Articles | Volume 9, issue 9
https://doi.org/10.5194/bg-9-3571-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/bg-9-3571-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
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07 Sep 2012
Research article | Highlight paper |
| 07 Sep 2012
The carbon budget of terrestrial ecosystems in East Asia over the last two decades
S. L. Piao
Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University,
Beijing 100871, China
Beijing 100871, China
Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100085, China
A. Ito
Center for Global Environmental Research, National Institute for Environmental Studies, Tsukuba, Ibaraki 305-8506, Japan
S. G. Li
Institute of Geographic Science and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Y. Huang
Institute of Botany, Chinese Academy of Sciences, Xiangshan, Beijing 100093, China
P. Ciais
Laboratoire des Sciences du Climat et de l'Environnement, CEA CNRS UVSQ, 91191 Gif sur Yvette, France
X. H. Wang
Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University,
Beijing 100871, China
Beijing 100871, China
S. S. Peng
Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University,
Beijing 100871, China
Beijing 100871, China
H. J. Nan
Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University,
Beijing 100871, China
Beijing 100871, China
C. Zhao
Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University,
Beijing 100871, China
Beijing 100871, China
A. Ahlström
Department of Earth and Ecosystem Sciences, Lund University, Sölvegatan 12, 223 62 Lund, Sweden
R. J. Andres
Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831-6290, USA
F. Chevallier
Laboratoire des Sciences du Climat et de l'Environnement, CEA CNRS UVSQ, 91191 Gif sur Yvette, France
J. Y. Fang
Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University,
Beijing 100871, China
Beijing 100871, China
Institute of Botany, Chinese Academy of Sciences, Xiangshan, Beijing 100093, China
J. Hartmann
Institute for Biogeochemistry and Marine Chemistry, Klimacampus, Universität Hamburg, Bundesstrasse 55,
20146 Hamburg, Germany
20146 Hamburg, Germany
C. Huntingford
Centre for Ecology and Hydrology, Benson Lane, Wallingford OX10 8BB, UK
S. Jeong
Department of Geosciences, Princeton University, Princeton, NJ, USA
S. Levis
National Center for Atmospheric Research, Boulder, Colorado, USA
P. E. Levy
Centre for Ecology and Hydrology, Bush Estate, Penicuik, Midlothian EH26 0QB, UK
J. S. Li
Chinese Research Academy of Environmental Sciences, Beijing 100012, China
M. R. Lomas
Department of Animal & Plant Sciences, University of Sheffield, Sheffield S10 2TN, UK
J. F. Mao
Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831-6290, USA
E. Mayorga
Applied Physics Laboratory, University of Washington, Seattle, WA, USA
A. Mohammat
Xinjiang institute of ecology and geography, Chinese Academy of Sciences, Urumqi 830011, China
H. Muraoka
River Basin Research Center, Gifu University, Gifu 501-1193, Japan
C. H. Peng
Laboratory for Ecological Forecasting and Global Change, College of Forestry, Northwest A & F University, Yangling, Shaanxi 712100, China
Department of Biology Sciences, Institute of Environment Sciences, University of Quebec, Montreal, Canada
P. Peylin
Laboratoire des Sciences du Climat et de l'Environnement, CEA CNRS UVSQ, 91191 Gif sur Yvette, France
B. Poulter
Laboratoire des Sciences du Climat et de l'Environnement, CEA CNRS UVSQ, 91191 Gif sur Yvette, France
Z. H. Shen
Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University,
Beijing 100871, China
Beijing 100871, China
X. Shi
Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831-6290, USA
S. Sitch
School of Geography, University of Exeter, Exeter EX4 4QF, UK
S. Tao
Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University,
Beijing 100871, China
Beijing 100871, China
H. Q. Tian
Ecosystem Dynamics and Global Ecology Laboratory, School of Forestry and Wildlife Sciences, Auburn University, Auburn 36849, USA
X. P. Wu
Chinese Research Academy of Environmental Sciences, Beijing 100012, China
M. Xu
Institute of Geographic Science and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
G. R. Yu
Institute of Geographic Science and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
N. Viovy
Laboratoire des Sciences du Climat et de l'Environnement, CEA CNRS UVSQ, 91191 Gif sur Yvette, France
S. Zaehle
Max Planck Institute for Biogeochemistry, P.O. Box 10 01 64, 07701 Jena, Germany
N. Zeng
Department of Atmospheric and Oceanic Science, University of Maryland, College Park, MD 20740, USA
B. Zhu
Department of Horticulture, Cornell University, Ithaca, NY 14853, USA
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Sophia Walther, Simon Besnard, Jacob Allen Nelson, Tarek Sebastian El-Madany, Mirco Migliavacca, Ulrich Weber, Nuno Carvalhais, Sofia Lorena Ermida, Christian Brümmer, Frederik Schrader, Anatoly Stanislavovich Prokushkin, Alexey Vasilevich Panov, and Martin Jung
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Satellite observations help interpret station measurements of local carbon, water, and energy exchange between the land surface and the atmosphere and are indispensable for simulations of the same in land surface models and their evaluation. We propose generalisable and efficient approaches to systematically ensure high quality and to estimate values in data gaps. We apply them to satellite data of surface reflectance and temperature with different resolutions at the stations.
