Articles | Volume 16, issue 22
https://doi.org/10.5194/bg-16-4463-2019
© 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/bg-16-4463-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
25 Nov 2019
Research article |
| 25 Nov 2019
| 25 Nov 2019
The importance of physiological, structural and trait responses to drought stress in driving spatial and temporal variation in GPP across Amazon forests
Sophie Flack-Prain
CORRESPONDING AUTHOR
School of GeoSciences, University of Edinburgh, Edinburgh, UK
Patrick Meir
School of GeoSciences, University of Edinburgh, Edinburgh, UK
Research School of Biology, Australian National University, Canberra,
ACT, Australia
Yadvinder Malhi
Environmental Change Institute, School of Geography and the
Environment, University of Oxford, Oxford, UK
Thomas Luke Smallman
School of GeoSciences, University of Edinburgh, Edinburgh, UK
National Centre for Earth Observation, University of Edinburgh, Edinburgh, UK
Mathew Williams
School of GeoSciences, University of Edinburgh, Edinburgh, UK
National Centre for Earth Observation, University of Edinburgh, Edinburgh, UK
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Yan Yang, A. Anthony Bloom, Shuang Ma, Paul Levine, Alexander Norton, Nicholas C. Parazoo, John T. Reager, John Worden, Gregory R. Quetin, T. Luke Smallman, Mathew Williams, Liang Xu, and Sassan Saatchi
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Stephanie G. Stettz, Nicholas C. Parazoo, A. Anthony Bloom, Peter D. Blanken, David R. Bowling, Sean P. Burns, Cédric Bacour, Fabienne Maignan, Brett Raczka, Alexander J. Norton, Ian Baker, Mathew Williams, Mingjie Shi, Yongguang Zhang, and Bo Qiu
Biogeosciences, 19, 541–558, https://doi.org/10.5194/bg-19-541-2022, https://doi.org/10.5194/bg-19-541-2022, 2022
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Sami W. Rifai, Martin G. De Kauwe, Anna M. Ukkola, Lucas A. Cernusak, Patrick Meir, Belinda E. Medlyn, and Andy J. Pitman
Biogeosciences, 19, 491–515, https://doi.org/10.5194/bg-19-491-2022, https://doi.org/10.5194/bg-19-491-2022, 2022
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Thomas Luke Smallman, David Thomas Milodowski, Eráclito Sousa Neto, Gerbrand Koren, Jean Ometto, and Mathew Williams
Earth Syst. Dynam., 12, 1191–1237, https://doi.org/10.5194/esd-12-1191-2021, https://doi.org/10.5194/esd-12-1191-2021, 2021
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Earth Syst. Sci. Data, 13, 2607–2649, https://doi.org/10.5194/essd-13-2607-2021, https://doi.org/10.5194/essd-13-2607-2021, 2021
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Transpiration is a key component of global water balance, but it is poorly constrained from available observations. We present SAPFLUXNET, the first global database of tree-level transpiration from sap flow measurements, containing 202 datasets and covering a wide range of ecological conditions. SAPFLUXNET and its accompanying R software package
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Caroline A. Famiglietti, T. Luke Smallman, Paul A. Levine, Sophie Flack-Prain, Gregory R. Quetin, Victoria Meyer, Nicholas C. Parazoo, Stephanie G. Stettz, Yan Yang, Damien Bonal, A. Anthony Bloom, Mathew Williams, and Alexandra G. Konings
Biogeosciences, 18, 2727–2754, https://doi.org/10.5194/bg-18-2727-2021, https://doi.org/10.5194/bg-18-2727-2021, 2021
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Model uncertainty dominates the spread in terrestrial carbon cycle predictions. Efforts to reduce it typically involve adding processes, thereby increasing model complexity. However, if and how model performance scales with complexity is unclear. Using a suite of 16 structurally distinct carbon cycle models, we find that increased complexity only improves skill if parameters are adequately informed. Otherwise, it can degrade skill, and an intermediate-complexity model is optimal.
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.
Thomas Luke Smallman and Mathew Williams
Geosci. Model Dev., 12, 2227–2253, https://doi.org/10.5194/gmd-12-2227-2019, https://doi.org/10.5194/gmd-12-2227-2019, 2019
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Photosynthesis and evapotranspiration are processes with global significance for climate, carbon and water cycling. Process-orientated simulation of these processes and their interactions have till now come at high computational cost. Here we present a new coupled model of intermediate complexity operating at orders of magnitude greater speed. Independent evaluation at FLUXNET sites for a single, global parameterization shows good agreement, with a typical R2 value of ~ 0.60.
Efrén López-Blanco, Jean-François Exbrayat, Magnus Lund, Torben R. Christensen, Mikkel P. Tamstorf, Darren Slevin, Gustaf Hugelius, Anthony A. Bloom, and Mathew Williams
Earth Syst. Dynam., 10, 233–255, https://doi.org/10.5194/esd-10-233-2019, https://doi.org/10.5194/esd-10-233-2019, 2019
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The terrestrial CO2 exchange in Arctic ecosystems plays an important role in the global carbon cycle and is particularly sensitive to the ongoing warming experienced in recent years. To improve our understanding of the atmosphere–biosphere interplay, we evaluated the state of the terrestrial pan-Arctic carbon cycling using a promising data assimilation system in the first 15 years of the 21st century. This is crucial when it comes to making predictions about the future state of the carbon cycle.
Vasileios Myrgiotis, Mathew Williams, Robert M. Rees, and Cairistiona F. E. Topp
Biogeosciences, 16, 1641–1655, https://doi.org/10.5194/bg-16-1641-2019, https://doi.org/10.5194/bg-16-1641-2019, 2019
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This study focuses on a northwestern European cropland region and shows that the type of crop growing on a soil has notable effects on the emission of nitrous oxide (N2O – a greenhouse gas) from that soil. It was found that N2O emissions from soils under oilseed cultivation are significantly higher than soils under cereal cultivation. This variation is mostly explained by the fact that oilseeds require more nitrogen (fertiliser) than cereals, especially at early crop growth stages.
Anne Sofie Lansø, Thomas Luke Smallman, Jesper Heile Christensen, Mathew Williams, Kim Pilegaard, Lise-Lotte Sørensen, and Camilla Geels
Biogeosciences, 16, 1505–1524, https://doi.org/10.5194/bg-16-1505-2019, https://doi.org/10.5194/bg-16-1505-2019, 2019
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Although coastal regions only amount to 7 % of the global oceans, their contribution to the global oceanic surface exchange of CO2 is much greater. In this study, we gain detailed insight into how these coastal marine fluxes compare to CO2 exchange from coastal land regions. Annually, the coastal marine exchanges are smaller than the total uptake of CO2 from the land surfaces within the study area but comparable in size to terrestrial fluxes from individual land cover classes of the region.
Emily D. White, Matthew Rigby, Mark F. Lunt, T. Luke Smallman, Edward Comyn-Platt, Alistair J. Manning, Anita L. Ganesan, Simon O'Doherty, Ann R. Stavert, Kieran Stanley, Mathew Williams, Peter Levy, Michel Ramonet, Grant L. Forster, Andrew C. Manning, and Paul I. Palmer
Atmos. Chem. Phys., 19, 4345–4365, https://doi.org/10.5194/acp-19-4345-2019, https://doi.org/10.5194/acp-19-4345-2019, 2019
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Understanding carbon dioxide (CO2) fluxes from the terrestrial biosphere on a national scale is important for evaluating land use strategies to mitigate climate change. We estimate emissions of CO2 from the UK biosphere using atmospheric data in a top-down approach. Our findings show that bottom-up estimates from models of biospheric fluxes overestimate the amount of CO2 uptake in summer. This suggests these models wrongly estimate or omit key processes, e.g. land disturbance due to harvest.
Tommaso Jucker, Gregory P. Asner, Michele Dalponte, Philip G. Brodrick, Christopher D. Philipson, Nicholas R. Vaughn, Yit Arn Teh, Craig Brelsford, David F. R. P. Burslem, Nicolas J. Deere, Robert M. Ewers, Jakub Kvasnica, Simon L. Lewis, Yadvinder Malhi, Sol Milne, Reuben Nilus, Marion Pfeifer, Oliver L. Phillips, Lan Qie, Nathan Renneboog, Glen Reynolds, Terhi Riutta, Matthew J. Struebig, Martin Svátek, Edgar C. Turner, and David A. Coomes
Biogeosciences, 15, 3811–3830, https://doi.org/10.5194/bg-15-3811-2018, https://doi.org/10.5194/bg-15-3811-2018, 2018
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Efforts to protect tropical forests hinge on recognizing the ecosystem services they provide, including their ability to store carbon. Airborne laser scanning (ALS) captures information on the 3-D structure of forests, allowing carbon stocks to be mapped. By combining ALS with data from 173 field plots on the island of Borneo, we develop a simple yet general model for estimating forest carbon stocks from the air. Our model underpins ongoing efforts to restore Borneo's unique tropical forests.
Jean-François Exbrayat, A. Anthony Bloom, Pete Falloon, Akihiko Ito, T. Luke Smallman, and Mathew Williams
Earth Syst. Dynam., 9, 153–165, https://doi.org/10.5194/esd-9-153-2018, https://doi.org/10.5194/esd-9-153-2018, 2018
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We use global observations of current terrestrial net primary productivity (NPP) to constrain the uncertainty in large ensemble 21st century projections of NPP under a "business as usual" scenario using a skill-based multi-model averaging technique. Our results show that this procedure helps greatly reduce the uncertainty in global projections of NPP. We also identify regions where uncertainties in models and observations remain too large to confidently conclude a sign of the change of NPP.
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.
Efrén López-Blanco, Magnus Lund, Mathew Williams, Mikkel P. Tamstorf, Andreas Westergaard-Nielsen, Jean-François Exbrayat, Birger U. Hansen, and Torben R. Christensen
Biogeosciences, 14, 4467–4483, https://doi.org/10.5194/bg-14-4467-2017, https://doi.org/10.5194/bg-14-4467-2017, 2017
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An improvement in our process-based understanding of CO2 exchanges in the Arctic and their climate sensitivity is critical. With continued warming temperatures and longer growing seasons, tundra systems will likely increase rates of C cycling, although shifts in sink strength could take place, challenging the forecast of upcoming C states. In this context, we investigated the functional responses of C exchange to environmental characteristics across 8 consecutive years in West Greenland.
Darren Slevin, Simon F. B. Tett, Jean-François Exbrayat, A. Anthony Bloom, and Mathew Williams
Geosci. Model Dev., 10, 2651–2670, https://doi.org/10.5194/gmd-10-2651-2017, https://doi.org/10.5194/gmd-10-2651-2017, 2017
Sam P. Jones, Torsten Diem, Lidia P. Huaraca Quispe, Adan J. Cahuana, Dave S. Reay, Patrick Meir, and Yit Arn Teh
Biogeosciences, 13, 4151–4165, https://doi.org/10.5194/bg-13-4151-2016, https://doi.org/10.5194/bg-13-4151-2016, 2016
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Tropical montane forests represent a significant portion of Andean land cover, however, soil-atmosphere methane exchange in these ecosystems is under studied. Here we report on soil methane cycling in montane forests of the southern Peruvian Andes. These soils acted as a net sink for atmospheric methane and variation in uptake across the studied forests was best explained by nitrate inhibition of oxidation and/or limitations on the inward diffusion of methane from the atmosphere into the soil.
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.
Fabien H. Wagner, Bruno Hérault, Damien Bonal, Clément Stahl, Liana O. Anderson, Timothy R. Baker, Gabriel Sebastian Becker, Hans Beeckman, Danilo Boanerges Souza, Paulo Cesar Botosso, David M. J. S. Bowman, Achim Bräuning, Benjamin Brede, Foster Irving Brown, Jesus Julio Camarero, Plínio Barbosa Camargo, Fernanda C. G. Cardoso, Fabrício Alvim Carvalho, Wendeson Castro, Rubens Koloski Chagas, Jérome Chave, Emmanuel N. Chidumayo, Deborah A. Clark, Flavia Regina Capellotto Costa, Camille Couralet, Paulo Henrique da Silva Mauricio, Helmut Dalitz, Vinicius Resende de Castro, Jaçanan Eloisa de Freitas Milani, Edilson Consuelo de Oliveira, Luciano de Souza Arruda, Jean-Louis Devineau, David M. Drew, Oliver Dünisch, Giselda Durigan, Elisha Elifuraha, Marcio Fedele, Ligia Ferreira Fedele, Afonso Figueiredo Filho, César Augusto Guimarães Finger, Augusto César Franco, João Lima Freitas Júnior, Franklin Galvão, Aster Gebrekirstos, Robert Gliniars, Paulo Maurício Lima de Alencastro Graça, Anthony D. Griffiths, James Grogan, Kaiyu Guan, Jürgen Homeier, Maria Raquel Kanieski, Lip Khoon Kho, Jennifer Koenig, Sintia Valerio Kohler, Julia Krepkowski, José Pires Lemos-Filho, Diana Lieberman, Milton Eugene Lieberman, Claudio Sergio Lisi, Tomaz Longhi Santos, José Luis López Ayala, Eduardo Eijji Maeda, Yadvinder Malhi, Vivian R. B. Maria, Marcia C. M. Marques, Renato Marques, Hector Maza Chamba, Lawrence Mbwambo, Karina Liana Lisboa Melgaço, Hooz Angela Mendivelso, Brett P. Murphy, Joseph J. O'Brien, Steven F. Oberbauer, Naoki Okada, Raphaël Pélissier, Lynda D. Prior, Fidel Alejandro Roig, Michael Ross, Davi Rodrigo Rossatto, Vivien Rossi, Lucy Rowland, Ervan Rutishauser, Hellen Santana, Mark Schulze, Diogo Selhorst, Williamar Rodrigues Silva, Marcos Silveira, Susanne Spannl, Michael D. Swaine, José Julio Toledo, Marcos Miranda Toledo, Marisol Toledo, Takeshi Toma, Mario Tomazello Filho, Juan Ignacio Valdez Hernández, Jan Verbesselt, Simone Aparecida Vieira, Grégoire Vincent, Carolina Volkmer de Castilho, Franziska Volland, Martin Worbes, Magda Lea Bolzan Zanon, and Luiz E. O. C. Aragão
Biogeosciences, 13, 2537–2562, https://doi.org/10.5194/bg-13-2537-2016, https://doi.org/10.5194/bg-13-2537-2016, 2016
K. E. Clark, A. J. West, R. G. Hilton, G. P. Asner, C. A. Quesada, M. R. Silman, S. S. Saatchi, W. Farfan-Rios, R. E. Martin, A. B. Horwath, K. Halladay, M. New, and Y. Malhi
Earth Surf. Dynam., 4, 47–70, https://doi.org/10.5194/esurf-4-47-2016, https://doi.org/10.5194/esurf-4-47-2016, 2016
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The key findings of this paper are that landslides in the eastern Andes of Peru in the Kosñipata Valley rapidly turn over the landscape in ~1320 years, with a rate of 0.076% yr-1. Additionally, landslides were concentrated at lower elevations, due to an intense storm in 2010 accounting for ~1/4 of the total landslide area over the 25-year remote sensing study. Valley-wide carbon stocks were determined, and we estimate that 26 tC km-2 yr-1 of soil and biomass are stripped by landslides.
