Articles | Volume 18, issue 6
https://doi.org/10.5194/bg-18-1917-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-18-1917-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Impacts of fertilization on grassland productivity and water quality across the European Alps under current and warming climate: insights from a mechanistic model
Institute of Environmental Engineering, ETH Zurich, Zurich, Switzerland
Matthias Zeeman
Karlsruhe Institute of Technology, Institute of Meteorology and Climate Research, Atmospheric Environmental Research, Garmisch-Partenkirchen, Germany
Paolo Burlando
Institute of Environmental Engineering, ETH Zurich, Zurich, Switzerland
Simone Fatichi
Department of Civil and Environmental Engineering, National University of Singapore, Singapore
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Martina Botter, Paolo Burlando, and Simone Fatichi
Hydrol. Earth Syst. Sci., 23, 1885–1904, https://doi.org/10.5194/hess-23-1885-2019, https://doi.org/10.5194/hess-23-1885-2019, 2019
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The study focuses on the solute export from rivers with the purpose of discerning the impacts of anthropic activities and catchment characteristics on water quality. The results revealed a more detectable impact of the anthropic activities than of the catchment characteristics. The solute export follows different dynamics depending on catchment characteristics and mainly on solute-specific properties. The export modality is consistent across different catchments only for a minority of solutes.
Matthias Zeeman, Andreas Christen, Sue Grimmond, Daniel Fenner, William Morrison, Gregor Feigel, Markus Sulzer, and Nektarios Chrysoulakis
Geosci. Instrum. Method. Data Syst., 13, 393–424, https://doi.org/10.5194/gi-13-393-2024, https://doi.org/10.5194/gi-13-393-2024, 2024
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This study presents an overview of a data system for documenting, processing, managing, and publishing data streams from research networks of atmospheric and environmental sensors of varying complexity in urban environments. Our solutions aim to deliver resilient, near-time data using freely available software.
Yue Zhu, Paolo Burlando, Puay Yok Tan, Christian Geiß, and Simone Fatichi
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-207, https://doi.org/10.5194/nhess-2024-207, 2024
Preprint under review for NHESS
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This study addresses the challenge of accurately predicting floods in regions with limited terrain data. By utilizing a deep learning model, we developed a method that improves the resolution of digital elevation data by fusing low-resolution elevation data with high-resolution satellite imagery. This approach not only substantially enhances flood prediction accuracy, but also holds potential for broader applications in simulating natural hazards that require terrain information.
Shanti Shwarup Mahto, Simone Fatichi, and Stefano Galelli
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-441, https://doi.org/10.5194/essd-2024-441, 2024
Preprint under review for ESSD
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The MSEA-Res database offers an open-access dataset tracking absolute water storage for 185 large reservoirs across Mainland Southeast Asia from 1985–2023. It provides valuable insights into how reservoir storage has grown by 130 % between 2008 and 2017, driven by dams in key river basins. Our data also reveal how droughts, like the 2019–2020 event, significantly impacted water reservoirs. This resource can aid water management, drought planning, and research globally.
Jordi Buckley Paules, Simone Fatichi, Bonnie Warring, and Athanasios Paschalis
EGUsphere, https://doi.org/10.5194/egusphere-2024-2072, https://doi.org/10.5194/egusphere-2024-2072, 2024
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We outline and validate developments to the pre-existing process-based model T&C to better represent cropland processes. Foreseen applications of T&C-CROP include hydrological and carbon storage implications of land-use transitions involving crop, forest, and pasture conversion, as well as studies on optimal irrigation and fertilization under a changing climate.
Tobias Karl David Weber, Lutz Weihermüller, Attila Nemes, Michel Bechtold, Aurore Degré, Efstathios Diamantopoulos, Simone Fatichi, Vilim Filipović, Surya Gupta, Tobias L. Hohenbrink, Daniel R. Hirmas, Conrad Jackisch, Quirijn de Jong van Lier, John Koestel, Peter Lehmann, Toby R. Marthews, Budiman Minasny, Holger Pagel, Martine van der Ploeg, Shahab Aldin Shojaeezadeh, Simon Fiil Svane, Brigitta Szabó, Harry Vereecken, Anne Verhoef, Michael Young, Yijian Zeng, Yonggen Zhang, and Sara Bonetti
Hydrol. Earth Syst. Sci., 28, 3391–3433, https://doi.org/10.5194/hess-28-3391-2024, https://doi.org/10.5194/hess-28-3391-2024, 2024
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Pedotransfer functions (PTFs) are used to predict parameters of models describing the hydraulic properties of soils. The appropriateness of these predictions critically relies on the nature of the datasets for training the PTFs and the physical comprehensiveness of the models. This roadmap paper is addressed to PTF developers and users and critically reflects the utility and future of PTFs. To this end, we present a manifesto aiming at a paradigm shift in PTF research.
Yiran Wang, Naika Meili, and Simone Fatichi
EGUsphere, https://doi.org/10.5194/egusphere-2024-768, https://doi.org/10.5194/egusphere-2024-768, 2024
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Our study uses climate model simulations and process-based ecohydrological modeling to assess the direct and climate feedback induced effects of solar radiation changes on hydrological variables. Results show that solar radiation without climate feedback primarily affects sensible heat with limited effects on hydrology and vegetation. However, climate feedback exacerbates the effects of radiation changes on evapotranspiration and affects vegetation productivity.
Benjamin Schumacher, Marwan Katurji, Jiawei Zhang, Peyman Zawar-Reza, Benjamin Adams, and Matthias Zeeman
Atmos. Meas. Tech., 15, 5681–5700, https://doi.org/10.5194/amt-15-5681-2022, https://doi.org/10.5194/amt-15-5681-2022, 2022
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This investigation presents adaptive thermal image velocimetry (A-TIV), a newly developed algorithm to spatially measure near-surface atmospheric velocities using an infrared camera mounted on uncrewed aerial vehicles. A validation and accuracy assessment of the retrieved velocity fields shows the successful application of the algorithm over short-cut grass and turf surfaces in dry conditions. This provides new opportunities for atmospheric scientists to study surface–atmosphere interactions.
Stefano Manzoni, Simone Fatichi, Xue Feng, Gabriel G. Katul, Danielle Way, and Giulia Vico
Biogeosciences, 19, 4387–4414, https://doi.org/10.5194/bg-19-4387-2022, https://doi.org/10.5194/bg-19-4387-2022, 2022
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Increasing atmospheric carbon dioxide (CO2) causes leaves to close their stomata (through which water evaporates) but also promotes leaf growth. Even if individual leaves save water, how much will be consumed by a whole plant with possibly more leaves? Using different mathematical models, we show that plant stands that are not very dense and can grow more leaves will benefit from higher CO2 by photosynthesizing more while adjusting their stomata to consume similar amounts of water.
Michael Schirmer, Adam Winstral, Tobias Jonas, Paolo Burlando, and Nadav Peleg
The Cryosphere, 16, 3469–3488, https://doi.org/10.5194/tc-16-3469-2022, https://doi.org/10.5194/tc-16-3469-2022, 2022
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Rain is highly variable in time at a given location so that there can be both wet and dry climate periods. In this study, we quantify the effects of this natural climate variability and other sources of uncertainty on changes in flooding events due to rain on snow (ROS) caused by climate change. For ROS events with a significant contribution of snowmelt to runoff, the change due to climate was too small to draw firm conclusions about whether there are more ROS events of this important type.
Stefan Fugger, Catriona L. Fyffe, Simone Fatichi, Evan Miles, Michael McCarthy, Thomas E. Shaw, Baohong Ding, Wei Yang, Patrick Wagnon, Walter Immerzeel, Qiao Liu, and Francesca Pellicciotti
The Cryosphere, 16, 1631–1652, https://doi.org/10.5194/tc-16-1631-2022, https://doi.org/10.5194/tc-16-1631-2022, 2022
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The monsoon is important for the shrinking and growing of glaciers in the Himalaya during summer. We calculate the melt of seven glaciers in the region using a complex glacier melt model and weather data. We find that monsoonal weather affects glaciers that are covered with a layer of rocky debris and glaciers without such a layer in different ways. It is important to take so-called turbulent fluxes into account. This knowledge is vital for predicting the future of the Himalayan glaciers.
Matthias Zeeman
Atmos. Meas. Tech., 14, 7475–7493, https://doi.org/10.5194/amt-14-7475-2021, https://doi.org/10.5194/amt-14-7475-2021, 2021
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Understanding turbulence near the surface is important for many applications. In this work, methods for observing and analysing temperature structures in a near-surface volume were explored. Experiments were conducted to identify modes of organised motion. These help explain interactions between the vegetation and the atmosphere that are not currently well understood. Techniques used include fibre-optic sensing, thermal infrared imaging, signal decomposition, and machine learning.
Lianyu Yu, Simone Fatichi, Yijian Zeng, and Zhongbo Su
The Cryosphere, 14, 4653–4673, https://doi.org/10.5194/tc-14-4653-2020, https://doi.org/10.5194/tc-14-4653-2020, 2020
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The role of soil water and heat transfer physics in portraying the function of a cold region ecosystem was investigated. We found that explicitly considering the frozen soil physics and coupled water and heat transfer is important in mimicking soil hydrothermal dynamics. The presence of soil ice can alter the vegetation leaf onset date and deep leakage. Different complexity in representing vadose zone physics does not considerably affect interannual energy, water, and carbon fluxes.
Giulia Battista, Peter Molnar, and Paolo Burlando
Earth Surf. Dynam., 8, 619–635, https://doi.org/10.5194/esurf-8-619-2020, https://doi.org/10.5194/esurf-8-619-2020, 2020
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Suspended sediment load in rivers is highly uncertain because of spatial and temporal variability. By means of a hydrology and suspended sediment transport model, we investigated the effect of spatial variability in precipitation and surface erodibility on catchment sediment fluxes in a mesoscale river basin.
We found that sediment load depends on the spatial variability in erosion drivers, as this affects erosion rates and the location and connectivity to the channel of the erosion areas.
Martin Kunz, Jost V. Lavric, Rainer Gasche, Christoph Gerbig, Richard H. Grant, Frank-Thomas Koch, Marcus Schumacher, Benjamin Wolf, and Matthias Zeeman
Atmos. Meas. Tech., 13, 1671–1692, https://doi.org/10.5194/amt-13-1671-2020, https://doi.org/10.5194/amt-13-1671-2020, 2020
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The nocturnal boundary layer (NBL) budget method enables the quantification of gas fluxes between ecosystems and the atmosphere under nocturnal stable stratification, a condition under which standard approaches struggle. However, up to now the application of the NBL method has been limited by difficulties in obtaining the required measurements. We show how an unmanned aircraft system (UAS) equipped with a carbon dioxide analyser can make this method more accessible.
Genki Katata, Rüdiger Grote, Matthias Mauder, Matthias J. Zeeman, and Masakazu Ota
Biogeosciences, 17, 1071–1085, https://doi.org/10.5194/bg-17-1071-2020, https://doi.org/10.5194/bg-17-1071-2020, 2020
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In this paper, we demonstrate that high physiological activity levels during the extremely warm winter are allocated into the below-ground biomass and only to a minor extent used for additional plant growth during early spring. This process is so far largely unaccounted for in scenario analysis using global terrestrial biosphere models, and it may lead to carbon accumulation in the soil and/or carbon loss from the soil as a response to global warming.
Naika Meili, Gabriele Manoli, Paolo Burlando, Elie Bou-Zeid, Winston T. L. Chow, Andrew M. Coutts, Edoardo Daly, Kerry A. Nice, Matthias Roth, Nigel J. Tapper, Erik Velasco, Enrique R. Vivoni, and Simone Fatichi
Geosci. Model Dev., 13, 335–362, https://doi.org/10.5194/gmd-13-335-2020, https://doi.org/10.5194/gmd-13-335-2020, 2020
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We developed a novel urban ecohydrological model (UT&C v1.0) that is able to account for the effects of different plant types on the urban climate and hydrology, as well as the effects of the urban environment on plant well-being and performance. UT&C performs well when compared against energy flux measurements in three cities in different climates (Singapore, Melbourne, Phoenix) and can be used to assess urban climate mitigation strategies that aim at increasing or changing urban green cover.
Nadav Peleg, Chris Skinner, Simone Fatichi, and Peter Molnar
Earth Surf. Dynam., 8, 17–36, https://doi.org/10.5194/esurf-8-17-2020, https://doi.org/10.5194/esurf-8-17-2020, 2020
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Extreme rainfall is expected to intensify with increasing temperatures, which will likely affect rainfall spatial structure. The spatial variability of rainfall can affect streamflow and sediment transport volumes and peaks. The sensitivity of the hydro-morphological response to changes in the structure of heavy rainfall was investigated. It was found that the morphological components are more sensitive to changes in rainfall spatial structure in comparison to the hydrological components.
Erkan Ibraim, Benjamin Wolf, Eliza Harris, Rainer Gasche, Jing Wei, Longfei Yu, Ralf Kiese, Sarah Eggleston, Klaus Butterbach-Bahl, Matthias Zeeman, Béla Tuzson, Lukas Emmenegger, Johan Six, Stephan Henne, and Joachim Mohn
Biogeosciences, 16, 3247–3266, https://doi.org/10.5194/bg-16-3247-2019, https://doi.org/10.5194/bg-16-3247-2019, 2019
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Nitrous oxide (N2O) is an important greenhouse gas and the major stratospheric ozone-depleting substance; therefore, mitigation of anthropogenic N2O emissions is needed. To trace N2O-emitting source processes, in this study, we observed N2O isotopocules above an intensively managed grassland research site with a recently developed laser spectroscopy method. Our results indicate that the domain of denitrification or nitrifier denitrification was the major N2O source.