Elisabeth Mauclet, Yannick Agnan, Catherine Hirst, Arthur Monhonval, Benoît Pereira, Aubry Vandeuren, Maëlle Villani, Justin Ledman, Meghan Taylor, Briana L. Jasinski, Edward A. G. Schuur, and Sophie Opfergelt
Biogeosciences, 19, 2333–2351, https://doi.org/10.5194/bg-19-2333-2022, https://doi.org/10.5194/bg-19-2333-2022, 2022
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Tiexi Chen, Renjie Guo, Qingyun Yan, Xin Chen, Shengjie Zhou, Chuanzhuang Liang, Xueqiong Wei, and Han Dolman
Biogeosciences, 19, 1515–1525, https://doi.org/10.5194/bg-19-1515-2022, https://doi.org/10.5194/bg-19-1515-2022, 2022
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Rahayu Adzhar, Douglas I. Kelley, Ning Dong, Charles George, Mireia Torello Raventos, Elmar Veenendaal, Ted R. Feldpausch, Oliver L. Phillips, Simon L. Lewis, Bonaventure Sonké, Herman Taedoumg, Beatriz Schwantes Marimon, Tomas Domingues, Luzmila Arroyo, Gloria Djagbletey, Gustavo Saiz, and France Gerard
Biogeosciences, 19, 1377–1394, https://doi.org/10.5194/bg-19-1377-2022, https://doi.org/10.5194/bg-19-1377-2022, 2022
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The MODIS Vegetation Continuous Fields (VCF) product underestimates tree cover compared to field data and could be underestimating tree cover significantly across the tropics. VCF is used to represent land cover or validate model performance in many land surface and global vegetation models and to train finer-scaled Earth observation products. Because underestimation in VCF may render it unsuitable for training data and bias model predictions, it should be calibrated before use in the tropics.
Lina Teckentrup, Martin G. De Kauwe, Andrew J. Pitman, Daniel S. Goll, Vanessa Haverd, Atul K. Jain, Emilie Joetzjer, Etsushi Kato, Sebastian Lienert, Danica Lombardozzi, Patrick C. McGuire, Joe R. Melton, Julia E. M. S. Nabel, Julia Pongratz, Stephen Sitch, Anthony P. Walker, and Sönke Zaehle
Biogeosciences, 18, 5639–5668, https://doi.org/10.5194/bg-18-5639-2021, https://doi.org/10.5194/bg-18-5639-2021, 2021
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The Australian continent is included in global assessments of the carbon cycle such as the global carbon budget, yet the performance of dynamic global vegetation models (DGVMs) over Australia has rarely been evaluated. We assessed simulations by an ensemble of dynamic global vegetation models over Australia and highlighted a number of key areas that lead to model divergence on both short (inter-annual) and long (decadal) timescales.
Juhwan Lee, Raphael A. Viscarra Rossel, Mingxi Zhang, Zhongkui Luo, and Ying-Ping Wang
Biogeosciences, 18, 5185–5202, https://doi.org/10.5194/bg-18-5185-2021, https://doi.org/10.5194/bg-18-5185-2021, 2021
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We performed Roth C simulations across Australia and assessed the response of soil carbon to changing inputs and future climate change using a consistent modelling framework. Site-specific initialisation of the C pools with measurements of the C fractions is essential for accurate simulations of soil organic C stocks and composition at a large scale. With further warming, Australian soils will become more vulnerable to C loss: natural environments > native grazing > cropping > modified grazing.
