Articles | Volume 10, issue 1
https://doi.org/10.5194/esd-10-9-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esd-10-9-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
07 Jan 2019
Research article |
| 07 Jan 2019
| 07 Jan 2019
Global vegetation variability and its response to elevated CO2, global warming, and climate variability – a study using the offline SSiB4/TRIFFID model and satellite data
University of California Los Angeles (UCLA), Los Angeles, CA, USA
University of California Los Angeles (UCLA), Los Angeles, CA, USA
Glen MacDonald
University of California Los Angeles (UCLA), Los Angeles, CA, USA
Peter Cox
College of Engineering, Mathematics and Physical Science, University of Exeter, Exeter, UK
Zhengqiu Zhang
Chinese Academy of Meteorological Sciences, Beijing, China
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Huilin Huang, Yun Qian, Ye Liu, Cenlin He, Jianyu Zheng, Zhibo Zhang, and Antonis Gkikas
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Zheng Xiang, Yongkang Xue, Weidong Guo, Melannie D. Hartman, Ye Liu, and William J. Parton
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Ye Liu, Yun Qian, and Larry K. Berg
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Limited nitrogen availbility can restrict the growth of plants and their ability to assimilate carbon. It is important to include the impact of this process on the global land carbon cycle. This paper presents a model of the coupled land carbon and nitrogen cycle, which is included within the UK Earth System model to improve projections of climate change and impacts on ecosystems.
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Most land surface models have difficulty in capturing the freeze–thaw cycle in the Tibetan Plateau and North China. This paper introduces a physically more realistic and efficient frozen soil module (FSM) into the SSiB3 model (SSiB3-FSM). A new and more stable semi-implicit scheme and a physics-based freezing–thawing scheme were applied, and results show that SSiB3-FSM can be used as an effective model for soil thermal characteristics at seasonal to decadal scales over frozen ground.
Bettina K. Gier, Michael Buchwitz, Maximilian Reuter, Peter M. Cox, Pierre Friedlingstein, and Veronika Eyring
Biogeosciences, 17, 6115–6144, https://doi.org/10.5194/bg-17-6115-2020, https://doi.org/10.5194/bg-17-6115-2020, 2020
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Models from Coupled Model Intercomparison Project (CMIP) phases 5 and 6 are compared to a satellite data product of column-averaged CO2 mole fractions (XCO2). The previously believed discrepancy of the negative trend in seasonal cycle amplitude in the satellite product, which is not seen in in situ data nor in the models, is attributed to a sampling characteristic. Furthermore, CMIP6 models are shown to have made progress in reproducing the observed XCO2 time series compared to CMIP5.
Huilin Huang, Yongkang Xue, Fang Li, and Ye Liu
Geosci. Model Dev., 13, 6029–6050, https://doi.org/10.5194/gmd-13-6029-2020, https://doi.org/10.5194/gmd-13-6029-2020, 2020
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We developed a fire-coupled dynamic vegetation model that captures the spatial distribution, temporal variability, and especially the seasonal variability of fire regimes. The fire model is applied to assess the long-term fire impact on ecosystems and surface energy. We find that fire is an important determinant of the structure and function of the tropical savanna. By changing the vegetation composition and ecosystem characteristics, fire significantly alters surface energy balance.
Arthur P. K. Argles, Jonathan R. Moore, Chris Huntingford, Andrew J. Wiltshire, Anna B. Harper, Chris D. Jones, and Peter M. Cox
Geosci. Model Dev., 13, 4067–4089, https://doi.org/10.5194/gmd-13-4067-2020, https://doi.org/10.5194/gmd-13-4067-2020, 2020
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Simon Jones, Lucy Rowland, Peter Cox, Deborah Hemming, Andy Wiltshire, Karina Williams, Nicholas C. Parazoo, Junjie Liu, Antonio C. L. da Costa, Patrick Meir, Maurizio Mencuccini, and Anna B. Harper
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Non-structural carbohydrates (NSCs) are an important set of molecules that help plants to grow and respire when photosynthesis is restricted by extreme climate events. In this paper we present a simple model of NSC storage and assess the effect that it has on simulations of vegetation at the ecosystem scale. Our model has the potential to significantly change predictions of plant behaviour in global vegetation models, which would have large implications for predictions of the future climate.
Jonathan R. Moore, Arthur P. K. Argles, Kai Zhu, Chris Huntingford, and Peter M. Cox
Biogeosciences, 17, 1013–1032, https://doi.org/10.5194/bg-17-1013-2020, https://doi.org/10.5194/bg-17-1013-2020, 2020
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The distribution of tree sizes across Amazonia can be fitted very well (for both trunk diameter and tree mass) by a simple equilibrium model assuming power law growth and size-independent mortality. We find tree growth to mirror some aspects of metabolic scaling theory and that there may be a trade-off between fast-growing, short-lived and longer-lived, slow-growing ones. Our Amazon mortality-to-growth ratio is very similar to US temperate forests, hinting at a universal property for trees.
Karina E. Williams, Anna B. Harper, Chris Huntingford, Lina M. Mercado, Camilla T. Mathison, Pete D. Falloon, Peter M. Cox, and Joon Kim
Geosci. Model Dev., 12, 3207–3240, https://doi.org/10.5194/gmd-12-3207-2019, https://doi.org/10.5194/gmd-12-3207-2019, 2019
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Data from the First ISLSCP Field Experiment, 1987–1989, is used to assess how well the JULES land-surface model simulates water stress in tallgrass prairie vegetation. We find that JULES simulates a decrease in key carbon and water cycle variables during the dry period, as expected, but that it does not capture the shape of the diurnal cycle on these days. These results will be used to inform future model development as part of wider evaluation efforts.
Qianyu Li, Xingjie Lu, Yingping Wang, Xin Huang, Peter M. Cox, and Yiqi Luo
Biogeosciences, 15, 6909–6925, https://doi.org/10.5194/bg-15-6909-2018, https://doi.org/10.5194/bg-15-6909-2018, 2018
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Land-surface models have been widely used to predict the responses of terrestrial ecosystems to climate change. A better understanding of model mechanisms that govern terrestrial ecosystem responses to rising atmosphere [CO2] is needed. Our study for the first time shows that the expansion of leaf area under rising [CO2] is the most important response for the stimulation of land carbon accumulation by a land-surface model: CABLE. Processes related to leaf area should be better calibrated.
Anna B. Harper, Andrew J. Wiltshire, Peter M. Cox, Pierre Friedlingstein, Chris D. Jones, Lina M. Mercado, Stephen Sitch, Karina Williams, and Carolina Duran-Rojas
Geosci. Model Dev., 11, 2857–2873, https://doi.org/10.5194/gmd-11-2857-2018, https://doi.org/10.5194/gmd-11-2857-2018, 2018
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Dynamic global vegetation models are used for studying historical and future changes to vegetation and the terrestrial carbon cycle. JULES is a DGVM that represents the land surface in the UK Earth System Model. We compared simulated gross and net primary productivity of vegetation, vegetation distribution, and aspects of the transient carbon cycle to observational datasets. JULES was able to accurately reproduce many aspects of the terrestrial carbon cycle with the recent improvements.
Chris Huntingford, Hui Yang, Anna Harper, Peter M. Cox, Nicola Gedney, Eleanor J. Burke, Jason A. Lowe, Garry Hayman, William J. Collins, Stephen M. Smith, and Edward Comyn-Platt
Earth Syst. Dynam., 8, 617–626, https://doi.org/10.5194/esd-8-617-2017, https://doi.org/10.5194/esd-8-617-2017, 2017
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Recent UNFCCC climate meetings have placed much emphasis on constraining global warming to remain below 2 °C. The 2015 Paris meeting went further and gave an aspiration to fulfil a 1.5 °C threshold. We provide a flexible set of algebraic global temperature profiles that stabilise to either target. This will potentially allow the climate research community to estimate local climatic implications for these temperature profiles, along with emissions trajectories to fulfil them.
Xueqian Wang, Weidong Guo, Bo Qiu, Ye Liu, Jianning Sun, and Aijun Ding
Atmos. Chem. Phys., 17, 4989–4996, https://doi.org/10.5194/acp-17-4989-2017, https://doi.org/10.5194/acp-17-4989-2017, 2017
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Land use or cover change is a fundamental anthropogenic forcing for climate change. Based on field observations, we quantified the contributions of different factors to surface temperature change and deepened the understanding of its mechanisms. We found evaporative cooling plays the most important role in the temperature change, while radiative forcing, which is traditionally emphasized, is not significant. This study provided firsthand evidence to verify the model results in IPCC AR5.