Martina Botter, Paolo Burlando, and Simone Fatichi
Hydrol. Earth Syst. Sci., 23, 1885–1904, https://doi.org/10.5194/hess-23-1885-2019, https://doi.org/10.5194/hess-23-1885-2019, 2019
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The study focuses on the solute export from rivers with the purpose of discerning the impacts of anthropic activities and catchment characteristics on water quality. The results revealed a more detectable impact of the anthropic activities than of the catchment characteristics. The solute export follows different dynamics depending on catchment characteristics and mainly on solute-specific properties. The export modality is consistent across different catchments only for a minority of solutes.
Anne Klosterhalfen, Alexander Graf, Nicolas Brüggemann, Clemens Drüe, Odilia Esser, María P. González-Dugo, Günther Heinemann, Cor M. J. Jacobs, Matthias Mauder, Arnold F. Moene, Patrizia Ney, Thomas Pütz, Corinna Rebmann, Mario Ramos Rodríguez, Todd M. Scanlon, Marius Schmidt, Rainer Steinbrecher, Christoph K. Thomas, Veronika Valler, Matthias J. Zeeman, and Harry Vereecken
Biogeosciences, 16, 1111–1132, https://doi.org/10.5194/bg-16-1111-2019, https://doi.org/10.5194/bg-16-1111-2019, 2019
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To obtain magnitudes of flux components of H2O and CO2 (e.g., transpiration, soil respiration), we applied source partitioning approaches after Scanlon and Kustas (2010) and after Thomas et al. (2008) to high-frequency eddy covariance measurements of 12 study sites covering various ecosystems (croplands, grasslands, and forests) in different climatic regions. We analyzed the interrelations among turbulence, site characteristics, and the performance of both partitioning methods.
Donghai Wu, Philippe Ciais, Nicolas Viovy, Alan K. Knapp, Kevin Wilcox, Michael Bahn, Melinda D. Smith, Sara Vicca, Simone Fatichi, Jakob Zscheischler, Yue He, Xiangyi Li, Akihiko Ito, Almut Arneth, Anna Harper, Anna Ukkola, Athanasios Paschalis, Benjamin Poulter, Changhui Peng, Daniel Ricciuto, David Reinthaler, Guangsheng Chen, Hanqin Tian, Hélène Genet, Jiafu Mao, Johannes Ingrisch, Julia E. S. M. Nabel, Julia Pongratz, Lena R. Boysen, Markus Kautz, Michael Schmitt, Patrick Meir, Qiuan Zhu, Roland Hasibeder, Sebastian Sippel, Shree R. S. Dangal, Stephen Sitch, Xiaoying Shi, Yingping Wang, Yiqi Luo, Yongwen Liu, and Shilong Piao
Biogeosciences, 15, 3421–3437, https://doi.org/10.5194/bg-15-3421-2018, https://doi.org/10.5194/bg-15-3421-2018, 2018
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Our results indicate that most ecosystem models do not capture the observed asymmetric responses under normal precipitation conditions, suggesting an overestimate of the drought effects and/or underestimate of the watering impacts on primary productivity, which may be the result of inadequate representation of key eco-hydrological processes. Collaboration between modelers and site investigators needs to be strengthened to improve the specific processes in ecosystem models in following studies.
Sahani Pathiraja, Daniela Anghileri, Paolo Burlando, Ashish Sharma, Lucy Marshall, and Hamid Moradkhani
Hydrol. Earth Syst. Sci., 22, 2903–2919, https://doi.org/10.5194/hess-22-2903-2018, https://doi.org/10.5194/hess-22-2903-2018, 2018
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Hydrologic modeling methodologies must be developed that are capable of predicting runoff in catchments with changing land cover conditions. This article investigates the efficacy of a recently developed approach that allows for runoff prediction in catchments with unknown land cover changes, through experimentation in a deforested catchment in Vietnam. The importance of key elements of the method in ensuring its success, such as the chosen hydrologic model, is investigated.
Matthias Mauder and Matthias J. Zeeman
Atmos. Meas. Tech., 11, 249–263, https://doi.org/10.5194/amt-11-249-2018, https://doi.org/10.5194/amt-11-249-2018, 2018
Caroline Brosy, Karina Krampf, Matthias Zeeman, Benjamin Wolf, Wolfgang Junkermann, Klaus Schäfer, Stefan Emeis, and Harald Kunstmann
Atmos. Meas. Tech., 10, 2773–2784, https://doi.org/10.5194/amt-10-2773-2017, https://doi.org/10.5194/amt-10-2773-2017, 2017
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Vertical and horizontal sounding of the planetary boundary layer can be complemented by unmanned aerial vehicles (UAV). Utilizing a multicopter-type UAV spatial sampling of air and simultaneously sensing of meteorological variables is possible for the study of surface exchange processes. During stable atmospheric conditions, vertical methane gradients of about 300 ppb were found. This approach extended the vertical profile height of existing tower-based infrastructure by a factor of five.
Nadav Peleg, Frank Blumensaat, Peter Molnar, Simone Fatichi, and Paolo Burlando
Hydrol. Earth Syst. Sci., 21, 1559–1572, https://doi.org/10.5194/hess-21-1559-2017, https://doi.org/10.5194/hess-21-1559-2017, 2017
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We investigated the relative contribution of the spatial versus climatic rainfall variability for flow peaks by applying an advanced stochastic rainfall generator to simulate rainfall for a small urban catchment and simulate flow dynamics in the sewer system. We found that the main contribution to the total flow variability originates from the natural climate variability. The contribution of spatial rainfall variability to the total flow variability was found to increase with return periods.
Bahareh Kianfar, Simone Fatichi, Athansios Paschalis, Max Maurer, and Peter Molnar
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2016-536, https://doi.org/10.5194/hess-2016-536, 2016
Revised manuscript has not been submitted
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Raingauge observations show a large variability in extreme rainfall depths in the current climate. Climate model predictions of extreme rainfall in the future have to be compared with this natural variability. Our work shows that predictions of future extreme rainfall often lie within the range of natural variability of present-day climate, and therefore predictions of change are highly uncertain. We demonstrate this by using stochastic rainfall models and 10-min rainfall data in Switzerland.
P. Molnar, S. Fatichi, L. Gaál, J. Szolgay, and P. Burlando
Hydrol. Earth Syst. Sci., 19, 1753–1766, https://doi.org/10.5194/hess-19-1753-2015, https://doi.org/10.5194/hess-19-1753-2015, 2015
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We present an empirical study of the rates of increase in precipitation intensity with air temperature using high-resolution 10 min precipitation records in Switzerland. We estimated the scaling rates for lightning (convective) and non-lightning event subsets and show that scaling rates are between 7 and 14%/C for convective rain and that mixing of storm types exaggerates the relations to air temperature. Doubled CC rates reported by other studies are an exception in our data set.
P. Michna, W. Eugster, R. V. Hiller, M. J. Zeeman, and H. Wanner
Geogr. Helv., 68, 249–263, https://doi.org/10.5194/gh-68-249-2013, https://doi.org/10.5194/gh-68-249-2013, 2013
T. Grünewald, J. Stötter, J. W. Pomeroy, R. Dadic, I. Moreno Baños, J. Marturià, M. Spross, C. Hopkinson, P. Burlando, and M. Lehning
Hydrol. Earth Syst. Sci., 17, 3005–3021, https://doi.org/10.5194/hess-17-3005-2013, https://doi.org/10.5194/hess-17-3005-2013, 2013
S. Fatichi, S. Rimkus, P. Burlando, R. Bordoy, and P. Molnar
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-10-3743-2013, https://doi.org/10.5194/hessd-10-3743-2013, 2013
Revised manuscript not accepted
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Matthew Forrest, Jessica Hetzer, Maik Billing, Simon P. K. Bowring, Eric Kosczor, Luke Oberhagemann, Oliver Perkins, Dan Warren, Fátima Arrogante-Funes, Kirsten Thonicke, and Thomas Hickler
Biogeosciences, 21, 5539–5560, https://doi.org/10.5194/bg-21-5539-2024, https://doi.org/10.5194/bg-21-5539-2024, 2024
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Climate change is causing an increase in extreme wildfires in Europe, but drivers of fire are not well understood, especially across different land cover types. We used statistical models with satellite data, climate data, and socioeconomic data to determine what affects burning in cropland and non-cropland areas of Europe. We found different drivers of burning in cropland burning vs. non-cropland to the point that some variables, e.g. population density, had the complete opposite effects.
Bettina K. Gier, Manuel Schlund, Pierre Friedlingstein, Chris D. Jones, Colin Jones, Sönke Zaehle, and Veronika Eyring
Biogeosciences, 21, 5321–5360, https://doi.org/10.5194/bg-21-5321-2024, https://doi.org/10.5194/bg-21-5321-2024, 2024
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This study investigates present-day carbon cycle variables in CMIP5 and CMIP6 simulations. Overall, CMIP6 models perform better but also show many remaining biases. A significant improvement in the simulation of photosynthesis in models with a nitrogen cycle is found, with only small differences between emission- and concentration-based simulations. Thus, we recommend using emission-driven simulations in CMIP7 by default and including the nitrogen cycle in all future carbon cycle models.
Sven Armin Westermann, Anke Hildebrandt, Souhail Bousetta, and Stephan Thober
Biogeosciences, 21, 5277–5303, https://doi.org/10.5194/bg-21-5277-2024, https://doi.org/10.5194/bg-21-5277-2024, 2024
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Plants at the land surface mediate between soil and the atmosphere regarding water and carbon transport. Since plant growth is a dynamic process, models need to consider these dynamics. Two models that predict water and carbon fluxes by considering plant temporal evolution were tested against observational data. Currently, dynamizing plants in these models did not enhance their representativeness, which is caused by a mismatch between implemented physical relations and observable connections.
Kamal Nyaupane, Umakant Mishra, Feng Tao, Kyongmin Yeo, William J. Riley, Forrest M. Hoffman, and Sagar Gautam
Biogeosciences, 21, 5173–5183, https://doi.org/10.5194/bg-21-5173-2024, https://doi.org/10.5194/bg-21-5173-2024, 2024
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Representing soil organic carbon (SOC) dynamics in Earth system models (ESMs) is a key source of uncertainty in predicting carbon–climate feedbacks. Using machine learning, we develop and compare predictive relationships in observations (Obs) and ESMs. We find different relationships between environmental factors and SOC stocks in Obs and ESMs. SOC prediction in ESMs may be improved by representing the functional relationships of environmental controllers in a way consistent with observations.
Jacob A. Nelson, Sophia Walther, Fabian Gans, Basil Kraft, Ulrich Weber, Kimberly Novick, Nina Buchmann, Mirco Migliavacca, Georg Wohlfahrt, Ladislav Šigut, Andreas Ibrom, Dario Papale, Mathias Göckede, Gregory Duveiller, Alexander Knohl, Lukas Hörtnagl, Russell L. Scott, Weijie Zhang, Zayd Mahmoud Hamdi, Markus Reichstein, Sergio Aranda-Barranco, Jonas Ardö, Maarten Op de Beeck, Dave Billesbach, David Bowling, Rosvel Bracho, Christian Brümmer, Gustau Camps-Valls, Shiping Chen, Jamie Rose Cleverly, Ankur Desai, Gang Dong, Tarek S. El-Madany, Eugenie Susanne Euskirchen, Iris Feigenwinter, Marta Galvagno, Giacomo A. Gerosa, Bert Gielen, Ignacio Goded, Sarah Goslee, Christopher Michael Gough, Bernard Heinesch, Kazuhito Ichii, Marcin Antoni Jackowicz-Korczynski, Anne Klosterhalfen, Sara Knox, Hideki Kobayashi, Kukka-Maaria Kohonen, Mika Korkiakoski, Ivan Mammarella, Mana Gharun, Riccardo Marzuoli, Roser Matamala, Stefan Metzger, Leonardo Montagnani, Giacomo Nicolini, Thomas O'Halloran, Jean-Marc Ourcival, Matthias Peichl, Elise Pendall, Borja Ruiz Reverter, Marilyn Roland, Simone Sabbatini, Torsten Sachs, Marius Schmidt, Christopher R. Schwalm, Ankit Shekhar, Richard Silberstein, Maria Lucia Silveira, Donatella Spano, Torbern Tagesson, Gianluca Tramontana, Carlo Trotta, Fabio Turco, Timo Vesala, Caroline Vincke, Domenico Vitale, Enrique R. Vivoni, Yi Wang, William Woodgate, Enrico A. Yepez, Junhui Zhang, Donatella Zona, and Martin Jung
Biogeosciences, 21, 5079–5115, https://doi.org/10.5194/bg-21-5079-2024, https://doi.org/10.5194/bg-21-5079-2024, 2024
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The movement of water, carbon, and energy from the Earth's surface to the atmosphere, or flux, is an important process to understand because it impacts our lives. Here, we outline a method called FLUXCOM-X to estimate global water and CO2 fluxes based on direct measurements from sites around the world. We go on to demonstrate how these new estimates of net CO2 uptake/loss, gross CO2 uptake, total water evaporation, and transpiration from plants compare to previous and independent estimates.
