Articles | Volume 15, issue 1
https://doi.org/10.5194/bg-15-349-2018
© Author(s) 2018. 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-15-349-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Preface: OzFlux: a network for the study of ecosystem carbon and water dynamics across Australia and New Zealand
Eva van Gorsel
CORRESPONDING AUTHOR
Fenner School of Environment and Society, The Australian National
University, ACT, Canberra, Australia
James Cleverly
School of Life Sciences, University of Technology Sydney, Broadway,
NSW, 2007, Australia
Jason Beringer
The UWA School of Agriculture and Environment, The University of
Western Australia, Crawley, WA, 6020, Australia
Helen Cleugh
CSIRO Climate Science Centre, Canberra, 2601, Australia
Derek Eamus
School of Life Sciences, University of Technology Sydney, Broadway,
NSW, 2007, Australia
Lindsay B. Hutley
Research Institute for the Environment and Livelihoods, Charles
Darwin University, Darwin, NT 0909 Australia
Peter Isaac
OzFlux, Melbourne, VIC 3159, Australia
Suzanne Prober
CSIRO Land and Water, Floreat, 6913, Australia
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Bimal K. Bhattacharya, Kaniska Mallick, Devansh Desai, Ganapati S. Bhat, Ross Morrison, Jamie R. Clevery, William Woodgate, Jason Beringer, Kerry Cawse-Nicholson, Siyan Ma, Joseph Verfaillie, and Dennis Baldocchi
Biogeosciences, 19, 5521–5551, https://doi.org/10.5194/bg-19-5521-2022, https://doi.org/10.5194/bg-19-5521-2022, 2022
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Evaporation retrieval in heterogeneous ecosystems is challenging due to empirical estimation of ground heat flux and complex parameterizations of conductances. We developed a parameter-sparse coupled ground heat flux-evaporation model and tested it across different limits of water stress and vegetation fraction in the Northern/Southern Hemisphere. The model performed particularly well in the savannas and showed good potential for evaporative stress monitoring from thermal infrared satellites.
Remko C. Nijzink, Jason Beringer, Lindsay B. Hutley, and Stanislaus J. Schymanski
Geosci. Model Dev., 15, 883–900, https://doi.org/10.5194/gmd-15-883-2022, https://doi.org/10.5194/gmd-15-883-2022, 2022
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The Vegetation Optimality Model (VOM) is a coupled water–vegetation model that predicts vegetation properties rather than determines them based on observations. A range of updates to previous applications of the VOM has been made for increased generality and improved comparability with conventional models. This showed that there is a large effect on the simulated water and carbon fluxes caused by the assumption of deep groundwater tables and updated soil profiles in the model.
Remko C. Nijzink, Jason Beringer, Lindsay B. Hutley, and Stanislaus J. Schymanski
Hydrol. Earth Syst. Sci., 26, 525–550, https://doi.org/10.5194/hess-26-525-2022, https://doi.org/10.5194/hess-26-525-2022, 2022
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Most models that simulate water and carbon exchanges with the atmosphere rely on information about vegetation, but optimality models predict vegetation properties based on general principles. Here, we use the Vegetation Optimality Model (VOM) to predict vegetation behaviour at five savanna sites. The VOM overpredicted vegetation cover and carbon uptake during the wet seasons but also performed similarly to conventional models, showing that vegetation optimality is a promising approach.
Atbin Mahabbati, Jason Beringer, Matthias Leopold, Ian McHugh, James Cleverly, Peter Isaac, and Azizallah Izady
Geosci. Instrum. Method. Data Syst., 10, 123–140, https://doi.org/10.5194/gi-10-123-2021, https://doi.org/10.5194/gi-10-123-2021, 2021
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We reviewed eight algorithms to estimate missing values of environmental drivers and three major fluxes in eddy covariance time series. Overall, machine-learning algorithms showed superiority over the rest. Among the top three models (feed-forward neural networks, eXtreme Gradient Boost, and random forest algorithms), the latter showed the most solid performance in different scenarios.
Sophie V. J. van der Horst, Andrew J. Pitman, Martin G. De Kauwe, Anna Ukkola, Gab Abramowitz, and Peter Isaac
Biogeosciences, 16, 1829–1844, https://doi.org/10.5194/bg-16-1829-2019, https://doi.org/10.5194/bg-16-1829-2019, 2019
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Measurements of surface fluxes are taken around the world and are extremely valuable for understanding how the land and atmopshere interact, and how the land can amplify temerature extremes. However, do these measurements sample extreme temperatures, or are they biased to the average? We examine this question and highlight data that do measure surface fluxes under extreme conditions. This provides a way forward to help model developers improve their models.