Nina M. Raoult, Tim E. Jupp, Peter M. Cox, and Catherine M. Luke
Geosci. Model Dev., 9, 2833–2852, https://doi.org/10.5194/gmd-9-2833-2016, https://doi.org/10.5194/gmd-9-2833-2016, 2016
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We present a set of "optimal" parameter values used to describe the influence of vegetation in a numerical climate model, and the software suite that we developed to find it. Observational data from ~ 100 locations were used, and the optimal parameters improve the fit in 90 % of the locations. The new parameter values will allow the climate model to give better predictions, and our software should prove useful in future calibrations.
Anna B. Harper, Peter M. Cox, Pierre Friedlingstein, Andy J. Wiltshire, Chris D. Jones, Stephen Sitch, Lina M. Mercado, Margriet Groenendijk, Eddy Robertson, Jens Kattge, Gerhard Bönisch, Owen K. Atkin, Michael Bahn, Johannes Cornelissen, Ülo Niinemets, Vladimir Onipchenko, Josep Peñuelas, Lourens Poorter, Peter B. Reich, Nadjeda A. Soudzilovskaia, and Peter van Bodegom
Geosci. Model Dev., 9, 2415–2440, https://doi.org/10.5194/gmd-9-2415-2016, https://doi.org/10.5194/gmd-9-2415-2016, 2016
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Dynamic global vegetation models (DGVMs) are used to predict the response of vegetation to climate change. We improved the representation of carbon uptake by ecosystems in a DGVM by including a wider range of trade-offs between nutrient allocation to photosynthetic capacity and leaf structure, based on observed plant traits from a worldwide data base. The improved model has higher rates of photosynthesis and net C uptake by plants, and more closely matches observations at site and global scales.
Stefan C. Dekker, Margriet Groenendijk, Ben B. B. Booth, Chris Huntingford, and Peter M. Cox
Earth Syst. Dynam., 7, 525–533, https://doi.org/10.5194/esd-7-525-2016, https://doi.org/10.5194/esd-7-525-2016, 2016
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Our analysis allows us to infer maps of changing plant water-use efficiency (WUE) for 1901–2010, using atmospheric observations of temperature, humidity and CO2. Our estimated increase in global WUE is consistent with the tree-ring and eddy covariance data, but much larger than the historical WUE increases simulated by Earth System Models (ESMs). We therefore conclude that the effects of increasing CO2 on plant WUE are significantly underestimated in the latest climate projections.
Tzu-Hsien Kuo, Jen-Ping Chen, and Yongkang Xue
Hydrol. Earth Syst. Sci., 20, 1509–1522, https://doi.org/10.5194/hess-20-1509-2016, https://doi.org/10.5194/hess-20-1509-2016, 2016
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The stem-root flow mechanism was parameterized and incorporated into the Simplified Simple Biosphere model to analyze its impact on soil moisture and land-atmospheric interactions. By testing against the Lien Hua Chih (Taiwan) and HAPEX-Mobilhy (France) measurements, the model shows that stem-root flow reduced the top-soil moisture content and moistened the deeper soil layers. Such soil moisture redistribution results in significant changes in heat flux exchange between land and atmosphere.
Z. A. Thomas, F. Kwasniok, C. A. Boulton, P. M. Cox, R. T. Jones, T. M. Lenton, and C. S. M. Turney
Clim. Past, 11, 1621–1633, https://doi.org/10.5194/cp-11-1621-2015, https://doi.org/10.5194/cp-11-1621-2015, 2015
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Using a combination of speleothem records and model simulations of the East Asian Monsoon over the penultimate glacial cycle, we search for early warning signals of past tipping points. We detect a characteristic slower response to perturbations prior to an abrupt monsoon shift at the glacial termination; however, we do not detect these signals in the preceding shifts. Our results have important implications for detecting tipping points in palaeoclimate records outside glacial terminations.
S. E. Chadburn, E. J. Burke, R. L. H. Essery, J. Boike, M. Langer, M. Heikenfeld, P. M. Cox, and P. Friedlingstein
The Cryosphere, 9, 1505–1521, https://doi.org/10.5194/tc-9-1505-2015, https://doi.org/10.5194/tc-9-1505-2015, 2015
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In this paper we use a global land-surface model to study the dynamics of Arctic permafrost. We examine the impact of new and improved processes in the model, namely soil depth and resolution, organic soils, moss and the representation of snow. These improvements make the simulated soil temperatures and thaw depth significantly more realistic. Simulations under future climate scenarios show that permafrost thaws more slowly in the new model version, but still a large amount is lost by 2100.
S. Chadburn, E. Burke, R. Essery, J. Boike, M. Langer, M. Heikenfeld, P. Cox, and P. Friedlingstein
Geosci. Model Dev., 8, 1493–1508, https://doi.org/10.5194/gmd-8-1493-2015, https://doi.org/10.5194/gmd-8-1493-2015, 2015
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Permafrost, ground that is frozen for 2 or more years, is found extensively in the Arctic. It stores large quantities of carbon, which may be released under climate warming, so it is important to include it in climate models. Here we improve the representation of permafrost in a climate model land-surface scheme, both in the numerical representation of soil and snow, and by adding the effects of organic soils and moss. Site simulations show significantly improved soil temperature and thaw depth.
L. Kwiatkowski, A. Yool, J. I. Allen, T. R. Anderson, R. Barciela, E. T. Buitenhuis, M. Butenschön, C. Enright, P. R. Halloran, C. Le Quéré, L. de Mora, M.-F. Racault, B. Sinha, I. J. Totterdell, and P. M. Cox
Biogeosciences, 11, 7291–7304, https://doi.org/10.5194/bg-11-7291-2014, https://doi.org/10.5194/bg-11-7291-2014, 2014
M. Shrestha, L. Wang, T. Koike, H. Tsutsui, Y. Xue, and Y. Hirabayashi
Hydrol. Earth Syst. Sci., 18, 747–761, https://doi.org/10.5194/hess-18-747-2014, https://doi.org/10.5194/hess-18-747-2014, 2014
A. M. Foley, D. Dalmonech, A. D. Friend, F. Aires, A. T. Archibald, P. Bartlein, L. Bopp, J. Chappellaz, P. Cox, N. R. Edwards, G. Feulner, P. Friedlingstein, S. P. Harrison, P. O. Hopcroft, C. D. Jones, J. Kolassa, J. G. Levine, I. C. Prentice, J. Pyle, N. Vázquez Riveiros, E. W. Wolff, and S. Zaehle
Biogeosciences, 10, 8305–8328, https://doi.org/10.5194/bg-10-8305-2013, https://doi.org/10.5194/bg-10-8305-2013, 2013
Related subject area
Earth system interactions with the biosphere: ecosystems
Opening Pandora's box: reducing global circulation model uncertainty in Australian simulations of the carbon cycle
Persistent La Niñas drive joint soybean harvest failures in North and South America
Spatiotemporal changes in the boreal forest in Siberia over the period 1985–2015 against the background of climate change
Downscaling of climate change scenarios for a high-resolution, site-specific assessment of drought stress risk for two viticultural regions with heterogeneous landscapes
Global climate change and the Baltic Sea ecosystem: direct and indirect effects on species, communities and ecosystem functioning
Widespread greening suggests increased dry-season plant water availability in the Rio Santa valley, Peruvian Andes
Spatiotemporal patterns and drivers of terrestrial dissolved organic carbon (DOC) leaching into the European river network
Impacts of compound hot–dry extremes on US soybean yields
Vulnerability of European ecosystems to two compound dry and hot summers in 2018 and 2019
Modelling forest ruin due to climate hazards
Exploring how groundwater buffers the influence of heatwaves on vegetation function during multi-year droughts
Diverging land-use projections cause large variability in their impacts on ecosystems and related indicators for ecosystem services
Impacts of land use change and elevated CO2 on the interannual variations and seasonal cycles of gross primary productivity in China
Investigating the applicability of emergent constraints
Tidal impacts on primary production in the North Sea
Steering operational synergies in terrestrial observation networks: opportunity for advancing Earth system dynamics modelling
Contrasting terrestrial carbon cycle responses to the 1997/98 and 2015/16 extreme El Niño events
Low-frequency variability in North Sea and Baltic Sea identified through simulations with the 3-D coupled physical–biogeochemical model ECOSMO
Vegetation–climate feedbacks modulate rainfall patterns in Africa under future climate change
Climate change increases riverine carbon outgassing, while export to the ocean remains uncertain
Spatial and temporal variations in plant water-use efficiency inferred from tree-ring, eddy covariance and atmospheric observations
Modelling short-term variability in carbon and water exchange in a temperate Scots pine forest
Establishment and maintenance of regulating ecosystem services in a dryland area of central Asia, illustrated using the Kökyar Protection Forest, Aksu, NW China, as an example
Do Himalayan treelines respond to recent climate change? An evaluation of sensitivity indicators
The impact of land cover generated by a dynamic vegetation model on climate over east Asia in present and possible future climate
Bimodality of woody cover and biomass across the precipitation gradient in West Africa
Critical impacts of global warming on land ecosystems
The influence of vegetation dynamics on anthropogenic climate change
Quantifying the thermodynamic entropy budget of the land surface: is this useful?