Xin Chen, Tiexi Chen, Xiaodong Li, Yuanfang Chai, Shengjie Zhou, Renjie Guo, and Jie Dai
Biogeosciences, 21, 4285–4300, https://doi.org/10.5194/bg-21-4285-2024, https://doi.org/10.5194/bg-21-4285-2024, 2024
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We provide an ensemble-model-based GPP dataset (ERF_GPP) that explains 85.1 % of the monthly variation in GPP across 170 sites, which is higher than other GPP estimate models. In addition, ERF_GPP improves the phenomenon of “high-value underestimation and low-value overestimation” in GPP estimation to some extent. Overall, ERF_GPP provides a more reliable estimate of global GPP and will facilitate further development of carbon cycle research.
Reza Kusuma Nurrohman, Tomomichi Kato, Hideki Ninomiya, Lea Végh, Nicolas Delbart, Tatsuya Miyauchi, Hisashi Sato, Tomohiro Shiraishi, and Ryuichi Hirata
Biogeosciences, 21, 4195–4227, https://doi.org/10.5194/bg-21-4195-2024, https://doi.org/10.5194/bg-21-4195-2024, 2024
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SPITFIRE (SPread and InTensity of FIRE) was integrated into a spatially explicit individual-based dynamic global vegetation model to improve the accuracy of depicting Siberian forest fire frequency, intensity, and extent. Fires showed increased greenhouse gas and aerosol emissions in 2006–2100 for Representative Concentration Pathways. This study contributes to understanding fire dynamics, land ecosystem–climate interactions, and global material cycles under the threat of escalating fires.
Stefano Manzoni and M. Francesca Cotrufo
Biogeosciences, 21, 4077–4098, https://doi.org/10.5194/bg-21-4077-2024, https://doi.org/10.5194/bg-21-4077-2024, 2024
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Organic carbon and nitrogen are stabilized in soils via microbial assimilation and stabilization of necromass (in vivo pathway) or via adsorption of the products of extracellular decomposition (ex vivo pathway). Here we use a diagnostic model to quantify which stabilization pathway is prevalent using data on residue-derived carbon and nitrogen incorporation in mineral-associated organic matter. We find that the in vivo pathway is dominant in fine-textured soils with low organic matter content.
Huajie Zhu, Xiuli Xing, Mousong Wu, Weimin Ju, and Fei Jiang
Biogeosciences, 21, 3735–3760, https://doi.org/10.5194/bg-21-3735-2024, https://doi.org/10.5194/bg-21-3735-2024, 2024
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Ecosystem carbonyl sulfide (COS) fluxes were employed to optimize GPP estimation across ecosystems with the Biosphere-atmosphere Exchange Process Simulator (BEPS), which was developed for simulating the canopy COS uptake under its state-of-the-art two-leaf modeling framework. Our results showcased the efficacy of COS in improving model prediction and reducing prediction uncertainty of GPP and enhanced insights into the sensitivity, identifiability, and interactions of parameters related to COS.
Moritz Laub, Magdalena Necpalova, Marijn Van de Broek, Marc Corbeels, Samuel Mathu Ndungu, Monicah Wanjiku Mucheru-Muna, Daniel Mugendi, Rebecca Yegon, Wycliffe Waswa, Bernard Vanlauwe, and Johan Six
Biogeosciences, 21, 3691–3716, https://doi.org/10.5194/bg-21-3691-2024, https://doi.org/10.5194/bg-21-3691-2024, 2024
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We used the DayCent model to assess the potential impact of integrated soil fertility management (ISFM) on maize production, soil fertility, and greenhouse gas emission in Kenya. After adjustments, DayCent represented measured mean yields and soil carbon stock changes well and N2O emissions acceptably. Our results showed that soil fertility losses could be reduced but not completely eliminated with ISFM and that, while N2O emissions increased with ISFM, emissions per kilogram yield decreased.
Hazel Cathcart, Julian Aherne, Michael D. Moran, Verica Savic-Jovcic, Paul A. Makar, and Amanda Cole
EGUsphere, https://doi.org/10.5194/egusphere-2024-2371, https://doi.org/10.5194/egusphere-2024-2371, 2024
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Deposition from sulfur and nitrogen pollution can harm ecosystems, and recovery from this type of pollution can take decades or longer. To identify risk to Canadian soils, we created maps showing sensitivity to sulfur and nitrogen pollution. Results show that some ecosystems are at risk from acid and nutrient nitrogen deposition; 10 % of protected areas are receiving acid deposition beyond their damage threshold and 70 % may be receiving nitrogen deposition that could cause biodiversity loss.
Erik Schwarz, Samia Ghersheen, Salim Belyazid, and Stefano Manzoni
Biogeosciences, 21, 3441–3461, https://doi.org/10.5194/bg-21-3441-2024, https://doi.org/10.5194/bg-21-3441-2024, 2024
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The occurrence of unstable equilibrium points (EPs) could impede the applicability of microbial-explicit soil organic carbon models. For archetypal model versions we identify when instability can occur and describe mathematical conditions to avoid such unstable EPs. We discuss implications for further model development, highlighting the important role of considering basic ecological principles to ensure biologically meaningful models.
Sian Kou-Giesbrecht, Vivek K. Arora, Christian Seiler, and Libo Wang
Biogeosciences, 21, 3339–3371, https://doi.org/10.5194/bg-21-3339-2024, https://doi.org/10.5194/bg-21-3339-2024, 2024
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Terrestrial biosphere models can either prescribe the geographical distribution of biomes or simulate them dynamically, capturing climate-change-driven biome shifts. We isolate and examine the differences between these different land cover implementations. We find that the simulated terrestrial carbon sink at the end of the 21st century is twice as large in simulations with dynamic land cover than in simulations with prescribed land cover due to important range shifts in the Arctic and Amazon.
Elizabeth S. Duan, Luciana Chavez Rodriguez, Nicole Hemming-Schroeder, Baptiste Wijas, Habacuc Flores-Moreno, Alexander W. Cheesman, Lucas A. Cernusak, Michael J. Liddell, Paul Eggleton, Amy E. Zanne, and Steven D. Allison
Biogeosciences, 21, 3321–3338, https://doi.org/10.5194/bg-21-3321-2024, https://doi.org/10.5194/bg-21-3321-2024, 2024
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Understanding the link between climate and carbon fluxes is crucial for predicting how climate change will impact carbon sinks. We estimated carbon dioxide (CO2) fluxes from deadwood in tropical Australia using wood moisture content and temperature. Our model predicted that the majority of deadwood carbon is released as CO2, except when termite activity is detected. Future models should also incorporate wood traits, like species and chemical composition, to better predict fluxes.
Daniel Nadal-Sala, Rüdiger Grote, David Kraus, Uri Hochberg, Tamir Klein, Yael Wagner, Fedor Tatarinov, Dan Yakir, and Nadine K. Ruehr
Biogeosciences, 21, 2973–2994, https://doi.org/10.5194/bg-21-2973-2024, https://doi.org/10.5194/bg-21-2973-2024, 2024
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A hydraulic model approach is presented that can be added to any physiologically based ecosystem model. Simulated plant water potential triggers stomatal closure, photosynthesis decline, root–soil resistance increases, and sapwood and foliage senescence. The model has been evaluated at an extremely dry site stocked with Aleppo pine and was able to represent gas exchange, soil water content, and plant water potential. The model also responded realistically regarding leaf senescence.
Patrick Neri, Lianhong Gu, and Yang Song
Biogeosciences, 21, 2731–2758, https://doi.org/10.5194/bg-21-2731-2024, https://doi.org/10.5194/bg-21-2731-2024, 2024
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A first-of-its-kind global-scale model of temperature resilience and tolerance of photosystem II maximum quantum yield informs how plants maintain their efficiency of converting light energy to chemical energy for photosynthesis under temperature changes. Our finding explores this variation across plant functional types and habitat climatology, highlighting diverse temperature response strategies and a method to improve global-scale photosynthesis modeling under climate change.
Liyuan He, Jorge L. Mazza Rodrigues, Melanie A. Mayes, Chun-Ta Lai, David A. Lipson, and Xiaofeng Xu
Biogeosciences, 21, 2313–2333, https://doi.org/10.5194/bg-21-2313-2024, https://doi.org/10.5194/bg-21-2313-2024, 2024
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Soil microbes are the driving engine for biogeochemical cycles of carbon and nutrients. This study applies a microbial-explicit model to quantify bacteria and fungal biomass carbon in soils from 1901 to 2016. Results showed substantial increases in bacterial and fungal biomass carbon over the past century, jointly influenced by vegetation growth and soil temperature and moisture. This pioneering century-long estimation offers crucial insights into soil microbial roles in global carbon cycling.
Tao Chen, Félicien Meunier, Marc Peaucelle, Guoping Tang, Ye Yuan, and Hans Verbeeck
Biogeosciences, 21, 2253–2272, https://doi.org/10.5194/bg-21-2253-2024, https://doi.org/10.5194/bg-21-2253-2024, 2024
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Chinese subtropical forest ecosystems are an extremely important component of global forest ecosystems and hence crucial for the global carbon cycle and regional climate change. However, there is still great uncertainty in the relationship between subtropical forest carbon sequestration and its drivers. We provide first quantitative estimates of the individual and interactive effects of different drivers on the gross primary productivity changes of various subtropical forest types in China.
Pritha Pande, Sam Bland, Nathan Booth, Jo Cook, Zhaozhong Feng, and Lisa Emberson
EGUsphere, https://doi.org/10.5194/egusphere-2024-694, https://doi.org/10.5194/egusphere-2024-694, 2024
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The DO3SE-crop model extends the DO3SE to simulate ozone's impact on crops with modules for ozone uptake, damage, and crop growth from JULES-Crop. It's versatile, suits China's varied agriculture, and improves yield predictions under ozone stress. It is essential for policy, water management, and climate response, it integrates into Earth System Models for a comprehensive understanding of agriculture's interaction with global systems.
Ke Liu, Yujie Wang, Troy S. Magney, and Christian Frankenberg
Biogeosciences, 21, 1501–1516, https://doi.org/10.5194/bg-21-1501-2024, https://doi.org/10.5194/bg-21-1501-2024, 2024
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Stomata are pores on leaves that regulate gas exchange between plants and the atmosphere. Existing land models unrealistically assume stomata can jump between steady states when the environment changes. We implemented dynamic modeling to predict gradual stomatal responses at different scales. Results suggested that considering this effect on plant behavior patterns in diurnal cycles was important. Our framework also simplified simulations and can contribute to further efficiency improvements.
Melanie A. Thurner, Silvia Caldararu, Jan Engel, Anja Rammig, and Sönke Zaehle
Biogeosciences, 21, 1391–1410, https://doi.org/10.5194/bg-21-1391-2024, https://doi.org/10.5194/bg-21-1391-2024, 2024
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Due to their crucial role in terrestrial ecosystems, we implemented mycorrhizal fungi into the QUINCY terrestrial biosphere model. Fungi interact with mineral and organic soil to support plant N uptake and, thus, plant growth. Our results suggest that the effect of mycorrhizal interactions on simulated ecosystem dynamics is minor under constant environmental conditions but necessary to reproduce and understand observed patterns under changing conditions, such as rising atmospheric CO2.
Jinyun Tang and William J. Riley
Biogeosciences, 21, 1061–1070, https://doi.org/10.5194/bg-21-1061-2024, https://doi.org/10.5194/bg-21-1061-2024, 2024
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A chemical kinetics theory is proposed to explain the non-monotonic relationship between temperature and biochemical rates. It incorporates the observed thermally reversible enzyme denaturation that is ensured by the ceaseless thermal motion of molecules and ions in an enzyme solution and three well-established theories: (1) law of mass action, (2) diffusion-limited chemical reaction theory, and (3) transition state theory.
Nina Raoult, Louis-Axel Edouard-Rambaut, Nicolas Vuichard, Vladislav Bastrikov, Anne Sofie Lansø, Bertrand Guenet, and Philippe Peylin
Biogeosciences, 21, 1017–1036, https://doi.org/10.5194/bg-21-1017-2024, https://doi.org/10.5194/bg-21-1017-2024, 2024
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Observations are used to reduce uncertainty in land surface models (LSMs) by optimising poorly constraining parameters. However, optimising against current conditions does not necessarily ensure that the parameters treated as invariant will be robust in a changing climate. Manipulation experiments offer us a unique chance to optimise our models under different (here atmospheric CO2) conditions. By using these data in optimisations, we gain confidence in the future projections of LSMs.
Kelsey T. Foster, Wu Sun, Yoichi P. Shiga, Jiafu Mao, and Anna M. Michalak
Biogeosciences, 21, 869–891, https://doi.org/10.5194/bg-21-869-2024, https://doi.org/10.5194/bg-21-869-2024, 2024
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Assessing agreement between bottom-up and top-down methods across spatial scales can provide insights into the relationship between ensemble spread (difference across models) and model accuracy (difference between model estimates and reality). We find that ensemble spread is unlikely to be a good indicator of actual uncertainty in the North American carbon balance. However, models that are consistent with atmospheric constraints show stronger agreement between top-down and bottom-up estimates.