C. Safta, D. M. Ricciuto, K. Sargsyan, B. Debusschere, H. N. Najm, M. Williams, and P. E. Thornton
Geosci. Model Dev., 8, 1899–1918, https://doi.org/10.5194/gmd-8-1899-2015, https://doi.org/10.5194/gmd-8-1899-2015, 2015
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In this paper we propose a probabilistic framework for an uncertainty quantification study of a carbon cycle model and focus on the comparison between steady-state and transient
simulation setups. We study model parameters via global sensitivity analysis and employ a Bayesian approach to calibrate these parameters using NEE observations at the Harvard Forest site. The calibration results are then used to assess the predictive skill of the model via posterior predictive checks.
L. Rowland, A. Harper, B. O. Christoffersen, D. R. Galbraith, H. M. A. Imbuzeiro, T. L. Powell, C. Doughty, N. M. Levine, Y. Malhi, S. R. Saleska, P. R. Moorcroft, P. Meir, and M. Williams
Geosci. Model Dev., 8, 1097–1110, https://doi.org/10.5194/gmd-8-1097-2015, https://doi.org/10.5194/gmd-8-1097-2015, 2015
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This study evaluates the capability of five vegetation models to simulate the response of forest productivity to changes in temperature and drought, using data collected from an Amazonian forest. This study concludes that model consistencies in the responses of net canopy carbon production to temperature and precipitation change were the result of inconsistently modelled leaf-scale process responses and substantial variation in modelled leaf area responses.
A. A. Bloom and M. Williams
Biogeosciences, 12, 1299–1315, https://doi.org/10.5194/bg-12-1299-2015, https://doi.org/10.5194/bg-12-1299-2015, 2015
D. Slevin, S. F. B. Tett, and M. Williams
Geosci. Model Dev., 8, 295–316, https://doi.org/10.5194/gmd-8-295-2015, https://doi.org/10.5194/gmd-8-295-2015, 2015
K. E. Clark, M. A. Torres, A. J. West, R. G. Hilton, M. New, A. B. Horwath, J. B. Fisher, J. M. Rapp, A. Robles Caceres, and Y. Malhi
Hydrol. Earth Syst. Sci., 18, 5377–5397, https://doi.org/10.5194/hess-18-5377-2014, https://doi.org/10.5194/hess-18-5377-2014, 2014
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This paper presents measurements of the balance of water inputs and outputs over 1 year for a river basin in the Andes of Peru. Our results show that the annual water budget is balanced within a few percent uncertainty; that is to say, the amount of water entering the basin was the same as the amount leaving, providing important information for understanding the water cycle. We also show that seasonal storage of water is important in sustaining the flow of water during the dry season.
M. Réjou-Méchain, H. C. Muller-Landau, M. Detto, S. C. Thomas, T. Le Toan, S. S. Saatchi, J. S. Barreto-Silva, N. A. Bourg, S. Bunyavejchewin, N. Butt, W. Y. Brockelman, M. Cao, D. Cárdenas, J.-M. Chiang, G. B. Chuyong, K. Clay, R. Condit, H. S. Dattaraja, S. J. Davies, A. Duque, S. Esufali, C. Ewango, R. H. S. Fernando, C. D. Fletcher, I. A. U. N. Gunatilleke, Z. Hao, K. E. Harms, T. B. Hart, B. Hérault, R. W. Howe, S. P. Hubbell, D. J. Johnson, D. Kenfack, A. J. Larson, L. Lin, Y. Lin, J. A. Lutz, J.-R. Makana, Y. Malhi, T. R. Marthews, R. W. McEwan, S. M. McMahon, W. J. McShea, R. Muscarella, A. Nathalang, N. S. M. Noor, C. J. Nytch, A. A. Oliveira, R. P. Phillips, N. Pongpattananurak, R. Punchi-Manage, R. Salim, J. Schurman, R. Sukumar, H. S. Suresh, U. Suwanvecho, D. W. Thomas, J. Thompson, M. Uríarte, R. Valencia, A. Vicentini, A. T. Wolf, S. Yap, Z. Yuan, C. E. Zartman, J. K. Zimmerman, and J. Chave
Biogeosciences, 11, 6827–6840, https://doi.org/10.5194/bg-11-6827-2014, https://doi.org/10.5194/bg-11-6827-2014, 2014
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Forest carbon mapping may greatly reduce uncertainties in the global carbon budget. Accuracy of such maps depends however on the quality of field measurements. Using 30 large forest plots, we found large local spatial variability in biomass. When field calibration plots are smaller than the remote sensing pixels, this high local spatial variability results in an underestimation of the variance in biomass.
G. B. Bonan, M. Williams, R. A. Fisher, and K. W. Oleson
Geosci. Model Dev., 7, 2193–2222, https://doi.org/10.5194/gmd-7-2193-2014, https://doi.org/10.5194/gmd-7-2193-2014, 2014
R. Q. Thomas and M. Williams
Geosci. Model Dev., 7, 2015–2037, https://doi.org/10.5194/gmd-7-2015-2014, https://doi.org/10.5194/gmd-7-2015-2014, 2014
G. Xenakis and M. Williams
Geosci. Model Dev., 7, 1519–1533, https://doi.org/10.5194/gmd-7-1519-2014, https://doi.org/10.5194/gmd-7-1519-2014, 2014
N. M. Fyllas, E. Gloor, L. M. Mercado, S. Sitch, C. A. Quesada, T. F. Domingues, D. R. Galbraith, A. Torre-Lezama, E. Vilanova, H. Ramírez-Angulo, N. Higuchi, D. A. Neill, M. Silveira, L. Ferreira, G. A. Aymard C., Y. Malhi, O. L. Phillips, and J. Lloyd
Geosci. Model Dev., 7, 1251–1269, https://doi.org/10.5194/gmd-7-1251-2014, https://doi.org/10.5194/gmd-7-1251-2014, 2014
T. R. Marthews, C. A. Quesada, D. R. Galbraith, Y. Malhi, C. E. Mullins, M. G. Hodnett, and I. Dharssi
Geosci. Model Dev., 7, 711–723, https://doi.org/10.5194/gmd-7-711-2014, https://doi.org/10.5194/gmd-7-711-2014, 2014
G. P. Asner, C. B. Anderson, R. E. Martin, D. E. Knapp, R. Tupayachi, F. Sinca, and Y. Malhi
Biogeosciences, 11, 843–856, https://doi.org/10.5194/bg-11-843-2014, https://doi.org/10.5194/bg-11-843-2014, 2014
T. L. Smallman, M. Williams, and J. B. Moncrieff
Biogeosciences, 11, 735–747, https://doi.org/10.5194/bg-11-735-2014, https://doi.org/10.5194/bg-11-735-2014, 2014
R. Valentini, A. Arneth, A. Bombelli, S. Castaldi, R. Cazzolla Gatti, F. Chevallier, P. Ciais, E. Grieco, J. Hartmann, M. Henry, R. A. Houghton, M. Jung, W. L. Kutsch, Y. Malhi, E. Mayorga, L. Merbold, G. Murray-Tortarolo, D. Papale, P. Peylin, B. Poulter, P. A. Raymond, M. Santini, S. Sitch, G. Vaglio Laurin, G. R. van der Werf, C. A. Williams, and R. J. Scholes
Biogeosciences, 11, 381–407, https://doi.org/10.5194/bg-11-381-2014, https://doi.org/10.5194/bg-11-381-2014, 2014
T. L. Smallman, J. B. Moncrieff, and M. Williams
Geosci. Model Dev., 6, 1079–1093, https://doi.org/10.5194/gmd-6-1079-2013, https://doi.org/10.5194/gmd-6-1079-2013, 2013
A. D. A. Castanho, M. T. Coe, M. H. Costa, Y. Malhi, D. Galbraith, and C. A. Quesada
Biogeosciences, 10, 2255–2272, https://doi.org/10.5194/bg-10-2255-2013, https://doi.org/10.5194/bg-10-2255-2013, 2013
Related subject area
Biogeochemistry: Modelling, Terrestrial
A 2001–2022 global gross primary productivity dataset using an ensemble model based on the random forest method
Future projections of Siberian wildfire and aerosol emissions
Mechanisms of soil organic carbon and nitrogen stabilization in mineral-associated organic matter – insights from modeling in phase space
Optimizing the terrestrial ecosystem gross primary productivity using carbonyl sulfide (COS) within a two-leaf modeling framework
Modeling integrated soil fertility management for maize production in Kenya using a Bayesian calibration of the DayCent model
Estimates of critical loads and exceedances of acidity and nutrient nitrogen for mineral soils in Canada for 2014–2016 average annual sulphur and nitrogen atmospheric deposition
Understanding and simulating cropland and non-cropland burning in Europe using the BASE (Burnt Area Simulator for Europe) model
When and why microbial-explicit soil organic carbon models can be unstable
The impacts of modelling prescribed vs. dynamic land cover in a high-CO2 future scenario – greening of the Arctic and Amazonian dieback
Climate-based prediction of carbon fluxes from deadwood in Australia
Integration of tree hydraulic processes and functional impairment to capture the drought resilience of a semiarid pine forest
The effect of temperature on photosystem II efficiency across plant functional types and climate
Modeling microbial carbon fluxes and stocks in global soils from 1901 to 2016
Elevated atmospheric CO2 concentration and vegetation structural changes contributed to gross primary productivity increase more than climate and forest cover changes in subtropical forests of China
Developing the DO3SE-crop model for Xiaoji, China
Non-steady-state stomatal conductance modeling and its implications: from leaf to ecosystem
Modelled forest ecosystem carbon–nitrogen dynamics with integrated mycorrhizal processes under elevated CO2
A chemical kinetics theory for interpreting the non-monotonic temperature dependence of enzymatic reactions
Representation of the Terrestrial Carbon Cycle in CMIP6
Using Free Air CO2 Enrichment data to constrain land surface model projections of the terrestrial carbon cycle
Multiscale assessment of North American terrestrial carbon balance
Simulating net ecosystem exchange under seasonal snow cover at an Arctic tundra site
X-BASE: the first terrestrial carbon and water flux products from an extended data-driven scaling framework, FLUXCOM-X
Spatial biases reduce the ability of Earth system models to simulate soil heterotrophic respiration fluxes
Future methane fluxes of peatlands are controlled by management practices and fluctuations in hydrological conditions due to climatic variability
Tropical dry forest response to nutrient fertilization: a model validation and sensitivity analysis
Connecting competitor, stress-tolerator and ruderal (CSR) theory and Lund Potsdam Jena managed Land 5 (LPJmL 5) to assess the role of environmental conditions, management and functional diversity for grassland ecosystem functions
A global fuel characteristic model and dataset for wildfire prediction
Can models adequately reflect how long-term nitrogen enrichment alters the forest soil carbon cycle?