Rizwana Rumman, James Cleverly, Rachael H. Nolan, Tonantzin Tarin, and Derek Eamus
Hydrol. Earth Syst. Sci., 22, 4875–4889, https://doi.org/10.5194/hess-22-4875-2018, https://doi.org/10.5194/hess-22-4875-2018, 2018
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Groundwater is a significant water resource for humans and for groundwater-dependent vegetation. Several challenges to managing both groundwater resources and dependent vegetation include defining the location of dependent vegetation, the rate of groundwater use, and the depth of roots accessing groundwater. In this study we demonstrate a novel application of measurements of stable isotopes of carbon that can be used to identify the location, the rooting depth, and the rate of groundwater use.
Philipp A. Nauer, Eleonora Chiri, David de Souza, Lindsay B. Hutley, and Stefan K. Arndt
Biogeosciences, 15, 3731–3742, https://doi.org/10.5194/bg-15-3731-2018, https://doi.org/10.5194/bg-15-3731-2018, 2018
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Termites perform important biogeochemical processes in tropical ecosystems, but the complex structure of their mounds impede an accurate quantitative description. We present two novel low-cost field methods, based on photogrammetry and image analysis, to quantify the volume, surface area and porosities of termite mounds. The methods are accurate, rapid to apply and superior to traditional methods, and thus improve biogeochemical rate estimates such as greenhouse-gas fluxes from termite mounds.
Alexandre A. Renchon, Anne Griebel, Daniel Metzen, Christopher A. Williams, Belinda Medlyn, Remko A. Duursma, Craig V. M. Barton, Chelsea Maier, Matthias M. Boer, Peter Isaac, David Tissue, Victor Resco de Dios, and Elise Pendall
Biogeosciences, 15, 3703–3716, https://doi.org/10.5194/bg-15-3703-2018, https://doi.org/10.5194/bg-15-3703-2018, 2018
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We report the seasonality of net ecosystem–atmosphere CO2 exchange (NEE) in a temperate evergreen broadleaved forest in Sydney, Australia. We investigated how carbon exchange varied with climatic drivers and canopy dynamics (leaf area index, litter fall). We found that our site acted as a net source of carbon in summer and a net sink in winter. Ecosystem respiration (ER) drove NEE seasonality, as the seasonal amplitude of ER was greater than gross primary productivity.
Henrique Fürstenau Togashi, Iain Colin Prentice, Owen K. Atkin, Craig Macfarlane, Suzanne M. Prober, Keith J. Bloomfield, and Bradley John Evans
Biogeosciences, 15, 3461–3474, https://doi.org/10.5194/bg-15-3461-2018, https://doi.org/10.5194/bg-15-3461-2018, 2018
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Ecosystem models commonly assume that photosynthetic traits, such as carboxylation capacity measured at a standard temperature, are constant in time and therefore do not acclimate. Optimality hypotheses suggest this assumption may be incorrect. We investigated acclimation by carrying out measurements on woody species during distinct seasons in Western Australia. Our study shows evidence that carboxylation capacity should acclimate so that it increases somewhat with growth temperature.
Rhys Whitley, Jason Beringer, Lindsay B. Hutley, Gabriel Abramowitz, Martin G. De Kauwe, Bradley Evans, Vanessa Haverd, Longhui Li, Caitlin Moore, Youngryel Ryu, Simon Scheiter, Stanislaus J. Schymanski, Benjamin Smith, Ying-Ping Wang, Mathew Williams, and Qiang Yu
Biogeosciences, 14, 4711–4732, https://doi.org/10.5194/bg-14-4711-2017, https://doi.org/10.5194/bg-14-4711-2017, 2017
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This paper attempts to review some of the current challenges faced by the modelling community in simulating the behaviour of savanna ecosystems. We provide a particular focus on three dynamic processes (phenology, root-water access, and fire) that are characteristic of savannas, which we believe are not adequately represented in current-generation terrestrial biosphere models. We highlight reasons for these misrepresentations, possible solutions and a future direction for research in this area.
Nina Hinko-Najera, Peter Isaac, Jason Beringer, Eva van Gorsel, Cacilia Ewenz, Ian McHugh, Jean-François Exbrayat, Stephen J. Livesley, and Stefan K. Arndt
Biogeosciences, 14, 3781–3800, https://doi.org/10.5194/bg-14-3781-2017, https://doi.org/10.5194/bg-14-3781-2017, 2017
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We undertook a 3-year study (2010–2012) of eddy covariance measurements in a dry temperate eucalypt (broadleaf evergreen) forest in southeastern Australia. The forest was a large and constant carbon sink, with the greatest uptake in early spring and summer. A strong seasonal pattern in environmental controls of daytime and night-time NEE was revealed. Our results show the potential of temperate eucalypt forests to sequester large amounts of carbon when not water limited.
