean have a high risk of not being able to meet future IRs due to water scarcity.
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Earth Syst. Sci. Data, 7, 349–396, https://doi.org/10.5194/essd-7-349-2015, https://doi.org/10.5194/essd-7-349-2015, 2015
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Accurate assessment of anthropogenic carbon dioxide emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to understand the global carbon cycle, support the development of climate policies, and project future climate change. We describe data sets and a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on a range of data and models and their interpretation by a broad scientific community.
A. Rammig, M. Wiedermann, J. F. Donges, F. Babst, W. von Bloh, D. Frank, K. Thonicke, and M. D. Mahecha
Biogeosciences, 12, 373–385, https://doi.org/10.5194/bg-12-373-2015, https://doi.org/10.5194/bg-12-373-2015, 2015
M. Forkel, N. Carvalhais, S. Schaphoff, W. v. Bloh, M. Migliavacca, M. Thurner, and K. Thonicke
Biogeosciences, 11, 7025–7050, https://doi.org/10.5194/bg-11-7025-2014, https://doi.org/10.5194/bg-11-7025-2014, 2014
M. Van Oijen, J. Balkovi, C. Beer, D. R. Cameron, P. Ciais, W. Cramer, T. Kato, M. Kuhnert, R. Martin, R. Myneni, A. Rammig, S. Rolinski, J.-F. Soussana, K. Thonicke, M. Van der Velde, and L. Xu
Biogeosciences, 11, 6357–6375, https://doi.org/10.5194/bg-11-6357-2014, https://doi.org/10.5194/bg-11-6357-2014, 2014
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We use a new risk analysis method, and six vegetation models, to analyse how climate change may alter drought risks in European ecosystems. The conclusions are (1) drought will pose increasing risks to productivity in the Mediterranean area; (2) this is because severe droughts will become more frequent, not because ecosystems will become more vulnerable; (3) future C sequestration will be at risk because carbon gain in primary productivity will be more affected than carbon loss in respiration.
H. Hoff, P. Döll, M. Fader, D. Gerten, S. Hauser, and S. Siebert
Hydrol. Earth Syst. Sci., 18, 213–226, https://doi.org/10.5194/hess-18-213-2014, https://doi.org/10.5194/hess-18-213-2014, 2014
P. Dass, C. Müller, V. Brovkin, and W. Cramer
Earth Syst. Dynam., 4, 409–424, https://doi.org/10.5194/esd-4-409-2013, https://doi.org/10.5194/esd-4-409-2013, 2013
F. Joos, R. Roth, J. S. Fuglestvedt, G. P. Peters, I. G. Enting, W. von Bloh, V. Brovkin, E. J. Burke, M. Eby, N. R. Edwards, T. Friedrich, T. L. Frölicher, P. R. Halloran, P. B. Holden, C. Jones, T. Kleinen, F. T. Mackenzie, K. Matsumoto, M. Meinshausen, G.-K. Plattner, A. Reisinger, J. Segschneider, G. Shaffer, M. Steinacher, K. Strassmann, K. Tanaka, A. Timmermann, and A. J. Weaver
Atmos. Chem. Phys., 13, 2793–2825, https://doi.org/10.5194/acp-13-2793-2013, https://doi.org/10.5194/acp-13-2793-2013, 2013
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Non-Redfieldian carbon model for the Baltic Sea (ERGOM version 1.2) – implementation and budget estimates
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
Geosci. Model Dev., 17, 5349–5367, https://doi.org/10.5194/gmd-17-5349-2024, https://doi.org/10.5194/gmd-17-5349-2024, 2024
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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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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.
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.
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.
Fang Li, Zhimin Zhou, Samuel Levis, Stephen Sitch, Felicity Hayes, Zhaozhong Feng, Peter Reich, Zhiyi Zhao, and Yanqing Zhou
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-6, https://doi.org/10.5194/gmd-2024-6, 2024
Revised manuscript accepted for GMD
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This study introduces a new scheme to simulate surface ozone damage to vegetation in regional and global process-based models. Based on 4210 data points from ozone experiments, it accurately reproduces statistically significant linear or nonlinear photosynthetic and stomatal response to ozone in observations for all vegetation types. It also enables models to implicitly capture the variability in plant ozone tolerance and the shift among species within a vegetation type.
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
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.
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.
Nina Raoult, Simon Beylat, James M. Salter, Frédéric Hourdin, Vladislav Bastrikov, Catherine Ottlé, and Philippe Peylin
EGUsphere, https://doi.org/10.5194/egusphere-2023-2996, https://doi.org/10.5194/egusphere-2023-2996, 2024
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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. Here we test a technique called “History matching” against more common approaches. This method adapts well to these models, helping better understand how they work and therefore how to make them more realistic.
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.
Alexander S. Brunmayr, Frank Hagedorn, Margaux Moreno Duborgel, Luisa I. Minich, and Heather D. Graven
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-242, https://doi.org/10.5194/gmd-2023-242, 2024
Revised manuscript accepted for GMD
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A new generation of soil models promises to more accurately predict the carbon cycle in soils under climate change. However, measurements of 14C (the radioactive carbon isotope) in soils reveal that the new soil models face similar problems as the traditional models: they underestimate the residence time of carbon in soils and may therefore overestimate the net uptake of CO2 by the land ecosystem. Proposed solutions include restructuring the models and calibrating model parameters with 14C data.