Victoria R. Dutch, Nick Rutter, Leanne Wake, Oliver Sonnentag, Gabriel Hould Gosselin, Melody Sandells, Chris Derksen, Branden Walker, Gesa Meyer, Richard Essery, Richard Kelly, Phillip Marsh, Julia Boike, and Matteo Detto
Biogeosciences, 21, 825–841, https://doi.org/10.5194/bg-21-825-2024, https://doi.org/10.5194/bg-21-825-2024, 2024
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We undertake a sensitivity study of three different parameters on the simulation of net ecosystem exchange (NEE) during the snow-covered non-growing season at an Arctic tundra site. Simulations are compared to eddy covariance measurements, with near-zero NEE simulated despite observed CO2 release. We then consider how to parameterise the model better in Arctic tundra environments on both sub-seasonal timescales and cumulatively throughout the snow-covered non-growing season.
Bertrand Guenet, Jérémie Orliac, Lauric Cécillon, Olivier Torres, Laura Sereni, Philip A. Martin, Pierre Barré, and Laurent Bopp
Biogeosciences, 21, 657–669, https://doi.org/10.5194/bg-21-657-2024, https://doi.org/10.5194/bg-21-657-2024, 2024
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Heterotrophic respiration fluxes are a major flux between surfaces and the atmosphere, but Earth system models do not yet represent them correctly. Here we benchmarked Earth system models against observation-based products, and we identified the important mechanisms that need to be improved in the next-generation Earth system models.
Vilna Tyystjärvi, Tiina Markkanen, Leif Backman, Maarit Raivonen, Antti Leppänen, Xuefei Li, Paavo Ojanen, Kari Minkkinen, Roosa Hautala, Mikko Peltoniemi, Jani Anttila, Raija Laiho, Annalea Lohila, Raisa Mäkipää, and Tuula Aalto
EGUsphere, https://doi.org/10.5194/egusphere-2023-3037, https://doi.org/10.5194/egusphere-2023-3037, 2024
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Drainage of boreal peatlands strongly influences soil methane fluxes with important implications to their climatic impacts. Here we simulate methane fluxes in forestry-drained and restored peatlands during the 21st century. We found that restoration turned peatlands to a source of methane but the magnitude varied regionally. In forests, changes in water table level influenced methane fluxes and in general, the sink was weaker under rotational forestry compared to continuous cover forestry.
Shuyue Li, Bonnie Waring, Jennifer Powers, and David Medvigy
Biogeosciences, 21, 455–471, https://doi.org/10.5194/bg-21-455-2024, https://doi.org/10.5194/bg-21-455-2024, 2024
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We used an ecosystem model to simulate primary production of a tropical forest subjected to 3 years of nutrient fertilization. Simulations parameterized such that relative allocation to fine roots increased with increasing soil phosphorus had leaf, wood, and fine root production consistent with observations. However, these simulations seemed to over-allocate to fine roots on multidecadal timescales, affecting aboveground biomass. Additional observations across timescales would benefit models.
Stephen Björn Wirth, Arne Poyda, Friedhelm Taube, Britta Tietjen, Christoph Müller, Kirsten Thonicke, Anja Linstädter, Kai Behn, Sibyll Schaphoff, Werner von Bloh, and Susanne Rolinski
Biogeosciences, 21, 381–410, https://doi.org/10.5194/bg-21-381-2024, https://doi.org/10.5194/bg-21-381-2024, 2024
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In dynamic global vegetation models (DGVMs), the role of functional diversity in forage supply and soil organic carbon storage of grasslands is not explicitly taken into account. We introduced functional diversity into the Lund Potsdam Jena managed Land (LPJmL) DGVM using CSR theory. The new model reproduced well-known trade-offs between plant traits and can be used to quantify the role of functional diversity in climate change mitigation using different functional diversity scenarios.
Joe R. McNorton and Francesca Di Giuseppe
Biogeosciences, 21, 279–300, https://doi.org/10.5194/bg-21-279-2024, https://doi.org/10.5194/bg-21-279-2024, 2024
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Wildfires have wide-ranging consequences for local communities, air quality and ecosystems. Vegetation amount and moisture state are key components to forecast wildfires. We developed a combined model and satellite framework to characterise vegetation, including the type of fuel, whether it is alive or dead, and its moisture content. The daily data is at high resolution globally (~9 km). Our characteristics correlate with active fire data and can inform fire danger and spread modelling efforts.
Brooke A. Eastman, William R. Wieder, Melannie D. Hartman, Edward R. Brzostek, and William T. Peterjohn
Biogeosciences, 21, 201–221, https://doi.org/10.5194/bg-21-201-2024, https://doi.org/10.5194/bg-21-201-2024, 2024
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We compared soil model performance to data from a long-term nitrogen addition experiment in a forested ecosystem. We found that in order for soil carbon models to accurately predict future forest carbon sequestration, two key processes must respond dynamically to nitrogen availability: (1) plant allocation of carbon to wood versus roots and (2) rates of soil organic matter decomposition. Long-term experiments can help improve our predictions of the land carbon sink and its climate impact.
Jan De Pue, Sebastian Wieneke, Ana Bastos, José Miguel Barrios, Liyang Liu, Philippe Ciais, Alirio Arboleda, Rafiq Hamdi, Maral Maleki, Fabienne Maignan, Françoise Gellens-Meulenberghs, Ivan Janssens, and Manuela Balzarolo
Biogeosciences, 20, 4795–4818, https://doi.org/10.5194/bg-20-4795-2023, https://doi.org/10.5194/bg-20-4795-2023, 2023
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The gross primary production (GPP) of the terrestrial biosphere is a key source of variability in the global carbon cycle. To estimate this flux, models can rely on remote sensing data (RS-driven), meteorological data (meteo-driven) or a combination of both (hybrid). An intercomparison of 11 models demonstrated that RS-driven models lack the sensitivity to short-term anomalies. Conversely, the simulation of soil moisture dynamics and stress response remains a challenge in meteo-driven models.
Chad A. Burton, Luigi J. Renzullo, Sami W. Rifai, and Albert I. J. M. Van Dijk
Biogeosciences, 20, 4109–4134, https://doi.org/10.5194/bg-20-4109-2023, https://doi.org/10.5194/bg-20-4109-2023, 2023
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Australia's land-based ecosystems play a critical role in controlling the variability in the global land carbon sink. However, uncertainties in the methods used for quantifying carbon fluxes limit our understanding. We develop high-resolution estimates of Australia's land carbon fluxes using machine learning methods and find that Australia is, on average, a stronger carbon sink than previously thought and that the seasonal dynamics of the fluxes differ from those described by other methods.
Yuan Yan, Anne Klosterhalfen, Fernando Moyano, Matthias Cuntz, Andrew C. Manning, and Alexander Knohl
Biogeosciences, 20, 4087–4107, https://doi.org/10.5194/bg-20-4087-2023, https://doi.org/10.5194/bg-20-4087-2023, 2023
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A better understanding of O2 fluxes, their exchange ratios with CO2 and their interrelations with environmental conditions would provide further insights into biogeochemical ecosystem processes. We, therefore, used the multilayer canopy model CANVEG to simulate and analyze the flux exchange for our forest study site for 2012–2016. Based on these simulations, we further successfully tested the application of various micrometeorological methods and the prospects of real O2 flux measurements.
Jie Zhang, Elisabeth Larsen Kolstad, Wenxin Zhang, Iris Vogeler, and Søren O. Petersen
Biogeosciences, 20, 3895–3917, https://doi.org/10.5194/bg-20-3895-2023, https://doi.org/10.5194/bg-20-3895-2023, 2023
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Manure application to agricultural land often results in large and variable N2O emissions. We propose a model with a parsimonious structure to investigate N transformations around such N2O hotspots. The model allows for new detailed insights into the interactions between transport and microbial activities regarding N2O emissions in heterogeneous soil environments. It highlights the importance of solute diffusion to N2O emissions from such hotspots which are often ignored by process-based models.
Jukka Alm, Antti Wall, Jukka-Pekka Myllykangas, Paavo Ojanen, Juha Heikkinen, Helena M. Henttonen, Raija Laiho, Kari Minkkinen, Tarja Tuomainen, and Juha Mikola
Biogeosciences, 20, 3827–3855, https://doi.org/10.5194/bg-20-3827-2023, https://doi.org/10.5194/bg-20-3827-2023, 2023
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In Finland peatlands cover one-third of land area. For half of those, with 4.3 Mha being drained for forestry, Finland reports sinks and sources of greenhouse gases in forest lands on organic soils following its UNFCCC commitment. We describe a new method for compiling soil CO2 balance that follows changes in tree volume, tree harvests and temperature. An increasing trend of emissions from 1.4 to 7.9 Mt CO2 was calculated for drained peatland forest soils in Finland for 1990–2021.
Siqi Li, Bo Zhu, Xunhua Zheng, Pengcheng Hu, Shenghui Han, Jihui Fan, Tao Wang, Rui Wang, Kai Wang, Zhisheng Yao, Chunyan Liu, Wei Zhang, and Yong Li
Biogeosciences, 20, 3555–3572, https://doi.org/10.5194/bg-20-3555-2023, https://doi.org/10.5194/bg-20-3555-2023, 2023
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Physical soil erosion and particulate carbon, nitrogen and phosphorus loss modules were incorporated into the process-oriented hydro-biogeochemical model CNMM-DNDC to realize the accurate simulation of water-induced erosion and subsequent particulate nutrient losses at high spatiotemporal resolution.
Ivan Cornut, Nicolas Delpierre, Jean-Paul Laclau, Joannès Guillemot, Yann Nouvellon, Otavio Campoe, Jose Luiz Stape, Vitoria Fernanda Santos, and Guerric le Maire
Biogeosciences, 20, 3093–3117, https://doi.org/10.5194/bg-20-3093-2023, https://doi.org/10.5194/bg-20-3093-2023, 2023
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Potassium is an essential element for living organisms. Trees are dependent upon this element for certain functions that allow them to build their trunks using carbon dioxide. Using data from experiments in eucalypt plantations in Brazil and a simplified computer model of the plantations, we were able to investigate the effect that a lack of potassium can have on the production of wood. Understanding nutrient cycles is useful to understand the response of forests to environmental change.
Ivan Cornut, Guerric le Maire, Jean-Paul Laclau, Joannès Guillemot, Yann Nouvellon, and Nicolas Delpierre
Biogeosciences, 20, 3119–3135, https://doi.org/10.5194/bg-20-3119-2023, https://doi.org/10.5194/bg-20-3119-2023, 2023
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After simulating the effects of low levels of potassium on the canopy of trees and the uptake of carbon dioxide from the atmosphere by leaves in Part 1, here we tried to simulate the way the trees use the carbon they have acquired and the interaction with the potassium cycle in the tree. We show that the effect of low potassium on the efficiency of the trees in acquiring carbon is enough to explain why they produce less wood when they are in soils with low levels of potassium.
Xiaojuan Yang, Peter Thornton, Daniel Ricciuto, Yilong Wang, and Forrest Hoffman
Biogeosciences, 20, 2813–2836, https://doi.org/10.5194/bg-20-2813-2023, https://doi.org/10.5194/bg-20-2813-2023, 2023
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We evaluated the performance of a land surface model (ELMv1-CNP) that includes both nitrogen (N) and phosphorus (P) limitation on carbon cycle processes. We show that ELMv1-CNP produces realistic estimates of present-day carbon pools and fluxes. We show that global C sources and sinks are significantly affected by P limitation. Our study suggests that introduction of P limitation in land surface models is likely to have substantial consequences for projections of future carbon uptake.
Kevin R. Wilcox, Scott L. Collins, Alan K. Knapp, William Pockman, Zheng Shi, Melinda D. Smith, and Yiqi Luo
Biogeosciences, 20, 2707–2725, https://doi.org/10.5194/bg-20-2707-2023, https://doi.org/10.5194/bg-20-2707-2023, 2023
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The capacity for carbon storage (C capacity) is an attribute that determines how ecosystems store carbon in the future. Here, we employ novel data–model integration techniques to identify the carbon capacity of six grassland sites spanning the US Great Plains. Hot and dry sites had low C capacity due to less plant growth and high turnover of soil C, so they may be a C source in the future. Alternately, cooler and wetter ecosystems had high C capacity, so these systems may be a future C sink.
Ara Cho, Linda M. J. Kooijmans, Kukka-Maaria Kohonen, Richard Wehr, and Maarten C. Krol
Biogeosciences, 20, 2573–2594, https://doi.org/10.5194/bg-20-2573-2023, https://doi.org/10.5194/bg-20-2573-2023, 2023
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Carbonyl sulfide (COS) is a useful constraint for estimating photosynthesis. To simulate COS leaf flux better in the SiB4 model, we propose a novel temperature function for enzyme carbonic anhydrase (CA) activity and optimize conductances using observations. The optimal activity of CA occurs below 40 °C, and Ball–Woodrow–Berry parameters are slightly changed. These reduce/increase uptakes in the tropics/higher latitudes and contribute to resolving discrepancies in the COS global budget.
Yunyao Ma, Bettina Weber, Alexandra Kratz, José Raggio, Claudia Colesie, Maik Veste, Maaike Y. Bader, and Philipp Porada
Biogeosciences, 20, 2553–2572, https://doi.org/10.5194/bg-20-2553-2023, https://doi.org/10.5194/bg-20-2553-2023, 2023
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We found that the modelled annual carbon balance of biocrusts is strongly affected by both the environment (mostly air temperature and CO2 concentration) and physiology, such as temperature response of respiration. However, the relative impacts of these drivers vary across regions with different climates. Uncertainty in driving factors may lead to unrealistic carbon balance estimates, particularly in temperate climates, and may be explained by seasonal variation of physiology due to acclimation.