Lina Teckentrup, Martin G. De Kauwe, Gab Abramowitz, Andrew J. Pitman, Anna M. Ukkola, Sanaa Hobeichi, Bastien François, and Benjamin Smith
Earth Syst. Dynam., 14, 549–576, https://doi.org/10.5194/esd-14-549-2023, https://doi.org/10.5194/esd-14-549-2023, 2023
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Studies analyzing the impact of the future climate on ecosystems employ climate projections simulated by global circulation models. These climate projections display biases that translate into significant uncertainty in projections of the future carbon cycle. Here, we test different methods to constrain the uncertainty in simulations of the carbon cycle over Australia. We find that all methods reduce the bias in the steady-state carbon variables but that temporal properties do not improve.
Raed Hamed, Sem Vijverberg, Anne F. Van Loon, Jeroen Aerts, and Dim Coumou
Earth Syst. Dynam., 14, 255–272, https://doi.org/10.5194/esd-14-255-2023, https://doi.org/10.5194/esd-14-255-2023, 2023
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Spatially compounding soy harvest failures can have important global impacts. Using causal networks, we show that soy yields are predominately driven by summer soil moisture conditions in North and South America. Summer soil moisture is affected by antecedent soil moisture and by remote extra-tropical SST patterns in both hemispheres. Both of these soil moisture drivers are again influenced by ENSO. Our results highlight physical pathways by which ENSO can drive spatially compounding impacts.
Wenxue Fu, Lei Tian, Yu Tao, Mingyang Li, and Huadong Guo
Earth Syst. Dynam., 14, 223–239, https://doi.org/10.5194/esd-14-223-2023, https://doi.org/10.5194/esd-14-223-2023, 2023
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Climate change has been proven to be an indisputable fact and to be occurring at a faster rate in boreal forest areas. The results of this paper show that boreal forest coverage has shown an increasing trend in the past 3 decades, and the area of broad-leaved forests has increased more rapidly than that of coniferous forests. In addition, temperature rather than precipitation is the main climate factor that is driving change.
Marco Hofmann, Claudia Volosciuk, Martin Dubrovský, Douglas Maraun, and Hans R. Schultz
Earth Syst. Dynam., 13, 911–934, https://doi.org/10.5194/esd-13-911-2022, https://doi.org/10.5194/esd-13-911-2022, 2022
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We modelled water budget developments of viticultural growing regions on the spatial scale of individual vineyard plots with respect to landscape features like the available water capacity of the soils, slope, and aspect of the sites. We used an ensemble of climate simulations and focused on the occurrence of drought stress. The results show a high bandwidth of projected changes where the risk of potential drought stress becomes more apparent in steep-slope regions.
Markku Viitasalo and Erik Bonsdorff
Earth Syst. Dynam., 13, 711–747, https://doi.org/10.5194/esd-13-711-2022, https://doi.org/10.5194/esd-13-711-2022, 2022
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Climate change has multiple effects on Baltic Sea species, communities and ecosystem functioning. Effects on species distribution, eutrophication and trophic interactions are expected. We review these effects, identify knowledge gaps and draw conclusions based on recent (2010–2021) field, experimental and modelling research. An extensive summary table is compiled to highlight the multifaceted impacts of climate-change-driven processes in the Baltic Sea.
Lorenz Hänchen, Cornelia Klein, Fabien Maussion, Wolfgang Gurgiser, Pierluigi Calanca, and Georg Wohlfahrt
Earth Syst. Dynam., 13, 595–611, https://doi.org/10.5194/esd-13-595-2022, https://doi.org/10.5194/esd-13-595-2022, 2022
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To date, farmers' perceptions of hydrological changes do not match analysis of meteorological data. In contrast to rainfall data, we find greening of vegetation, indicating increased water availability in the past decades. The start of the season is highly variable, making farmers' perceptions comprehensible. We show that the El Niño–Southern Oscillation has complex effects on vegetation seasonality but does not drive the greening we observe. Improved onset forecasts could help local farmers.
Céline Gommet, Ronny Lauerwald, Philippe Ciais, Bertrand Guenet, Haicheng Zhang, and Pierre Regnier
Earth Syst. Dynam., 13, 393–418, https://doi.org/10.5194/esd-13-393-2022, https://doi.org/10.5194/esd-13-393-2022, 2022
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Dissolved organic carbon (DOC) leaching from soils into river networks is an important component of the land carbon (C) budget, but its spatiotemporal variation is not yet fully constrained. We use a land surface model to simulate the present-day land C budget at the European scale, including leaching of DOC from the soil. We found average leaching of 14.3 Tg C yr−1 (0.6 % of terrestrial net primary production) with seasonal variations. We determine runoff and temperature to be the main drivers.
Raed Hamed, Anne F. Van Loon, Jeroen Aerts, and Dim Coumou
Earth Syst. Dynam., 12, 1371–1391, https://doi.org/10.5194/esd-12-1371-2021, https://doi.org/10.5194/esd-12-1371-2021, 2021
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Soy yields in the US are affected by climate variability. We identify the main within-season climate drivers and highlight potential compound events and associated agricultural impacts. Our results show that soy yields are most negatively influenced by the combination of high temperature and low soil moisture during the summer crop reproductive period. Furthermore, we highlight the role of temperature and moisture coupling across the year in generating these hot–dry extremes and linked impacts.
Ana Bastos, René Orth, Markus Reichstein, Philippe Ciais, Nicolas Viovy, Sönke Zaehle, Peter Anthoni, Almut Arneth, Pierre Gentine, Emilie Joetzjer, Sebastian Lienert, Tammas Loughran, Patrick C. McGuire, Sungmin O, Julia Pongratz, and Stephen Sitch
Earth Syst. Dynam., 12, 1015–1035, https://doi.org/10.5194/esd-12-1015-2021, https://doi.org/10.5194/esd-12-1015-2021, 2021
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Temperate biomes in Europe are not prone to recurrent dry and hot conditions in summer. However, these conditions may become more frequent in the coming decades. Because stress conditions can leave legacies for many years, this may result in reduced ecosystem resilience under recurrent stress. We assess vegetation vulnerability to the hot and dry summers in 2018 and 2019 in Europe and find the important role of inter-annual legacy effects from 2018 in modulating the impacts of the 2019 event.
Pascal Yiou and Nicolas Viovy
Earth Syst. Dynam., 12, 997–1013, https://doi.org/10.5194/esd-12-997-2021, https://doi.org/10.5194/esd-12-997-2021, 2021
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This paper presents a model of tree ruin as a response to drought hazards. This model is inspired by a standard model of ruin in the insurance industry. We illustrate how ruin can occur in present-day conditions and the sensitivity of ruin and time to ruin to hazard statistical properties. We also show how tree strategies to cope with hazards can affect their long-term reserves and the probability of ruin.
Mengyuan Mu, Martin G. De Kauwe, Anna M. Ukkola, Andy J. Pitman, Weidong Guo, Sanaa Hobeichi, and Peter R. Briggs
Earth Syst. Dynam., 12, 919–938, https://doi.org/10.5194/esd-12-919-2021, https://doi.org/10.5194/esd-12-919-2021, 2021
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Groundwater can buffer the impacts of drought and heatwaves on ecosystems, which is often neglected in model studies. Using a land surface model with groundwater, we explained how groundwater sustains transpiration and eases heat pressure on plants in heatwaves during multi-year droughts. Our results showed the groundwater’s influences diminish as drought extends and are regulated by plant physiology. We suggest neglecting groundwater in models may overstate projected future heatwave intensity.