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.
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.
Huajie Zhu, Mousong Wu, Fei Jiang, Michael Vossbeck, Thomas Kaminski, Xiuli Xing, Jun Wang, Weimin Ju, and Jing M. Chen
EGUsphere, https://doi.org/10.5194/egusphere-2023-1955, https://doi.org/10.5194/egusphere-2023-1955, 2023
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In this work, Nanjing University Carbon Assimilation System (NUCAS) was developed. Data assimilation experiments were conducted to demonstrate the robustness and to investigate the feasibility and applicability of NUCAS. The assimilation of COS significantly improved the model performance in gross primary productivity, sensible heat, latent heat and even soil moisture, demonstrating that COS can provide strong constraints on parameters relevant to water, energy and carbon processes.
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.
Nathaelle Bouttes, Lester Kwiatkowski, Manon Berger, Victor Brovkin, and Guy Munhoven
EGUsphere, https://doi.org/10.5194/egusphere-2023-1162, https://doi.org/10.5194/egusphere-2023-1162, 2023
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Coral reefs are crucial for biodiversity, but they also play a role in the carbon cycle on long time scales of a few thousand years. To better simulate the future and past evolution of coral reefs and their effect on the global carbon cycle, hence on atmospheric CO2 concentration, it is necessary to include coral reefs within a climate model. Here we describe the inclusion of coral reef carbonate production in a carbon-climate model and its validation in comparison to existing modern data.
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.
Cited articles
Aguilera, F., Ruiz, L., Fornaciari, M., Romano, B., Galán, C., Oteros, J., Ben Dhiab, A., Msallem, M., and Orlandi, F.: Heat accumulation period in the Mediterranean region: phenological response of the olive in different climate areas (Spain, Italy and Tunisia), Int. J. Biometeorol., 58, 867–876, https://doi.org/10.1007/s00484-013-0666-7, 2014.
Alasalvar, C. and Shahidi, F. (Eds.): Tree Nuts: Composition, Phytochemicals, and Health Effects (Nutraceutical Science and Technology), Taylor and Francis, 340 pp., 2008.
Al-Khayri, J. M. and Niblett, C. L.: Envision of an international consortium for palm research, Emirates J. Food Agric., 24, 470–479, 2012.
Álvaro-Fuentes, J., Easter, M., Cantero-Martinez, C., and Paustian, K.: Modelling soil organic carbon stocks and their changes in the northeast of Spain, Eur. J. Soil Sci., 62, 685–695, https://doi.org/10.1111/j.1365-2389.2011.01390.x, 2011.
Arnell, N. W.: Climate change and global water resources: SRES emissions and socio-economic scenarios, Global Environ. Chang., 14, 31–52, https://doi.org/10.1016/j.gloenvcha.2003.10.006, 2004.
Baldocchi, D. and Wong, S.: An Assessment of Impacts of Future CO2 and Climate on Agriculture, California Climate Change Center, 40 pp., 2006.
Bastin, S. and Henken, K.: Water Content of Fruits and Vegetables, University of Kentucky, available at: http://www2.ca.uky.edu/enri/pubs/enri129.pdf (last access: 13 March 2015), 1997.
Belluscio, A.: Planting trees can shift water flows, Nature News 7th November 2009, available at: http://www.nature.com/news/2009/091107/full/news.2009.1057.html (last access: 22 April 2015), 2009.
Beringer, T. and Lucht, W.: Nachhaltiges globales Bioenergiepotenzial, Commissioned expert study for the German Advisory Council on Global Change (WBGU) as a contribution to the flagship report World in Transition – Future Bioenergy and Sustainable Land Use, 2008.
Biemans, H., Haddeland, I., Kabat, P., Ludwig, F., Hutjes, R. W. A., Heinke, J., von Bloh, W., and Gerten, D.: Impact of reservoirs on river discharge and irrigation water supply during the 20th century, Water Resour. Res., 47, W03509, https://doi.org/10.1029/2009WR008929, 2011.
Bondeau, A., Smith, P., Zaehle, S., Schaphoff, S., Lucht, W., Cramer, W., Gerten, D., Lotze-Campen, H., Müller, C., Reichstein, M., and Smith, B.: Modelling the role of agriculture for the 20th century global terrestrial carbon balance, Global Change Biol., 13, 1–28, https://doi.org/10.1111/j.1365-2486.2006.01305.x, 2007.
Byrne, D. H. and Bacon, T.: Chilling accumulation: its importance and estimation, Dept. Of Horticultural Sciences, Texas AandM University, available at: http://aggie-horticulture.tamu.edu/stonefruit/chillacc.html (last access: 21 September 2015), 2015.
California Rare Fruit Growers: Olive, Olea Europaea L., available at: http://www.crfg.org/pubs/ff/olive.html (last access: 13 March 2015), 1997.
Cannell, M. G. R.: Dry matter partitioning in tree crops, in: Attributes of trees as crop plants, edited by: Cannell, M. G. R. and Jackson, J. E., Abbotts Ripton, Institute of Terrestrial Ecology, 160–193, available at: http://nora.nerc.ac.uk/7081/1/N007081CP.pdf (last access: 13 March 2015), 1985.