Temporal variability of observed and simulated gross primary productivity, modulated by vegetation state and hydrometeorological drivers
Does dynamically modelled leaf area improve predictions of land surface water and carbon fluxes? – Insights into dynamic vegetation modules
Empirical upscaling of OzFlux eddy covariance for high-resolution monitoring of terrestrial carbon uptake in Australia
A modeling approach to investigate drivers, variability and uncertainties in O2 fluxes and O2 : CO2 exchange ratios in a temperate forest
Modeling coupled nitrification–denitrification in soil with an organic hotspot
A new method for estimating carbon dioxide emissions from drained peatland forest soils for the greenhouse gas inventory of Finland
Enabling a process-oriented hydro-biogeochemical model to simulate soil erosion and nutrient losses
Potassium limitation of forest productivity – Part 1: A mechanistic model simulating the effects of potassium availability on canopy carbon and water fluxes in tropical eucalypt stands
Potassium limitation of forest productivity – Part 2: CASTANEA-MAESPA-K shows a reduction in photosynthesis rather than a stoichiometric limitation of tissue formation
Global evaluation of terrestrial biogeochemistry in the Energy Exascale Earth System Model (E3SM) and the role of the phosphorus cycle in the historical terrestrial carbon balance
Assessing carbon storage capacity and saturation across six central US grasslands using data–model integration
Optimizing the carbonic anhydrase temperature response and stomatal conductance of carbonyl sulfide leaf uptake in the Simple Biosphere model (SiB4)
Exploring environmental and physiological drivers of the annual carbon budget of biocrusts from various climatic zones with a mechanistic data-driven model
Improved process representation of leaf phenology significantly shifts climate sensitivity of ecosystem carbon balance
Mapping of ESA's Climate Change Initiative land cover data to plant functional types for use in the CLASSIC land model
Exploring the impacts of unprecedented climate extremes on forest ecosystems: hypotheses to guide modeling and experimental studies
Effect of droughts and climate change on future soil weathering rates in Sweden
Information content in time series of litter decomposition studies and the transit time of litter in arid lands
Long-term changes of nitrogen leaching and the contributions of terrestrial nutrient sources to lake eutrophication dynamics on the Yangtze Plain of China
Towards an ensemble-based evaluation of land surface models in light of uncertain forcings and observations
Observational benchmarks inform representation of soil organic carbon dynamics in land surface models
Xin Chen, Tiexi Chen, Xiaodong Li, Yuanfang Chai, Shengjie Zhou, Renjie Guo, and Jie Dai
Biogeosciences, 21, 4285–4300, https://doi.org/10.5194/bg-21-4285-2024, https://doi.org/10.5194/bg-21-4285-2024, 2024
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We provide an ensemble-model-based GPP dataset (ERF_GPP) that explains 85.1 % of the monthly variation in GPP across 170 sites, which is higher than other GPP estimate models. In addition, ERF_GPP improves the phenomenon of “high-value underestimation and low-value overestimation” in GPP estimation to some extent. Overall, ERF_GPP provides a more reliable estimate of global GPP and will facilitate further development of carbon cycle research.
Reza Kusuma Nurrohman, Tomomichi Kato, Hideki Ninomiya, Lea Végh, Nicolas Delbart, Tatsuya Miyauchi, Hisashi Sato, Tomohiro Shiraishi, and Ryuichi Hirata
Biogeosciences, 21, 4195–4227, https://doi.org/10.5194/bg-21-4195-2024, https://doi.org/10.5194/bg-21-4195-2024, 2024
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SPITFIRE (SPread and InTensity of FIRE) was integrated into a spatially explicit individual-based dynamic global vegetation model to improve the accuracy of depicting Siberian forest fire frequency, intensity, and extent. Fires showed increased greenhouse gas and aerosol emissions in 2006–2100 for Representative Concentration Pathways. This study contributes to understanding fire dynamics, land ecosystem–climate interactions, and global material cycles under the threat of escalating fires.
Stefano Manzoni and M. Francesca Cotrufo
Biogeosciences, 21, 4077–4098, https://doi.org/10.5194/bg-21-4077-2024, https://doi.org/10.5194/bg-21-4077-2024, 2024
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Organic carbon and nitrogen are stabilized in soils via microbial assimilation and stabilization of necromass (in vivo pathway) or via adsorption of the products of extracellular decomposition (ex vivo pathway). Here we use a diagnostic model to quantify which stabilization pathway is prevalent using data on residue-derived carbon and nitrogen incorporation in mineral-associated organic matter. We find that the in vivo pathway is dominant in fine-textured soils with low organic matter content.
Huajie Zhu, Xiuli Xing, Mousong Wu, Weimin Ju, and Fei Jiang
Biogeosciences, 21, 3735–3760, https://doi.org/10.5194/bg-21-3735-2024, https://doi.org/10.5194/bg-21-3735-2024, 2024
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Ecosystem carbonyl sulfide (COS) fluxes were employed to optimize GPP estimation across ecosystems with the Biosphere-atmosphere Exchange Process Simulator (BEPS), which was developed for simulating the canopy COS uptake under its state-of-the-art two-leaf modeling framework. Our results showcased the efficacy of COS in improving model prediction and reducing prediction uncertainty of GPP and enhanced insights into the sensitivity, identifiability, and interactions of parameters related to COS.
Moritz Laub, Magdalena Necpalova, Marijn Van de Broek, Marc Corbeels, Samuel Mathu Ndungu, Monicah Wanjiku Mucheru-Muna, Daniel Mugendi, Rebecca Yegon, Wycliffe Waswa, Bernard Vanlauwe, and Johan Six
Biogeosciences, 21, 3691–3716, https://doi.org/10.5194/bg-21-3691-2024, https://doi.org/10.5194/bg-21-3691-2024, 2024
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We used the DayCent model to assess the potential impact of integrated soil fertility management (ISFM) on maize production, soil fertility, and greenhouse gas emission in Kenya. After adjustments, DayCent represented measured mean yields and soil carbon stock changes well and N2O emissions acceptably. Our results showed that soil fertility losses could be reduced but not completely eliminated with ISFM and that, while N2O emissions increased with ISFM, emissions per kilogram yield decreased.
Hazel Cathcart, Julian Aherne, Michael D. Moran, Verica Savic-Jovcic, Paul A. Makar, and Amanda Cole
EGUsphere, https://doi.org/10.5194/egusphere-2024-2371, https://doi.org/10.5194/egusphere-2024-2371, 2024
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Deposition from sulfur and nitrogen pollution can harm ecosystems, and recovery from this type of pollution can take decades or longer. To identify risk to Canadian soils, we created maps showing sensitivity to sulfur and nitrogen pollution. Results show that some ecosystems are at risk from acid and nutrient nitrogen deposition; 10 % of protected areas are receiving acid deposition beyond their damage threshold and 70 % may be receiving nitrogen deposition that could cause biodiversity loss.
Matthew Forrest, Jessica Hetzer, Maik Billing, Simon P. K. Bowring, Eric Kosczor, Luke Oberhagemann, Oliver Perkins, Dan Warren, Fátima Arrogante-Funes, Kirsten Thonicke, and Thomas Hickler
EGUsphere, https://doi.org/10.5194/egusphere-2024-1973, https://doi.org/10.5194/egusphere-2024-1973, 2024
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Climate change is causing an increase in extreme wildfires in Europe but drivers of fire are not well understood, especially across different land cover types. We used statistical models with satellite data, climate data and socioeconomic data to determine what affects burning in cropland and non-cropland area Europe. We found different drivers of burning in cropland burning vs non-cropland, to the point that some variable, e.g. population density, had completely the opposite effects.
Erik Schwarz, Samia Ghersheen, Salim Belyazid, and Stefano Manzoni
Biogeosciences, 21, 3441–3461, https://doi.org/10.5194/bg-21-3441-2024, https://doi.org/10.5194/bg-21-3441-2024, 2024
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The occurrence of unstable equilibrium points (EPs) could impede the applicability of microbial-explicit soil organic carbon models. For archetypal model versions we identify when instability can occur and describe mathematical conditions to avoid such unstable EPs. We discuss implications for further model development, highlighting the important role of considering basic ecological principles to ensure biologically meaningful models.
Sian Kou-Giesbrecht, Vivek K. Arora, Christian Seiler, and Libo Wang
Biogeosciences, 21, 3339–3371, https://doi.org/10.5194/bg-21-3339-2024, https://doi.org/10.5194/bg-21-3339-2024, 2024
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Terrestrial biosphere models can either prescribe the geographical distribution of biomes or simulate them dynamically, capturing climate-change-driven biome shifts. We isolate and examine the differences between these different land cover implementations. We find that the simulated terrestrial carbon sink at the end of the 21st century is twice as large in simulations with dynamic land cover than in simulations with prescribed land cover due to important range shifts in the Arctic and Amazon.
Elizabeth S. Duan, Luciana Chavez Rodriguez, Nicole Hemming-Schroeder, Baptiste Wijas, Habacuc Flores-Moreno, Alexander W. Cheesman, Lucas A. Cernusak, Michael J. Liddell, Paul Eggleton, Amy E. Zanne, and Steven D. Allison
Biogeosciences, 21, 3321–3338, https://doi.org/10.5194/bg-21-3321-2024, https://doi.org/10.5194/bg-21-3321-2024, 2024
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Understanding the link between climate and carbon fluxes is crucial for predicting how climate change will impact carbon sinks. We estimated carbon dioxide (CO2) fluxes from deadwood in tropical Australia using wood moisture content and temperature. Our model predicted that the majority of deadwood carbon is released as CO2, except when termite activity is detected. Future models should also incorporate wood traits, like species and chemical composition, to better predict fluxes.
Daniel Nadal-Sala, Rüdiger Grote, David Kraus, Uri Hochberg, Tamir Klein, Yael Wagner, Fedor Tatarinov, Dan Yakir, and Nadine K. Ruehr
Biogeosciences, 21, 2973–2994, https://doi.org/10.5194/bg-21-2973-2024, https://doi.org/10.5194/bg-21-2973-2024, 2024
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A hydraulic model approach is presented that can be added to any physiologically based ecosystem model. Simulated plant water potential triggers stomatal closure, photosynthesis decline, root–soil resistance increases, and sapwood and foliage senescence. The model has been evaluated at an extremely dry site stocked with Aleppo pine and was able to represent gas exchange, soil water content, and plant water potential. The model also responded realistically regarding leaf senescence.
Patrick Neri, Lianhong Gu, and Yang Song
Biogeosciences, 21, 2731–2758, https://doi.org/10.5194/bg-21-2731-2024, https://doi.org/10.5194/bg-21-2731-2024, 2024
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A first-of-its-kind global-scale model of temperature resilience and tolerance of photosystem II maximum quantum yield informs how plants maintain their efficiency of converting light energy to chemical energy for photosynthesis under temperature changes. Our finding explores this variation across plant functional types and habitat climatology, highlighting diverse temperature response strategies and a method to improve global-scale photosynthesis modeling under climate change.
Liyuan He, Jorge L. Mazza Rodrigues, Melanie A. Mayes, Chun-Ta Lai, David A. Lipson, and Xiaofeng Xu
Biogeosciences, 21, 2313–2333, https://doi.org/10.5194/bg-21-2313-2024, https://doi.org/10.5194/bg-21-2313-2024, 2024
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Soil microbes are the driving engine for biogeochemical cycles of carbon and nutrients. This study applies a microbial-explicit model to quantify bacteria and fungal biomass carbon in soils from 1901 to 2016. Results showed substantial increases in bacterial and fungal biomass carbon over the past century, jointly influenced by vegetation growth and soil temperature and moisture. This pioneering century-long estimation offers crucial insights into soil microbial roles in global carbon cycling.
Tao Chen, Félicien Meunier, Marc Peaucelle, Guoping Tang, Ye Yuan, and Hans Verbeeck
Biogeosciences, 21, 2253–2272, https://doi.org/10.5194/bg-21-2253-2024, https://doi.org/10.5194/bg-21-2253-2024, 2024
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Chinese subtropical forest ecosystems are an extremely important component of global forest ecosystems and hence crucial for the global carbon cycle and regional climate change. However, there is still great uncertainty in the relationship between subtropical forest carbon sequestration and its drivers. We provide first quantitative estimates of the individual and interactive effects of different drivers on the gross primary productivity changes of various subtropical forest types in China.
Pritha Pande, Sam Bland, Nathan Booth, Jo Cook, Zhaozhong Feng, and Lisa Emberson
EGUsphere, https://doi.org/10.5194/egusphere-2024-694, https://doi.org/10.5194/egusphere-2024-694, 2024
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The DO3SE-crop model extends the DO3SE to simulate ozone's impact on crops with modules for ozone uptake, damage, and crop growth from JULES-Crop. It's versatile, suits China's varied agriculture, and improves yield predictions under ozone stress. It is essential for policy, water management, and climate response, it integrates into Earth System Models for a comprehensive understanding of agriculture's interaction with global systems.
Ke Liu, Yujie Wang, Troy S. Magney, and Christian Frankenberg
Biogeosciences, 21, 1501–1516, https://doi.org/10.5194/bg-21-1501-2024, https://doi.org/10.5194/bg-21-1501-2024, 2024
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Stomata are pores on leaves that regulate gas exchange between plants and the atmosphere. Existing land models unrealistically assume stomata can jump between steady states when the environment changes. We implemented dynamic modeling to predict gradual stomatal responses at different scales. Results suggested that considering this effect on plant behavior patterns in diurnal cycles was important. Our framework also simplified simulations and can contribute to further efficiency improvements.
Melanie A. Thurner, Silvia Caldararu, Jan Engel, Anja Rammig, and Sönke Zaehle
Biogeosciences, 21, 1391–1410, https://doi.org/10.5194/bg-21-1391-2024, https://doi.org/10.5194/bg-21-1391-2024, 2024
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Due to their crucial role in terrestrial ecosystems, we implemented mycorrhizal fungi into the QUINCY terrestrial biosphere model. Fungi interact with mineral and organic soil to support plant N uptake and, thus, plant growth. Our results suggest that the effect of mycorrhizal interactions on simulated ecosystem dynamics is minor under constant environmental conditions but necessary to reproduce and understand observed patterns under changing conditions, such as rising atmospheric CO2.