Anita D. Bayer, Richard Fuchs, Reinhard Mey, Andreas Krause, Peter H. Verburg, Peter Anthoni, and Almut Arneth
Earth Syst. Dynam., 12, 327–351, https://doi.org/10.5194/esd-12-327-2021, https://doi.org/10.5194/esd-12-327-2021, 2021
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Many projections of future land-use/-cover exist. We evaluate a number of these and determine the variability they cause in ecosystems and their services. We found that projections differ a lot in regional patterns, with some patterns being at least questionable in a historical context. Across ecosystem service indicators, resulting variability until 2040 was highest in crop production. Results emphasize that such variability should be acknowledged in assessments of future ecosystem provisions.
Binghao Jia, Xin Luo, Ximing Cai, Atul Jain, Deborah N. Huntzinger, Zhenghui Xie, Ning Zeng, Jiafu Mao, Xiaoying Shi, Akihiko Ito, Yaxing Wei, Hanqin Tian, Benjamin Poulter, Dan Hayes, and Kevin Schaefer
Earth Syst. Dynam., 11, 235–249, https://doi.org/10.5194/esd-11-235-2020, https://doi.org/10.5194/esd-11-235-2020, 2020
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We quantitatively examined the relative contributions of climate change, land
use and land cover change, and elevated CO2 to interannual variations and seasonal cycle amplitude of gross primary productivity (GPP) in China based on multi-model ensemble simulations. The contributions of major subregions to the temporal change in China's total GPP are also presented. This work may help us better understand GPP spatiotemporal patterns and their responses to regional changes and human activities.
Alexander J. Winkler, Ranga B. Myneni, and Victor Brovkin
Earth Syst. Dynam., 10, 501–523, https://doi.org/10.5194/esd-10-501-2019, https://doi.org/10.5194/esd-10-501-2019, 2019
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The concept of
emergent constraintsis a key method to reduce uncertainty in multi-model climate projections using historical simulations and observations. Here, we present an in-depth analysis of the applicability of the method and uncover possible limitations. Key limitations are a lack of comparability (temporal, spatial, and conceptual) between models and observations and the disagreement between models on system dynamics throughout different levels of atmospheric CO2 concentration.
Changjin Zhao, Ute Daewel, and Corinna Schrum
Earth Syst. Dynam., 10, 287–317, https://doi.org/10.5194/esd-10-287-2019, https://doi.org/10.5194/esd-10-287-2019, 2019
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Our study highlights the importance of tides in controlling the spatial and temporal distributions North Sea primary production based on numerical experiments. We identified two different response chains acting in different regions of the North Sea. (i) In the southern shallow areas, strong tidal mixing dilutes phytoplankton concentrations and increases turbidity, thus decreasing NPP. (ii) In the frontal regions, tidal mixing infuses nutrients into the surface mixed layer, thus increasing NPP.
Roland Baatz, Pamela L. Sullivan, Li Li, Samantha R. Weintraub, Henry W. Loescher, Michael Mirtl, Peter M. Groffman, Diana H. Wall, Michael Young, Tim White, Hang Wen, Steffen Zacharias, Ingolf Kühn, Jianwu Tang, Jérôme Gaillardet, Isabelle Braud, Alejandro N. Flores, Praveen Kumar, Henry Lin, Teamrat Ghezzehei, Julia Jones, Henry L. Gholz, Harry Vereecken, and Kris Van Looy
Earth Syst. Dynam., 9, 593–609, https://doi.org/10.5194/esd-9-593-2018, https://doi.org/10.5194/esd-9-593-2018, 2018
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Focusing on the usage of integrated models and in situ Earth observatory networks, three challenges are identified to advance understanding of ESD, in particular to strengthen links between biotic and abiotic, and above- and below-ground processes. We propose developing a model platform for interdisciplinary usage, to formalize current network infrastructure based on complementarities and operational synergies, and to extend the reanalysis concept to the ecosystem and critical zone.
Jun Wang, Ning Zeng, Meirong Wang, Fei Jiang, Hengmao Wang, and Ziqiang Jiang
Earth Syst. Dynam., 9, 1–14, https://doi.org/10.5194/esd-9-1-2018, https://doi.org/10.5194/esd-9-1-2018, 2018
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Behaviors of terrestrial ecosystems differ in different El Niños. We analyze terrestrial carbon cycle responses to two extreme El Niños (2015/16 and 1997/98), and find large differences. We find that global land–atmosphere carbon flux anomaly was about 2 times smaller in 2015/16 than in 1997/98 event, without the obvious lagged response. Then we illustrate the climatic and biological mechanisms of the different terrestrial carbon cycle responses in 2015/16 and 1997/98 El Niños regionally.
Ute Daewel and Corinna Schrum
Earth Syst. Dynam., 8, 801–815, https://doi.org/10.5194/esd-8-801-2017, https://doi.org/10.5194/esd-8-801-2017, 2017
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Processes behind observed long-term variations in marine ecosystems are difficult to be deduced from in situ observations only. By statistically analysing a 61-year model simulation for the North Sea and Baltic Sea and additional model scenarios, we identified major modes of variability in the environmental variables and associated those with changes in primary production. We found that the dominant impact on changes in ecosystem productivity was introduced by modulations of the wind fields.
Minchao Wu, Guy Schurgers, Markku Rummukainen, Benjamin Smith, Patrick Samuelsson, Christer Jansson, Joe Siltberg, and Wilhelm May
Earth Syst. Dynam., 7, 627–647, https://doi.org/10.5194/esd-7-627-2016, https://doi.org/10.5194/esd-7-627-2016, 2016
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On Earth, vegetation does not merely adapt to climate but also imposes significant influences on climate with both local and remote effects. In this study we evaluated the role of vegetation in African climate with a regional Earth system model. By the comparison between the experiments with and without dynamic vegetation changes, we found that vegetation can influence climate remotely, resulting in modulating rainfall patterns over Africa.
F. Langerwisch, A. Walz, A. Rammig, B. Tietjen, K. Thonicke, and W. Cramer
Earth Syst. Dynam., 7, 559–582, https://doi.org/10.5194/esd-7-559-2016, https://doi.org/10.5194/esd-7-559-2016, 2016
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In Amazonia, carbon fluxes are considerably influenced by annual flooding. We applied the newly developed model RivCM to several climate change scenarios to estimate potential changes in riverine carbon. We find that climate change causes substantial changes in riverine organic and inorganic carbon, as well as changes in carbon exported to the atmosphere and ocean. Such changes could have local and regional impacts on the carbon budget of the whole Amazon basin and parts of the Atlantic Ocean.
Stefan C. Dekker, Margriet Groenendijk, Ben B. B. Booth, Chris Huntingford, and Peter M. Cox
Earth Syst. Dynam., 7, 525–533, https://doi.org/10.5194/esd-7-525-2016, https://doi.org/10.5194/esd-7-525-2016, 2016
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Our analysis allows us to infer maps of changing plant water-use efficiency (WUE) for 1901–2010, using atmospheric observations of temperature, humidity and CO2. Our estimated increase in global WUE is consistent with the tree-ring and eddy covariance data, but much larger than the historical WUE increases simulated by Earth System Models (ESMs). We therefore conclude that the effects of increasing CO2 on plant WUE are significantly underestimated in the latest climate projections.
M. H. Vermeulen, B. J. Kruijt, T. Hickler, and P. Kabat
Earth Syst. Dynam., 6, 485–503, https://doi.org/10.5194/esd-6-485-2015, https://doi.org/10.5194/esd-6-485-2015, 2015
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We compared a process-based ecosystem model (LPJ-GUESS) with EC measurements to test whether observed interannual variability (IAV) in carbon and water fluxes can be reproduced because it is important to understand the driving mechanisms of IAV. We show that the model's mechanistic process representation for photosynthesis at low temperatures and during drought could be improved, but other process representations are still lacking in order to fully reproduce the observed IAV.