Cánovas Cuenca, J.: Report on water desalination status in the Mediterranean countries, Instituto Murciano de Investigación y Desarrollo Agrario y Alimentario, Consejería de Agricultura y Agua de la Región de Murcia, 308 pp., 2012.
Clothier, B., Hall, A. and Green, S.: Chapter 6, Horticulture, Adapting the horticultural and vegetable industries to climate change, available at: http://www.climatecloud.co.nz/CloudLibrary/2012-33-CC-Impacts-Adaptation_SLMACC-Chapter6.pdf (last access: 20 March 2015), 2012.
Diffenbaugh, N. S. and Giorgi, F.: Climate change hotspots in the CMIP5 global climate model ensemble, Climatic Change, 114, 813–822, https://doi.org/10.1007/s10584-012-0570-x, 2012.
Doblas-Miranda, E., Martínez-Vilalta, J., Lloret, F., Álvarez, A., Ávila, A., Bonet, F., Brotons, L., Castro, J., Curiel, J., Díaz, M., Ferrandis, P., García-Hurtado, E., Iriondo, J., Keenan, T., Latron, J., Llusià, J., Loepfe, L., Mayol, M., Moré, G., Moya, D., Peñuelas, J., Pons, X., Poyatos, R., Sardans, J., Sus, O., Vallejo, V., Vayreda, J., and Retana, J.: Reassessing global change research priorities in Mediterranean terrestrial ecosystems: how far have we come and where do we go from here?, Global Ecol. Biogeogr., 24, 25–43, https://doi.org/10.1111/geb.12224, 2015.
Doblas-Miranda, E., Rovira, P., Brotons, L., Mart\'inez-Vilalta, J., Retana, J., Pla, M., and Vayreda, J.: Soil carbon stocks and their variability across the forests, shrublands and grasslands of peninsular Spain, Biogeosciences, 10, 8353–8361, https://doi.org/10.5194/bg-10-8353-2013, 2013.
Döll, P. and Siebert, S.: Global modeling of irrigation water requirements, Water Resour. Res., 38, 1037, https://doi.org/10.1029/2001WR000355, 2002.
Duke, J. A.: Handbook of energy crops, Purdue University, Center for New Crops and Plant Products, available at: http://www.hort.purdue.edu/newcrop/duke_energy/refa-f.html (last access: 13 March 2015), 1983.
Eclesia, R. P., Jobbagy, E. G., Jackson, R. B., Biganzoli, F., and Piñeiro, G.: Shifts in soil organic carbon for plantation and pasture establishment in native forests and grasslands of South America, Global Change Biol., 18, 3237–3251, https://doi.org/10.1111/j.1365-2486.2012.02761.x, 2012.
Elliott J., Deryng, D., Müller, C., Frieler, K., Konzmann, M., Gerten, D., Glotter, M., Flörke, M., Wada, Y., Best, N., Eisner, S., Fekete, B. M., Folberth, C., Foster, I., Gosling, S. N., Haddeland, I., Khabarov, N., Ludwig, F., Masaki, Y., Olin, S., Rosenzweig, C., Ruane, A. C., Satoh, Y., Schmid, E., Stacke, T., Tang, Q., and Wisser, D.: Constraints and potentials of future irrigation water availability on agricultural production under climate change, Proc. Natl. Acad. Sci., 111 , 3239–3244, https://doi.org/10.1073/pnas.1222474110, 2014.
Elshibli, S.: Genetic Diversity and Adaptation of Date Palm (Phoenix dactylifera L.), PhD Thesis University of Helsinki, 2009.
Fader, M., Rost, S., Müller, C., Bondeau, A., and Gerten, D.: Virtual water content of temperate cereals and maize: Present and potential future patterns, J. Hydrol., 384, 218–231, https://doi.org/10.1016/j.jhydrol.2009.12.011, 2010.
Fader, M., Gerten, D., Krause, M., Lucht, W., and Cramer, W.: Spatial decoupling of agricultural production and consumption: quantifying dependence of countries on food imports due to domestic land and water constraints, Environ. Res. Lett., 8, 014046, https://doi.org/10.1088/1748-9326/8/1/014046, 2013.
Fader, M., Shi, S., von Bloh, W., Bondeau, A., and Cramer, W.: Mediterranean irrigation under climate change: more efficient irrigation needed to compensate increases in irrigation water requirements, Hydrol. Earth Syst. Sci. Discuss., 12, 8459–8504, https://doi.org/10.5194/hessd-12-8459-2015, 2015.
FAO: Cultivation of Potatoes, available at: http://www.fao.org/potato-2008/en/potato/cultivation.html (last access: 13 March 2015), 2008.
FAO: Crop Water Information: Citrus, available at: http://www.fao.org/nr/water/cropinfo_citrus.html (last access: 13 March 2015), 2013a.
FAO: Crop Water Information: Olive, available at: http://www.fao.org/nr/water/cropinfo_olive.html, (last access: 13 March 2015), 2013b.
FAO: Crop Water Information: Grape, available at: http://www.fao.org/nr/water/cropinfo_grape.html (last access: 13 March 2015), 2013c.
FAO: Date palm cultivation, FAO Plant production and protection paper 156, Rev. 1, edited and compiled by: Zaid, A., available at: http://www.fao.org/docrep/006/y4360e/y4360e00.HTM (last access: 13 March 2015), 2002.