Alexander J. Norton, A. Anthony Bloom, Nicholas C. Parazoo, Paul A. Levine, Shuang Ma, Renato K. Braghiere, and T. Luke Smallman
Biogeosciences, 20, 2455–2484, https://doi.org/10.5194/bg-20-2455-2023, https://doi.org/10.5194/bg-20-2455-2023, 2023
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This study explores how the representation of leaf phenology affects our ability to predict changes to the carbon balance of land ecosystems. We calibrate a new leaf phenology model against a diverse range of observations at six forest sites, showing that it improves the predictive capability of the processes underlying the ecosystem carbon balance. We then show how changes in temperature and rainfall affect the ecosystem carbon balance with this new model.
Libo Wang, Vivek K. Arora, Paul Bartlett, Ed Chan, and Salvatore R. Curasi
Biogeosciences, 20, 2265–2282, https://doi.org/10.5194/bg-20-2265-2023, https://doi.org/10.5194/bg-20-2265-2023, 2023
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Plant functional types (PFTs) are groups of plant species used to represent vegetation distribution in land surface models. There are large uncertainties associated with existing methods for mapping land cover datasets to PFTs. This study demonstrates how fine-resolution tree cover fraction and land cover datasets can be used to inform the PFT mapping process and reduce the uncertainties. The proposed largely objective method makes it easier to implement new land cover products in models.
Jennifer A. Holm, David M. Medvigy, Benjamin Smith, Jeffrey S. Dukes, Claus Beier, Mikhail Mishurov, Xiangtao Xu, Jeremy W. Lichstein, Craig D. Allen, Klaus S. Larsen, Yiqi Luo, Cari Ficken, William T. Pockman, William R. L. Anderegg, and Anja Rammig
Biogeosciences, 20, 2117–2142, https://doi.org/10.5194/bg-20-2117-2023, https://doi.org/10.5194/bg-20-2117-2023, 2023
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Unprecedented climate extremes (UCEs) are expected to have dramatic impacts on ecosystems. We present a road map of how dynamic vegetation models can explore extreme drought and climate change and assess ecological processes to measure and reduce model uncertainties. The models predict strong nonlinear responses to UCEs. Due to different model representations, the models differ in magnitude and trajectory of forest loss. Therefore, we explore specific plant responses that reflect knowledge gaps.
Veronika Kronnäs, Klas Lucander, Giuliana Zanchi, Nadja Stadlinger, Salim Belyazid, and Cecilia Akselsson
Biogeosciences, 20, 1879–1899, https://doi.org/10.5194/bg-20-1879-2023, https://doi.org/10.5194/bg-20-1879-2023, 2023
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In a future climate, extreme droughts might become more common. Climate change and droughts can have negative effects on soil weathering and plant health.
In this study, climate change effects on weathering were studied on sites in Sweden using the model ForSAFE, a climate change scenario and an extreme drought scenario. The modelling shows that weathering is higher during summer and increases with global warming but that weathering during drought summers can become as low as winter weathering.
Agustín Sarquis and Carlos A. Sierra
Biogeosciences, 20, 1759–1771, https://doi.org/10.5194/bg-20-1759-2023, https://doi.org/10.5194/bg-20-1759-2023, 2023
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Although plant litter is chemically and physically heterogenous and undergoes multiple transformations, models that represent litter dynamics often ignore this complexity. We used a multi-model inference framework to include information content in litter decomposition datasets and studied the time it takes for litter to decompose as measured by the transit time. In arid lands, the median transit time of litter is about 3 years and has a negative correlation with mean annual temperature.
Qi Guan, Jing Tang, Lian Feng, Stefan Olin, and Guy Schurgers
Biogeosciences, 20, 1635–1648, https://doi.org/10.5194/bg-20-1635-2023, https://doi.org/10.5194/bg-20-1635-2023, 2023
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Understanding terrestrial sources of nitrogen is vital to examine lake eutrophication changes. Combining process-based ecosystem modeling and satellite observations, we found that land-leached nitrogen in the Yangtze Plain significantly increased from 1979 to 2018, and terrestrial nutrient sources were positively correlated with eutrophication trends observed in most lakes, demonstrating the necessity of sustainable nitrogen management to control eutrophication.
Vivek K. Arora, Christian Seiler, Libo Wang, and Sian Kou-Giesbrecht
Biogeosciences, 20, 1313–1355, https://doi.org/10.5194/bg-20-1313-2023, https://doi.org/10.5194/bg-20-1313-2023, 2023
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The behaviour of natural systems is now very often represented through mathematical models. These models represent our understanding of how nature works. Of course, nature does not care about our understanding. Since our understanding is not perfect, evaluating models is challenging, and there are uncertainties. This paper illustrates this uncertainty for land models and argues that evaluating models in light of the uncertainty in various components provides useful information.
Cited articles
Ammann, C.: FLUXNET2015 CH-Oe1 Oensingen grassland, Fluxnet, https://doi.org/10.18140/FLX/1440135, 2020.
Ammann, C., Flechard, C. R., Leifeld, J., Neftel, A., and Fuhrer, J.: The carbon budget
of newly established temperate grassland depends on management intensity, Agric. Ecosyst. Env.,
121, 5–20, https://doi.org/10.1016/j.agee.2006.12.002, 2007.
Ammann, C., Spirig, C., Leifeld, J., and Neftel, A.: Assessment of the nitrogen
and carbon budget of two managed temperate grassland fields, Agric. Ecosyst. Env., 133, 150–162,
https://doi.org/10.1016/j.agee.2009.05.006, 2009.
Ammann, C., Wolff, V., Marx, O., Brümmer, C., and Neftel, A.: Measuring the
biosphere-atmosphere exchange of total reactive nitrogen by eddy covariance, Biogeosciences, 9,
4247–4261, https://doi.org/10.5194/bg-9-4247-2012, 2012.
Amon, B., Kryvoruchko, V., Amon, T., and Zechmeister-Boltenstern, S.: Methane, nitrous
oxide and ammonia emissions during storage and after application of dairy cattle slurry and
influence of slurry treatment, Agric. Ecosyst. Env., 112, 153–162,
https://doi.org/10.1016/j.agee.2005.08.030, 2006.
Aubinet, M., Vesala, T., and Papale, D.: Eddy Covariance: A Practical Guide to
Measurement and Data Analysis, Springer, Dordrecht, 2012.
Bao, C., Li, L., Shi, Y., and Duffy, C.: Understanding watershed hydrogeochemistry:
1. Development of RT-Flux-PIHM, Water Resour. Res., 53, 2328–2345, https://doi.org/10.1002/2016WR018934,
2017.
Behrendt, H., Bach, M., Kunkel, R., Opitz, D., Pagenkopf, W. G., Scholz, G., and
Wendland, F.: Nutrient Emissions into River Basins of Germany on the Basis of a Harmonized
Procedure, available at: http://www.umweltbundesamt.de (last access: July 2020), 2003.
Benettin, P., Queloz, P., Bensimon, M., McDonnell, J. J., and Rinaldo, A.: Velocities,
Residence Times, Tracer Breakthroughs in a Vegetated Lysimeter: A Multitracer Experiment, Water
Resour. Res., 55, 21–33, https://doi.org/10.1029/2018WR023894, 2019
Bergström, L., Johnsson, H., and Torstensson, G.: Simulation of soil nitrogen
dynamics using the SOILN model, Fert. Res., 27, 181–188, https://doi.org/10.1007/BF01051126, 1991.
Brisson, N., Mary, B., Ripoche, D., Jeuffroy, M. H., Ruget, F., Nicoullaud, B., Gate,
P., Devienne-Barret, F., Antonioletti, R., Durr, C., Richard, G., Beaudoin, N., Recous, S., Tayot,
X., Plenet, D., Cellier, P., Machet, J.-M., Meynard, J. M., and Delécolle, R.: STICS: a
generic model for the simulation of crops and their water and nitrogen balances. I. Theory and
parameterization applied to wheat and corn, Agronomie, 18, 311–346, https://doi.org/10.1051/agro:19980501,
1998.
Brisson, N., Ruget, F., Gate, P., Lorgeou, J., Nicoullaud, B., Tayot, X., Plenet, D.,
Jeuffroy, M.-H., Bouthier, A., Ripoche, D., Mary, B., and Justes, E.: STICS: a generic model for
simulating crops and their water and nitrogen balances. II. Model validation for wheat and maize,
Agronomie, 22, 69–92, https://doi.org/10.1051/agro:2001005, 2002.
Brisson, N., Gary, C., Justes, E., Roche, R., Mary, B., Ripoche, D., Zimmer, D.,
Sierra, J., Bertuzzi, P., Burger, P., Bussière, F., Cabidoche, Y. M., Cellier, P., Debaeke,
P., Gaudillère, J. P., Hénault, C., Maraux, F., Seguin, B., and Sinoquet, H.: An overview
of the crop model STICS, Eur. J. Agron., 18, 309–332, https://doi.org/10.1016/S1161-0301(02)00110-7, 2003.
Casson, J. P., Olson, B. M., Little, J. L., and Nolan, S. C.: Assessment of
Environmental Sustainability in Alberta's Agricultural Watersheds Project, Volume 4: Nitrogen loss
in surface runoff, Alberta Agriculture and Rural Development, Lethbridge, Alberta, Canada, 71 pp.,
2008.
Chang, J. F., Viovy, N., Vuichard, N., Ciais, P., Wang, T., Cozic, A., Lardy, R.,
Graux, A.-I., Klumpp, K., Martin, R., and Soussana, J.-F.: Incorporating grassland management in
ORCHIDEE: model description and evaluation at 11 eddy-covariance sites in Europe, Geosci. Model
Dev., 6, 2165–2181, https://doi.org/10.5194/gmd-6-2165-2013, 2013.
Chen, F. and Dudhia, J.: Coupling an Advanced Land Surface–Hydrology Model with the
Penn State–NCAR MM5 Modeling System. Part I: Model Implementation and Sensitivity, Mon. Weather
Rev., 129, 569–585, 2001.
Cremonese, E., Galvagno, M., Morra di Cella, U., and Migliavacca, M.: FLUXNET2015 IT-Tor Torgnon, Dataset, Fluxnet, https://doi.org/10.18140/FLX/1440237, 2020.
Decrem, M., Spiess, E., Richner, W., and Herzog, F.: Impact of Swiss agricultural
policies on nitrate leaching from arable land, Agron. Sustain. Dev., 27, 243–253,
https://doi.org/10.1051/agro:2007012, 2007.
Del Grosso, S. J., Parton, W. J., Mosier, A. R., Ojima, D. S., Kulmala, A. E., and
Phongpan, S.: General model for N2O and N2 gas emissions from soils due to
dentrification, Global Biogeochem. Cy., 14, 1045–1060, https://doi.org/10.1029/1999GB001225, 2000.
Del Grosso, S., Ojima, D., Parton, W., Mosier, A., Peterson, G., and Schimel, D.:
Simulated effects of dryland cropping intensification on soil organic matter and greenhouse gas
exchanges using the DAYCENT ecosystem model, Environ. Pollut., 116, S75–S83,
https://doi.org/10.1016/S0269-7491(01)00260-3, 2002.
Eder, A., Blöschl, G., Feichtinger, F., Herndl, M., Klammler, G., Hösch, J.,
Erhart, E., and Strauss, P.: Indirect nitrogen losses of managed soils contributing to greenhouse
emissions of agricultural areas in Austria: results from lysimeter studies,
Nutr. Cycl. Agroecosyst., 101, 351–364, https://doi.org/10.1007/s10705-015-9682-9, 2015.
EEC: Council Directive 19/676/EEC of 12 December, 1991 concerning the protection of
waters against pollution caused by nitrates from agricultural sources, Official Journal, Brussels, 1991.
EEC: Council Directive 98/83/EC of 3 November 1998 on the quality of water intended for
human consumption, Official Journal, Brussels, 1998.
Fatichi, S.: Tethys-Chloris (T&C) – Terrestrial Biosphere Model – Public release September 2020, Code Ocean, https://doi.org/10.24433/CO.0905087.v1, 2020.
Fatichi, S. and Pappas, C.: Constrained variability of modeled T:ET ratio across
biomes, Geophys. Res. Lett., 44, 6795–6803, https://doi.org/10.1002/2017GL074041, 2017.
Fatichi, S., Ivanov, V. Y., and Caporali, E.: A mechanistic ecohydrological model to
investigate complex interactions in cold and warm water-controlled environments: 1. Theoretical
framework and plot-scale analysis, J. Adv. Model. Earth Syst., 4, M05002,
https://doi.org/10.1029/2011MS000086, 2012a.
Fatichi, S., Ivanov, V. Y., and Caporali, E.: A mechanistic ecohydrological model to
investigate complex interactions in cold and warm water-controlled environments: 2. Spatiotemporal
analyses, J. Adv. Model. Earth Syst., 4, M05003, https://doi.org/10.1029/2011MS000087, 2012b.
Fatichi, S., Zeeman, M. J., Fuhrer, J., and Burlando, P.: Ecohydrological effects of
management on subalpine grasslands: From local to catchment scale, Water Resour. Res., 50,
148–164, https://doi.org/10.1002/2013WR014535, 2014.