S. Missall, M. Welp, N. Thevs, A. Abliz, and Ü. Halik
Earth Syst. Dynam., 6, 359–373, https://doi.org/10.5194/esd-6-359-2015, https://doi.org/10.5194/esd-6-359-2015, 2015
U. Schickhoff, M. Bobrowski, J. Böhner, B. Bürzle, R. P. Chaudhary, L. Gerlitz, H. Heyken, J. Lange, M. Müller, T. Scholten, N. Schwab, and R. Wedegärtner
Earth Syst. Dynam., 6, 245–265, https://doi.org/10.5194/esd-6-245-2015, https://doi.org/10.5194/esd-6-245-2015, 2015
Short summary
Short summary
Near-natural Himalayan treelines are usually krummholz treelines, which are relatively unresponsive to climate change. Intense recruitment of treeline trees suggests a great potential for future treeline advance. Competitive abilities of tree seedlings within krummholz thickets and dwarf scrub heaths will be a major source of variation in treeline dynamics. Tree growth-climate relationships show mature treeline trees to be responsive in particular to high pre-monsoon temperature trends.
M.-H. Cho, K.-O. Boo, G. M. Martin, J. Lee, and G.-H. Lim
Earth Syst. Dynam., 6, 147–160, https://doi.org/10.5194/esd-6-147-2015, https://doi.org/10.5194/esd-6-147-2015, 2015
Z. Yin, S. C. Dekker, B. J. J. M. van den Hurk, and H. A. Dijkstra
Earth Syst. Dynam., 5, 257–270, https://doi.org/10.5194/esd-5-257-2014, https://doi.org/10.5194/esd-5-257-2014, 2014
S. Ostberg, W. Lucht, S. Schaphoff, and D. Gerten
Earth Syst. Dynam., 4, 347–357, https://doi.org/10.5194/esd-4-347-2013, https://doi.org/10.5194/esd-4-347-2013, 2013
U. Port, V. Brovkin, and M. Claussen
Earth Syst. Dynam., 3, 233–243, https://doi.org/10.5194/esd-3-233-2012, https://doi.org/10.5194/esd-3-233-2012, 2012
N. A. Brunsell, S. J. Schymanski, and A. Kleidon
Earth Syst. Dynam., 2, 87–103, https://doi.org/10.5194/esd-2-87-2011, https://doi.org/10.5194/esd-2-87-2011, 2011
Cited articles
Ahlbeck, J. R.: Comment on “Variations in northern vegetation activity
inferred from satellite data of vegetation index during 1981–1999” by
L. Zhou et al., J. Geophys. Res.-Atmos., 107, 2002.
Ahlstrom, A., Raupach, M. R., Schurgers, G., Smith, B., Arneth, A., Jung, M.,
Reichstein, M., Canadell, J. G., Friedlingstein, P., Jain, A. K., Kato, E.,
Poulter, B., Sitch, S., Stocker, B. D., Viovy, N., Wang, Y. P., Wiltshire, A.,
Zaehle, S., and Zeng, N.: Carbon cycle. The dominant role of semi-arid ecosystems
in the trend and variability of the land CO2 sink, Science, 348, 895–899, 2015.
Anav, A., Friedlingstein, P., Beer, C., Ciais, P., Harper, A., Jones, C.,
Murray-Tortarolo, G., Papale, D., Parazoo, N. C., Peylin, P., Piao, S. L.,
Sitch, S., Viovy, N., Wiltshire, A., and Zhao, M. S.: Spatiotemporal patterns
of terrestrial gross primary production: A review, Rev. Geophys., 53, 785–818, 2015.
Ballantyne, A. P., Alden, C. B., Miller, J. B., and Tans, P. P.: Increase in
observed net carbon dioxide uptake by land and oceans during the past
50 years – ProQuest, Nature, 488, 7409, https://doi.org/10.1038/nature11299 2012.
Bartalev, S. A., Belward, A. S., Erchov, D. V., and Isaev, A. S.: A new
SPOT4-VEGETATION derived land cover map of Northern Eurasia, Int. J. Remote
Sens., 24, 1977–1982, 2003.
Bartholome, E., Belward, A. S., Achard, F., Bartalev, S., Carmona-Moreno, C.,
Eva, H., Fritz, S., Gregoire, J. M., Mayaux, P., and Stibig, H. J.: GLC 2000:
Global Land Cover mapping for the year 2000, Project status November 2002,
Publication of the European Commission, JRC, Ispra, 2002.
Beer, C., Reichstein, M., Tomelleri, E., Ciais, P., Jung, M., Carvalhais, N.,
Rodenbeck, C., Arain, M. A., Baldocchi, D., Bonan, G. B., Bondeau, A., Cescatti,
A., Lasslop, G., Lindroth, A., Lomas, M., Luyssaert, S., Margolis, H., Oleson,
K. W., Roupsard, O., Veenendaal, E., Viovy, N., Williams, C., Woodward, F. I.,
and Papale, D.: Terrestrial gross carbon dioxide uptake: global distribution
and covariation with climate, Science, 329, 834–838, 2010.
Bonan, G. B. and Levis, S.: Evaluating aspects of the community land and
atmosphere models (CLM3 and CAM3) using a Dynamic Global Vegetation Model, J.
Climate, 19, 2290–2301, 2006.
Bonan, G. B., Levis, S., Sitch, S., Vertenstein, M., and Oleson, K. W.: A
dynamic global vegetation model for use with climate models, Global Change Biol.,
9, 1543–1566, 2002.
Bond, W. J., Woodward, F. I., and Midgley, G. F.: The global distribution of
ecosystems in a world without fire, New Phytol., 165, 525–537, https://doi.org/10.1111/j.1469-8137.2004.01252.x, 2005.
Claussen, M. and Gayler, V.: The greening of the Sahara during the mid-Holocene:
results of an interactive atmosphere-biome model, Global Ecol. Biogeogr. Lett.,
6, 369–377, 1997.
Collatz, G. J., Ball, J. T., Grivet, C., and Berry, J. A.: Physiological and
Environmental-Regulation of Stomatal Conductance, Photosynthesis and
Transpiration – a Model That Includes a Laminar Boundary-Layer, Agr. Forest
Meteorol., 54, 107–136, 1991.
Collatz, G. J., Ribas-Carbo, M., and Berry, J. A.: Coupled Photosynthesis-Stomatal
Conductance Model for Leaves of C4 Plants, Aust. J. Plant Physiol., 19, 519–538, 1992.
Cox, P.: Description of the “TRIFFID” Dynamic Global Vegetation Model, Hadley
Centre technical note 24, Hadley Centre, Exeter, UK, 1–16, 2001.
Cox, P., Betts, R. A., Jones, C. D., Spall, S. A., and Totterdell, I. J.:
Acceleration of global warming due to carbon-cycle feedbacks in a coupled
climate model, Nature, 408, 184–187, 2000.
Cramer, W., Bondeau, A., Woodward, F. I., Prentice, I. C., Betts, R. A.,
Brovkin, V., Cox, P. M., Fisher, V., Foley, J. A., Friend, A. D., Kucharik, C.,
Lomas, M. R., Ramankutty, N., Sitch, S., Smith, B., White, A., and Young-Molling,
C.: Global response of terrestrial ecosystem structure and function to
CO2 and climate change: results from six dynamic global vegetation
models, Global Change Biol., 7, 357–373, 2001.
Devaraju, N., Bala, G., Caldeira, K., and Nemani, R.: A model based investigation
of the relative importance of CO2-fertilization, climate warming,
nitrogen deposition and land use change on the global terrestrial carbon uptake
in the historical period, Clim. Dynam., 47, 173–190, 2016.
Donohue, R. J., McVicar, T. R., and Roderick, M. L.: Climate-related trends in
Australian vegetation cover as inferred from satellite observations, 1981–2006,
Global Change Biol., 15, 1025–1039, 2009.
Dorman, J. L. and Sellers, P. J.: A Global Climatology of Albedo, Roughness
Length and Stomatal-Resistance for Atmospheric General-Circulation Models as
Represented by the Simple Biosphere Model (Sib), J. Appl. Meteorol., 28, 833–855, 1989.