FAO: Tree crops, Guidelines for estimating area data, Statistics division, available at: http://www.fao.org/fileadmin/templates/ess/ess_test_folder/documents/Production_trade/definitions/Tree_crops_guidelines_for_estaimating_area.doc (last access: 13 March 2015), 2011.
FAO: FAOSTAT, available at: http://faostat.fao.org/site/567/default.aspx#ancor (last access: 1 July 2014), 2015a.
FAO: AQUASTAT, available at: http://www.fao.org/nr/water/aquastat/main/index.stm, (last access: 1 July 2014), 2015b.
Fischer, G., Tubiello, F. N., van Velthuizen, H., and Wiberg, D. A.: Climate change impacts on irrigation water requirements: Effects of mitigation, 1990–2080. Technol. Forecast. Soc., 74, 1083–1107, https://doi.org/10.1016/j.techfore.2006.05.021, 2007.
Gallardo, M. and Thompson, R. B.: Water requirements and irrigation management in Mediterranean greenhouses: the case of the southeast coast of Spain, in: Good Agricultural Practices for Greenhouse Vegetable Crops: Principles for Mediterranean Climate Areas, edited by: FAO-AGP and ISHS-CMPC, FAO, Rome, Italy, 109–136, 2013.
Garcia de Cortázar-Atauri, I.: Adaptation du modèle STICS à la vigne (Vitis vinifera L.): utilisation dans le cadre d'une étude d'impact du changement climatique à l'échelle de la France, PhD thesis ENSAM, 292 pp., 2006.
García-Orenes, F., Roldán, A., Mataix-Solera, J., Cerda, A., Campoy, M., Arcenegui, V., and Caravaca, F.: Soil structural stability and erosion rates influenced by agricultural management practices in a semi-arid Mediterranean agro-ecosystem, Soil Use Manage., 28, 571–579, https://doi.org/10.1111/j.1475-2743.2012.00451.x, 2012.
Gerik, T., Williams, J., Francis, L., Greiner, J., Magre, M., Meinardus, A., Steglich, E., and Taylor, R.: EPIC-Environmental Policy Integrated Climate Model, User's Manual Version 0810, 2014.
Gerten, D., Luo, Y., Le Maire, G., Parton, W. J., Keough, C., Weng, E., Beier, C., Ciais, P., Cramer, W., Dukes, J. S., Sowerby, A., Hanson, P. J., Knapp, A., Linder, S., Nepstad, D., and Rustad, L.: Modelled effects of precipitation, on ecosystem carbon and water dynamics in different climatic zones, Global Change Biol., 14, 1–15, https://doi.org/10.1111/j.1365-2486.2008.01651.x, 2008.
Gerten, D., Schaphoff, S., Haberlandt, U., Lucht, W., and Sitch, S.: Terrestrial vegetation and water balance – hydrological evaluation of a dynamic global vegetation model, J. Hydrol., 286, 249–270, https://doi.org/10.1016/j.jhydrol.2003.09.029, 2004.
Gordon, R., Brown, D. M., and Dixon, M. A.: Estimating potato leaf area index for specific cultivars, Potato Res., 40, 251–266, https://doi.org/10.1007/BF02358007, 1997.
Gutierrez, A. P., Ponti, L., Ellis, C. K., and d'Oultremont, T.: Analysis of climate effects on agricultural systems: A report to the Governor of California, 43 pp., available at: http://www.climatechange.ca.gov/climate_action_team/reports/index.html (last access: 20 March 2015), 2006.
Harris, I., Jones, P. D., Osborn, T. J., and Lister, D. H.: Updated high-resolution grids of monthly climatic observations – the CRU TS3.10 Dataset, Int. J. Climatol., 34, 623–642, https://doi.org/10.1002/joc.3711, 2014.
Haverkort, A. J. and MacKerron, D. K. L. (Eds.): Potato ecology and modelling of crops under conditions limiting growth, Kluwer Academic Publishers, The Netherlands, 1995.
Hervieu, B.: Agriculture: a strategic sector in the Mediterranean area, CIHEAM analytic note No. 18, 2006.
Hiederer, R. and Köchy, M.: Global Soil Organic Carbon Estimates and the Harmonized World Soil Database, EUR Scientific and Technical Research series – ISSN 1831-9424 (online), https://doi.org/10.2788/13267, 2012.
Holzworth, D. P., Huth, N. I., deVoil, P. G., Zurcher, E. J., Herrmann, N. I., McLean, G., Chenu, K., van Oosterom, E. J., Snow, V., Murphy, C., Moore, A. D., Brown, H., Whish, J. P. M., Verrall, S., Fainges, J., Bell, L. W., Peake, A. S., Poulton, P. L., Hochman, Z., Thorburn, P. J., Gaydon, D. S., Dalgliesh, N. P., Rodriguez, D., Cox, H., Chapman, S., Doherty, A., Teixeira, E., Sharp, J., Cichota, R., Vogeler, I., Li, F. Y., Wang, E., Hammer, G. L., Robertson, M. J., Dimes, J. P., Whitbread, A. M., Hunt, J. van Rees, H., McClelland, T., Carberry, P. S., Hargreaves, J. N.G., MacLeod, N., McDonald, C., Harsdorf, J., Wedgwood, S., and Keating, B. A.: APSIM – Evolution towards a new generation of agricultural systems simulation, Environ. Model. Softw., 62, 327–350, https://doi.org/10.1016/j.envsoft.2014.07.009, 2014.