Fatichi, S., Katul, G. G., Ivanov, V. Y., Pappas, C., Paschalis, A., Consolo, A., Kim,
J., and Burlando, P.: Abiotic and biotic controls of soil moisture spatiotemporal variability and
the occurrence of hysteresis, Water Resour. Res., 51, 3505–3524, https://doi.org/10.1002/2014WR016102,
2015.
Fatichi, S., Pappas, C., and Ivanov, V. Y.: Modeling plant-water interactions: an
ecohydrological overview from the cell to the global scale, WIRES Water, 3, 327–368,
https://doi.org/10.1002/wat2.1125, 2016.
Fatichi, S., Manzoni, S., Or, D., and Paschalis, A.: A Mechanistic Model of Microbially
Mediated Soil Biogeochemical Processes: A Reality Check, Global Biogeochem. Cy., 33, 2018GB006077,
https://doi.org/10.1029/2018GB006077, 2019.
Feichtinger, F.: STOTRASIM – Ein Modell zur Simulation der Stickstoffdynamik in der
ungesättigten Zone eines Ackerstandortes, Schriftenreihe des Bundesamtes für Wasserwirtschaft, Wien, 1998.
Ferrara, R. M., Trevisiol, P., Acutis, M., Rana, G., Richter, G. M., and Baggaley, N.:
Topographic impacts on wheat yields under climate change: Two contrasted case studies in Europe,
Theor. Appl. Climatol., 99, 53–65, https://doi.org/10.1007/s00704-009-0126-9, 2010.
Filippa, G., Cremonese, E., Galvagno, M., Migliavacca, M., Morra di Cella, U., Petey,
M., and Siniscalco, C.: Five years of phenological monitoring in a mountain grassland:
inter-annual patterns and evaluation of the sampling protocol, Int. J. Biometeorol., 59,
1927–1937, https://doi.org/10.1007/s00484-015-0999-5, 2015.
Finger, R., Gilgen, A. K., Prechsl, U. E., and Buchmann, N.: An economic assessment of
drought effects on three grassland systems in Switzerland, Reg. Environ. Change, 13, 365–374,
https://doi.org/10.1007/s10113-012-0346-x, 2013.
Foken, T.: Die scheinbar ungeschlossene Energiebilanz am Erdboden – eine
Herausforderung an die Experimentelle Meteorologie, Sitzungsberichte der Leibniz-Sozietät, Sitzungsberichte der Leibnitz-Sozietaet, Berlin, 1998.
Foken, T.: The energy balance closure problem: an overview, Ecol. Appl., 18,
1351–1367, https://doi.org/10.1890/06-0922.1, 2008.
Fu, J., Gasche, R., Wang, N., Lu, H., Butterbach-Bahl, K., and Kiese, R.: Impacts of
climate and management on water balance and nitrogen leaching from montane grassland soils of
S-Germany, Environ. Pollut., 229, 119–131, https://doi.org/10.1016/J.ENVPOL.2017.05.071, 2017.
Fu, J., Gasche, R., Wang, N., Lu, H., Butterbach-Bahl, K., and Kiese, R. : Dissolved
organic carbon leaching from montane grasslands under contrasting climate, soil and management
conditions, Biogeochemistry, 145, 47–61, https://doi.org/10.1007/s10533-019-00589-y, 2019.
Gabrielle, B. and Kengni, L.: Analysis and Field-Evaluation of the CERES Models' Soil
Components: Nitrogen Transfer and Transformations, Soil Sci. Soc. Am. J., 60, 142–149,
https://doi.org/10.2136/sssaj1996.03615995006000010023x, 1996.
Gabrielle, B., Menasseri, S., and Houot, S.: Analysis and Field Evaluation of the Ceres
Models Water Balance Component, Soil Sci. Soc. Am. J., 59, 1403–1412,
https://doi.org/10.2136/sssaj1995.03615995005900050029x, 1995.
Galloway, J. N., Dentener, F. J., Capone, D. G., Boyer, E. W., Howarth, R. W.,
Seitzinger, S. P., Asner, G. P., Cleveland, C. C., Green, P. A., Holland, E. A., Karl, D. M.,
Michaels, A. F., Porter, J. H., Townsend, A. R., and Vörösmarty, C. J.: Nitrogen cycles:
Past, present, and future, Biogeochemistry, 70, 153–226, https://doi.org/10.1007/s10533-004-0370-0, 2004.
Galvagno, M., Wohlfahrt, G., Cremonese, E., Rossini, M., Colombo, R., Filippa, G.,
Julitta, T., Manca, G., Siniscalco, C., Morra di Cella, U., and Migliavacca, M.: Phenology and
carbon dioxide source/sink strength of a subalpine grassland in response to an exceptionally short
snow season, Environ. Res. Lett., 8, 025008, https://doi.org/10.1088/1748-9326/8/2/025008, 2013.
Gianelle, D., Vescovo, L., Marcolla, B., Manca, G., and Cescatti, A.: Ecosystem carbon
fluxes and canopy spectral reflectance of a mountain meadow, Int. J. Remote Sens., 30, 435–449,
https://doi.org/10.1080/01431160802314855, 2009.
Gianelle, D., Cavagna, M., Zampedri, R., and Marcolla, B.: FLUXNET2015 IT-MBo Monte Bondone, Dataset, Fluxnet, https://doi.org/10.18140/FLX/1440170, 2020.
Gilgen, A. K. and Buchmann, N.: Response of temperate grasslands at different altitudes
to simulated summer drought differed but scaled with annual precipitation, Biogeosciences, 6,
2525–2539, https://doi.org/10.5194/bg-6-2525-2009, 2009.
Gilmanov, T. G., Soussana, J. F., Aires, L., Allard, V., Ammann, C., Balzarolo, M.,
Barcza, Z., Bernhofer, C., Campbell, C. L., Cernusca, A., Cescatti, A., Clifton-Brown, J., Dirks,
B. O. M., Dore, S., Eugster, W., Fuhrer, J., Gimeno, C., Gruenwald, T., Haszpra, L., Hensen, A., Ibrom, A., Jacobs, A. F. G., Jones, M. B.,
Lenigan, G., Laurila, T., Lohila, A., Manca, G., Marcolla, B., Nagy, Z.,
Pilegaard, K., Pinter, K., Pio, C., Raschi, A., Rogiers, N., Sanz, M. J.,
Stefani, P., Sutton, M., Tuba, Z., Valentini, R., Williams, M. L., and
Wohlfahrt, G.: Partitioning European grassland
net ecosystem CO2 exchange into gross primary productivity and ecosystem respiration using
light response function analysis, Agric. Ecosyst. Env., 121, 93–120,
https://doi.org/10.1016/j.agee.2006.12.008, 2007.
Groenendijk, P., Renaud, L. V., and Roelsma, J.: Prediction of nitrogen and phosphorus
leaching to groundwater and surface waters; process descriptions of the animo4.0 model, Alterra, Wageningen, the Netherlands, 2005.
Groenendijk, P., Heinen, M., Klammler, G., Fank, J., Kupfersberger, H., Pisinaras, V.,
Gemitzi, A., Peña-Haro, S., García-Prats, A., Pulido-Velazquez, M., Perego, A., Acutis,
M., and Trevisan, M.: Performance assessment of nitrate leaching models for highly vulnerable
soils used in low-input farming based on lysimeter data, Sci. Total Environ., 499,
463–480, https://doi.org/10.1016/j.scitotenv.2014.07.002, 2014.
Groh, J., Pütz, T., Jülich, F., Vanderborght, J., and Vereecken, H.: Estimation
of evapotranspiration and crop coefficient of an intensively managed grassland ecosystem with
lysimeter measurements, 16. Gumpensteiner Lysimetertagung 2015, 107–112, available at:
https://www.researchgate.net/publication/275533480 (last access: July 2020), 2015.
Hammerle, A., Haslwanter, A., Tappeiner, U., Cernusca, A., and Wohlfahrt, G.: Leaf area
controls on energy partitioning of a temperate mountain grassland, Biogeosciences, 5, 421–431,
https://doi.org/10.5194/bg-5-421-2008, 2008.
Hansen, S.: Equation Section 1 Daisy, a flexible Soil-Plant-Atmosphere system Model, The Royal Veterinary and Agricultural University, Copenhagen, 2002.
Hansen, S., Jensen, H. E., Nielsen, N. E., and Svendsen, H.: DAISY: Soil plant
atmosphere system model, National Agency for Environmental Protection, Copenhagen, 1990.
Heathwaite, L.: Sources of eutrophication: hydrological pathways of catchment nutrient
export, in: Man's Influence on Freshwater Ecosystems and Water Use (Issue 230), Int. Assoc. Hydrol. Sci., 230, 161–176, 1995.
Hénault, C., Bizouard, F., Laville, P., Gabrielle, B., Nicoullaud, B., Germon,
J. C., and Cellier, P.: Predicting in situ soil N2O emission using NOE algorithm and soil
database, Glob. Change Biol., 11, 115–127, https://doi.org/10.1111/j.1365-2486.2004.00879.x, 2005.
Hörtnagl, L., Feigenwinter, I., Fuchs, K., Merbold, L., Buchmann, N., Eugster, W., and Zeeman, M.: FLUXNET2015 CH-Cha Chamau, Dataset, Fluxnet, https://doi.org/10.18140/FLX/1440131, 2020a.
Hörtnagl, L., Feigenwinter, I., Fuchs, K., Merbold, L., Buchmann, N., Eugster, W., Zeeman, M., Käslin, F., Meier, P., Koller, P., Baur, T., and Pluess, P.: FLUXNET2015 CH-Fru Früebüel. Switzerland, Fluxnet, https://doi.org/10.18140/FLX/1440133, 2020b.
Ibraim, E., Wolf, B., Harris, E., Gasche, R., Wei, J., Yu, L., Kiese, R., Eggleston,
S., Butterbach-Bahl, K., Zeeman, M., Tuzson, B., Emmenegger, L., Six, J., Henne, S., and Mohn, J.:
Attribution of N2O sources in a grassland soil with laser spectroscopy based isotopocule
analysis, Biogeosciences, 16, 3247–3266, https://doi.org/10.5194/bg-16-3247-2019, 2019.
IPCC: IPCC – Task Force on National Greenhouse Gas Inventories, available at:
https://www.ipcc-nggip.iges.or.jp/public/gp/english/ (last access: May 2020), 2000.
IPCC: IPCC – Overview 2 2006 IPCC Guidelines for National Greenhouse Gas Inventories,
available at: http://www.ipcc-nggip.iges.or.jp/ (last access: May 2020), 2006.
Ivanov, V. Y., Bras, R. L., and Vivoni, E. R.: Vegetation-hydrology dynamics in complex
terrain of semiarid areas: 1. A mechanistic approach to modeling dynamic feedbacks, Water
Resour. Res., W03429, 44, https://doi.org/10.1029/2006WR005588, 2008.
Jackson, W. A., Asmussen, L. E., Hauser, E. W., and White, A. W.: Nitrate in Surface
and Subsurface Flow from a Small Agricultural Watershed, J. Environ. Qual., 2, 480–482,
https://doi.org/10.2134/jeq1973.00472425000200040017x, 1973.
Jansson, P. E.: CoupModel: Model Use, Calibration, and Validation, T. ASABE, 55,
1337–1346, https://doi.org/10.13031/2013.42245, 2012.
Keeling, R. F., Piper, S. C., Bollenbacher, A. F., and Walker, J. S.: Atmospheric
CO2 records from sites in the sio air sampling network, in trends: A compendium of data on
global change, in: Trends: A Compendium of Data on Global Change. Carbon Dioxide Information
Analysis Center, Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, TN, 2009.
Kiese, R., Fersch, B., Baessler, C., Brosy, C., Butterbach-Bahl, K., Chwala, C.,
Dannenmann, M., Fu, J., Gasche, R., Grote, R., Jahn, C., Klatt, J., Kunstmann, H., Mauder, M.,
Rödiger, T., Smiatek, G., Soltani, M., Steinbrecher, R., Völksch, I., Werhahn, J., Wolf,
B., Zeeman, M., and Schmid, H. P.: The TERENO Pre-Alpine Observatory: Integrating Meteorological,
Hydrological, and Biogeochemical Measurements and Modeling, Vadose Zone J., 17, 180060,
https://doi.org/10.2136/vzj2018.03.0060, 2018.
Klammler, G., Kupfersberger, H., Rock, G., and Fank, J.: Modeling coupled unsaturated
and saturated nitrate distribution of the aquifer Westliches Leibnitzer Feld, Austria,
Environ. Earth Sci., 69, 663–678, https://doi.org/10.1007/s12665-013-2302-6, 2013.
Kraus, D., Weller, S., Klatt, S., Haas, E., Wassmann, R., Kiese, R., and
Butterbach-Bahl, K.: A new LandscapeDNDC biogeochemical module to predict CH4 and
N2O emissions from lowland rice and upland cropping systems, Plant Soil, 386,
125–149, https://doi.org/10.1007/s11104-014-2255-x, 2014, 2014.
Kroes, J. G. and van Dam, J. C.: Reference Manual SWAP; version 3.0.3, Alterra-rapport 773, ISSN 1566-7197, 2003.