Elmendorf, S. C., Henry, G. H. R., Hollister, R. D., Bjork, R. G.,
Boulanger-Lapointe, N., Cooper, E. J., Cornelissen, J. H. C., Day, T. A.,
Dorrepaal, E., Elumeeva, T. G., Gill, M., Gould, W. A., Harte, J., Hik, D. S.,
Hofgaard, A., Johnson, D. R., Johnstone, J. F., Jonsdottir, I. S., Jorgenson,
J. C., Klanderud, K., Klein, J. A., Koh, S., Kudo, G., Lara, M., Levesque, E.,
Magnusson, B., May, J. L., Mercado-Diaz, J. A., Michelsen, A., Molau, U.,
Myers-Smith, I. H., Oberbauer, S. F., Onipchenko, V. G., Rixen, C., Schmidt,
N. M., Shaver, G. R., Spasojevic, M. J., Porhallsdottir, P. E., Tolvanen, A.,
Troxler, T., Tweedie, C. E., Villareal, S., Wahren, C. H., Walker, X., Webber,
P. J., Welker, J. M., and Wipf, S.: Plot-scale evidence of tundra vegetation
change and links to recent summer warming, Nat. Clim. Change, 2, 453–457, 2012.
Epstein, H. E., Raynolds, M. K., Walker, D. A., Bhatt, U. S., Tucker, C. J.,
and Pinzon, J. E.: Dynamics of aboveground phytomass of the circumpolar Arctic
tundra during the past three decades, Environ. Res. Lett., 7, 015506,
https://doi.org/10.1088/1748-9326/7/1/015506, 2012.
Friedl, M. A., Sulla-Menashe, D., Tan, B., Schneider, A., Ramankutty, N.,
Sibley, A., and Huang, X. M.: MODIS Collection 5 global land cover: Algorithm
refinements and characterization of new datasets, Remote Sens. Environ., 114, 168–182, 2010.
Friedlingstein, P., Cox, P., Betts, R., Bopp, L., Von Bloh, W., Brovkin, V.,
Cadule, P., Doney, S., Eby, M., Fung, I., Bala, G., John, J., Jones, C., Joos,
F., Kato, T., Kawamiya, M., Knorr, W., Lindsay, K., Matthews, H. D., Raddatz,
T., Rayner, P., Reick, C., Roeckner, E., Schnitzler, K. G., Schnur, R.,
Strassmann, K., Weaver, A. J., Yoshikawa, C., and Zeng, N.: Climate-carbon cycle
feedback analysis: Results from the (CMIP)-M-4 model intercomparison, J. Climate,
19, 3337–3353, 2006.
Fu, C., Yan, X. D., and Guo, W. D.: Aridification of northern china and
adaptability of humanbeing: Use the concept of earth system science to solve
global regional respondence and adaptability problems under demands of natio,
Prog. Nat. Sci., 16, 1216–1223, 2006.
Garcia, R. A., Cabeza, M., Rahbek, C., and Araujo, M. B.: Multiple dimensions
of climate change and their implications for biodiversity, Science, 344, 1247579,
https://doi.org/10.1126/science.1247579, 2014.
Giglio, L., Csiszar, I., and Justice, C. O.: Global distribution and seasonality
of active fires as observed with the Terra and Aqua Moderate Resolution Imaging
Spectroradiometer (MODIS) sensors, J. Geophys. Res.-Biogeo., 111, https://doi.org/10.1029/2005JG000142, 2006.
Gong, D. and Ho, C. H.: Shift in the summer rainfall over the Yangtze River
valley in the late 1970s, Geophys. Res. Lett., 29, 78-71–78-74, 2002.
Harper, A. B., Cox, P. M., Friedlingstein, P., Wiltshire, A. J., Jones, C. D.,
Sitch, S., Mercado, L. M., Groenendijk, M., Robertson, E., Kattge, J.,
Bönisch, G., Atkin, O. K., Bahn, M., Cornelissen, J., Niinemets, Ü.,
Onipchenko, V., Peñuelas, J., Poorter, L., Reich, P. B., Soudzilovskaia, N.
A., and Bodegom, P. V.: Improved representation of plant functional types and
physiology in the Joint UK Land Environment Simulator (JULES v4.2) using plant
trait information, Geosci. Model Dev., 9, 2415–2440, https://doi.org/10.5194/gmd-9-2415-2016, 2016.
Herrmann, S. M., Anyamba, A., and Tucker, C. J.: Recent trends in vegetation
dynamics in the African Sahel and their relationship to climate, Global Environ.
Change-Human Policy Dimens., 15, 394–404, 2005.
Hilker, T., Lyapustin, A. I., Tucker, C. J., Hall, F. G., Myneni, R. B., Wang,
Y., Bi, J., Mendes de Moura, Y., and Sellers, P. J.: Vegetation dynamics and
rainfall sensitivity of the Amazon, P. Natl. Acad. Sci. USA, 111, 16041–16046, 2014.
Huntzinger, D. N., Michalak, A. M., Schwalm, C., Ciais, P., King, A. W., Fang,
Y., Schaefer, K., Wei, Y., Cook, R. B., Fisher, J. B., Hayes, D., Huang, M.,
Ito, A., Jain, A. K., Lei, H., Lu, C., Maignan, F., Mao, J., Parazoo, N., Peng,
S., Poulter, B., Ricciuto, D., Shi, X., Tian, H., Wang, W., Zeng, N., and Zhao,
F.: Uncertainty in the response of terrestrial carbon sink to environmental
drivers undermines carbon-climate feedback predictions, Sci. Rep., 7, 4765,
https://doi.org/10.1038/s41598-017-03818-2, 2017.
Ichii, K., Kondo, M., Okabe, Y., Ueyama, M., Kobayashi, H., Lee, S. J., Saigusa,
N., Zhu, Z. C., and Myneni, R. B.: Recent Changes in Terrestrial Gross Primary
Productivity in Asia from 1982 to 2011, Remote Sensing, 5, 6043–6062, 2013.
Jiang, C., Ryu, Y., Fang, H., Myneni, R., Claverie, M., and Zhu, Z.:
Inconsistencies of interannual variability and trends in long-term satellite
leaf area index products, Global Change Biol., 23, 4133–4146, 2017.
Jung, M., Reichstein, M., and Bondeau, A.: Towards global empirical upscaling
of FLUXNET eddy covariance observations: validation of a model tree ensemble
approach using a biosphere model, Biogeosciences, 6, 2001–2013, https://doi.org/10.5194/bg-6-2001-2009, 2009.
Krinner, G., Viovy, N., de Noblet-Ducoudré, N., Ogée, J., Polcher, J.,
Friedlingstein, P., Ciais, P., Sitch, S., and Prentice, I. C.: A dynamic global
vegetation model for studies of the coupled atmosphere-biosphere system, Global
Biogeochem. Cy., 19, GB1015, https://doi.org/10.1029/2003GB002199, 2005.
Lawrence, D. M., Oleson, K. W., Flanner, M. G., Thornton, P. E., Swenson, S. C.,
Lawrence, P. J., Zeng, X. B., Yang, Z. L., Levis, S., Sakaguchi, K., Bonan, G.
B., and Slater, A. G.: Parameterization Improvements and Functional and
Structural Advances in Version 4 of the Community Land Model, J. Adv. Model
Earth Syst., 3, https://doi.org/10.1029/2011MS00045, 2011.
Leakey, A. D. B., Ainsworth, E. A., Bernacchi, C. J., Rogers, A., Long, S. P.,
and Ort, D. R.: Elevated CO2 effects on plant carbon, nitrogen, and
water relations: six important lessons from FACE, J. Exp. Bot., 60, 2859–2876, 2009.
Lee, J.-S.: Combined effect of elevated CO2 and temperature on the
growth and phenology of two annual C3 and C4 weedy species, Agricult.
Ecosyst. Environ., 140, 484–491, 2011.
Le Quéré, C., Andres, R. J., Boden, T., Conway, T., Houghton, R. A.,
House, J. I., Marland, G., Peters, G. P., van der Werf, G. R., Ahlström, A.,
Andrew, R. M., Bopp, L., Canadell, J. G., Ciais, P., Doney, S. C., Enright, C.,
Friedlingstein, P., Huntingford, C., Jain, A. K., Jourdain, C., Kato, E.,
Keeling, R. F., Klein Goldewijk, K., Levis, S., Levy, P., Lomas, M., Poulter,
B., Raupach, M. R., Schwinger, J., Sitch, S., Stocker, B. D., Viovy, N., Zaehle,
S., and Zeng, N.: The global carbon budget 1959–2011, Earth Syst. Sci. Data,
5, 165–185, https://doi.org/10.5194/essd-5-165-2013, 2013.
Liu, Y. and Xue, Y.: SSiB4/TRIFFID simulated vegetation fraction, LAI and GPP,
available at: https://ucla.box.com/v/ssib4-offline, 2015.