Jinyun Tang and William J. Riley
Biogeosciences, 21, 1061–1070, https://doi.org/10.5194/bg-21-1061-2024, https://doi.org/10.5194/bg-21-1061-2024, 2024
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A chemical kinetics theory is proposed to explain the non-monotonic relationship between temperature and biochemical rates. It incorporates the observed thermally reversible enzyme denaturation that is ensured by the ceaseless thermal motion of molecules and ions in an enzyme solution and three well-established theories: (1) law of mass action, (2) diffusion-limited chemical reaction theory, and (3) transition state theory.
Bettina K. Gier, Manuel Schlund, Pierre Friedlingstein, Chris D. Jones, Colin Jones, Sönke Zaehle, and Veronika Eyring
EGUsphere, https://doi.org/10.5194/egusphere-2024-277, https://doi.org/10.5194/egusphere-2024-277, 2024
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This study investigates present day carbon cycle variables in CMIP5 and CMIP6 simulations. A significant improvement in the simulation of photosynthesis in models with nitrogen cycle is found, as well as only small differences between emission and concentration based simulations. Thus, we recommend the use of emission driven simulations in CMIP7 as default setup, and to view the nitrogen cycle as a necessary part of all future carbon cycle models.
Nina Raoult, Louis-Axel Edouard-Rambaut, Nicolas Vuichard, Vladislav Bastrikov, Anne Sofie Lansø, Bertrand Guenet, and Philippe Peylin
Biogeosciences, 21, 1017–1036, https://doi.org/10.5194/bg-21-1017-2024, https://doi.org/10.5194/bg-21-1017-2024, 2024
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Observations are used to reduce uncertainty in land surface models (LSMs) by optimising poorly constraining parameters. However, optimising against current conditions does not necessarily ensure that the parameters treated as invariant will be robust in a changing climate. Manipulation experiments offer us a unique chance to optimise our models under different (here atmospheric CO2) conditions. By using these data in optimisations, we gain confidence in the future projections of LSMs.
Kelsey T. Foster, Wu Sun, Yoichi P. Shiga, Jiafu Mao, and Anna M. Michalak
Biogeosciences, 21, 869–891, https://doi.org/10.5194/bg-21-869-2024, https://doi.org/10.5194/bg-21-869-2024, 2024
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Assessing agreement between bottom-up and top-down methods across spatial scales can provide insights into the relationship between ensemble spread (difference across models) and model accuracy (difference between model estimates and reality). We find that ensemble spread is unlikely to be a good indicator of actual uncertainty in the North American carbon balance. However, models that are consistent with atmospheric constraints show stronger agreement between top-down and bottom-up estimates.
Victoria R. Dutch, Nick Rutter, Leanne Wake, Oliver Sonnentag, Gabriel Hould Gosselin, Melody Sandells, Chris Derksen, Branden Walker, Gesa Meyer, Richard Essery, Richard Kelly, Phillip Marsh, Julia Boike, and Matteo Detto
Biogeosciences, 21, 825–841, https://doi.org/10.5194/bg-21-825-2024, https://doi.org/10.5194/bg-21-825-2024, 2024
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We undertake a sensitivity study of three different parameters on the simulation of net ecosystem exchange (NEE) during the snow-covered non-growing season at an Arctic tundra site. Simulations are compared to eddy covariance measurements, with near-zero NEE simulated despite observed CO2 release. We then consider how to parameterise the model better in Arctic tundra environments on both sub-seasonal timescales and cumulatively throughout the snow-covered non-growing season.
Jacob A. Nelson, Sophia Walther, Fabian Gans, Basil Kraft, Ulrich Weber, Kimberly Novick, Nina Buchmann, Mirco Migliavacca, Georg Wohlfahrt, Ladislav Šigut, Andreas Ibrom, Dario Papale, Mathias Göckede, Gregory Duveiller, Alexander Knohl, Lukas Hörtnagl, Russell L. Scott, Weijie Zhang, Zayd Mahmoud Hamdi, Markus Reichstein, Sergio Aranda-Barranco, Jonas Ardö, Maarten Op de Beeck, Dave Billdesbach, David Bowling, Rosvel Bracho, Christian Brümmer, Gustau Camps-Valls, Shiping Chen, Jamie Rose Cleverly, Ankur Desai, Gang Dong, Tarek S. El-Madany, Eugenie Susanne Euskirchen, Iris Feigenwinter, Marta Galvagno, Giacomo Gerosa, Bert Gielen, Ignacio Goded, Sarah Goslee, Christopher Michael Gough, Bernard Heinesch, Kazuhito Ichii, Marcin Antoni Jackowicz-Korczynski, Anne Klosterhalfen, Sara Knox, Hideki Kobayashi, Kukka-Maaria Kohonen, Mika Korkiakoski, Ivan Mammarella, Gharun Mana, Riccardo Marzuoli, Roser Matamala, Stefan Metzger, Leonardo Montagnani, Giacomo Nicolini, Thomas O'Halloran, Jean-Marc Ourcival, Matthias Peichl, Elise Pendall, Borja Ruiz Reverter, Marilyn Roland, Simone Sabbatini, Torsten Sachs, Marius Schmidt, Christopher R. Schwalm, Ankit Shekhar, Richard Silberstein, Maria Lucia Silveira, Donatella Spano, Torbern Tagesson, Gianluca Tramontana, Carlo Trotta, Fabio Turco, Timo Vesala, Caroline Vincke, Domenico Vitale, Enrique R. Vivoni, Yi Wang, William Woodgate, Enrico A. Yepez, Junhui Zhang, Donatella Zona, and Martin Jung
EGUsphere, https://doi.org/10.5194/egusphere-2024-165, https://doi.org/10.5194/egusphere-2024-165, 2024
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The movement of water, carbon, and energy from the earth surface to the atmosphere, or flux, is an important process to understand that impacts all of our lives. Here we outline a method to estimate global water and CO2 fluxes based on direct measurements from site around the world called FLUXCOM-X. We go on to demonstrate how these new estimates of net CO2 uptake/loss, gross CO2 uptake, total water evaporation, and transpiration from plants compare to previous and independent estimates.
Bertrand Guenet, Jérémie Orliac, Lauric Cécillon, Olivier Torres, Laura Sereni, Philip A. Martin, Pierre Barré, and Laurent Bopp
Biogeosciences, 21, 657–669, https://doi.org/10.5194/bg-21-657-2024, https://doi.org/10.5194/bg-21-657-2024, 2024
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Heterotrophic respiration fluxes are a major flux between surfaces and the atmosphere, but Earth system models do not yet represent them correctly. Here we benchmarked Earth system models against observation-based products, and we identified the important mechanisms that need to be improved in the next-generation Earth system models.
Vilna Tyystjärvi, Tiina Markkanen, Leif Backman, Maarit Raivonen, Antti Leppänen, Xuefei Li, Paavo Ojanen, Kari Minkkinen, Roosa Hautala, Mikko Peltoniemi, Jani Anttila, Raija Laiho, Annalea Lohila, Raisa Mäkipää, and Tuula Aalto
EGUsphere, https://doi.org/10.5194/egusphere-2023-3037, https://doi.org/10.5194/egusphere-2023-3037, 2024
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Drainage of boreal peatlands strongly influences soil methane fluxes with important implications to their climatic impacts. Here we simulate methane fluxes in forestry-drained and restored peatlands during the 21st century. We found that restoration turned peatlands to a source of methane but the magnitude varied regionally. In forests, changes in water table level influenced methane fluxes and in general, the sink was weaker under rotational forestry compared to continuous cover forestry.
Shuyue Li, Bonnie Waring, Jennifer Powers, and David Medvigy
Biogeosciences, 21, 455–471, https://doi.org/10.5194/bg-21-455-2024, https://doi.org/10.5194/bg-21-455-2024, 2024
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We used an ecosystem model to simulate primary production of a tropical forest subjected to 3 years of nutrient fertilization. Simulations parameterized such that relative allocation to fine roots increased with increasing soil phosphorus had leaf, wood, and fine root production consistent with observations. However, these simulations seemed to over-allocate to fine roots on multidecadal timescales, affecting aboveground biomass. Additional observations across timescales would benefit models.
Stephen Björn Wirth, Arne Poyda, Friedhelm Taube, Britta Tietjen, Christoph Müller, Kirsten Thonicke, Anja Linstädter, Kai Behn, Sibyll Schaphoff, Werner von Bloh, and Susanne Rolinski
Biogeosciences, 21, 381–410, https://doi.org/10.5194/bg-21-381-2024, https://doi.org/10.5194/bg-21-381-2024, 2024
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In dynamic global vegetation models (DGVMs), the role of functional diversity in forage supply and soil organic carbon storage of grasslands is not explicitly taken into account. We introduced functional diversity into the Lund Potsdam Jena managed Land (LPJmL) DGVM using CSR theory. The new model reproduced well-known trade-offs between plant traits and can be used to quantify the role of functional diversity in climate change mitigation using different functional diversity scenarios.
Joe R. McNorton and Francesca Di Giuseppe
Biogeosciences, 21, 279–300, https://doi.org/10.5194/bg-21-279-2024, https://doi.org/10.5194/bg-21-279-2024, 2024
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Wildfires have wide-ranging consequences for local communities, air quality and ecosystems. Vegetation amount and moisture state are key components to forecast wildfires. We developed a combined model and satellite framework to characterise vegetation, including the type of fuel, whether it is alive or dead, and its moisture content. The daily data is at high resolution globally (~9 km). Our characteristics correlate with active fire data and can inform fire danger and spread modelling efforts.
Brooke A. Eastman, William R. Wieder, Melannie D. Hartman, Edward R. Brzostek, and William T. Peterjohn
Biogeosciences, 21, 201–221, https://doi.org/10.5194/bg-21-201-2024, https://doi.org/10.5194/bg-21-201-2024, 2024
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We compared soil model performance to data from a long-term nitrogen addition experiment in a forested ecosystem. We found that in order for soil carbon models to accurately predict future forest carbon sequestration, two key processes must respond dynamically to nitrogen availability: (1) plant allocation of carbon to wood versus roots and (2) rates of soil organic matter decomposition. Long-term experiments can help improve our predictions of the land carbon sink and its climate impact.
Jan De Pue, Sebastian Wieneke, Ana Bastos, José Miguel Barrios, Liyang Liu, Philippe Ciais, Alirio Arboleda, Rafiq Hamdi, Maral Maleki, Fabienne Maignan, Françoise Gellens-Meulenberghs, Ivan Janssens, and Manuela Balzarolo
Biogeosciences, 20, 4795–4818, https://doi.org/10.5194/bg-20-4795-2023, https://doi.org/10.5194/bg-20-4795-2023, 2023
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The gross primary production (GPP) of the terrestrial biosphere is a key source of variability in the global carbon cycle. To estimate this flux, models can rely on remote sensing data (RS-driven), meteorological data (meteo-driven) or a combination of both (hybrid). An intercomparison of 11 models demonstrated that RS-driven models lack the sensitivity to short-term anomalies. Conversely, the simulation of soil moisture dynamics and stress response remains a challenge in meteo-driven models.
Sven Armin Westermann, Anke Hildebrandt, Souhail Bousetta, and Stephan Thober
EGUsphere, https://doi.org/10.5194/egusphere-2023-2101, https://doi.org/10.5194/egusphere-2023-2101, 2023
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Plants at the land surface mediates between soil and atmosphere regarding water and carbon transport. Since plant growth is a dynamic process, models need to care for this dynamics. Here, two models which predict water and carbon fluxes by considering plant temporal evolution were tested against observational data. Currently, dynamizing plants in these models did not enhance their representativeness which is caused by a mismatch between implemented physical relations and observable connections.
Chad A. Burton, Luigi J. Renzullo, Sami W. Rifai, and Albert I. J. M. Van Dijk
Biogeosciences, 20, 4109–4134, https://doi.org/10.5194/bg-20-4109-2023, https://doi.org/10.5194/bg-20-4109-2023, 2023
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Australia's land-based ecosystems play a critical role in controlling the variability in the global land carbon sink. However, uncertainties in the methods used for quantifying carbon fluxes limit our understanding. We develop high-resolution estimates of Australia's land carbon fluxes using machine learning methods and find that Australia is, on average, a stronger carbon sink than previously thought and that the seasonal dynamics of the fluxes differ from those described by other methods.
Yuan Yan, Anne Klosterhalfen, Fernando Moyano, Matthias Cuntz, Andrew C. Manning, and Alexander Knohl
Biogeosciences, 20, 4087–4107, https://doi.org/10.5194/bg-20-4087-2023, https://doi.org/10.5194/bg-20-4087-2023, 2023
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A better understanding of O2 fluxes, their exchange ratios with CO2 and their interrelations with environmental conditions would provide further insights into biogeochemical ecosystem processes. We, therefore, used the multilayer canopy model CANVEG to simulate and analyze the flux exchange for our forest study site for 2012–2016. Based on these simulations, we further successfully tested the application of various micrometeorological methods and the prospects of real O2 flux measurements.
Jie Zhang, Elisabeth Larsen Kolstad, Wenxin Zhang, Iris Vogeler, and Søren O. Petersen
Biogeosciences, 20, 3895–3917, https://doi.org/10.5194/bg-20-3895-2023, https://doi.org/10.5194/bg-20-3895-2023, 2023
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Manure application to agricultural land often results in large and variable N2O emissions. We propose a model with a parsimonious structure to investigate N transformations around such N2O hotspots. The model allows for new detailed insights into the interactions between transport and microbial activities regarding N2O emissions in heterogeneous soil environments. It highlights the importance of solute diffusion to N2O emissions from such hotspots which are often ignored by process-based models.