Kronvang, B., Borgvang, S. A., and Barkved, L. J.: Towards European harmonised
procedures for quantification of nutrient losses from diffuse sources – The EUROHARP project,
J. Environ. Monit., 11, 503–505, https://doi.org/10.1039/b902869m, 2009.
Kuhn, T.: The revision of the German Fertiliser Ordinance in 2017 The revision of the
German Fertiliser Ordinance in 2017 Till Kuhn, Institute for Food and Resource Economics, Discussion Paper 2017, 2, 2017.
Kumar, M., Ou, Y. L., and Lin, J. G.: Co-composting of green waste and food waste at
low C/N ratio, Waste Manage., 30, 602–609, https://doi.org/10.1016/j.wasman.2009.11.023, 2010.
Lamarque, P., Tappeiner, U., Turner, C., Steinbacher, M., Bardgett, R. D., Szukics, U.,
Schermer, M., and Lavorel, S.: Stakeholder perceptions of grassland ecosystem services in relation
to knowledge on soil fertility and biodiversity, Reg. Environ. Change, 11, 791–804,
https://doi.org/10.1007/s10113-011-0214-0, 2011.
Li, C. S.: Modeling trace gas emissions from agricultural ecosystems, in: Methane
Emissions from Major Rice Ecosystems in Asia, 259–276, Springer, Dordrecht,
https://doi.org/10.1007/978-94-010-0898-3_20, 2000.
Li, C., Salas, W., Zhang, R., Krauter, C., Rotz, A., and Mitloehner, F.: Manure-DNDC: A
biogeochemical process model for quantifying greenhouse gas and ammonia emissions from livestock
manure systems, Nutr. Cycl. Agroecosyst., 93, 163–200, https://doi.org/10.1007/s10705-012-9507-z, 2012.
Liu, S. M., Xu, Z. W., Wang, W. Z., Jia, Z. Z., Zhu, M. J., Bai, J., and Wang, J. M.: A
comparison of eddy-covariance and large aperture scintillometer measurements with respect to the
energy balance closure problem, Hydrol. Earth Syst. Sci., 15, 1291–1306,
https://doi.org/10.5194/hess-15-1291-2011, 2011.
Lü, X. T., Dijkstra, F. A., Kong, D. L., Wang, Z. W., and Han, X. G.: Plant
nitrogen uptake drives responses of productivity to nitrogen and water addition in a grassland,
Sci. Rep., 4, 1–7, https://doi.org/10.1038/srep04817, 2014.
Mahowald, N., Jickells, T. D., Baker, A. R., Artaxo, P., Benitez-Nelson, C. R.,
Bergametti, G., Bond, T. C., Chen, Y., Cohen, D. D., Herut, B., Kubilay, N., Losno, R., Luo, C.,
Maenhaut, W., McGee, K. A., Okin, G. S., Siefert, R. L., and Tsukuda, S.: Global distribution of
atmospheric phosphorus sources, concentrations and deposition rates, and anthropogenic impacts,
Global Biogeochem. Cy., 22, GB4026, https://doi.org/10.1029/2008GB003240, 2008
Manoli, G., Ivanov, V. Y., and Fatichi, S.: Dry-Season Greening and Water Stress in
Amazonia: The Role of Modeling Leaf Phenology, J. Geophys. Res.-Biogeosci., 123, 1909–1926,
https://doi.org/10.1029/2017JG004282, 2018.
Manzoni, S., Moyano, F., Kätterer, T., and Schimel, J.: Modeling coupled enzymatic
and solute transport controls on decomposition in drying soils, Soil Biol. Biochem., 95, 275–287,
https://doi.org/10.1016/j.soilbio.2016.01.006, 2016.
Marcolla, B., Cescatti, A., Manca, G., Zorer, R., Cavagna, M., Fiora, A., Gianelle, D.,
Rodeghiero, M., Sottocornola, M., and Zampedri, R.: Climatic controls and ecosystem responses
drive the inter-annual variability of the net ecosystem exchange of an alpine meadow,
Agric. Forest Meteorol., 151, 1233–1243, https://doi.org/10.1016/j.agrformet.2011.04.015, 2011.
Mastrotheodoros, T., Pappas, C., Molnar, P., Burlando, P., Hadjidoukas, P., and
Fatichi, S.: Ecohydrological dynamics in the Alps: Insights from a modelling analysis of the
spatial variability, Ecohydrology, 12, e2054, https://doi.org/10.1002/eco.2054, 2019.
Mastrotheodoros, T., Pappas, C., Molnar, P., Burlando, P., Manoli, G., Parajka, J.,
Rigon, R., Szeles, B., Bottazzi, M., Hadjidoukas, P., and Fatichi, S.: More green and less blue
water in the Alps during warmer summers, Nat. Clim. Change, 10, 155–161,
https://doi.org/10.1038/s41558-019-0676-5, 2020.
Mauder, M., Liebethal, C., Göckede, M., Leps, J. P., Beyrich, F., and Foken, T.:
Processing and quality control of flux data during LITFASS-2003, Bound.-Layer Meteorol., 121,
67–88, https://doi.org/10.1007/s10546-006-9094-0, 2006.
Mauder, M., Genzel, S., Fu, J., Kiese, R., Soltani, M., Steinbrecher, R., Zeeman, M.,
Banerjee, T., De Roo, F., and Kunstmann, H.: Evaluation of energy balance closure adjustment
methods by independent evapotranspiration estimates from lysimeters and hydrological simulations,
Hydrol. Process., 32, 39–50, https://doi.org/10.1002/hyp.11397, 2018.
Mauder, M., Foken, T., and Cuxart, J.: Surface-Energy-Balance Closure over Land: A
Review, Bound.-Layer Meteorol., 177, 395–426, https://doi.org/10.1007/s10546-020-00529-6, 2020.
Merbold, L., Eugster, W., Stieger, J., Zahniser, M., Nelson, D., and Buchmann, N.:
Greenhouse gas budget (CO2, CH4 and N2O) of intensively managed
grassland following restoration, Glob. Change Biol., 20, 1913–1928, https://doi.org/10.1111/gcb.12518,
2014.
Migliavacca, M., Galvagno, M., Cremonese, E., Rossini, M., Meroni, M., Sonnentag, O.,
Cogliati, S., Manca, G., Diotri, F., Busetto, L., Cescatti, A., Colombo, R., Fava, F., Morra di
Cella, U., Emiliano, P., Consolata, S., and Richardson, A. D.: Using digital repeat photography
and eddy covariance data to model grasslandphenology and photosynthetic CO2 uptake,
Agric. Forest Meteorol., 151, 1325–1337, 2011.
Millar, D. J., Ewers, B. E., Mackay, D. S., Peckham, S., Reed, D. E., and Sekoni, A.:
Improving ecosystem-scale modeling of evapotranspiration using ecological mechanisms that account
for compensatory responses following disturbance, Water Resour. Res., 53, 7853–7868,
https://doi.org/10.1002/2017WR020823, 2017.
Mittelbach, H., Lehner, I., and Seneviratne, S. I.: Comparison of four soil moisture
sensor types under field conditions in Switzerland, J. Hydrol., 430–431, 39–49,
https://doi.org/10.1016/j.jhydrol.2012.01.041, 2012.
Moorhead, D. L., Sinsabaugh, R. L., Linkins, A. E., and Reynolds, J. F.: Decomposition
processes: Modelling approaches and applications, Sci. Total Environ., 183,
137–149. https://doi.org/10.1016/0048-9697(95)04974-6, 1996.
Niklaus, P. A., Wardle, D. A., and Tate, K. R.: Effects of plant species diversity and
composition on nitrogen cycling and the trace gas balance of soils, Plant Soil, 282, 83–98,
https://doi.org/10.1007/s11104-005-5230-8, 2006.
Nyamangara, J., Piha, M. I., and Kirchmann, H.: Interactions of aerobically decomposed
cattle manure and nitrogen fertilizer applied to soil, Nutr. Cycl. Agroecosyst., 54, 183–188, https://doi.org/10.1023/A:1009794416012, 1999.
Oberholzer, S., Prasuhn, V., and Hund, A.: Crop water use under Swiss pedoclimatic
conditions – Evaluation of lysimeter data covering a seven-year period, Field Crops Res., 211,
48–65, https://doi.org/10.1016/j.fcr.2017.06.003, 2017.
Parton, W. J., Hartman, M., Ojima, D., and Schimel, D.: DAYCENT and its land surface
submodel: Description and testing, Global Planet. Change, 19, 35–48,
https://doi.org/10.1016/S0921-8181(98)00040-X, 1998.
Parton, W. J., Schimel, D. S., Ojima, D. S., and Cole, C. V.:
A generalmodel for soil organic matter dynamics, in: Sensitivity to LitterChemistry,
Texture and Management, edited by: Bryant, R. B. and Arnold, R. W., Quantitative modeling of soil
forming processes, Soil Science Society of America Special Publication, 38, 137–167, 1994.
Pastorello, G., Trotta, C., Canfora, E., et al.: The FLUXNET2015 dataset and the ONEFlux processing
pipeline for eddy covariance data, Sci. Data, 7, 225, https://doi.org/10.1038/s41597-020-0534-3, 2020.
Perego, A., Giussani, A., Sanna, M., and Fumagalli, M.: The ARMOSA simulation crop
model: Overall features, calibration and validation results Space-time mapping and modelling of
soil properties in Mediterranean and Temperate areas View project, Ital. J. Agrometeorol., 18,
23–38, 2013.
Peukert, S., Griffith, B. A., Murray, P. J., Macleod, C. J. A., and Brazier, R. E.:
Intensive Management in Grasslands Causes Diffuse Water Pollution at the Farm Scale,
J. Environ. Qual., 43, 2009–2023, https://doi.org/10.2134/jeq2014.04.0193, 2014.
Phogat, V., Skewes, M. A., Cox, J. W., Alam, J., Grigson, G., and Šimůnek, J.:
Evaluation of water movement and nitrate dynamics in a lysimeter planted with an orange tree,
Agric. Water Manage., 127, 74–84, https://doi.org/10.1016/j.agwat.2013.05.017, 2013.
Prechsl, U. E., Burri, S., Gilgen, A. K., Kahmen, A., and Buchmann, N.: No shift to a
deeper water uptake depth in response to summer drought of two lowland and sub-alpine
C3-grasslands in Switzerland, Oecologia, 177, 97–111, https://doi.org/10.1007/s00442-014-3092-6, 2015.
Pütz, T., Kiese, R., Wollschläger, U., Groh, J., Rupp, H., Zacharias, S.,
Priesack, E., Gerke, H. H., Gasche, R., Bens, O., Borg, E., Baessler, C., Kaiser, K., Herbrich,
M., Munch, J., Sommer, M., Vogel, H., Vanderborght, J., and Vereecken, H.: TERENO-SOILCan: a lysimeter-network in Germany observing soil
processes and plant diversity influenced by climate change, Environ. Earth Sci., 75, 1242,
https://doi.org/10.1007/s12665-016-6031-5, 2016.
Pütz, T., Fank, J., and Flury, M.: Lysimeters in Vadose Zone Research, Vadose Zone
J., 17, 1–4, https://doi.org/10.2136/vzj2018.02.0035, 2018.
Richter, G. M., Acutis, M., Trevisiol, P., Latiri, K., and Confalonieri, R.:
Sensitivity analysis for a complex crop model applied to Durum wheat in the Mediterranean,
Eur. J. Agron., 32, 127–136, https://doi.org/10.1016/j.eja.2009.09.002, 2010.
Robertson, A. D., Paustian, K., Ogle, S., Wallenstein, M. D., Lugato, E., and Cotrufo,
M. F.: Unifying soil organic matter formation and persistence frameworks: the MEMS model,
Biogeosciences, 16, 1225–1248, https://doi.org/10.5194/bg-16-1225-2019, 2019.
Sala, O. E. and Paruelo, J. M.: Ecosystem services in grasslands, in: Nature's
services: societal dependence on natural ecosystems, edited by: Daily, G. C., Nature's Services: Societal Dependence
on Natural Ecosystems, Island Press, Washington, DC, USA, 237–251, 1997.
Saxton, K. E. and Rawls, W. J.: Soil Water Characteristic Estimates by Texture and
Organic Matter for Hydrologic Solutions, Soil Sci. Soc. Am. J., 70, 1569–1578,
https://doi.org/10.2136/sssaj2005.0117, 2006.
Schirpke, U., Kohler, M., Leitinger, G., Fontana, V., Tasser, E., and Tappeiner, U.:
Future impacts of changing land-use and climate on ecosystem services of mountain grassland and
their resilience, Ecosyst. Serv., 26, 79–94, https://doi.org/10.1016/j.ecoser.2017.06.008, 2017.
Schlingmann, M., Tobler, U., Berauer, B., Garcia-Franco, N., Wilfahrt, P., Wiesmeier,
M., Jentsch, A., Wolf, B., Kiese, R., and Dannenmann, M.: Intensive slurry management and climate
change promote nitrogen mining from organic matter-rich montane grassland soils, Plant Soil, 456,
81–98, https://doi.org/10.1007/s11104-020-04697-9, 2020.
Schoen, R., Gaudet, J. P., and Bariac, T.: Preferential flow and solute transport in a
large lysimeter, under controlled boundary conditions, J. Hydrol., 215, 70–81,
https://doi.org/10.1016/S0022-1694(98)00262-5, 1999.