Anam M. Khan, Paul C. Stoy, James T. Douglas, Martha Anderson, George Diak, Jason A. Otkin, Christopher Hain, Elizabeth M. Rehbein, and Joel McCorkel
Biogeosciences, 18, 4117–4141, https://doi.org/10.5194/bg-18-4117-2021, https://doi.org/10.5194/bg-18-4117-2021, 2021
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Remote sensing has played an important role in the study of land surface processes. Geostationary satellites, such as the GOES-R series, can observe the Earth every 5–15 min, providing us with more observations than widely used polar-orbiting satellites. Here, we outline current efforts utilizing geostationary observations in environmental science and look towards the future of GOES observations in the carbon cycle, ecosystem disturbance, and other areas of application in environmental science.
Lydia Stolpmann, Caroline Coch, Anne Morgenstern, Julia Boike, Michael Fritz, Ulrike Herzschuh, Kathleen Stoof-Leichsenring, Yury Dvornikov, Birgit Heim, Josefine Lenz, Amy Larsen, Katey Walter Anthony, Benjamin Jones, Karen Frey, and Guido Grosse
Biogeosciences, 18, 3917–3936, https://doi.org/10.5194/bg-18-3917-2021, https://doi.org/10.5194/bg-18-3917-2021, 2021
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Our new database summarizes DOC concentrations of 2167 water samples from 1833 lakes in permafrost regions across the Arctic to provide insights into linkages between DOC and environment. We found increasing lake DOC concentration with decreasing permafrost extent and higher DOC concentrations in boreal permafrost sites compared to tundra sites. Our study shows that DOC concentration depends on the environmental properties of a lake, especially permafrost extent, ecoregion, and vegetation.
Gustaf Granath, Christopher D. Evans, Joachim Strengbom, Jens Fölster, Achim Grelle, Johan Strömqvist, and Stephan J. Köhler
Biogeosciences, 18, 3243–3261, https://doi.org/10.5194/bg-18-3243-2021, https://doi.org/10.5194/bg-18-3243-2021, 2021
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We measured element losses and impacts on water quality following a wildfire in Sweden. We observed the largest carbon and nitrogen losses during the fire and a strong pulse of elements 1–3 months after the fire that showed a fast (weeks) and a slow (months) release from the catchments. Total carbon export through water did not increase post-fire. Overall, we observed a rapid recovery of the biogeochemical cycling of elements within 3 years but still an annual net release of carbon dioxide.
Lina Teckentrup, Martin G. De Kauwe, Andrew J. Pitman, and Benjamin Smith
Biogeosciences, 18, 2181–2203, https://doi.org/10.5194/bg-18-2181-2021, https://doi.org/10.5194/bg-18-2181-2021, 2021
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The El Niño–Southern Oscillation (ENSO) describes changes in the sea surface temperature patterns of the Pacific Ocean. This influences the global weather, impacting vegetation on land. There are two types of El Niño: central Pacific (CP) and eastern Pacific (EP). In this study, we explored the long-term impacts on the carbon balance on land linked to the two El Niño types. Using a dynamic vegetation model, we simulated what would happen if only either CP or EP El Niño events had occurred.
Matthias Volk, Matthias Suter, Anne-Lena Wahl, and Seraina Bassin
Biogeosciences, 18, 2075–2090, https://doi.org/10.5194/bg-18-2075-2021, https://doi.org/10.5194/bg-18-2075-2021, 2021
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Grassland ecosystem services like forage production and greenhouse gas storage in the soil depend on plant growth.
In an experiment in the mountains with warming treatments, we found that despite dwindling soil water content, the grassland growth increased with up to +1.3 °C warming (annual mean) compared to present temperatures. Even at +2.4 °C the growth was still larger than at the reference site.
This suggests that plant growth will increase due to global warming in the near future.
Bernice C. Hwang and Daniel B. Metcalfe
Biogeosciences, 18, 1259–1268, https://doi.org/10.5194/bg-18-1259-2021, https://doi.org/10.5194/bg-18-1259-2021, 2021
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Despite growing recognition of herbivores as important ecosystem engineers, many major gaps remain in our understanding of how silicon and herbivory interact to shape biogeochemical processes. We highlight the need for more research particularly in natural settings as well as on the potential effects of herbivory on terrestrial silicon cycling to understand potentially critical animal–plant–soil feedbacks.
Ali Asaadi and Vivek K. Arora
Biogeosciences, 18, 669–706, https://doi.org/10.5194/bg-18-669-2021, https://doi.org/10.5194/bg-18-669-2021, 2021
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More than a quarter of the current anthropogenic CO2 emissions are taken up by land, reducing the atmospheric CO2 growth rate. This is because of the CO2 fertilization effect which benefits 80 % of global vegetation. However, if nitrogen and phosphorus nutrients cannot keep up with increasing atmospheric CO2, the magnitude of this terrestrial ecosystem service may reduce in future. This paper implements nitrogen constraints on photosynthesis in a model to understand the mechanisms involved.