IIASA/FAO: Global Agro-ecological Zones (GAEZ v3.0), IIASA, Laxenburg, Austria and FAO, 2012.
IPCC: Summary for Policymakers, in: Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation, , A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change, edited by: Field, C. B., Barros, V., Stocker, T. F., Qin, D., Dokken, D. J., Ebi, K. L., Mastrandrea, M. D., Mach, K. J., Plattner, G.-K., Allen, S. K., Tignor, M., and Midgley, P. M., Cambridge University Press, Cambridge, UK, and New York, NY, USA, 3–21, 2012.
Janick, J. and Paull, R. E. (Eds.): Encyclopedia of Fruit and Nuts, Purdue University, USA, CAB International, 972 pp., 2008.
Jobbagy, E. G. and Jackson, R. B.: The vertical distribution of soil organic carbon and its relation to climate and vegetation, Ecol. Appl., 10, 423–436, 2000.
Kailis, S. and Harris, D.: Producing Table Olives, CSIRO Publishing, Collingwood, 2007.
Kiranga, N. A.: Morpho-argro-physio-karyotypic characterization of wild cotton (Gossypium spp.), Germplasm from selected counties in Kenya, available at: http://ir-library.ku.ac.ke/bitstream/handle/123456789/9050/Njagi Anthony Kiranga.pdf?sequence=1 (last access: 13 March 2015), 2013.
Klein Goldewijk, K., Beusen, A., de Vos, M., and van Drecht, G.: The HYDE 3.1 spatially explicit database of human induced land use change over the past 12,000 years, Global Ecol. Biogeogr., 20, 73–86, https://doi.org/10.1111/j.1466-8238.2010.00587.x, 2011.
Konzmann, M., Gerten, G., and Heinke, J.: Climate impacts on global irrigation requirements under 19 GCMs, simulated with a vegetation and hydrology model, Hydrol. Sci. J., 58, 88–105, https://doi.org/10.1080/02626667.2013.746495, 2013.
Kovats, R. S., Valentini, R., Bouwer, L. M., Georgopoulou, E., Jacob, D., Martin, E., Rounsevell, M. and Soussana, J.-F.: Europe, in: Climate Change 2014: Impacts, Adaptation, and Vulnerability, Part B: Regional Aspects, Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Barros, V. R., Field, C. B., Dokken, D. J., Mastrandrea, M. D., Mach, K. J., Bilir, T. E., Chatterjee, M., Ebi, K. L., Estrada, Y. O., Genova, R. C., Girma, B., Kissel, E. S., Levy, A. N., MacCracken, S., Mastrandrea, P. R., and White, L. L., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 1267–1326, 2014.
Kroes, J. G. and van Dam, J. C.: Reference Manual SWAP version 3.0.3. Alterra-report 773 3, Alterra, Green World Research, Wageningen, 211 pp., 2003.
Ku, S,-B., Edwards, G. E., and Tanner, C. B.: Effects of light, carbon dioxide, and temperature on photosynthesis, oxygen inhibition of photosynthesis, and transpiration in Solanum tuberosum, Plant Physiol., 59, 868–872, 1977.
Lapola, D. M., Priess, J. A., and Bondeau, A.: Modeling the land requirements and potential productivity of sugarcane and jatropha in Brazil and India using the LPJmL dynamic global vegetation model, Biomass Bioenergy, 33, 1087–95, https://doi.org/10.1016/j.biombioe.2009.04.005, 2009.
Lavorel, S., Canadell, J., Rambal, S., and Terradas, J.: Mediterranean terrestrial ecosystems: Research priorities on global change effects, Global Ecol. Biogeogr. Lett., 7, 157–166, https://doi.org/10.1046/j.1466-822X.1998.00277.x, 1998.
Lionello, P., Malanotte-Rizzoli, P., Boscolo, R., Alpert, P., Artale, V., Li, L., Luterbacher, J., May, W., Trigo, R., Tsimplis, M., Ulbrich, U., and Xoplaki, E.: The Mediterranean Climate: An Overview of the Main Characteristics and Issues, in: Mediterranean Climate Variability, edited by: Lionello, P., Malanotte-Rizzoli, P., and Boscolo, R., Developments in Earth and Environmental Sciences, 4, 1–26, 2006.
Lobell, D. B., Nicholas Cahill, K., and Field, C. B.: Historical effects of temperature and precipitation on California crop yields, Climatic Change, 81, 187–203, https://doi.org/10.1007/s10584-006-9141-3, 2007.
Lobianco, A. and Esposti, R.: The regional model for Mediterranean agriculture. IDEMA research project paper, available at: https://lobianco.org/antonello/_media/academic:pubs:idema_deliverable17.pdf, (last access: 21 September 2015), 2006.
Marsal, J. and Stöckle, C. O.: Use of CropSyst as a decision support system for scheduling regulated deficit irrigation in a pear orchard, Irrigation Sci., 30, 139–147, https://doi.org/10.1007/s00271-011-0273-5, 2012.