Eduardo Eiji Maeda, Xuanlong Ma, Fabien Hubert Wagner, Hyungjun Kim, Taikan Oki, Derek Eamus, and Alfredo Huete
Earth Syst. Dynam., 8, 439–454, https://doi.org/10.5194/esd-8-439-2017, https://doi.org/10.5194/esd-8-439-2017, 2017
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The Amazon River basin continuously transfers massive volumes of water from the land surface to the atmosphere, thereby having massive influence on global climate patterns. Nonetheless, the characteristics of ET across the Amazon basin, as well as the relative contribution of the multiple drivers to this process, are still uncertain. This study carries out a water balance approach to analyse seasonal patterns in ET and their relationships with water and energy drivers across the Amazon Basin.
Ian D. McHugh, Jason Beringer, Shaun C. Cunningham, Patrick J. Baker, Timothy R. Cavagnaro, Ralph Mac Nally, and Ross M. Thompson
Biogeosciences, 14, 3027–3050, https://doi.org/10.5194/bg-14-3027-2017, https://doi.org/10.5194/bg-14-3027-2017, 2017
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We analysed a 3-year record of CO2 exchange at a eucalypt woodland and found that substantial nocturnal advective CO2 losses occurred, thus requiring correction. We demonstrated that the most common of these correction methods incurred substantial bias in long-term estimates of carbon balance if storage of CO2 below the measurement height was excluded. This is important because the majority of sites both in Australia and internationally lack such measurements.
Peter Isaac, James Cleverly, Ian McHugh, Eva van Gorsel, Cacilia Ewenz, and Jason Beringer
Biogeosciences, 14, 2903–2928, https://doi.org/10.5194/bg-14-2903-2017, https://doi.org/10.5194/bg-14-2903-2017, 2017
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Networks of flux towers present diverse challenges to data collectors, managers and users. For data collectors, the goal is to minimise the time spent producing usable data sets. For data managers, the challenge is making data available in a timely and broad manner. For data users, the quest is for consistency in data processing across sites and networks. The OzFlux data path was developed to address these disparate needs and serves as an example of intra- and inter-network integration.
Jason Beringer, Ian McHugh, Lindsay B. Hutley, Peter Isaac, and Natascha Kljun
Biogeosciences, 14, 1457–1460, https://doi.org/10.5194/bg-14-1457-2017, https://doi.org/10.5194/bg-14-1457-2017, 2017
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Standardised, quality-controlled and robust data from flux networks underpin the understanding of ecosystem processes and tools to manage our natural resources. The Dynamic INtegrated Gap-filling and partitioning for OzFlux (DINGO) system enables gap-filling and partitioning of fluxes and subsequently provides diagnostics and results. Quality data from robust systems like DINGO ensure the utility and uptake of flux data and facilitates synergies between flux, remote sensing and modelling.
Cassandra Denise Wilks Rogers and Jason Beringer
Biogeosciences, 14, 597–615, https://doi.org/10.5194/bg-14-597-2017, https://doi.org/10.5194/bg-14-597-2017, 2017
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Savannas are extensive yet sensitive to variability in precipitation. We examined the relationship between climate phenomena and historical rainfall variability across Australian savannas using 16 climate indicies. Seasonal variation was most correlated with the Australian Monsoon Index, whereas interannual variability was related to a greater number of phenomena. Rainfall variability and the underlying climate processes driving variability are important.
Caitlin E. Moore, Jason Beringer, Bradley Evans, Lindsay B. Hutley, and Nigel J. Tapper
Biogeosciences, 14, 111–129, https://doi.org/10.5194/bg-14-111-2017, https://doi.org/10.5194/bg-14-111-2017, 2017
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Separating tree and grass productivity dynamics in savanna ecosystems is vital for understanding how they function over time. We showed how tree-grass phenology information can improve model estimates of gross primary productivity in an Australian tropical savanna. Our findings will contribute towards improved modelling of productivity in savannas, which will assist with their management into the future.