Jukka Alm, Antti Wall, Jukka-Pekka Myllykangas, Paavo Ojanen, Juha Heikkinen, Helena M. Henttonen, Raija Laiho, Kari Minkkinen, Tarja Tuomainen, and Juha Mikola
Biogeosciences, 20, 3827–3855, https://doi.org/10.5194/bg-20-3827-2023, https://doi.org/10.5194/bg-20-3827-2023, 2023
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In Finland peatlands cover one-third of land area. For half of those, with 4.3 Mha being drained for forestry, Finland reports sinks and sources of greenhouse gases in forest lands on organic soils following its UNFCCC commitment. We describe a new method for compiling soil CO2 balance that follows changes in tree volume, tree harvests and temperature. An increasing trend of emissions from 1.4 to 7.9 Mt CO2 was calculated for drained peatland forest soils in Finland for 1990–2021.
Siqi Li, Bo Zhu, Xunhua Zheng, Pengcheng Hu, Shenghui Han, Jihui Fan, Tao Wang, Rui Wang, Kai Wang, Zhisheng Yao, Chunyan Liu, Wei Zhang, and Yong Li
Biogeosciences, 20, 3555–3572, https://doi.org/10.5194/bg-20-3555-2023, https://doi.org/10.5194/bg-20-3555-2023, 2023
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Physical soil erosion and particulate carbon, nitrogen and phosphorus loss modules were incorporated into the process-oriented hydro-biogeochemical model CNMM-DNDC to realize the accurate simulation of water-induced erosion and subsequent particulate nutrient losses at high spatiotemporal resolution.
Ivan Cornut, Nicolas Delpierre, Jean-Paul Laclau, Joannès Guillemot, Yann Nouvellon, Otavio Campoe, Jose Luiz Stape, Vitoria Fernanda Santos, and Guerric le Maire
Biogeosciences, 20, 3093–3117, https://doi.org/10.5194/bg-20-3093-2023, https://doi.org/10.5194/bg-20-3093-2023, 2023
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Potassium is an essential element for living organisms. Trees are dependent upon this element for certain functions that allow them to build their trunks using carbon dioxide. Using data from experiments in eucalypt plantations in Brazil and a simplified computer model of the plantations, we were able to investigate the effect that a lack of potassium can have on the production of wood. Understanding nutrient cycles is useful to understand the response of forests to environmental change.
Ivan Cornut, Guerric le Maire, Jean-Paul Laclau, Joannès Guillemot, Yann Nouvellon, and Nicolas Delpierre
Biogeosciences, 20, 3119–3135, https://doi.org/10.5194/bg-20-3119-2023, https://doi.org/10.5194/bg-20-3119-2023, 2023
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After simulating the effects of low levels of potassium on the canopy of trees and the uptake of carbon dioxide from the atmosphere by leaves in Part 1, here we tried to simulate the way the trees use the carbon they have acquired and the interaction with the potassium cycle in the tree. We show that the effect of low potassium on the efficiency of the trees in acquiring carbon is enough to explain why they produce less wood when they are in soils with low levels of potassium.
Xiaojuan Yang, Peter Thornton, Daniel Ricciuto, Yilong Wang, and Forrest Hoffman
Biogeosciences, 20, 2813–2836, https://doi.org/10.5194/bg-20-2813-2023, https://doi.org/10.5194/bg-20-2813-2023, 2023
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We evaluated the performance of a land surface model (ELMv1-CNP) that includes both nitrogen (N) and phosphorus (P) limitation on carbon cycle processes. We show that ELMv1-CNP produces realistic estimates of present-day carbon pools and fluxes. We show that global C sources and sinks are significantly affected by P limitation. Our study suggests that introduction of P limitation in land surface models is likely to have substantial consequences for projections of future carbon uptake.
Kevin R. Wilcox, Scott L. Collins, Alan K. Knapp, William Pockman, Zheng Shi, Melinda D. Smith, and Yiqi Luo
Biogeosciences, 20, 2707–2725, https://doi.org/10.5194/bg-20-2707-2023, https://doi.org/10.5194/bg-20-2707-2023, 2023
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The capacity for carbon storage (C capacity) is an attribute that determines how ecosystems store carbon in the future. Here, we employ novel data–model integration techniques to identify the carbon capacity of six grassland sites spanning the US Great Plains. Hot and dry sites had low C capacity due to less plant growth and high turnover of soil C, so they may be a C source in the future. Alternately, cooler and wetter ecosystems had high C capacity, so these systems may be a future C sink.
Ara Cho, Linda M. J. Kooijmans, Kukka-Maaria Kohonen, Richard Wehr, and Maarten C. Krol
Biogeosciences, 20, 2573–2594, https://doi.org/10.5194/bg-20-2573-2023, https://doi.org/10.5194/bg-20-2573-2023, 2023
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Carbonyl sulfide (COS) is a useful constraint for estimating photosynthesis. To simulate COS leaf flux better in the SiB4 model, we propose a novel temperature function for enzyme carbonic anhydrase (CA) activity and optimize conductances using observations. The optimal activity of CA occurs below 40 °C, and Ball–Woodrow–Berry parameters are slightly changed. These reduce/increase uptakes in the tropics/higher latitudes and contribute to resolving discrepancies in the COS global budget.
Yunyao Ma, Bettina Weber, Alexandra Kratz, José Raggio, Claudia Colesie, Maik Veste, Maaike Y. Bader, and Philipp Porada
Biogeosciences, 20, 2553–2572, https://doi.org/10.5194/bg-20-2553-2023, https://doi.org/10.5194/bg-20-2553-2023, 2023
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We found that the modelled annual carbon balance of biocrusts is strongly affected by both the environment (mostly air temperature and CO2 concentration) and physiology, such as temperature response of respiration. However, the relative impacts of these drivers vary across regions with different climates. Uncertainty in driving factors may lead to unrealistic carbon balance estimates, particularly in temperate climates, and may be explained by seasonal variation of physiology due to acclimation.
Alexander J. Norton, A. Anthony Bloom, Nicholas C. Parazoo, Paul A. Levine, Shuang Ma, Renato K. Braghiere, and T. Luke Smallman
Biogeosciences, 20, 2455–2484, https://doi.org/10.5194/bg-20-2455-2023, https://doi.org/10.5194/bg-20-2455-2023, 2023
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This study explores how the representation of leaf phenology affects our ability to predict changes to the carbon balance of land ecosystems. We calibrate a new leaf phenology model against a diverse range of observations at six forest sites, showing that it improves the predictive capability of the processes underlying the ecosystem carbon balance. We then show how changes in temperature and rainfall affect the ecosystem carbon balance with this new model.
Libo Wang, Vivek K. Arora, Paul Bartlett, Ed Chan, and Salvatore R. Curasi
Biogeosciences, 20, 2265–2282, https://doi.org/10.5194/bg-20-2265-2023, https://doi.org/10.5194/bg-20-2265-2023, 2023
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Plant functional types (PFTs) are groups of plant species used to represent vegetation distribution in land surface models. There are large uncertainties associated with existing methods for mapping land cover datasets to PFTs. This study demonstrates how fine-resolution tree cover fraction and land cover datasets can be used to inform the PFT mapping process and reduce the uncertainties. The proposed largely objective method makes it easier to implement new land cover products in models.
Jennifer A. Holm, David M. Medvigy, Benjamin Smith, Jeffrey S. Dukes, Claus Beier, Mikhail Mishurov, Xiangtao Xu, Jeremy W. Lichstein, Craig D. Allen, Klaus S. Larsen, Yiqi Luo, Cari Ficken, William T. Pockman, William R. L. Anderegg, and Anja Rammig
Biogeosciences, 20, 2117–2142, https://doi.org/10.5194/bg-20-2117-2023, https://doi.org/10.5194/bg-20-2117-2023, 2023
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Unprecedented climate extremes (UCEs) are expected to have dramatic impacts on ecosystems. We present a road map of how dynamic vegetation models can explore extreme drought and climate change and assess ecological processes to measure and reduce model uncertainties. The models predict strong nonlinear responses to UCEs. Due to different model representations, the models differ in magnitude and trajectory of forest loss. Therefore, we explore specific plant responses that reflect knowledge gaps.
Veronika Kronnäs, Klas Lucander, Giuliana Zanchi, Nadja Stadlinger, Salim Belyazid, and Cecilia Akselsson
Biogeosciences, 20, 1879–1899, https://doi.org/10.5194/bg-20-1879-2023, https://doi.org/10.5194/bg-20-1879-2023, 2023
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In a future climate, extreme droughts might become more common. Climate change and droughts can have negative effects on soil weathering and plant health.
In this study, climate change effects on weathering were studied on sites in Sweden using the model ForSAFE, a climate change scenario and an extreme drought scenario. The modelling shows that weathering is higher during summer and increases with global warming but that weathering during drought summers can become as low as winter weathering.
Agustín Sarquis and Carlos A. Sierra
Biogeosciences, 20, 1759–1771, https://doi.org/10.5194/bg-20-1759-2023, https://doi.org/10.5194/bg-20-1759-2023, 2023
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Although plant litter is chemically and physically heterogenous and undergoes multiple transformations, models that represent litter dynamics often ignore this complexity. We used a multi-model inference framework to include information content in litter decomposition datasets and studied the time it takes for litter to decompose as measured by the transit time. In arid lands, the median transit time of litter is about 3 years and has a negative correlation with mean annual temperature.
Qi Guan, Jing Tang, Lian Feng, Stefan Olin, and Guy Schurgers
Biogeosciences, 20, 1635–1648, https://doi.org/10.5194/bg-20-1635-2023, https://doi.org/10.5194/bg-20-1635-2023, 2023
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Understanding terrestrial sources of nitrogen is vital to examine lake eutrophication changes. Combining process-based ecosystem modeling and satellite observations, we found that land-leached nitrogen in the Yangtze Plain significantly increased from 1979 to 2018, and terrestrial nutrient sources were positively correlated with eutrophication trends observed in most lakes, demonstrating the necessity of sustainable nitrogen management to control eutrophication.
Vivek K. Arora, Christian Seiler, Libo Wang, and Sian Kou-Giesbrecht
Biogeosciences, 20, 1313–1355, https://doi.org/10.5194/bg-20-1313-2023, https://doi.org/10.5194/bg-20-1313-2023, 2023
Short summary
Short summary
The behaviour of natural systems is now very often represented through mathematical models. These models represent our understanding of how nature works. Of course, nature does not care about our understanding. Since our understanding is not perfect, evaluating models is challenging, and there are uncertainties. This paper illustrates this uncertainty for land models and argues that evaluating models in light of the uncertainty in various components provides useful information.
Kamal Nyaupane, Umakant Mishra, Feng Tao, Kyongmin Yeo, William J. Riley, Forrest M. Hoffman, and Sagar Gautam
Biogeosciences Discuss., https://doi.org/10.5194/bg-2023-50, https://doi.org/10.5194/bg-2023-50, 2023
Revised manuscript accepted for BG
Short summary
Short summary
Representing soil organic carbon (SOC) dynamics in Earth system models (ESMs) is a key source of uncertainty in predicting carbon climate feedbacks. We used machine learning to develop and compare predictive relationships in observations and ESMs. We found different relationships between environmental factors and SOC stocks in observations and ESMs. SOC predictions in ESMs may be improved by representing the functional relationships of environmental controllers consistent with observations.
Cited articles
Anderegg, W. R. L.: Spatial and temporal variation in plant hydraulic traits
and their relevance for climate change impacts on vegetation, New Phytol.,
205, 1008–1014, 2015.
Aragao, L. E. O. C., Malhi, Y., Roman-Cuesta, R. M., Saatchi, S., Anderson,
L. O., and Shimabukuro, Y. E.: Spatial patterns and fire response of recent
Amazonian droughts, Geophys. Res. Lett., 34, L07701,
https://doi.org/10.1029/2006GL028946, 2007.
Aragao, L. E. O. C., Malhi, Y., Metcalfe, D. B., Silva-Espejo, J. E., Jiménez, E., Navarrete, D., Almeida, S., Costa, A. C. L., Salinas, N., Phillips, O. L., Anderson, L. O., Alvarez, E., Baker, T. R., Goncalvez, P. H., Huamán-Ovalle, J., Mamani-Solórzano, M., Meir, P., Monteagudo, A., Patiño, S., Peñuela, M. C., Prieto, A., Quesada, C. A., Rozas-Dávila, A., Rudas, A., Silva Jr., J. A., and Vásquez, R.: Above- and below-ground net primary productivity across ten Amazonian forests on contrasting soils, Biogeosciences, 6, 2759–2778, https://doi.org/10.5194/bg-6-2759-2009, 2009.
Asner, G. P. and Alencar, A.: Drought impacts on the Amazon forest: the
remote sensing perspective, New Phytol., 187, 569–578, 2010.
Asner, G. P., Scurlock, J. M. O., and Hicke, J. A.: Global synthesis of leaf
area index observations: implications for ecological and remote sensing
studies, Global Ecol. Biogeogr., 12, 191–205, 2003.
Asner, G. P., Martin, R. E., Anderson, C. B., and Knapp, D. E.: Quantifying
forest canopy traits: Imaging spectroscopy versus field survey, Remote Sens.