Marsal, J., Girona, J., Casadesus, J., López, G., and Stöckle, C. O.: Crop coefficient (Kc) for apple: comparison between measurements by a weighing lysimeter and prediction by CropSyst, Irrigation Sci., 31, 455–463, https://doi.org/10.1007/s00271-012-0323-7, 2013.
Marsal, J., Johnson, S., Casadesus, J., López, G., Girona, J., and Stöckle, C.: Fraction of canopy intercepted radiation relates differently with crop coefficient depending on the season and the fruit tree species, Agr. Forest Meteorol., 184, 1–11, https://doi.org/10.1016/j.agrformet.2013.08.008, 2014.
Meier, U.: Growth stages of mono-and dicotyledonous plants, BBCH Monograph, Federal Biological Research Centre for Agriculture and Forestry, Blackwell Wissenschafts-Verlag, 622 pp., 2001.
Ministry of Agriculture, Food and Rural Affairs: Wine grape production outside traditional areas in Ontario, available at: http://www.omafra.gov.on.ca/english/crops/facts/info_grapeprod.htm (last access: 13 March 2015), 2013.
Monfreda, C., Ramankutty, N., and Foley, J. A.: Farming the planet: 2. Geographic distribution of crop areas, yields, physiological types, and net primary production in the year 2000, Global Biogeochem. Cy., 22, GB1022, https://doi.org/10.1029/2007GB002947, 2008.
Morales Sierra, A.: A model of productivity for olive orchards, MSc Thesis Plant Production Systems, Wageningen University, 2012.
Moriondo, M., Ferrise, R., Trombi, G., Brilli, L., Dibari, C., and Bindi, M.: Modelling olive trees and grapevines in a changing climate. Environ. Model. Softw., 72, 387–401, https://doi.org/10.1016/j.envsoft.2014.12.016, 2015.
Müller, C., Waha, K., Bondeau, A., and Heinke, J.: Hotspots of climate change impacts in sub-Saharan Africa and implications for adaptation and development, Global Change Biol., 20, 2505–2517, https://doi.org/10.1111/gcb.12586, 2014.
Neitsch, S. L., Arnold, J. G., Kiniry, J. R., Srinivasan, R., and Williams, J. R.: Assessment Tool, Input/output file documentation, Version 2005, Grassland, Soil and Water Research Laboratory, Temple, Texas, available at: http://swat.tamu.edu/media/1291/swat2005io.pdf (last access: 13 March 2015), 2004.
Nesme, T., Brisson, N., Lescourret, F., Bellon, S., Crété, X., Plénet, D., and Habib, R.: Epistics: A dynamic model to generate nitrogen fertilisation and irrigation schedules in apple orchards, with special attention to qualitative evaluation of the model, Agr. Syst., 90, 202–225, https://doi.org/10.1016/j.agsy.2005.12.006, 2006.
Netafim: Irrigation, Almond best practices, available at: https://www.netafim.com/crop/almond/best-practice (last access: 13 March 2015), 2013.
Orlandi, F., Garcia-Mozo, H., Ben Dhiab, A., Galán, C., Msallem, M., and Fornaciari, M.: Olive tree phenology and climate variations in the Mediterranean area over the last two decades, Theor. Appl. Climatol., 115, 207–218, https://doi.org/10.1007/s00704-013-0892-2, 2014.
Orwa, C., Mutua, A., Kindt, R., Jamnadass, R., and Anthony, S.: Agroforestree Database: a tree reference and selection guide version 4.0, World Agroforestry Centre, Kenya, 2009.
Paytas, M. and Tarrago, J.: Cotton genotypes performance under rainfed and irrigated conditions in two regions of northern Argentina, in: World Cotton Research Conference-5, edited by: Kranthi, K. R., Venugopalan, M. V., Balasubramanya, R. H., Kranthi, S., Singh, S., and Blaise, S.: Mumbai, India, 7-11 November 2011, 309–311, Excel India Publishers, New Delhi, 2011.
Perry, L.: Cold Climate Fruit Trees, University of Vermont Extension Department of Plant and Soil Science, available at: http://perrysperennials.info/articles/coldfruit.html (last access: 13 March 2015), 2011.
Pontificia Universidad Católica de Chile: El Almendro, available at: https://climafrutal.wordpress.com/el-almendro/ (last access: 13 March 2015), 2008.
Portmann, F., Siebert, S., and Döll, P.: MIRCA 2000 – Global monthly irrigated and rainfed crop areas around the year 2000: A new high-resolution data set for agricultural and hydrological modelling, Global Biogeochem. Cy., 24, GB1011, https://doi.org/10.1029/2008GB003435, 2011.
Ramankutty, N., Evan, A. T., Monfreda, C., and Foley, J. A.: Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000, Global Biogeochem. Cy., 22, GB1003, https://doi.org/10.1029/2007GB002952, 2008.
Rayan, M. A. and Djebedjian, B.: Egypt's Water Demand, Supply and Management Policies. International Water Demand Management Conference, 30 May–3 June 2004, Dead Sea – Jordan, available at: http://www.academia.edu/2085529/Egypt_s Water_Demand_Supply_and_Management_Policies (last access: 13 March 2015), 2004.