Shajari, F., Einsiedl, F., and Rein, A.: Characterizing Water Flow in Vegetated
Lysimeters with Stable Water Isotopes and Modeling, Groundwater, 58, 759–770,
https://doi.org/10.1111/gwat.12970, 2019.
Shi, Y., Davis, K. J., Duffy, C. J., and Yu, X.: Development of a Coupled Land Surface
Hydrologic Model and Evaluation at a Critical Zone Observatory, J. Hydrometeorol., 14, 1401–1420,
https://doi.org/10.1175/JHM-D-12-0145.1, 2013.
Siderius C., Groenendijk, P.,
van Gerven, L. P. A., Jeuken, M. H. J. L., and Smit, A. A. M. F. R.: Process
description of NuswaLite; a simplified model for the fate of
nutrients in surface waters, Alterra Report 1226.2, Alterra,
Wageningen, 2008.
Simmelsgaard, S. E. and Djurhuus, J.: An empirical model for estimating nitrate
leaching as affected by crop type and the long-term N fertilizer rate, Soil Use Manage., 14,
37–43, https://doi.org/10.1111/j.1475-2743.1998.tb00608.x, 1998.
Smit, A. A. M. F. R., Siderius, C., and van Gerven, L. P. A.:
Process description of SWQN, A simplified hydraulic
model, Report 1226.1, Alterra, Wageningen, 2009.
Smith, W., Grant, B., Qi, Z., He, W., VanderZaag, A., Drury, C. F., and Helmers, M.:
Development of the DNDC model to improve soil hydrology and incorporate mechanistic tile drainage:
A comparative analysis with RZWQM2, Environ. Model. Softw., 123, 104577,
https://doi.org/10.1016/j.envsoft.2019.104577, 2020.
Sohier, C., Degre, A., and Dautrebande, S.: From root zone modelling to regional
forecasting of nitrate concentration in recharge flows – The case of the Walloon Region
(Belgium), Elsevier, available at:
https://www.sciencedirect.com/science/article/pii/S0022169409001218 (last access: May 2020), 2009.
Sommerfeldt, T. G., Chang, C., and Entz, T.: Long-term Annual Manure Applications
Increase Soil Organic Matter and Nitrogen, and Decrease Carbon to Nitrogen Ratio, Soil
Sci. Soc. Am. J., 52, 1668–1672, https://doi.org/10.2136/sssaj1988.03615995005200060030x, 1988.
Spehn, E. M., Hector, A., Joshi, J., Scherer-Lorenzen, M., Schmid, B., Bazeley-White,
E., Beierkuhnlein, C., Caldeira, M. C., Diemer, M., Dimitrakopoulos, P. G., Finn, J. A., Freitas,
H., Giller, P. S., Good, J., Harris, R., Högberg, P., Huss-Danell, K., Jumpponen, A.,
Koricheva, J., Leadley, P. W., Loreau, M., Minns, A., Mulder, C. P. H.,
O'Donovan, G., Otway, S. J., Palmborg, C., Pereira, J. S.,
Pfisterer, A. B., Prinz, A., Read, D. J., Schulze, E.-D.,
Siamantziouras, A.-S. D., Terry, A. C., Troumbis, A. Y., Woodward, F. I.,
Yachi, S., and Lawton, J. H.: Ecosystem
effects of biodiversity manipulations in european grasslands, Ecol. Monogr., 75, 37–63,
https://doi.org/10.1890/03-4101, 2005.
Stenitzer, E.: Ein numerisches Modell zur
Simulation des Bodenwasserhaushaltes und des
Pflanzenertrages eines Standortes, Mitt. Bundesanstalt
Kulturtech. Bodenwasserhaushalt 31, 201 pp., 1988.
Swiss Federal Council: Verordnung vom 23. Oktober 2013 über die Direktzahlungen an
die Landwirtschaft (Direktzahlungsverordnung, DZV), available at:
https://www.admin.ch/opc/de/classified-compilation/20130216/index.html (last access: May 2020), 1998.
Tafteh, A. and Sepaskhah, A. R.: Application of HYDRUS-1D model for simulating water
and nitrate leaching from continuous and alternate furrow irrigated rapeseed and maize fields,
Agric. Water Manage., 113, 19–29, https://doi.org/10.1016/j.agwat.2012.06.011, 2012.
Tague, C. L., McDowell, N. G., and Allen, C. D.: An Integrated Model of Environmental
Effects on Growth, Carbohydrate Balance, and Mortality of Pinus ponderosa Forests in the Southern
Rocky Mountains, PLoS ONE, 8, e80286, https://doi.org/10.1371/journal.pone.0080286, 2013.
Takruri, M., Rajasegarar, S., Challa, S., Leckie, C., and Palaniswami, M.:
Spatio-temporal modelling-based drift-aware wireless sensor networks, IET Wireless Sens. Syst., 1,
110–122, https://doi.org/10.1049/iet-wss.2010.0091, 2011.
Tilman, D., Wedin, D., and Knops, J.: Productivity and sustainability influenced by
biodiversity in grassland ecosystems, Nature, 379, 718–720, https://doi.org/10.1038/379718a0, 1996.
Van Dam, J. C.: Field-scale water flow and solute transport: SWAP model concepts,
parameter estimation and case studies, Wageningen University, Wageningen, 2000.
Velthof, G. L., Lesschen, J. P., Schils, R. L. M., Smit, A., Elbersen, B. S., Hazeu,
G. W., Mucher, C. A., and Oenema, O.: Grassland areas, production and use. Lot 2. Methodological
studies in the field of Agro-Environmental
Indicators, European Commission, Wageningen, 2014.
Vescovo, L. and Gianelle, D.: Using the MIR bands in vegetation indices for the
estimation of grassland biophysical parameters from satellite remote sensing in the Alps region of
Trentino (Italy), Adv. Space Res., 41, 1764–1772, https://doi.org/10.1016/j.asr.2007.07.043, 2008.
Vet, R., Artz, R. S., Carou, S., Shaw, M., Ro, C. U., Aas, W., Baker, A., Bowersox,
V. C., Dentener, F., Galy-Lacaux, C., Hou, A., Pienaar, J. J., Gillett, R., Forti, M. C., Gromov,
S., Hara, H., Khodzher, T., Mahowald, N. M., Nickovic, S., Rao, P. S. P., and Reid, N. W.: A global assessment of precipitation chemistry and deposition of
sulfur, nitrogen, sea salt, base cations, organic acids, acidity and pH, and phosphorus,
Atmos. Environ., 93, 3–100, https://doi.org/10.1016/j.atmosenv.2013.10.060, 2014.
Wang, C., Chen, Z., Unteregelsbacher, S., Lu, H., Gschwendtner, S., Gasche, R., Kolar,
A., Schloter, M., Kiese, R., Butterbach-Bahl, K., and Dannenmann, M.: Climate change amplifies
gross nitrogen turnover in montane grasslands of Central Europe in both summer and winter seasons,
Glob, Change Biol., 22, 2963–2978, https://doi.org/10.1111/gcb.13353, 2016.
Widmoser, P. and Wohlfahrt, G.: Attributing the energy imbalance by concurrent
lysimeter and eddy covariance evapotranspiration measurements, Agric. Forest Meteorol., 263,
287–291, https://doi.org/10.1016/j.agrformet.2018.09.003, 2018.
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,
https://doi.org/10.1038/nclimate1951, 2013.
Williams, J., Jones, C., and Dyke, P. T.: A modeling approach to determining the
relationship between erosion and soil productivity, T. ASAE, 27, 129–144,
https://doi.org/10.13031/2013.32748, 1984.
Wilson, K., Goldstein, A., Falge, E., Aubinet, M., Baldocchi, D., Berbigier, P.,
Bernhofer, C., Ceulemans, R., Dolman, H., Field, C., Grelle, A., Ibrom, A., Law, B. E., Kowalski,
A., Meyers, T., Moncrieff, J., Monson, R., Oechel, W., Tenhunen, J., Valentini, R., and Verma, S.: Energy balance closure at FLUXNET sites, Agric. Forest Meteorol.,
113, 223–243, https://doi.org/10.1016/S0168-1923(02)00109-0, 2002.
Wohlfahrt, G., Anderson-Dunn, M., Bahn, M., Balzarolo, M., Berninger, F., Campbell,
C., Carrara, A., Cescatti, A., Christensen, T., Dore, S., Eugster, W., Friborg, T., Furger, M.,
Gianelle, D., Gimeno, C., Hargreaves, K., Hari, P., Haslwanter, A., Johansson, T.,
Marcolla, B., Milford, C., Nagy, Z., Nemitz, E.,
Rogiers, N., Sanz, M. J., Siegwolf, R. T. W., Susiluoto, S., Sutton, M.,
Tuba, Z., Ugolini, F., Valentini, R., Zorer, R., and Cernusca, A.: Biotic, abiotic, and management
controls on the net ecosystem CO2 exchange of European mountain grassland ecosystems,
Ecosystems, 11, 1338–1351, https://doi.org/10.1007/s10021-008-9196-2, 2008a.
Wohlfahrt, G., Hammerle, A., Haslwanter, A., Bahn, M., Tappeiner, U., and Cernusca,
A.: Seasonal and inter-annual variability of the net ecosystem CO2 exchange of a
temperate mountain grassland: Effects of weather and management, J. Geophys. Res., 113, D8,
https://doi.org/10.1029/2007JD009286, 2008b.
Wohlfahrt, G., Irschick, C., Thalinger, B., Hörtnagl, L., Obojes, N., and
Hammerle, A.: Insights from Independent Evapotranspiration Estimates for Closing the Energy
Balance: A Grassland Case Study, Vadose Zone J., 9, 1025–1033, https://doi.org/10.2136/vzj2009.0158, 2010.
Wohlfahrt, G., Hammerle, A., and Hörtnagl, L.: FLUXNET2015 AT-Neu Neustift, Dataset, Fluxnet, https://doi.org/10.18140/FLX/1440121, 2020.
Wolf, B., Chwala, C., Fersch, B., Garvelmann, J., Junkermann, W., Zeeman, M. J.,
Angerer, A., Adler, B., Beck, C., Brosy, C., Brugggger, P., Emeis, S., Dannenmann, M., De Roo, F.,
Diaz-Pines, E., Haas, E., Hagen, M., Hajnsek, I., Jacobeit, J., Jagdhuber, T., Kalthoff, N.,
Kiese, R., Kunstmann, H., Kosak, O., Krieg, R., Malchow, C., Mauder, M., Merz, R.,
Notarnicola, C., Philipp, A., Reif, W., Reineke, S., Rödiger, T., Ruehr, N., Schäfer, K., Schrön, M., Senatore,
A., Shupe, H., Völksch, I., Wanninger, C., Zacharias, S., and Schmid, H. P.: The scalex campaign: Scale-crossing land surface and boundary
layer processes in the TERENO-prealpine observatory, B. Am. Meteorol. Soc., 98, 1217–1234,
https://doi.org/10.1175/BAMS-D-15-00277.1, 2017.
Yu, L., Fatichi, S., Zeng, Y., and Su, Z.: The role of vadose zone physics in the
ecohydrological response of a Tibetan meadow to freeze–thaw cycles, The Cryosphere, 14, 4653–4673,
https://doi.org/10.5194/tc-14-4653-2020, 2020.
Zacharias, S., Bogena, H., Samaniego, L., Mauder, M., Fuß, R., Pütz, T.,
Frenzel, M., Schwank, M., Baessler, C., Butterbach-Bahl, K., Bens, O., Borg, E., Brauer, A.,
Dietrich, P., Hajnsek, I., Helle, G., Kiese, R., Kunstmann, H., Klotz, S., and Vereecken, H.: A
Network of Terrestrial Environmental Observatories in Germany, Vadose Zone J., 10, 955–973,
https://doi.org/10.2136/vzj2010.0139, 2011.
Zeeman, M.: Meteorology, environment and surface flux data for grassland sites in Germany, Zenodo, https://doi.org/10.5281/zenodo.4267887, 2020.
Zeeman, M. and Ruehr, N.: Management and plant physiology data for grassland sites in Germany, Zenodo, https://doi.org/10.5281/zenodo.4267810, 2020.
Zeeman, M. J., Hiller, R., Gilgen, A. K., Michna, P., Plüss, P., Buchmann, N., and
Eugster, W.: Management and climate impacts on net CO2 fluxes and carbon budgets of three
grasslands along an elevational gradient in Switzerland, Agric. Forest Meteorol., 150, 519–530,
https://doi.org/10.1016/j.agrformet.2010.01.011, 2010.
Zeeman, M. J., Mauder, M., Steinbrecher, R., Heidbach, K., Eckart, E., and Schmid,
H. P.: Reduced snow cover affects productivity of upland temperate grasslands, Agric. Forest
Meteorol., 232, 514–526, https://doi.org/10.1016/j.agrformet.2016.09.002, 2017.
Zeeman, M. J., Shupe, H., Baessler, C., and Ruehr, N. K.: Productivity and vegetation
structure of three differently managed temperate grasslands, Agric. Ecosyst. Env., 270–271,
129–148, https://doi.org/10.1016/j.agee.2018.10.003, 2019.
Zhu, N.: Effect of low initial C/N ratio on aerobic composting of swine manure with
rice straw, Biores. Technol., 98, 9–13, https://doi.org/10.1016/j.biortech.2005.12.003, 2007.
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