Liu, Z., Notaro, M., Kutzbach, J., and Liu, N.: Assessing global vegetation-climate
feedbacks from observations, J. Climate, 19, 787–814, 2006.
Lo, T. T. and Hsu, H. H.: Change in the dominant decadal patterns and the
late 1980s abrupt warming in the extratropical Northern Hemisphere, Atmos. Sci.
Lett., 11, 210–215, 2010.
Los, S. O.: Analysis of trends in fused AVHRR and MODIS NDVI data for 1982–2006:
Indication for a CO2 fertilization effect in global vegetation, Global
Biogeochem. Cy., 27, 318–330, 2013.
Ma, H., Mechoso, C. R., Xue, Y., Xiao, H., Neelin, J. D., and Ji, X.: On the
Connection between Continental-Scale Land Surface Processes and the Tropical
Climate in a Coupled Ocean-Atmosphere-Land System, J. Climate, 26, 9006–9025, 2013.
MacDonald, G. M.: Biogeography: Introduction to Space, Time and Life, Wiley, New York, 2003.
Mahowald, N., Lo, F., Zheng, Y., Harrison, L., Funk, C., Lombardozzi, D., and
Goodale, C.: Leaf Area Index in Earth System Models: evaluation and projections,
Earth Syst. Dynam., 7, 211–229, https://doi.org/10.5194/esd-7-211-2016, 2016.
Mao, J., Shi, X., Thornton, P. E., Hoffman, F. M., Zhu, Z., and Myneni, R. B.:
Global latitudinal-asymmetric vegetation growth trends and their driving
mechanisms: 1982–2009, Remote Sensing, 5, 1484–1497, 2013.
Martin, A. C., Jeffers, E. S., Petrokofsky, G., Myers-Smith, I., and Macias-Fauria,
M.: Shrub growth and expansion in the Arctic tundra: an assessment of controlling
factors using an evidence-based approach, Environ. Res. Lett., 12, 085007,
https://doi.org/10.1088/1748-9326/aa7989, 2017.
McDowell, N. G., Coops, N. C., Beck, P. S., Chambers, J. Q., Gangodagamage, C.,
Hicke, J. A., Huang, C. Y., Kennedy, R., Krofcheck, D. J., Litvak, M., Meddens,
A. J., Muss, J., Negron-Juarez, R., Peng, C., Schwantes, A. M., Swenson, J. J.,
Vernon, L. J., Williams, A. P., Xu, C., Zhao, M., Running, S. W., and Allen,
C. D.: Global satellite monitoring of climate-induced vegetation disturbances,
Trends Plant Sci., 20, 114–123, https://doi.org/10.1016/j.tplants.2014.10.008, 2015.
Miri, H. R., Rastegar, A., and Bagheri, A. R.: The impact of elevated CO2
on growth and competitiveness of C3 and C4 crops and weeds, Eur. J.
Exp. Biol., 2, 1144–1150, 2012.
Mod, H. K. and Luoto, M.: Arctic shrubification mediates the impacts of warming
climate on changes to tundra vegetation, Environ. Res. Lett., 11, 124028, 2016.
Murray-Tortarolo, G., Anav, A., Friedlingstein, P., Sitch, S., Piao, S. L., Zhu,
Z. C., Poulter, B., Zaehle, S., Ahlstrom, A., Lomas, M., Levis, S., Viovy, N.,
and Zeng, N.: Evaluation of Land Surface Models in Reproducing Satellite-Derived
LAI over the High-Latitude Northern Hemisphere. Part I: Uncoupled DGVMs, Remote
Sensing, 5, 4819–4838, 2013.
Myers-Smith, I. H., Elmendorf, S. C., Beck, P. S. A., Wilmking, M., Hallinger,
M., Blok, D., Tape, K. D., Rayback, S. A., Macias-Fauria, M., Forbes, B. C.,
Speed, J. D. M., Boulanger-Lapointe, N., Rixen, C., Lévesque, E., Schmidt,
N. M., Baittinger, C., Trant, A. J., Hermanutz, L., Collier, L. S., Dawes, M.
A., Lantz, T. C., Weijers, S., Jørgensen, R. H., Buchwal, A., Buras, A.,
Naito, A. T., Ravolainen, V., Schaepman-Strub, G., Wheeler, J. A., Wipf, S.,
Guay, K. C., Hik, D. S., and Vellend, M.: Climate sensitivity of shrub growth
across the tundra biome, Nat. Clim. Change, 5, 887–891, 2015.
Myneni, R. B., Keeling, C. D., Tucker, C. J., Asrar, G., and Nemani, R. R.:
Increased plant growth in the northern high latitudes from 1981 to 1991,
Nature, 386, 698–702, 1997.
Nemani, R. R., Keeling, C. D., Hashimoto, H., Jolly, W. M., Piper, S. C., Tucker,
C. J., Myneni, R. B., and Running, S. W.: Climate-driven increases in global
terrestrial net primary production from 1982 to 1999, Science, 300, 1560–1563, 2003.
O'Sullivan O, S., Heskel, M. A., Reich, P. B., Tjoelker, M. G., Weerasinghe, L.
K., Penillard, A., Zhu, L., Egerton, J. J., Bloomfield, K. J., Creek, D., Bahar,
N. H., Griffin, K. L., Hurry, V., Meir, P., Turnbull, M. H., and Atkin, O. K.:
Thermal limits of leaf metabolism across biomes, Global Change Biol., 23, 209–223, 2017.
Piao, S., Fang, J., Liu, H., and Zhu, B.: NDVI-indicated decline in
desertification in China in the past two decades, Geophys. Res. Lett., 32,
L06402, https://doi.org/10.1029/2004GL021764, 2005.
Piao, S., Wang, X., Ciais, P., Zhu, B., Wang, T., and Liu, J.: Changes in
satellite-derived vegetation growth trend in temperate and boreal Eurasia
from 1982 to 2006, Global Change Biol., 17, 3228–3239, 2011.
Piao, S., Sitch, S., Ciais, P., Friedlingstein, P., Peylin, P., Wang, X.,
Ahlstrom, A., Anav, A., Canadell, J. G., Cong, N., Huntingford, C., Jung, M.,
Levis, S., Levy, P. E., Li, J., Lin, X., Lomas, M. R., Lu, M., Luo, Y., Ma, Y.,
Myneni, R. B., Poulter, B., Sun, Z., Wang, T., Viovy, N., Zaehle, S., and Zeng,
N.: Evaluation of terrestrial carbon cycle models for their response to climate
variability and to CO2 trends, Global Change Biol., 19, 2117–2132,
https://doi.org/10.1111/gcb.12187, 2013.
Piao, S., Yin, G., Tan, J., Cheng, L., Huang, M., Li, Y., Liu, R., Mao, J.,
Myneni, R. B., Peng, S., Poulter, B., Shi, X., Xiao, Z., Zeng, N., Zeng, Z.,
and Wang, Y.: Detection and attribution of vegetation greening trend in China
over the last 30 years, Global Change Biol., 21, 1601–1609, 2015.
Poulter, B., Frank, D., Ciais, P., Myneni, R. B., Andela, N., Bi, J., Broquet,
G., Canadell, J. G., Chevallier, F., Liu, Y. Y., and Running, S. W.: Contribution
of semi-arid ecosystems to interannual variability of the global carbon cycle,
Nature, 509, 600–603, 2014.
Reid, P. C., Hari, R. E., Beaugrand, G., Livingstone, D. M., Marty, C., Straile,
D., Barichivich, J., Goberville, E., Adrian, R., Aono, Y., Brown, R., Foster,
J., Groisman, P., Helaouet, P., Hsu, H. H., Kirby, R., Knight, J., Kraberg, A.,
Li, J., Lo, T. T., Myneni, R. B., North, R. P., Pounds, J. A., Sparks, T.,
Stubi, R., Tian, Y., Wiltshire, K. H., Xiao, D., and Zhu, Z.: Global impacts
of the 1980s regime shift, Global Change Biol., 22, 682–703, 2016.
Schimel, D., Stephens, B. B., and Fisher, J. B.: Effect of increasing CO2
on the terrestrial carbon cycle, P. Natl. Acad. Sci. USA, 112, 436–441, 2015.
Sheffield, J., Goteti, G., and Wood, E. F.: Development of a 50-year
high-resolution global dataset of meteorological forcings for land surface
modeling, J. Climate, 19, 3088–3111, 2006.