Rohwer, J., Gerten, D., and Lucht, W.: Development of functional irrigation types for improved global crop modelling, PIK Report 104, Potsdam, 98 pp., 2006.
Rost, S., Gerten, D., Bondeau, A., Lucht, W., Rohwer, J., and Schaphoff, S.: Agricultural green and blue water consumption and its influence on the global water system, Water Resour. Res., 44, W09405, https://doi.org/10.1029/2007WR006331, 2008.
Roussos, P. A.: Training and Pruning Olives. Proceedings of the MGS Symposium: Dry Gardening – Philosophy and Practice, Agricultural University of Athens, Greece, available at: http://www.mediterraneangardensociety.org/olives.html (last access: 13 March 2015), 2007.
Sakin, E.: Net primary productivity of southeast Anatolia Region (SAR) in Turkey, Int. J. Agr. Biol., 14, 617–620, 2012.
Savva, A. P. and Frenken, K.: Monitoring the Technical and Financial Performance of an Irrigation Scheme, Irrigation Manual Module, 14, 58 pp., 2002.
Scarascia-Mugnozza, G., Oswald, H., Piussi, P., and Radoglou, K.: Forests of the Mediterranean region: gaps in knowledge and research needs, Forest Ecol. Manage., 132, 97–109, https://doi.org/10.1016/S0378-1127(00)00383-2, 2000.
Schaphoff, S., Heyder, U., Ostberg, S., Gerten, D., Heinke, J., and Lucht, W.: Contribution of permafrost soils to the global carbon budget, Environ. Res. Lett., 8, 014026, https://doi.org/10.1088/1748-9326/8/1/014026, 2013.
Scheidel, A. and Krausmann, F.: Diet, trade and land use: a socio-ecological analysis of the transformation of the olive oil system, Land Use Policy, 28, 47–56, https://doi.org/10.1016/j.landusepol.2010.04.008, 2011.
Schröter, D., Cramer, W., Leemans, R., Prentice, I. C., Araújo, M. B., Arnell, N. W., Bondeau, A., Bugmann, H., Carter, T. R., Garcia, C. A., de la Vega-Leinert, A. C., Erhard, M., Ewert, F., Glendining, M., House, J. I., Kankaanpää, S., Klein, R. J. T., Lavorel, S., Lindner, M., Metzger, M. J., Meyer, J., Mitchell, T. D., Reginster, I., Rounsevell, M., Sabaté, S., Sitch, S., Smith, B., Smith, J., Smith, P., Sykes M. T., Thonicke, K., Thuiller, W., Tuck, G., Zaehle, S., and Zierl, B.: Ecosystem service supply and vulnerability to global change in Europe, Science, 310, 1333–1337, https://doi.org/10.1126/science.1115233, 2005.
Siebert, S. and Döll, P.: The Global Crop Water Model (GCWM): Documentation and first results for irrigated crops, Frankfurt Hydrology Paper 07, Institute of Physical Geography, University of Frankfurt, Frankfurt am Main, Germany, 2008.
Siebert, S. and Döll, P.: Quantifying blue and green virtual water contents in global crop production as well as potential production losses without irrigation, J. Hydrol., 384, 198–217, https://doi.org/10.1016/j.jhydrol.2009.07.031, 2010.
Siebert, S., Burke, J., Faures, J. M., Frenken, K., Hoogeveen, J., Döll, P., and Portmann, F. T.: Groundwater use for irrigation – a global inventory, Hydrol. Earth Syst. Sci., 14, 1863–1880, https://doi.org/10.5194/hess-14-1863-2010, 2010.
Sitch, S., Smith, B., Prentice, C., Arneth, A., Bondeau, A., Cramer, W., Kaplan, J. O., Levis, S., Lucht, W., Sykes, M. T., Thonicke, K. and Venevsky, S.: Evaluation of ecosystem dynamics, plant geography and terrestrial carbon cycling in the LPJ dynamic global vegetation model, Global Change Biol., 9, 161–185, https://doi.org/10.1046/j.1365-2486.2003.00569.x, 2003.
Skuras, D. and Psaltopoulos, D.: A broad overview of the main problems derived from climate change that will affect agricultural production in the Mediterranean area, in: Building Resilience for Adaptation to Climate Change in the Agriculture Sector, edited by: Meybeck, A., Lankoski, J., Redfern, S., Azzu, N., and Gitz, V., Proceedings of a Joint FAO/OECD Workshop 23–24 April 2012.
Slowak Wine Academy Pezinok: Viticulture and viniculture, Study material, Elementary Seminar, Module 1, European Comission, Leonardo Davinci Transfer of Innovation Programm, 50 pp., available at: http://svapezinok.sk/files/gallery/20130103172711_WEB_SVA%20 Zakladny
Sperling, O.: Water Relations in Date Palm Trees – a Combined Approach using Water, Plant, and Atmospheric Data, Ph.D. Thesis, Ben-Gurion University, 2013.
Strik, B. C.: Growing Table Grapes, EC 1639, Oregon State University, Extension Service, http://smallfarms.oregonstate.edu/sites/default/files/publications/growing_table_grapes_ec1639_may_2011.pdf (last access: 13 March 2015), 2011.