Environ., 158, 15–27, 2015.
Bahar, N. H., Ishida, F. Y., Weerasinghe, L. K., Guerrieri, R., O'Sullivan,
O. S., Bloomfield, K. J., Asner, G. P., Martin, R. E., Lloyd, J., Malhi, Y.,
Phillips, O. L., Meir, P., Salinas, N., Cosio, E. G., Domingues, T. F.,
Quesada, C. A., Sinca, F., Escudero Vega, A., Zuloaga Ccorimanya, P. P., Del
Aguila-Pasquel, J., Quispe Huaypar, K., Cuba Torres, I., Butron Loayza, R.,
Pelaez Tapia, Y., Huaman Ovalle, J., Long, B. M., Evans, J. R., and Atkin,
O. K.: Leaf-level photosynthetic capacity in lowland Amazonian and
high-elevation Andean tropical moist forests of Peru, New Phytol., 214,
1002–1018, 2017.
Baker, I. T., Prihodko, L., Denning, A. S., Goulden, M., Miller, S., and da
Rocha, H. R.: Seasonal drought stress in the Amazon: Reconciling models and
observations, J. Geophys. Res.-Biogeo., 113, G00B01,
https://doi.org/10.1029/2007JG000644, 2008.
Beer, C., Reichstein, M., Tomelleri, E., Ciais, P., Jung, M., Carvalhais,
N., Rödenbeck, C., Arain, M. A., Baldocchi, D., and Bonan, G. B.:
Terrestrial gross carbon dioxide uptake: global distribution and covariation
with climate, Science, 329, 834–838, 2010.
Bennett, A. C., McDowell, N. G., Allen, C. D., and Anderson-Teixeira, K. J.:
Larger trees suffer most during drought in forests worldwide, Nat. Plants,
1, 15139, https://doi.org/10.1038/nplants.2015.139, 2015.
Bi, J., Knyazikhin, Y., Choi, S. H., Park, T., Barichivich, J., Ciais, P.,
Fu, R., Ganguly, S., Hall, F., Hilker, T., Huete, A., Jones, M., Kimball,
J., Lyapustin, A. I., Mottus, M., Nemani, R. R., Piao, S. L., Poulter, B.,
Saleska, S. R., Saatchi, S. S., Xu, L., Zhou, L. M., and Myneni, R. B.:
Sunlight mediated seasonality in canopy structure and photosynthetic
activity of Amazonian rainforests, Environ. Res. Lett., 10, 064014, https://doi.org/10.1088/1748-9326/10/6/064014, 2015.
Bloom, A. A. and Williams, M.: Constraining ecosystem carbon dynamics in a data-limited world: integrating ecological “common sense” in a model-data fusion framework, Biogeosciences, 12, 1299–1315, https://doi.org/10.5194/bg-12-1299-2015, 2015.
Bloom, A. J., Chapin, F. S., and Mooney, H. A.: Resource Limitation in
Plants – an Economic Analogy, Annu. Rev. Ecol. Syst., 16, 363–392, 1985.
Boisier, J. P., Ciais, P., Ducharne, A., and Guimberteau, M.: Projected
strengthening of Amazonian dry season by constrained climate model
simulations, Nat. Clim. Change, 5, 656–660, 2015.
Bonan, G. B., Williams, M., Fisher, R. A., and Oleson, K. W.: Modeling stomatal conductance in the earth system: linking leaf water-use efficiency and water transport along the soil-plant-atmosphere continuum, Geosci. Model Dev., 7, 2193–2222, https://doi.org/10.5194/gmd-7-2193-2014, 2014.
Brando, P. M., Nepstad, D. C., Davidson, E. A., Trumbore, S. E., Ray, D.,
and Camargo, P.: Drought effects on litterfall, wood production and
belowground carbon cycling in an Amazon forest: results of a throughfall
reduction experiment, Philos. T. R. Soc. B, 363, 1839–1848, 2008.
Brando, P. M., Goetz, S. J., Baccini, A., Nepstad, D. C., Beck, P. S., and
Christman, M. C.: Seasonal and interannual variability of climate and
vegetation indices across the Amazon, P. Natl. Acad. Sci. USA, 107,
14685–14690, 2010.
Bréda, N. J. J.: Ground-based measurements of leaf area index: a review
of methods, instruments and current controversies, J. Exp. Bot., 54,
2403–2417, 2003.
Breiman, L.: Random forests, Mach. Learn., 45, 5–32, 2001.
Carswell, F. E., Costa, A. L., Palheta, M., Malhi, Y., Meir, P., Costa, J.
D. R., Ruivo, M. D., Leal, L. D. M., Costa, J. M. N., Clement, R. J., and
Grace, J.: Seasonality in CO2 and H2O flux at an eastern Amazonian
rain forest, J. Geophys. Res.-Atmos, 107, D208076,
https://doi.org/10.1029/2000JD000284, 2002.
Castanho, A. D. A., Coe, M. T., Costa, M. H., Malhi, Y., Galbraith, D., and Quesada, C. A.: Improving simulated Amazon forest biomass and productivity by including spatial variation in biophysical parameters, Biogeosciences, 10, 2255–2272, https://doi.org/10.5194/bg-10-2255-2013, 2013.
Choat, B., Jansen, S., Brodribb, T. J., Cochard, H., Delzon, S., Bhaskar,
R., Bucci, S. J., Feild, T. S., Gleason, S. M., Hacke, U. G., Jacobsen, A.
L., Lens, F., Maherali, H., Martinez-Vilalta, J., Mayr, S., Mencuccini, M.,
Mitchell, P. J., Nardini, A., Pittermann, J., Pratt, R. B., Sperry, J. S.,
Westoby, M., Wright, I. J., and Zanne, A. E.: Global convergence in the
vulnerability of forests to drought, Nature, 491, 752–755, 2012.
Cleveland, C. C., Townsend, A. R., Taylor, P., Alvarez-Clare, S.,
Bustamante, M. M. C., Chuyong, G., Dobrowski, S. Z., Grierson, P., Harms, K.
E., and Houlton, B. Z.: Relationships among net primary productivity,
nutrients and climate in tropical rain forest: a pan-tropical analysis,
Ecol. Lett., 14, 939–947, 2011.
Corlett, R. T.: The Impacts of Droughts in Tropical Forests, Trends Plant
Sci., 21, 584–593, 2016.
da Costa, A. C. L., Rowland, L., Oliveira, R. S., Oliveira, A. A. R., Binks,
O. J., Salmon, Y., Vasconcelos, S. S., Junior, J. A. S., Ferreira, L. V.,
Poyatos, R., Mencuccini, M., and Meir, P.: Stand dynamics modulate water
cycling and mortality risk in droughted tropical forest, Glob. Change Biol.,
24, 249–258, 2018.
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P.,
Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., and Bauer, P.: The
ERA-Interim reanalysis: Configuration and performance of the data
assimilation system, Q. J. Roy. Meteor. Soc., 137, 553–597, 2011.
Dietze, M. C., Sala, A., Carbone, M. S., Czimczik, C. I., Mantooth, J. A.,
Richardson, A. D., and Vargas, R.: Nonstructural carbon in woody plants,
Annu. Rev. Plant Biol., 65, 667–687, 2014.
Dobbertin, M., Eilmann, B., Bleuler, P., Giuggiola, A., Graf Pannatier, E.,
Landolt, W., Schleppi, P., and Rigling, A.: Effect of irrigation on needle
morphology, shoot and stem growth in a drought-exposed Pinus sylvestris
forest, Tree Physiol., 30, 346–360, 2010.
Doughty, C. E., Metcalfe, D. B., Girardin, C. A., Amezquita, F. F., Cabrera,
D. G., Huasco, W. H., Silva-Espejo, J. E., Araujo-Murakami, A., da Costa, M.
C., Rocha, W., Feldpausch, T. R., Mendoza, A. L., da Costa, A. C., Meir, P.,
Phillips, O. L., and Malhi, Y.: Drought impact on forest carbon dynamics and
fluxes in Amazonia, Nature, 519, 78–82, https://doi.org/10.1038/nature14213, 2015.
Drusch, M., Moreno, J., Del Bello, U., Franco, R., Goulas, Y., Huth, A.,
Kraft, S., Middleton, E. M., Miglietta, F., and Mohammed, G.: The
FLuorescence EXplorer Mission Concept – ESA's Earth Explorer 8, IEEE T.
Geosci. Remote, 55, 1273–1284, 2017.
Duffy, P. B., Brando, P., Asner, G. P., and Field, C. B.: Projections of
future meteorological drought and wet periods in the Amazon, P. Natl. Acad.
Sci. USA, 112, 13172–13177, 2015.
Eller, C. B., Rowland, L., Oliveira, R. S., Bittencourt, P. R. L., Barros,
F. V., da Costa, A. C. L., Meir, P., Friend, A. D., Mencuccini, M., Sitch,
S., and Cox, P.: Modelling tropical forest responses to drought and El Nino
with a stomatal optimization model based on xylem hydraulics, Philos. T. R.
Soc. B., 373, 20170315, https://doi.org/10.1098/rstb.2017.0315, 2018.
Fauset, S., Baker, T. R., Lewis, S. L., Feldpausch, T. R., Affum-Baffoe, K.,
Foli, E. G., Hamer, K. C., and Swaine, M. D.: Drought-induced shifts in the
floristic and functional composition of tropical forests in Ghana, Ecol.
Lett., 15, 1120–1129, 2012.
Fisher, R. A., Williams, M., Do, V., Lobo, R., Da Costa, A. L., and Meir,
P.: Evidence from Amazonian forests is consistent with isohydric control of
leaf water potential, Plant Cell Environ., 29, 151–165, 2006.
Fisher, R. A., Williams, M., Da Costa, A. L., Malhi, Y., Da Costa, R. F.,
Almeida, S., and Meir, P.: The response of an Eastern Amazonian rain forest
to drought stress: results and modelling analyses from a throughfall
exclusion experiment, Glob. Change Biol., 13, 2361–2378, 2007.
Fisher, R. A., Koven, C. D., Anderegg, W. R. L., Christoffersen, B. O., Dietze, M. C., Farrior, C. E., Holm, J. A., Hurtt, G. C., Knox, R. G., Lawrence, P. J., Lichstein, J. W., Longo, M., Matheny, A. M., Medvigy, D., Muller-Landau, H. C., Powell, T. L., Serbin, S. P., Sato, H., Shuman, J. K., Smith, B., Trugman, A. T., Viskari, T., Verbeeck, H., Weng, E., Xu, C., Xu, X., Zhang, T., and Moorcroft, P. R.: Vegetation demographics in Earth System Models: A review of progress and priorities, Glob. Change Biol., 24, 35–54, 2018.
Flack-Prain, S., Meir, P., Malhi, Y., Smallman, T., and Williams, M.: The importance of physiological, structural and trait responses to drought stress in driving spatial and temporal variation in GPP across Amazon forests, University of Edinburgh, School of Geosciences, https://doi.org/10.7488/ds/2710, 2019.
Fyllas, N. M., Patiño, S., Baker, T. R., Bielefeld Nardoto, G., Martinelli, L. A., Quesada, C. A., Paiva, R., Schwarz, M., Horna, V., Mercado, L. M., Santos, A., Arroyo, L., Jiménez, E. M., Luizão, F. J., Neill, D. A., Silva, N., Prieto, A., Rudas, A., Silviera, M., Vieira, I. C. G., Lopez-Gonzalez, G., Malhi, Y., Phillips, O. L., and Lloyd, J.: Basin-wide variations in foliar properties of Amazonian forest: phylogeny, soils and climate, Biogeosciences, 6, 2677–2708, https://doi.org/10.5194/bg-6-2677-2009, 2009.
Fyllas, N. M., Bentley, L. P., Shenkin, A., Asner, G. P., Atkin, O. K.,
Diaz, S., Enquist, B. J., Farfan-Rios, W., Gloor, E., Guerrieri, R., Huasco,
W. H., Ishida, Y., Martin, R. E., Meir, P., Phillips, O., Salinas, N.,
Silman, M., Weerasinghe, L. K., Zaragoza-Castells, J., and Malhi, Y.: Solar
radiation and functional traits explain the decline of forest primary
productivity along a tropical elevation gradient, Ecol. Lett., 20, 730–740,
2017.
Galbraith, D., Levy, P. E., Sitch, S., Huntingford, C., Cox, P., Williams,
M., and Meir, P.: Multiple mechanisms of Amazonian forest biomass losses in
three dynamic global vegetation models under climate change, New Phytol.,
187, 647–665, 2010.
Goulden, M. L., Miller, S. D., da Rocha, H. R., Menton, M. C., de Freitas,
H. C., Figueira, A. M. E. S., and de Sousa, C. A. D.: Diel and seasonal
patterns of tropical forest CO2 exchange, Ecol. Appl., 14, S42–S54,
2004.
Green, J. K., Seneviratne, S. I., Berg, A. M., Findell, K. L., Hagemann, S.,
Lawrence, D. M., and Gentine, P.: Large influence of soil moisture on
long-term terrestrial carbon uptake, Nature, 565, 476–479, 2019.
Grier, C. C. and Running, S. W.: Leaf Area of Mature Northwestern Coniferous
Forests – Relation to Site Water-Balance, Ecology, 58, 893–899, 1977.
Guan, K., Pan, M., Li, H., Wolf, A., Wu, J., Medvigy, D., Caylor, K. K., Sheffield, J., Wood, E. F., Malhi, Y., and Liang, M.: Photosynthetic seasonality of global tropical forests constrained by hydroclimate, Nat. Geosci., 8, 284–289, 2015.