Sitch, S., Smith, B., Prentice, I. C., Arneth, A., Bondeau, A., Cramer, W.,
Kaplan, J. O., Levis, S., Lucht, W., Sykes, M. T., Thonicke, K., and Venevsky,
S.: Evaluation of ecosystem dynamics, plant geography and terrestrial carbon
cycling in the LPJ dynamic global vegetation model, Global Change Biol.,
9, 161–185, 2003.
Sitch, S., Friedlingstein, P., Gruber, N., Jones, S. D., Murray-Tortarolo, G.,
Ahlström, A., Doney, S. C., Graven, H., Heinze, C., Huntingford, C., Levis,
S., Levy, P. E., Lomas, M., Poulter, B., Viovy, N., Zaehle, S., Zeng, N., Arneth,
A., Bonan, G., Bopp, L., Canadell, J. G., Chevallier, F., Ciais, P., Ellis, R.,
Gloor, M., Peylin, P., Piao, S. L., Le Quéré, C., Smith, B., Zhu, Z.,
and Myneni, R.: Recent trends and drivers of regional sources and sinks of
carbon dioxide, Biogeosciences, 12, 653–679, https://doi.org/10.5194/bg-12-653-2015, 2015.
Slevin, D., Tett, S. F. B., Exbrayat, J.-F., Bloom, A. A., and Williams, M.:
Global evaluation of gross primary productivity in the JULES land surface
model v3.4.1, Geosci. Model Dev., 10, 2651–2670, https://doi.org/10.5194/gmd-10-2651-2017, 2017.
Smith, B., Prentice, I. C., and Sykes, M. T.: Representation of vegetation
dynamics in the modelling of terrestrial ecosystems: comparing two contrasting
approaches within European climate space, Global Ecol. Biogeogr., 10, 621–637, 2001.
Smith, W. K., Reed, S. C., Cleveland, C. C., Ballantyne, A. P., Anderegg, W.
R., Wieder, W. R., Liu, Y. Y., and Running, S. W.: Large divergence of
satellite and Earth system model estimates of global terrestrial CO2
fertilization, Nat. Clim. Change, 6, 306–310, 2016.
Stevens, N., Lehmann, C. E., Murphy, B. P., and Durigan, G.: Savanna woody
encroachment is widespread across three continents, Global Change Biol.,
23, 235–244, 2017.
Still, C. J., Berry, J. A., Collatz, G. J., and DeFries, R. S.: Global
distribution of C3 and C4 vegetation: Carbon cycle implications,
Global Biogeochem. Cy., 17, 6-1–6-14, 2003.
Tape, K., Sturm, M., and Racine, C.: The evidence for shrub expansion in
Northern Alaska and the Pan-Arctic, Global Change Biol., 12, 686–702, 2006.
Thomas, N. and Nigam, S.: Twentieth-Century Climate Change over Africa: Seasonal
Hydroclimate Trends and Sahara Desert Expansion, J. Climate, 31, 3349–3370, 2018.
Woodward, F. I. and Lomas, M. R.: Vegetation dynamics – simulating responses
to climatic change, Biol. Rev. Camb. Philos. Soc., 79, 643–670, 2004.
Wu, Z. D., Ahlstrom, A., Smith, B., Ardo, J., Eklundh, L., Fensholt, R., and
Lehsten, V.: Climate data induced uncertainty in model-based estimations of
terrestrial primary productivity, Environ. Res. Lett., 12, 064013,
https://doi.org/10.1088/1748-9326/aa6fd8, 2017.
Xiao, Z., Liang, S., Wang, J., Chen, P., Yin, X., Zhang, L. Q., and Song, J.:
Use of General Regression Neural Networks for Generating the GLASS Leaf Area
Index Product From Time-Series MODIS Surface Reflectance, IEEE T. Geosci.
Remote, 52, 209–223, 2014.
Xue, Y., Sellers, P. J., Kinter, J. L., and Shukla, J.: A Simplified Biosphere
Model for Global Climate Studies, J. Climate, 4, 345–364, 1991.
Xue, Y., Juang, H. M. H., Li, W. P., Prince, S., DeFries, R., Jiao, Y., and
Vasic, R.: Role of land surface processes in monsoon development: East Asia
and West Africa, J. Geophys. Res.-Atmos., 109, https://doi.org/10.1029/2003JD003556, 2004.
Xue, Y., De Sales, F., Vasic, R., Mechoso, C. R., Arakawa, A., and Prince, S.:
Global and Seasonal Assessment of Interactions between Climate and Vegetation
Biophysical Processes: A GCM Study with Different Land-Vegetation Representations,
J. Climate, 23, 1411–1433, 2010.
Yue, X., Unger, N., and Zheng, Y.: Distinguishing the drivers of trends in land
carbon fluxes and plant volatile emissions over the past 3 decades, Atmos. Chem.
Phys., 15, 11931–11948, https://doi.org/10.5194/acp-15-11931-2015, 2015.
Zaehle, S. and Friend, A. D.: Carbon and nitrogen cycle dynamics in the O-CN
land surface model: 1. Model description, site-scale evaluation, and sensitivity
to parameter estimates, Global Biogeochem. Cy., 24, https://doi.org/10.1029/2009GB003521, 2010.
Zeng, F., Collatz, G. J., Pinzon, J. E., and Ivanoff, A.: Evaluating and
Quantifying the Climate-Driven Interannual Variability in Global Inventory
Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI3g)
at Global Scales, Remote Sensing, 5, 3918–3950, 2013.
Zeng, N., Mariotti, A., and Wetzel, P.: Terrestrial mechanisms of interannual
CO2 variability, Global Biogeochem. Cy., 19, GB1016, https://doi.org/10.1029/2004gb002273, 2005.
Zeng, X., Zeng, X., and Barlage, M.: Growing temperate shrubs over arid and
semiarid regions in the Community Land Model-Dynamic Global Vegetation Model,
Global Biogeochem. Cy., 22, GB3003, https://doi.org/10.1029/2007GB003014, 2008.
Zhan, X., Xue, Y., and Collatz, G. J.: An analytical approach for estimating
CO2 and heat fluxes over the Amazonian region, Ecol. Model., 162, 97–117, 2003.
Zhang, Z., Xue, Y., MacDonald, G., Cox, P., and Collatz, G.: Investigation of
North American vegetation variability under recent climate: A study using
the SSiB4/TRIFFID biophysical/dynamic vegetation model, J. Geophys. Res.-Atmos.,
120, 1300–1321, 2015.
Zhu, Z., Bi, J., Pan, Y., Ganguly, S., Anav, A., Xu, L., Samanta, A., Piao, S.,
Nemani, R. R, and Myneni, R. B.: Global Data Sets of Vegetation Leaf Area
Index (LAI)3g and Fraction of Photosynthetically Active Radiation (FPAR)3g
Derived from Global Inventory Modeling and Mapping Studies (GIMMS) Normalized
Difference Vegetation Index (NDVI3g) for the Period 1981 to 2011, Remote Sensing,
5, 927–948, 2013.
Zhu, Z., Piao, S., Myneni, R. B., Huang, M., Zeng, Z., Canadell, J. G., Ciais,
P., Sitch, S., Friedlingstein, P., Arneth, A., Cao, C., Cheng, L., Kato, E.,
Koven, C., Li, Y., Lian, X., Liu, Y. W., Liu, R. G., Mao, J. F., Pan, Y. Z.,
Peng, S. S., Penuelas, J., Poulter, B., Pugh, T. A. M., Stocker, B. D., Viovy,
N., Wang, X., Wang, Y., Xiao, Z., Yang, H., Zaehle, S., and Zeng, N.: Greening
of the Earth and its drivers, Nat. Clim. Change, 6, 791–795, 2016.
Zhu, Z., Piao, S., Lian, X., Myneni, R. B., Peng, S., and Yang, H.: Attribution
of seasonal leaf area index trends in the northern latitudes with “optimally”
integrated ecosystem models, Global Change Biol., 23, 4798–4813, 2017.
Short summary
Climate regime shift during the 1980s identified by abrupt change in temperature, precipitation, etc. had a substantial impact on the ecosystem at different scales. Our paper identifies the spatial and temporal characteristics of the effects of climate variability, global warming, and eCO2 on ecosystem trends before and after the shift. We found about 15 % (20 %) of the global land area had enhanced positive trend (trend sign reversed) during the 1980s due to climate regime shift.
Climate regime shift during the 1980s identified by abrupt change in temperature, precipitation,...
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