Toky, O. M., Kumar, P., and Kumar, P.: Structure and function of traditional agroforestry systems in the western Himalaya. I. Biomass and productivity, Agroforest. Syst., 9, 47–70, https://doi.org/10.1007/BF00120155, 1989.
Tsiros, E., Domenikiotis, C., and Dalezios, N. R.: Assessment of cotton phenological stages using agroclimatic indices: An innovative approach, It. J. Agrometeorol., 2009, 50–55, 2009.
Valdés-Gómez, H., Celette, F., García De Cortázar-Atauri, I., Jara-Rojas, F., and Gary, C.: Modelling soil water content and grapevine growth and development with the STICS crop-soil model under two different water management strategies, J. Int. Scie Vigne Vin, 43, 13–28, 2009.
Verner, D.: Adaptation to a Changing Climate in the Arab Countries: A Case for Adaptation Governance and Leadership in Building Climate Resilience, The World Bank, Washington, DC, 2012.
Villalobos, F. J., Testi, L., Orgaz, F., García-Tejera, O., Lopez-Bernal, A., González-Dugo, M. V., Ballester-Lurbe, C., Castel, J. R., Alarcón-Cabañero, J. J., Nicolás-Nicolás, E., Girona, J., Marsal, J., and Fereres, E.: Modelling canopy conductance and transpiration of fruit trees in Mediterranean areas: a simplified approach, Agr. Forest Meteorol., 171–172, 93–103, https://doi.org/10.1016/j.agrformet.2012.11.010, 2013.
Wada, Y., Beek, L. P. H., van Kempen, C. M., Reckman, J. W. T. M., Vasak, S., and Bierkens, M. F. P.: Global depletion of groundwater resources, Geophys. Res. Lett., 37, L20402, https://doi.org/10.1029/2010GL044571, 2010.
Waha, K., van Bussel, L. G. J., Müller, C., and Bondeau, A.: Climate-driven simulation of global crop sowing dates, Global Ecol. Biogeogr., 12, 247–259, https://doi.org/10.1111/j.1466-8238.2011.00678.x, 2012.
Waha, K., Müller, C., Bondeau, A., Dietrich, J. P., Kurukulasuriya, P., Heinke, J., and Lotze-Campen, H.: Adaptation to climate change through the choice of cropping system and sowing date in sub-Saharan Africa, Global Environ. Chang., 23, 130–143, https://doi.org/10.1016/j.gloenvcha.2012.11.001, 2013.
Werth, M., Brauckmann, H.-J., Broll, G., and Schreiber, K.-F.: Analysis and simulation of soil organic-carbon stocks in grassland ecosystems in SW Germany, J. Plant Nutr. Soil Sci., 168, 472–482, https://doi.org/10.1002/jpln.200421704, 2005.
Willmott, C. J.: Some comments on the evaluation of model performance, Bulletin American Meteorological Society, 1309–1313, 1982.
World Bank: Population Growth (Annual
Wright, S., Hutmacher, B., Shrestha, A., Banuelos, G., Keeley, M., Delgado, R., and Elam, S.: Double Row and Conventional Cotton in Tulare County, California, in: New directions for a diverse planet, edited by: Fischer, R. A., Proceedings of the 4th International Crop Science Congress, Brisbane, Australia, 26 September–1 October 2004, available at: http://www.regional.org.au/au/asa/2004/poster/2/7/4/1774_wrightsd.htm (last access: 13 March 2015), 2014.
Wünsche, J. N. and Lakso, A. N.: Apple Tree Physiology–Implications for Orchard and Tree Management. Presented at the 43rd Annual IDFTA Conference, 6–9 February 2000, Napier, New Zealand, available at: http://virtualorchard.net/IDFTA/cft/2000/july/cftjuly2000p82.pdf (last access: 13 March 2015), 2000.
Yan, H., Cao, M., Liu, J., and Tao, B.: Potential and sustainability for carbon sequestration with improved soil management in agricultural soils of China. Agriculture, Ecosyst. Environ., 121, 325–335, https://doi.org/10.1016/j.agee.2006.11.008, 2007.
Zamski, E. and Schaffer, A. A.: Photoassimilate distribution in plants and crops: source-sink relationships, Marcel Dekker, Inc., New York, 33 pp., 1996.
Zanotelli, D., Montagnani, L., Manca, G., and Tagliavini, M.: Net primary productivity, allocation pattern and carbon use efficiency in an apple orchard assessed by integrating eddy covariance, biometric and continuous soil chamber measurements, Biogeosciences, 10, 3089–3108, https://doi.org/10.5194/bg-10-3089-2013, 2013.
Zdruli, P.: Land resources of the Mediterranean: Status, pressures, trends and impacts of future regional development, Land Degrad. Dev., 25, 373–384, https://doi.org/10.1002/ldr.2150, 2014.
Short summary
This study presents the inclusion of 10 Mediterranean agricultural plants in an agro-ecosystem model (LPJmL): nut trees, date palms, citrus trees, orchards, olive trees, grapes, cotton, potatoes, vegetables and fodder grasses.
The model was successfully tested in three model outputs: agricultural yields, irrigation requirements and soil carbon density. With this development presented, LPJmL is now able to simulate in good detail and mechanistically the functioning of Mediterranean agriculture.
This study presents the inclusion of 10 Mediterranean agricultural plants in an agro-ecosystem...
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