Arianna Peron, Lisa Kaser, Anne Charlott Fitzky, Martin Graus, Heidi Halbwirth, Jürgen Greiner, Georg Wohlfahrt, Boris Rewald, Hans Sandén, and Thomas Karl
Biogeosciences, 18, 535–556, https://doi.org/10.5194/bg-18-535-2021, https://doi.org/10.5194/bg-18-535-2021, 2021
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Drought events are expected to become more frequent with climate change. Along with these events atmospheric ozone is also expected to increase. Both can stress plants. Here we investigate to what extent these factors modulate the emission of volatile organic compounds (VOCs) from oak plants. We find an antagonistic effect between drought stress and ozone, impacting the emission of different BVOCs, which is indirectly controlled by stomatal opening, allowing plants to control their water budget.
Lena Wohlgemuth, Stefan Osterwalder, Carl Joseph, Ansgar Kahmen, Günter Hoch, Christine Alewell, and Martin Jiskra
Biogeosciences, 17, 6441–6456, https://doi.org/10.5194/bg-17-6441-2020, https://doi.org/10.5194/bg-17-6441-2020, 2020
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Mercury uptake by trees from the air represents an important but poorly quantified pathway in the global mercury cycle. We determined mercury uptake fluxes by leaves and needles at 10 European forests which were 4 times larger than mercury deposition via rainfall. The amount of mercury taken up by leaves and needles depends on their age and growing height on the tree. Scaling up our measurements to the forest area of Europe, we estimate that each year 20 t of mercury is taken up by trees.
A. Anthony Bloom, Kevin W. Bowman, Junjie Liu, Alexandra G. Konings, John R. Worden, Nicholas C. Parazoo, Victoria Meyer, John T. Reager, Helen M. Worden, Zhe Jiang, Gregory R. Quetin, T. Luke Smallman, Jean-François Exbrayat, Yi Yin, Sassan S. Saatchi, Mathew Williams, and David S. Schimel
Biogeosciences, 17, 6393–6422, https://doi.org/10.5194/bg-17-6393-2020, https://doi.org/10.5194/bg-17-6393-2020, 2020
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We use a model of the 2001–2015 tropical land carbon cycle, with satellite measurements of land and atmospheric carbon, to disentangle lagged and concurrent effects (due to past and concurrent meteorological events, respectively) on annual land–atmosphere carbon exchanges. The variability of lagged effects explains most 2001–2015 inter-annual carbon flux variations. We conclude that concurrent and lagged effects need to be accurately resolved to better predict the world's land carbon sink.
Erqian Cui, Chenyu Bian, Yiqi Luo, Shuli Niu, Yingping Wang, and Jianyang Xia
Biogeosciences, 17, 6237–6246, https://doi.org/10.5194/bg-17-6237-2020, https://doi.org/10.5194/bg-17-6237-2020, 2020
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Mean annual net ecosystem productivity (NEP) is related to the magnitude of the carbon sink of a specific ecosystem, while its inter-annual variation (IAVNEP) characterizes the stability of such a carbon sink. Thus, a better understanding of the co-varying NEP and IAVNEP is critical for locating the major and stable carbon sinks on land. Based on daily NEP observations from eddy-covariance sites, we found local indicators for the spatially varying NEP and IAVNEP, respectively.
Taraka Davies-Barnard, Johannes Meyerholt, Sönke Zaehle, Pierre Friedlingstein, Victor Brovkin, Yuanchao Fan, Rosie A. Fisher, Chris D. Jones, Hanna Lee, Daniele Peano, Benjamin Smith, David Wårlind, and Andy J. Wiltshire
Biogeosciences, 17, 5129–5148, https://doi.org/10.5194/bg-17-5129-2020, https://doi.org/10.5194/bg-17-5129-2020, 2020
Rui Cheng, Troy S. Magney, Debsunder Dutta, David R. Bowling, Barry A. Logan, Sean P. Burns, Peter D. Blanken, Katja Grossmann, Sophia Lopez, Andrew D. Richardson, Jochen Stutz, and Christian Frankenberg
Biogeosciences, 17, 4523–4544, https://doi.org/10.5194/bg-17-4523-2020, https://doi.org/10.5194/bg-17-4523-2020, 2020
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We measured reflected sunlight from an evergreen canopy for a year to detect changes in pigments that play an important role in regulating the seasonality of photosynthesis. Results show a strong mechanistic link between spectral reflectance features and pigment content, which is validated using a biophysical model. Our results show spectrally where, why, and when spectral features change over the course of the season and show promise for estimating photosynthesis remotely.
