Articles | Volume 15, issue 5
https://doi.org/10.5194/bg-15-1607-2018
https://doi.org/10.5194/bg-15-1607-2018
Research article
 | 
16 Mar 2018
Research article |  | 16 Mar 2018

Ages and transit times as important diagnostics of model performance for predicting carbon dynamics in terrestrial vegetation models

Verónika Ceballos-Núñez, Andrew D. Richardson, and Carlos A. Sierra

Related authors

DeepPhenoMem V1.0: deep learning modelling of canopy greenness dynamics accounting for multi-variate meteorological memory effects on vegetation phenology
Guohua Liu, Mirco Migliavacca, Christian Reimers, Basil Kraft, Markus Reichstein, Andrew D. Richardson, Lisa Wingate, Nicolas Delpierre, Hui Yang, and Alexander J. Winkler
Geosci. Model Dev., 17, 6683–6701, https://doi.org/10.5194/gmd-17-6683-2024,https://doi.org/10.5194/gmd-17-6683-2024, 2024
Short summary
High capacity of integrated crop–pasture systems to preserve old soil carbon evaluated in a 60-year-old experiment
Maximiliano González-Sosa, Carlos A. Sierra, J. Andrés Quincke, Walter E. Baethgen, Susan Trumbore, and M. Virginia Pravia
SOIL, 10, 467–486, https://doi.org/10.5194/soil-10-467-2024,https://doi.org/10.5194/soil-10-467-2024, 2024
Short summary
How long does carbon stay in a near-pristine central Amazon forest? An empirical estimate with radiocarbon
Ingrid Chanca, Ingeborg Levin, Susan Trumbore, Kita Macario, Jost Lavric, Carlos Alberto Quesada, Alessandro Carioca de Araújo, Cléo Quaresma Dias Júnior, Hella van Asperen, Samuel Hammer, and Carlos Sierra
EGUsphere, https://doi.org/10.5194/egusphere-2024-883,https://doi.org/10.5194/egusphere-2024-883, 2024
Short summary
Moisture and temperature effects on the radiocarbon signature of respired carbon dioxide to assess stability of soil carbon in the Tibetan Plateau
Andrés Tangarife-Escobar, Georg Guggenberger, Xiaojuan Feng, Guohua Dai, Carolina Urbina-Malo, Mina Azizi-Rad, and Carlos A. Sierra
Biogeosciences, 21, 1277–1299, https://doi.org/10.5194/bg-21-1277-2024,https://doi.org/10.5194/bg-21-1277-2024, 2024
Short summary
How well does ramped thermal oxidation quantify the age distribution of soil carbon? Assessing thermal stability of physically and chemically fractionated soil organic matter
Shane W. Stoner, Marion Schrumpf, Alison Hoyt, Carlos A. Sierra, Sebastian Doetterl, Valier Galy, and Susan Trumbore
Biogeosciences, 20, 3151–3163, https://doi.org/10.5194/bg-20-3151-2023,https://doi.org/10.5194/bg-20-3151-2023, 2023
Short summary

Related subject area

Biogeochemistry: Modelling, Terrestrial
Future methane fluxes of peatlands are controlled by management practices and fluctuations in hydrological conditions due to climatic variability
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
Biogeosciences, 21, 5745–5771, https://doi.org/10.5194/bg-21-5745-2024,https://doi.org/10.5194/bg-21-5745-2024, 2024
Short summary
Understanding and simulating cropland and non-cropland burning in Europe using the BASE (Burnt Area Simulator for Europe) model
Matthew Forrest, Jessica Hetzer, Maik Billing, Simon P. K. Bowring, Eric Kosczor, Luke Oberhagemann, Oliver Perkins, Dan Warren, Fátima Arrogante-Funes, Kirsten Thonicke, and Thomas Hickler
Biogeosciences, 21, 5539–5560, https://doi.org/10.5194/bg-21-5539-2024,https://doi.org/10.5194/bg-21-5539-2024, 2024
Short summary
Representation of the terrestrial carbon cycle in CMIP6
Bettina K. Gier, Manuel Schlund, Pierre Friedlingstein, Chris D. Jones, Colin Jones, Sönke Zaehle, and Veronika Eyring
Biogeosciences, 21, 5321–5360, https://doi.org/10.5194/bg-21-5321-2024,https://doi.org/10.5194/bg-21-5321-2024, 2024
Short summary
Does dynamically modeled leaf area improve predictions of land surface water and carbon fluxes? Insights into dynamic vegetation modules
Sven Armin Westermann, Anke Hildebrandt, Souhail Bousetta, and Stephan Thober
Biogeosciences, 21, 5277–5303, https://doi.org/10.5194/bg-21-5277-2024,https://doi.org/10.5194/bg-21-5277-2024, 2024
Short summary
Observational benchmarks inform representation of soil organic carbon dynamics in land surface models
Kamal Nyaupane, Umakant Mishra, Feng Tao, Kyongmin Yeo, William J. Riley, Forrest M. Hoffman, and Sagar Gautam
Biogeosciences, 21, 5173–5183, https://doi.org/10.5194/bg-21-5173-2024,https://doi.org/10.5194/bg-21-5173-2024, 2024
Short summary

Cited articles

Bolin, B. and Rodhe, H.: A note on the concepts of age distribution and transit time in natural reservoirs, Tellus, 25, 58–62, 1973.
Canadell, J. G., Le Quéré, C., Raupach, M. R., Field, C. B., Buitenhuis, E. T., Ciais, P., Conway, T. J., Gillett, N. P., Houghton, R. A., and Marland, G.: Contributions to accelerating atmospheric CO2 growth from economic activity, carbon intensity, and efficiency of natural sinks, P. Natl. Acad. Sci. USA, 104, 18866–18870, 2007.
Cressie, N., Calder, C. A., Clark, J. S., Hoef, J. M. V., and Wikle, C. K.: Accounting for Uncertainty in Ecological Analysis: the Strengths and Limitations of Hierarchical Statistical Modeling, Ecol. Appl., 19, 553–570, 2009.
Ericsson, T., Rytter, L., and Vapaavuori, E.: Physiology of carbon allocation in trees, Biomass Bioenerg., 11, 115–127, https://doi.org/10.1016/0961-9534(96)00032-3, 1996.
Fox, A., Williams, M., Richardson, A. D., Cameron, D., Gove, J. H., Quaife, T., Ricciuto, D., Reichstein, M., Tomelleri, E., Trudinger, C. M., and Wijk, M. T. V.: The REFLEX project: Comparing different algorithms and implementations for the inversion of a terrestrial ecosystem model against eddy covariance data, Agr. Forest Meteorol., 149, 1597–1615, https://doi.org/10.1016/j.agrformet.2009.05.002, 2009.
Download
Short summary
Will the terrestrial biosphere be a carbon source or sink in the future? Different model simulations cannot reach a consensus, so we need to diagnose the performance of these models. We implemented three models differing in their carbon allocation strategies and assessed their performance using three metrics. The most sensible metric was the distribution of carbon age and transit times. Thus, empirical measurements of these distributions could be key to reduce the model uncertainty.
Altmetrics
Final-revised paper
Preprint