Mila Bristow, Lindsay B. Hutley, Jason Beringer, Stephen J. Livesley, Andrew C. Edwards, and Stefan K. Arndt
Biogeosciences, 13, 6285–6303, https://doi.org/10.5194/bg-13-6285-2016, https://doi.org/10.5194/bg-13-6285-2016, 2016
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Northern Australian savanna landscapes are a region earmarked for potential agricultural expansion. Greenhouse gas emissions from savanna land use change were quantified to determine the relative impact of increased rates of deforestation on Australia's national greenhouse gas accounts. Emissions from historic rates of deforestation were similar to savanna burning, but expanded clearing across northern Australia could add 3 % to Australia’s national greenhouse gas emissions.
Eva van Gorsel, Sebastian Wolf, James Cleverly, Peter Isaac, Vanessa Haverd, Cäcilia Ewenz, Stefan Arndt, Jason Beringer, Víctor Resco de Dios, Bradley J. Evans, Anne Griebel, Lindsay B. Hutley, Trevor Keenan, Natascha Kljun, Craig Macfarlane, Wayne S. Meyer, Ian McHugh, Elise Pendall, Suzanne M. Prober, and Richard Silberstein
Biogeosciences, 13, 5947–5964, https://doi.org/10.5194/bg-13-5947-2016, https://doi.org/10.5194/bg-13-5947-2016, 2016
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Temperature extremes are expected to become more prevalent in the future and understanding ecosystem response is crucial. We synthesised measurements and model results to investigate the effect of a summer heat wave on carbon and water exchange across three biogeographic regions in southern Australia. Forests proved relatively resilient to short-term heat extremes but the response of woodlands indicates that the carbon sinks of large areas of Australia may not be sustainable in a future climate.
Jason Beringer, Lindsay B. Hutley, Ian McHugh, Stefan K. Arndt, David Campbell, Helen A. Cleugh, James Cleverly, Víctor Resco de Dios, Derek Eamus, Bradley Evans, Cacilia Ewenz, Peter Grace, Anne Griebel, Vanessa Haverd, Nina Hinko-Najera, Alfredo Huete, Peter Isaac, Kasturi Kanniah, Ray Leuning, Michael J. Liddell, Craig Macfarlane, Wayne Meyer, Caitlin Moore, Elise Pendall, Alison Phillips, Rebecca L. Phillips, Suzanne M. Prober, Natalia Restrepo-Coupe, Susanna Rutledge, Ivan Schroder, Richard Silberstein, Patricia Southall, Mei Sun Yee, Nigel J. Tapper, Eva van Gorsel, Camilla Vote, Jeff Walker, and Tim Wardlaw
Biogeosciences, 13, 5895–5916, https://doi.org/10.5194/bg-13-5895-2016, https://doi.org/10.5194/bg-13-5895-2016, 2016
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OzFlux is the regional Australian and New Zealand flux tower network that aims to provide a continental-scale national facility to monitor and assess trends, and improve predictions, of Australia’s terrestrial biosphere and climate. We describe the evolution, design, and status as well as an overview of data processing. We suggest that a synergistic approach is required to address all of the spatial, ecological, human, and cultural challenges of managing Australian ecosystems.
Natalia Restrepo-Coupe, Alfredo Huete, Kevin Davies, James Cleverly, Jason Beringer, Derek Eamus, Eva van Gorsel, Lindsay B. Hutley, and Wayne S. Meyer
Biogeosciences, 13, 5587–5608, https://doi.org/10.5194/bg-13-5587-2016, https://doi.org/10.5194/bg-13-5587-2016, 2016
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We re-evaluated the connection between satellite greenness products and C-flux tower data in four Australian ecosystems. We identify key mechanisms driving the carbon cycle, and provide an ecological basis for the interpretation of vegetation indices. We found relationships between productivity and greenness to be non-significant in meteorologically driven evergreen forests and sites where climate and vegetation phenology were asynchronous, and highly correlated in phenology-driven ecosystems.
Caitlin E. Moore, Tim Brown, Trevor F. Keenan, Remko A. Duursma, Albert I. J. M. van Dijk, Jason Beringer, Darius Culvenor, Bradley Evans, Alfredo Huete, Lindsay B. Hutley, Stefan Maier, Natalia Restrepo-Coupe, Oliver Sonnentag, Alison Specht, Jeffrey R. Taylor, Eva van Gorsel, and Michael J. Liddell
Biogeosciences, 13, 5085–5102, https://doi.org/10.5194/bg-13-5085-2016, https://doi.org/10.5194/bg-13-5085-2016, 2016
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Australian vegetation phenology is highly variable due to the diversity of ecosystems on the continent. We explore continental-scale variability using satellite remote sensing by broadly classifying areas as seasonal, non-seasonal, or irregularly seasonal. We also examine ecosystem-scale phenology using phenocams and show that some broadly non-seasonal ecosystems do display phenological variability. Overall, phenocams are useful for understanding ecosystem-scale Australian vegetation phenology.