Jarmo Mäkelä, Francesco Minunno, Tuula Aalto, Annikki Mäkelä, Tiina Markkanen, and Mikko Peltoniemi
Biogeosciences, 17, 2681–2700, https://doi.org/10.5194/bg-17-2681-2020, https://doi.org/10.5194/bg-17-2681-2020, 2020
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We assess the relative magnitude of uncertainty sources on ecosystem indicators of the 21st century climate change on two boreal forest sites. In addition to RCP and climate model uncertainties, we included the overlooked model parameter uncertainty and management actions in our analysis. Management was the dominant uncertainty factor for the more verdant southern site, followed by RCP, climate and parameter uncertainties. The uncertainties were estimated with canonical correlation analysis.
Guido Kraemer, Gustau Camps-Valls, Markus Reichstein, and Miguel D. Mahecha
Biogeosciences, 17, 2397–2424, https://doi.org/10.5194/bg-17-2397-2020, https://doi.org/10.5194/bg-17-2397-2020, 2020
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To closely monitor the state of our planet, we require systems that can monitor
the observation of many different properties at the same time. We create
indicators that resemble the behavior of many different simultaneous
observations. We apply the method to create indicators representing the
Earth's biosphere. The indicators show a productivity gradient and a water
gradient. The resulting indicators can detect a large number of changes and
extremes in the Earth system.
Barbara Marcolla, Mirco Migliavacca, Christian Rödenbeck, and Alessandro Cescatti
Biogeosciences, 17, 2365–2379, https://doi.org/10.5194/bg-17-2365-2020, https://doi.org/10.5194/bg-17-2365-2020, 2020
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This work investigates the sensitivity of terrestrial CO2 fluxes to climate drivers. We observed that CO2 flux is mostly controlled by temperature during the growing season and by radiation off season. We also observe that radiation importance is increasing over time while sensitivity to temperature is decreasing in Eurasia. Ultimately this analysis shows that ecosystem response to climate is changing, with potential repercussions for future terrestrial sink and land role in climate mitigation.
Stephanie C. Pennington, Nate G. McDowell, J. Patrick Megonigal, James C. Stegen, and Ben Bond-Lamberty
Biogeosciences, 17, 771–780, https://doi.org/10.5194/bg-17-771-2020, https://doi.org/10.5194/bg-17-771-2020, 2020
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Soil respiration (Rs) is the flow of CO2 from the soil surface to the atmosphere and is one of the largest carbon fluxes on land. This study examined the effect of local basal area (tree area) on Rs in a coastal forest in eastern Maryland, USA. Rs measurements were taken as well as distance from soil collar, diameter, and species of each tree within a 15 m radius. We found that trees within 5 m of our sampling points had a positive effect on how sensitive soil respiration was to temperature.
Keri L. Bowering, Kate A. Edwards, Karen Prestegaard, Xinbiao Zhu, and Susan E. Ziegler
Biogeosciences, 17, 581–595, https://doi.org/10.5194/bg-17-581-2020, https://doi.org/10.5194/bg-17-581-2020, 2020
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We examined the effects of season and tree harvesting on the flow of water and the organic carbon (OC) it carries from boreal forest soils. We found that more OC was lost from the harvested forest because more precipitation reached the soil surface but that during periods of flushing in autumn and snowmelt a limit on the amount of water-extractable OC is reached. These results contribute to an increased understanding of carbon loss from boreal forest soils.
Jason Philip Kaye, Susan L. Brantley, Jennifer Zan Williams, and the SSHCZO team
Biogeosciences, 16, 4661–4669, https://doi.org/10.5194/bg-16-4661-2019, https://doi.org/10.5194/bg-16-4661-2019, 2019
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Interdisciplinary teams can only capitalize on innovative ideas if members work well together through collegial and efficient use of field sites, instrumentation, samples, data, and model code. Thus, biogeoscience teams may benefit from developing a set of best practices for collaboration. We present one such example from a the Susquehanna Shale Hills critical zone observatory. Many of the themes from our example are universal, and they offer insights useful to other biogeoscience teams.