Hutyra, L. R., Munger, J. W., Saleska, S. R., Gottlieb, E., Daube, B. C.,
Dunn, A. L., Amaral, D. F., De Camargo, P. B., and Wofsy, S. C.: Seasonal
controls on the exchange of carbon and water in an Amazonian rain forest,
J. Geophys. Res.-Biogeo., 112, G03008, https://doi.org/10.1029/2006JG000365, 2007.
Ichii, K., Hashimoto, H., White, M. A., Potters, C., Hutyra, L. R., Huete,
A. R., Myneni, R. B., and Nemanis, R. R.: Constraining rooting depths in
tropical rainforests using satellite data and ecosystem modeling for
accurate simulation of gross primary production seasonality, Glob. Change
Biol., 13, 67–77, 2007.
Iio, A., Hikosaka, K., Anten, N. P. R., Nakagawa, Y., and Ito, A.: Global
dependence of field-observed leaf area index in woody species on climate: a
systematic review, Global Ecol. Biogeogr., 23, 274–285, 2014.
Joetzjer, E., Douville, H., Delire, C., and Ciais, P.: Present-day and
future Amazonian precipitation in global climate models: CMIP5 versus CMIP3,
Clim. Dynam., 41, 2921–2936, 2013.
Jonckheere, I., Fleck, S., Nackaerts, K., Muys, B., Coppin, P., Weiss, M.,
and Baret, F.: Review of methods for in situ leaf area index determination –
Part I, Theories, sensors and hemispherical photography, Agr. Forest
Meteorol., 121, 19–35, 2004.
Kattge, J., Diaz, S., Lavorel, S., Prentice, I. C., Leadley, P.,
Bönisch, G., Garnier, E., Westoby, M., Reich, P. B., and Wright, I. J.:
TRY–a global database of plant traits, Glob. Change Biol., 17, 2905–2935,
2011.
Lee, J. E., Frankenberg, C., van der Tol, C., Berry, J. A., Guanter, L.,
Boyce, C. K., Fisher, J. B., Morrow, E., Worden, J. R., Asefi, S., Badgley,
G., and Saatchi, S.: Forest productivity and water stress in Amazonia:
observations from GOSAT chlorophyll fluorescence, P. R. Soc. B., 280,
20130171, https://doi.org/10.1098/rspb.2013.0171, 2013.
Liu, J., Bowman, K. W., Schimel, D. S., Parazoo, N. C., Jiang, Z., Lee, M.,
Bloom, A. A., Wunch, D., Frankenberg, C., and Sun, Y.: Contrasting carbon
cycle responses of the tropical continents to the 2015–2016 El Niño,
Science, 358, eaam5690, https://doi.org/10.1126/science.aam5690, 2017.
López-Blanco, E., Lund, M., Williams, M., Tamstorf, M. P., Westergaard-Nielsen, A., Exbrayat, J.-F., Hansen, B. U., and Christensen, T. R.: Exchange of CO2 in Arctic tundra: impacts of meteorological variations and biological disturbance, Biogeosciences, 14, 4467–4483, https://doi.org/10.5194/bg-14-4467-2017, 2017.
Malhi, Y., Roberts, J. T., Betts, R. A., Killeen, T. J., Li, W., and Nobre,
C. A.: Climate change, deforestation, and the fate of the Amazon, Science,
319, 169–172, 2008.
Malhi, Y., Aragao, L. E., Galbraith, D., Huntingford, C., Fisher, R.,
Zelazowski, P., Sitch, S., McSweeney, C., and Meir, P.: Exploring the
likelihood and mechanism of a climate-change-induced dieback of the Amazon
rainforest, P. Natl. Acad. Sci. USA, 106, 20610–20615, 2009.
Malhi, Y., Doughty, C. E., Goldsmith, G. R., Metcalfe, D. B., Girardin, C.
A. J., Marthews, T. R., del Aguila-Pasquel, J., Aragao, L. E. O. C.,
Araujo-Murakami, A., Brando, P., da Costa, A. C. L., Silva-Espejo, J. E.,
Amezquita, F. F., Galbraith, D. R., Quesada, C. A., Rocha, W.,
Salinas-Revilla, N., Silverio, D., Meir, P., and Phillips, O. L.: The
linkages between photosynthesis, productivity, growth and biomass in lowland
Amazonian forests, Glob. Change Biol., 21, 2283–2295, 2015.
McMurtrie, R. E. and Dewar, R. C.: Leaf-trait variation explained by the
hypothesis that plants maximize their canopy carbon export over the lifespan
of leaves, Tree Physiol., 31, 1007–1023, 2011.
McWilliam, A. L., Roberts, J. M., Cabral, O. M. R., Leitao, M., De Costa, A.
C. L., Maitelli, G. T., and Zamparoni, C.: Leaf area index and above-ground
biomass of terra firme rain forest and adjacent clearings in Amazonia,
Funct. Ecol., 7, 310–317, 1993.
Meir, P. and Woodward, F. I.: Amazonian rain forests and drought: response
and vulnerability, New Phytol., 187, 553–557, 2010.
Meir, P., Metcalfe, D. B., Costa, A. C., and Fisher, R. A.: The fate of
assimilated carbon during drought: impacts on respiration in Amazon
rainforests, Philos. T. R. Soc. B, 363, 1849–1855, 2008.
Meir, P., Brando, P. M., Nepstad, D., Vasconcelos, S., Costa, A. C. L.,
Davidson, E., Almeida, S., Fisher, R. A., Sotta, E. D., and Zarin, D.: The
effects of drought on Amazonian rain forests, Amazonia and Global Change,
186, 429–449, 2009.
Meir, P., Mencuccini, M., and Dewar, R. C.: Drought-related tree mortality:
addressing the gaps in understanding and prediction, New Phytol., 207,
28–33, 2015a.
Meir, P., Wood, T. E., Galbraith, D. R., Brando, P. M., Da Costa, A. C.,
Rowland, L., and Ferreira, L. V.: Threshold Responses to Soil Moisture
Deficit by Trees and Soil in Tropical Rain Forests: Insights from Field
Experiments, Bioscience, 65, 882–892, 2015b.
Mercado, L. M., Patino, S., Domingues, T. F., Fyllas, N. M., Weedon, G. P.,
Sitch, S., Quesada, C. A., Phillips, O. L., Aragao, L. E., Malhi, Y.,
Dolman, A. J., Restrepo-Coupe, N., Saleska, S. R., Baker, T. R., Almeida,
S., Higuchi, N., and Lloyd, J.: Variations in Amazon forest productivity
correlated with foliar nutrients and modelled rates of photosynthetic carbon
supply, Philos. T. R. Soc. B, 366, 3316–3329, 2011.
Metcalfe, D. B., Meir, P., Aragao, L., Malhi, Y., Da Costa, A. C. L., Braga,
A., Gonçalves, P. H. L., de Athaydes, J., De Almeida, S. S., and
Williams, M.: Factors controlling spatio-temporal variation in carbon
dioxide efflux from surface litter, roots, and soil organic matter at four
rain forest sites in the eastern Amazon, J. Geophys. Res.-Biogeo., 112, G04001, https://doi.org/10.1029/2007JG000443, 2007.
Metcalfe, D. B., Meir, P., Aragao, L. E. O. C., da Costa, A. C. L., Braga,
A. P., Goncalves, P. H. L., Silva, J. D., de Almeida, S. S., Dawson, L. A.,
Malhi, Y., and Williams, M.: The effects of water availability on root
growth and morphology in an Amazon rainforest, Plant Soil, 311, 189–199,
2008.
Moore, C. E., Beringer, J., Donohue, R. J., Evans, B., Exbrayat, J. F.,
Hutley, L. B., and Tapper, N. J.: Seasonal, interannual and decadal drivers
of tree and grass productivity in an Australian tropical savanna, Glob.
Change Biol., 24, 2530–2544, 2018.
Morton, D. C.: FOREST CARBON FLUXES A satellite perspective, Nat. Clim.
Change, 6, 346–348, 2016.
Myneni, R. B., Yang, W., Nemani, R. R., Huete, A. R., Dickinson, R. E.,
Knyazikhin, Y., Didan, K., Fu, R., Negron Juarez, R. I., Saatchi, S. S.,
Hashimoto, H., Ichii, K., Shabanov, N. V., Tan, B., Ratana, P., Privette, J.
L., Morisette, J. T., Vermote, E. F., Roy, D. P., Wolfe, R. E., Friedl, M.
A., Running, S. W., Votava, P., El-Saleous, N., Devadiga, S., Su, Y., and
Salomonson, V. V.: Large seasonal swings in leaf area of Amazon rainforests,
P. Natl. Acad. Sci. USA, 104, 4820–4823, 2007.
Nepstad, D. C., Decarvalho, C. R., Davidson, E. A., Jipp, P. H., Lefebvre,
P. A., Negreiros, G. H., Dasilva, E. D., Stone, T. A., Trumbore, S. E., and
Vieira, S.: The Role of Deep Roots in the Hydrological and Carbon Cycles of
Amazonian Forests and Pastures, Nature, 372, 666–669, 1994.
Nepstad, D. C., Moutinho, P., Dias, M. B., Davidson, E., Cardinot, G.,
Markewitz, D., Figueiredo, R., Vianna, N., Chambers, J., Ray, D.,
Guerreiros, J. B., Lefebvre, P., Sternberg, L., Moreira, M., Barros, L.,
Ishida, F. Y., Tohlver, I., Belk, E., Kalif, K., and Schwalbe, K.: The
effects of partial throughfall exclusion on canopy processes, aboveground
production, and biogeochemistry of an Amazon forest, J. Geophys. Res.-Atmos,
107, D208085, https://doi.org/10.1029/2001JD000360, 2002.
Nepstad, D. C., Tohver, I. M., Ray, D., Moutinho, P., and Cardinot, G.:
Mortality of large trees and lianas following experimental drought in an
Amazon forest, Ecology, 88, 2259–2269, 2007.
O'Brien, M. J., Leuzinger, S., Philipson, C. D., Tay, J., and Hector, A.:
Drought survival of tropical tree seedlings enhanced by non-structural
carbohydrate levels, Nat. Clim. Change, 4, 710–740, 2014.
Oliveira, R. S., Dawson, T. E., Burgess, S. S., and Nepstad, D. C.:
Hydraulic redistribution in three Amazonian trees, Oecologia, 145, 354–363,
2005.
Onoda, Y., Wright, I. J., Evans, J. R., Hikosaka, K., Kitajima, K.,
Niinemets, Ü., Poorter, H., Tosens, T., and Westoby, M.: Physiological
and structural tradeoffs underlying the leaf economics spectrum, New
Phytol., 214, 1447–1463, 2017.
Osnas, J. L., Lichstein, J. W., Reich, P. B., and Pacala, S. W.: Global leaf
trait relationships: mass, area, and the leaf economics spectrum, Science,
340, 741–744, 2013.
Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel,
O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J.,
Passos, A., Cournapeau, D., Brucher, M., Perrot, M., and Duchesnay, E.:
Scikit-learn: Machine Learning in Python, J. Mach. Learn Res., 12,
2825–2830, 2011.
Pettorelli, N., Buhne, H. S. T., Tulloch, A., Dubois, G., Macinnis-Ng, C.,
Queiros, A. M., Keith, D. A., Wegmann, M., Schrodt, F., Stellmes, M.,
Sonnenschein, R., Geller, G. N., Roy, S., Somers, B., Murray, N., Bland, L.,
Geijzendorffer, I., Kerr, J. T., Broszeit, S., Leitao, P. J., Duncan, C., El
Serafy, G., He, K. S., Blanchard, J. L., Lucas, R., Mairota, P., Webb, T.
J., and Nicholson, E.: Satellite remote sensing of ecosystem functions:
opportunities, challenges and way forward, Remote Sens. Ecol.
Conserv., 4, 71–93, 2018.
Poorter, L. and Bongers, F.: Leaf traits are good predictors of plant
performance across 53 rain forest species, Ecology, 87, 1733–1743, 2006.
Powell, T. L., Galbraith, D. R., Christoffersen, B. O., Harper, A.,
Imbuzeiro, H. M., Rowland, L., Almeida, S., Brando, P. M., da Costa, A. C.,
Costa, M. H., Levine, N. M., Malhi, Y., Saleska, S. R., Sotta, E., Williams,
M., Meir, P., and Moorcroft, P. R.: Confronting model predictions of carbon
fluxes with measurements of Amazon forests subjected to experimental
drought, New Phytol., 200, 350–365, 2013.
Quesada, C. A., Phillips, O. L., Schwarz, M., Czimczik, C. I., Baker, T. R., Patiño, S., Fyllas, N. M., Hodnett, M. G., Herrera, R., Almeida, S., Alvarez Dávila, E., Arneth, A., Arroyo, L., Chao, K. J., Dezzeo, N., Erwin, T., di Fiore, A., Higuchi, N., Honorio Coronado, E., Jimenez, E. M., Killeen, T., Lezama, A. T., Lloyd, G., López-González, G., Luizão, F. J., Malhi, Y., Monteagudo, A., Neill, D. A., Núñez Vargas, P., Paiva, R., Peacock, J., Peñuela, M. C., Peña Cruz, A., Pitman, N., Priante Filho, N., Prieto, A., Ramírez, H., Rudas, A., Salomão, R., Santos, A. J. B., Schmerler, J., Silva, N., Silveira, M., Vásquez, R., Vieira, I., Terborgh, J., and Lloyd, J.: Basin-wide variations in Amazon forest structure and function are mediated by both soils and climate, Biogeosciences, 9, 2203–2246, https://doi.org/10.5194/bg-9-2203-2012, 2012.