Rhys Whitley, Jason Beringer, Lindsay B. Hutley, Gab Abramowitz, Martin G. De Kauwe, Remko Duursma, Bradley Evans, Vanessa Haverd, Longhui Li, Youngryel Ryu, Benjamin Smith, Ying-Ping Wang, Mathew Williams, and Qiang Yu
Biogeosciences, 13, 3245–3265, https://doi.org/10.5194/bg-13-3245-2016, https://doi.org/10.5194/bg-13-3245-2016, 2016
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In this study we assess how well terrestrial biosphere models perform at predicting water and carbon cycling for savanna ecosystems. We apply our models to five savanna sites in Northern Australia and highlight key causes for model failure. Our assessment of model performance uses a novel benchmarking system that scores a model’s predictive ability based on how well it is utilizing its driving information. On average, we found the models as a group display only moderate levels of performance.
Caitlin E. Moore, Jason Beringer, Bradley Evans, Lindsay B. Hutley, Ian McHugh, and Nigel J. Tapper
Biogeosciences, 13, 2387–2403, https://doi.org/10.5194/bg-13-2387-2016, https://doi.org/10.5194/bg-13-2387-2016, 2016
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Savannas cover 20 % of the global land surface and account for 25 % of global terrestrial carbon uptake. They support 20 % of the world’s human population and are one of the most important ecosystems on our planet. We evaluated the temporal partitioning of carbon between overstory and understory in Australian tropical savanna using eddy covariance. We found the understory contributed ~ 32 % to annual productivity, increasing to 40 % in the wet season, thus driving seasonality in carbon uptake.
V. Haverd, B. Smith, M. Raupach, P. Briggs, L. Nieradzik, J. Beringer, L. Hutley, C. M. Trudinger, and J. Cleverly
Biogeosciences, 13, 761–779, https://doi.org/10.5194/bg-13-761-2016, https://doi.org/10.5194/bg-13-761-2016, 2016
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We present a new approach for modelling coupled phenology and carbon allocation in savannas, and test it using data from the OzFlux network. Model behaviour emerges from complex feedbacks between the plant physiology and vegetation dynamics, in response to resource availability, and not from imposed hypotheses about the controls on tree-grass co-existence. Results indicate that resource limitation is a stronger determinant of tree cover than disturbance in Australian savannas.
D. Eamus, S. Zolfaghar, R. Villalobos-Vega, J. Cleverly, and A. Huete
Hydrol. Earth Syst. Sci., 19, 4229–4256, https://doi.org/10.5194/hess-19-4229-2015, https://doi.org/10.5194/hess-19-4229-2015, 2015
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In this review, we discuss a range of techniques, including remote sensing, for identifying groundwater-dependent ecosystems and determining rates of water use by GDEs. In addition, gravity recovery satellite data are discussed in relation to changes in soil and groundwater stores. Ecophysiological and structural attributes of GDEs are reviewed, from which we present an integrated ecosystem-scale response as a function of differences in depth-to-groundwater.
C. Werner, K. Reiser, M. Dannenmann, L. B. Hutley, J. Jacobeit, and K. Butterbach-Bahl
Biogeosciences, 11, 6047–6065, https://doi.org/10.5194/bg-11-6047-2014, https://doi.org/10.5194/bg-11-6047-2014, 2014
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Atmospheric loss of N from savanna soil was dominated by N2 emissions (82-99% of total N loss to atmosphere). Nitric oxide emissions significantly contributed at 50% WFPS; high temperatures and N2O emissions were negligible. Based on a simple upscale approach we estimated annual loss of N to the atmosphere at 7.5kg yr-1. N2O emission was low for most samples, but high for a small subset of cores at 75% WFPS (due to short periods where such conditions occur this has little effect on totals).
H. Jamali, S. J. Livesley, L. B. Hutley, B. Fest, and S. K. Arndt
Biogeosciences, 10, 2229–2240, https://doi.org/10.5194/bg-10-2229-2013, https://doi.org/10.5194/bg-10-2229-2013, 2013
V. Haverd, M. R. Raupach, P. R. Briggs, J. G. Canadell, P. Isaac, C. Pickett-Heaps, S. H. Roxburgh, E. van Gorsel, R. A. Viscarra Rossel, and Z. Wang
Biogeosciences, 10, 2011–2040, https://doi.org/10.5194/bg-10-2011-2013, https://doi.org/10.5194/bg-10-2011-2013, 2013
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