Anne Alexandre, Elizabeth Webb, Amaelle Landais, Clément Piel, Sébastien Devidal, Corinne Sonzogni, Martine Couapel, Jean-Charles Mazur, Monique Pierre, Frédéric Prié, Christine Vallet-Coulomb, Clément Outrequin, and Jacques Roy
Biogeosciences, 16, 4613–4625, https://doi.org/10.5194/bg-16-4613-2019, https://doi.org/10.5194/bg-16-4613-2019, 2019
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This calibration study shows that despite isotope heterogeneity along grass leaves, the triple oxygen isotope composition of bulk leaf phytoliths can be estimated from the Craig and Gordon model, a mixing equation and a mean leaf water–phytolith fractionation exponent (lambda) of 0.521. The results strengthen the reliability of the 17O–excess of phytoliths to be used as a proxy of atmospheric relative humidity and open tracks for its use as an imprint of leaf water 17O–excess.
Lina Teckentrup, Sandy P. Harrison, Stijn Hantson, Angelika Heil, Joe R. Melton, Matthew Forrest, Fang Li, Chao Yue, Almut Arneth, Thomas Hickler, Stephen Sitch, and Gitta Lasslop
Biogeosciences, 16, 3883–3910, https://doi.org/10.5194/bg-16-3883-2019, https://doi.org/10.5194/bg-16-3883-2019, 2019
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This study compares simulated burned area of seven global vegetation models provided by the Fire Model Intercomparison Project (FireMIP) since 1900. We investigate the influence of five forcing factors: atmospheric CO2, population density, land–use change, lightning and climate.
We find that the anthropogenic factors lead to the largest spread between models. Trends due to climate are mostly not significant but climate strongly influences the inter-annual variability of burned area.
Marcos A. S. Scaranello, Michael Keller, Marcos Longo, Maiza N. dos-Santos, Veronika Leitold, Douglas C. Morton, Ekena R. Pinagé, and Fernando Del Bon Espírito-Santo
Biogeosciences, 16, 3457–3474, https://doi.org/10.5194/bg-16-3457-2019, https://doi.org/10.5194/bg-16-3457-2019, 2019
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The coarse dead wood component of the tropical forest carbon pool is rarely measured. For the first time, we developed models for predicting coarse dead wood in Amazonian forests by using airborne laser scanning data. Our models produced site-based estimates similar to independent field estimates found in the literature. Our study provides an approach for estimating coarse dead wood pools from remotely sensed data and mapping those pools over large scales in intact and degraded forests.
James Brennan, Jose L. Gómez-Dans, Mathias Disney, and Philip Lewis
Biogeosciences, 16, 3147–3164, https://doi.org/10.5194/bg-16-3147-2019, https://doi.org/10.5194/bg-16-3147-2019, 2019
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We estimate the uncertainties associated with three global satellite-derived burned area estimates. The method provides unique uncertainties for the three estimates at the global scale for 2001–2013. We find uncertainties of 4 %–5.5 % in global burned area and uncertainties of 8 %–10 % in the frequently burning regions of Africa and Australia.
Alexander J. Norton, Peter J. Rayner, Ernest N. Koffi, Marko Scholze, Jeremy D. Silver, and Ying-Ping Wang
Biogeosciences, 16, 3069–3093, https://doi.org/10.5194/bg-16-3069-2019, https://doi.org/10.5194/bg-16-3069-2019, 2019
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This study presents an estimate of global terrestrial photosynthesis. We make use of satellite chlorophyll fluorescence measurements, a visible indicator of photosynthesis, to optimize model parameters and estimate photosynthetic carbon uptake. This new framework incorporates nonlinear, process-based understanding of the link between fluorescence and photosynthesis, an advance on past approaches. This will aid in the utility of fluorescence to quantify terrestrial carbon cycle feedbacks.
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.
Friederike Gerschlauer, Gustavo Saiz, David Schellenberger Costa, Michael Kleyer, Michael Dannenmann, and Ralf Kiese
Biogeosciences, 16, 409–424, https://doi.org/10.5194/bg-16-409-2019, https://doi.org/10.5194/bg-16-409-2019, 2019
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Mount Kilimanjaro is an iconic environmental asset under serious threat due to increasing human pressures and climate change constraints. We studied variations in the stable isotopic composition of carbon and nitrogen in plant, litter, and soil material sampled along a strong land-use and altitudinal gradient. Our results show that, besides management, increasing temperatures in a changing climate may promote carbon and nitrogen losses, thus altering the stability of Kilimanjaro ecosystems.
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