Reich, P. B., Uhl, C., Walters, M. B., and Ellsworth, D. S.: Leaf lifespan
as a determinant of leaf structure and function among 23 Amazonian tree
species, Oecologia, 86, 16–24, 1991.
Reich, P. B., Tjoelker, M. G., Pregitzer, K. S., Wright, I. J., Oleksyn, J.,
and Machado, J. L.: Scaling of respiration to nitrogen in leaves, stems and
roots of higher land plants, Ecol. Lett., 11, 793–801, 2008.
Reichstein, M., Bahn, M., Mahecha, M. D., Kattge, J., and Baldocchi, D. D.:
Linking plant and ecosystem functional biogeography, P. Natl. Acad. Sci.
USA, 111, 13697–13702, 2014.
Restrepo-Coupe, N., da Rocha, H. R., Hutyra, L. R., da Araujo, A. C., Borma,
L. S., Christoffersen, B., Cabral, O. M. R., de Camargo, P. B., Cardoso, F.
L., and da Costa, A. C. L.: What drives the seasonality of photosynthesis
across the Amazon basin? A cross-site analysis of eddy flux tower
measurements from the Brasil flux network, Agr. Forest Meteorol., 182,
128–144, 2013.
Restrepo-Coupe, N., Levine, N. M., Christoffersen, B. O., Albert, L. P., Wu,
J., Costa, M. H., Galbraith, D., Imbuzeiro, H., Martins, G., and Araujo, A.
C.: Do dynamic global vegetation models capture the seasonality of carbon
fluxes in the Amazon basin? A data-model intercomparison, Glob. Change
Biol., 23, 191–208, 2017.
Richardson, A. D., Hollinger, D. Y., Aber, J. D., Ollinger, S. V., and
Braswell, B. H.: Environmental variation is directly responsible for
short-but not long-term variation in forest-atmosphere carbon exchange,
Glob. Change Biol., 13, 788–803, 2007.
Rodig, E., Cuntz, M., Rammig, A., Fischer, R., Taubert, F., and Huth, A.:
The importance of forest structure for carbon fluxes of the Amazon
rainforest, Environ. Res. Lett., 13, 054013, https://doi.org/10.1088/1748-9326/aabc61, 2018.
Rowland, L., Hill, T. C., Stahl, C., Siebicke, L., Burban, B.,
Zaragoza-Castells, J., Ponton, S., Bonal, D., Meir, P., and Williams, M.:
Evidence for strong seasonality in the carbon storage and carbon use
efficiency of an Amazonian forest, Glob. Change Biol., 20, 979–991, 2014.
Rowland, L., Da Costa, A. C. L., Galbraith, D. R., Oliveira, R. S., Binks,
O. J., Oliveira, A. A. R., Pullen, A. M., Doughty, C. E., Metcalfe, D. B.,
and Vasconcelos, S. S.: Death from drought in tropical forests is triggered
by hydraulics not carbon starvation, Nature, 528, 119–122, 2015a.
Rowland, L., Harper, A., Christoffersen, B. O., Galbraith, D. R., Imbuzeiro, H. M. A., Powell, T. L., Doughty, C., Levine, N. M., Malhi, Y., Saleska, S. R., Moorcroft, P. R., Meir, P., and Williams, M.: Modelling climate change responses in tropical forests: similar productivity estimates across five models, but different mechanisms and responses, Geosci. Model Dev., 8, 1097–1110, https://doi.org/10.5194/gmd-8-1097-2015, 2015b.
Rowland, L., da Costa, A. C. L., Oliveira, A. A. R., Almeida, S. S.,
Ferreira, L. V., Malhi, Y., Metcalfe, D. B., Mencuccini, M., Grace, J., and
Meir, P.: Shock and stabilisation following long-term drought in tropical
forest from 15 years of litterfall dynamics, J. Ecol., 106, 1673–1682, 2018.
Sakschewski, B., von Bloh, W., Boit, A., Poorter, L., Pena-Claros, M.,
Heinke, J., Joshi, J., and Thonicke, K.: Resilience of Amazon forests
emerges from plant trait diversity, Nat. Clim. Change, 6, 1032–1036, 2016.
Saleska, S. R., Miller, S. D., Matross, D. M., Goulden, M. L., Wofsy, S. C.,
da Rocha, H. R., de Camargo, P. B., Crill, P., Daube, B. C., de Freitas, H.
C., Hutyra, L., Keller, M., Kirchhoff, V., Menton, M., Munger, J. W., Pyle,
E. H., Rice, A. H., and Silva, H.: Carbon in Amazon forests: unexpected
seasonal fluxes and disturbance-induced losses, Science, 302, 1554–1557,
2003.
Saleska, S. R., Didan, K., Huete, A. R., and da Rocha, H. R.: Amazon forests
green-up during 2005 drought, Science, 318, p. 612, 2007.
Samanta, A., Ganguly, S., Hashimoto, H., Devadiga, S., Vermote, E.,
Knyazikhin, Y., Nemani, R. R., and Myneni, R. B.: Amazon forests did not
green-up during the 2005 drought, Geophys. Res. Lett., 37, L05401, https://doi.org/10.1029/2009GL042154, 2010.
Santiago, L. S., Goldstein, G., Meinzer, F. C., Fisher, J. B., Machado, K.,
Woodruff, D., and Jones, T.: Leaf photosynthetic traits scale with hydraulic
conductivity and wood density in Panamanian forest canopy trees, Oecologia,
140, 543–550, 2004.
Saxton, K. E., Rawls, W. J., Romberger, J. S., and Papendick, R. I.:
Estimating generalized soil-water characteristics from texture 1, Soil Sci.
Soc. Am. J., 50, 1031–1036, 1986.
Schleppi, P., Thimonier, A., and Walthert, L.: Estimating leaf area index of
mature temperate forests using regressions on site and vegetation data,
Forest Ecol. Manag., 261, 601–610, 2011.
Schuldt, B., Leuschner, C., Horna, V., Moser, G., Köhler, M., van Straaten, O., and Barus, H.: Change in hydraulic properties and leaf traits in a tall rainforest tree species subjected to long-term throughfall exclusion in the perhumid tropics, Biogeosciences, 8, 2179–2194, https://doi.org/10.5194/bg-8-2179-2011, 2011.
Smallman, T. L., Moncrieff, J. B., and Williams, M.: WRFv3.2-SPAv2: development and validation of a coupled ecosystem–atmosphere model, scaling from surface fluxes of CO2 and energy to atmospheric profiles, Geosci. Model Dev., 6, 1079–1093, https://doi.org/10.5194/gmd-6-1079-2013, 2013.
Sperry, J. S., Hacke, U. G., Oren, R., and Comstock, J. P.: Water deficits
and hydraulic limits to leaf water supply, Plant Cell Environ., 25, 251–263,
2002.
Sus, O., Williams, M., Bernhofer, C., Béziat, P., Buchmann, N., Ceschia, E., Doherty, R., Eugster, W., Grünwald, T., Kutsch, W., and Smith, P.: A linked carbon cycle and crop developmental model: Description and evaluation against measurements of carbon fluxes and carbon stocks at several European agricultural sites, Agr. Ecosys. Environ., 139, 402–418, 2010.
van de Weg, M. J., Shaver, G. R., and Salmon, V. G.: Contrasting effects of
long term versus short-term nitrogen addition on photosynthesis and
respiration in the Arctic, Plant Ecol., 214, 1273–1286, 2013.
Von Randow, C., Zeri, M., Restrepo-Coupe, N., Muza, M. N., de Gonçalves,
L. G. G., Costa, M. H., Araujo, A. C., Manzi, A. O., da Rocha, H. R., and
Saleska, S. R.: Inter-annual variability of carbon and water fluxes in
Amazonian forest, Cerrado and pasture sites, as simulated by terrestrial
biosphere models, Agr. Forest Meteorol., 182, 145–155, 2013.
Wagner, F. H., Herault, B., Rossi, V., Hilker, T., Maeda, E. E., Sanchez,
A., Lyapustin, A. I., Galvao, L. S., Wang, Y., and Aragao, L.: Climate
drivers of the Amazon forest greening, PLoS One, 12, e0180932, https://doi.org/10.1371/journal.pone.0180932, 2017.
Walker, A. P., Beckerman, A. P., Gu, L., Kattge, J., Cernusak, L. A.,
Domingues, T. F., Scales, J. C., Wohlfahrt, G., Wullschleger, S. D., and
Woodward, F. I.: The relationship of leaf photosynthetic traits – Vcmax and
Jmax – to leaf nitrogen, leaf phosphorus, and specific leaf area: a
meta-analysis and modeling study, Ecol. Evol., 4, 3218–3235, 2014.
Wang, G., Alo, C., Mei, R., and Sun, S.: Droughts, hydraulic redistribution,
and their impact on vegetation composition in the Amazon forest, Plant
Ecol., 212, 663–673, 2011.
Waring, R. H. and Schlesinger, W. H.: Forest ecosystems. Concepts and
management, Academic Press, 7–37, 1985.
Weiss, M., Baret, F., Smith, G. J., Jonckheere, I., and Coppin, P.: Review
of methods for in situ leaf area index (LAI) determination Part II,
Estimation of LAI, errors and sampling, Agr. Forest Meteorol., 121, 37–53,
2004.
Williams, M., Rastetter, E. B., Fernandes, D. N., Goulden, M. L., Wofsy, S.
C., Shaver, G. R., Melillo, J. M., Munger, J. W., Fan, S. M., and
Nadelhoffer, K. J.: Modelling the soil-plant-atmosphere continuum in a
Quercus–Acer stand at Harvard Forest: the regulation of stomatal
conductance by light, nitrogen and soil ∕ plant hydraulic properties, Plant
Cell Environ., 19, 911–927, 1996.
Williams, M., Malhi, Y., Nobre, A. D., Rastetter, E. B., Grace, J., and
Pereira, M. G. P.: Seasonal variation in net carbon exchange and
evapotranspiration in a Brazilian rain forest: a modelling analysis, Plant
Cell Environ., 21, 953–968, 1998.
Wright, I. J., Reich, P. B., Westoby, M., Ackerly, D. D., Baruch, Z.,
Bongers, F., Cavender-Bares, J., Chapin, T., Cornelissen, J. H., Diemer, M.,
Flexas, J., Garnier, E., Groom, P. K., Gulias, J., Hikosaka, K., Lamont, B.
B., Lee, T., Lee, W., Lusk, C., Midgley, J. J., Navas, M. L., Niinemets, U.,
Oleksyn, J., Osada, N., Poorter, H., Poot, P., Prior, L., Pyankov, V. I.,
Roumet, C., Thomas, S. C., Tjoelker, M. G., Veneklaas, E. J., and Villar,
R.: The worldwide leaf economics spectrum, Nature, 428, 821–827, 2004.
Wright, J. K., Williams, M., Starr, G., McGee, J., and Mitchell, R. J.:
Measured and modelled leaf and stand-scale productivity across a soil
moisture gradient and a severe drought, Plant Cell Environ., 36, 467–483,
2013.
Wu, J., Albert, L. P., Lopes, A. P., Restrepo-Coupe, N., Hayek, M.,
Wiedemann, K. T., Guan, K., Stark, S. C., Christoffersen, B., Prohaska, N.,
Tavares, J. V., Marostica, S., Kobayashi, H., Ferreira, M. L., Campos, K.
S., da Silva, R., Brando, P. M., Dye, D. G., Huxman, T. E., Huete, A. R.,
Nelson, B. W., and Saleska, S. R.: Leaf development and demography explain
photosynthetic seasonality in Amazon evergreen forests, Science, 351,
972–976, 2016.
Wu, J., Guan, K. Y., Hayek, M., Restrepo-Coupe, N., Wiedemann, K. T., Xu, X.
T., Wehr, R., Christoffersen, B. O., Miao, G. F., da Silva, R., de Araujo,
A. C., Oliviera, R. C., Camargo, P. B., Monson, R. K., Huete, A. R., and
Saleska, S. R.: Partitioning controls on Amazon forest photosynthesis
between environmental and biotic factors at hourly to interannual
timescales, Glob. Change Biol., 23, 1240–1257, 2017.
Zhang, K., Castanho, A. D. D., Galbraith, D. R., Moghim, S., Levine, N. M.,
Bras, R. L., Coe, M. T., Costa, M. H., Malhi, Y., Longo, M., Knox, R. G.,
McKnight, S., Wang, J. F., and Moorcroft, P. R.: The fate of Amazonian
ecosystems over the coming century arising from changes in climate,
atmospheric CO2, and land use, Glob. Change Biol., 21, 2569–2587, 2015.
Short summary
Across the Amazon rainforest, trees take in carbon through photosynthesis. However, photosynthesis across the basin is threatened by predicted shifts in rainfall patterns. To unpick how changes in rainfall affect photosynthesis, we use a model which combines climate data with our knowledge of photosynthesis and other plant processes. We find that stomatal constraints are less important, and instead shifts in leaf surface area and leaf properties drive changes in photosynthesis with rainfall.
Across the Amazon rainforest, trees take in carbon through photosynthesis. However,...
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