Articles | Volume 13, issue 4
https://doi.org/10.5194/bg-13-925-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/bg-13-925-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
18 Feb 2016
Research article |
| 18 Feb 2016
The effect of using the plant functional type paradigm on a data-constrained global phenology model
Microsoft Research, Cambridge, UK
now at: Max Planck Institute for Biogeochemistry, Jena, Germany
Drew W. Purves
Microsoft Research, Cambridge, UK
Matthew J. Smith
Microsoft Research, Cambridge, UK
Related authors
Tea Thum, Tuuli Miinalainen, Outi Seppälä, Holly Croft, Cheryl Rogers, Ralf Staebler, Silvia Caldararu, and Sönke Zaehle
EGUsphere, https://doi.org/10.5194/egusphere-2024-2802, https://doi.org/10.5194/egusphere-2024-2802, 2024
Short summary
Short summary
Climate change has potential to influence the carbon sequestration potential of terrestrial ecosystems and here also nitrogen cycle is important. We used a terrestrial biosphere model QUINCY at mixed deciduous forest in Canada. We investigated the usefulness of using leaf area index and leaf chlorophyll content to improve the parameterization of the model. This work paves way for using spaceborn observations in the model parameterization, also including information on the nitrogen cycle.
Gabriela Sophia, Silvia Caldararu, Benjamin David Stocker, and Sönke Zaehle
Biogeosciences, 21, 4169–4193, https://doi.org/10.5194/bg-21-4169-2024, https://doi.org/10.5194/bg-21-4169-2024, 2024
Short summary
Short summary
Through an extensive global dataset of leaf nutrient resorption and a multifactorial analysis, we show that the majority of spatial variation in nutrient resorption may be driven by leaf habit and type, with thicker, longer-lived leaves having lower resorption efficiencies. Climate, soil fertility and soil-related factors emerge as strong drivers with an additional effect on its role. These results are essential for comprehending plant nutrient status, plant productivity and nutrient cycling.
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
Short summary
Short summary
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.
Gab Abramowitz, Anna Ukkola, Sanaa Hobeichi, Jon Cranko Page, Mathew Lipson, Martin De Kauwe, Sam Green, Claire Brenner, Jonathan Frame, Grey Nearing, Martyn Clark, Martin Best, Peter Anthoni, Gabriele Arduini, Souhail Boussetta, Silvia Caldararu, Kyeungwoo Cho, Matthias Cuntz, David Fairbairn, Craig Ferguson, Hyungjun Kim, Yeonjoo Kim, Jürgen Knauer, David Lawrence, Xiangzhong Luo, Sergey Malyshev, Tomoko Nitta, Jerome Ogee, Keith Oleson, Catherine Ottlé, Phillipe Peylin, Patricia de Rosnay, Heather Rumbold, Bob Su, Nicolas Vuichard, Anthony Walker, Xiaoni Wang-Faivre, Yunfei Wang, and Yijian Zeng
EGUsphere, https://doi.org/10.5194/egusphere-2023-3084, https://doi.org/10.5194/egusphere-2023-3084, 2024
Short summary
Short summary
This paper evaluates land models – computer based models that simulate ecosystem dynamics, the land carbon, water and energy cycles and the role of land in the climate system. It uses machine learning / AI approaches to show that despite the complexity of land models, they do not perform nearly as well as they could, given the amount of information they are provided with about the prediction problem.
Richard Nair, Yunpeng Luo, Tarek El-Madany, Victor Rolo, Javier Pacheco-Labrador, Silvia Caldararu, Kendalynn A. Morris, Marion Schrumpf, Arnaud Carrara, Gerardo Moreno, Markus Reichstein, and Mirco Migliavacca
EGUsphere, https://doi.org/10.5194/egusphere-2023-2434, https://doi.org/10.5194/egusphere-2023-2434, 2023
Preprint archived
Short summary
Short summary
We studied a Mediterranean ecosystem to understand carbon uptake efficiency and its controls. These ecosystems face potential nitrogen-phosphorus imbalances due to pollution. Analysing six years of carbon data, we assessed controls at different timeframes. This is crucial for predicting such vulnerable regions. Our findings revealed N limitation on C uptake, not N:P imbalance, and strong influence of water availability. whether drought or wetness promoted net C uptake depended on timescale.
Silvia Caldararu, Victor Rolo, Benjamin D. Stocker, Teresa E. Gimeno, and Richard Nair
Biogeosciences, 20, 3637–3649, https://doi.org/10.5194/bg-20-3637-2023, https://doi.org/10.5194/bg-20-3637-2023, 2023
Short summary
Short summary
Ecosystem manipulative experiments are large experiments in real ecosystems. They include processes such as species interactions and weather that would be omitted in more controlled settings. They offer a high level of realism but are underused in combination with vegetation models used to predict the response of ecosystems to global change. We propose a workflow using models and ecosystem experiments together, taking advantage of the benefits of both tools for Earth system understanding.
Lin Yu, Silvia Caldararu, Bernhard Ahrens, Thomas Wutzler, Marion Schrumpf, Julian Helfenstein, Chiara Pistocchi, and Sönke Zaehle
Biogeosciences, 20, 57–73, https://doi.org/10.5194/bg-20-57-2023, https://doi.org/10.5194/bg-20-57-2023, 2023
Short summary
Short summary
In this study, we addressed a key weakness in current ecosystem models regarding the phosphorus exchange in the soil and developed a new scheme to describe this process. We showed that the new scheme improved the model performance for plant productivity, soil organic carbon, and soil phosphorus content at five beech forest sites in Germany. We claim that this new model could be used as a better tool to study ecosystems under future climate change, particularly phosphorus-limited systems.
Tea Thum, Silvia Caldararu, Jan Engel, Melanie Kern, Marleen Pallandt, Reiner Schnur, Lin Yu, and Sönke Zaehle
Geosci. Model Dev., 12, 4781–4802, https://doi.org/10.5194/gmd-12-4781-2019, https://doi.org/10.5194/gmd-12-4781-2019, 2019
Short summary
Short summary
To predict the response of the vegetation to climate change, we need global models that describe the relevant processes taking place in the vegetation. Recently, we have obtained more in-depth understanding of vegetation processes and the role of nutrients in the biogeochemical cycles. We have developed a new global vegetation model that includes carbon, water, nitrogen, and phosphorus cycles. We show that the model is successful in evaluation against a wide range of observations.
Mingkai Jiang, Sönke Zaehle, Martin G. De Kauwe, Anthony P. Walker, Silvia Caldararu, David S. Ellsworth, and Belinda E. Medlyn
Geosci. Model Dev., 12, 2069–2089, https://doi.org/10.5194/gmd-12-2069-2019, https://doi.org/10.5194/gmd-12-2069-2019, 2019
Short summary
Short summary
Here we used a simple analytical framework developed by Comins and McMurtrie (1993) to investigate how different model assumptions affected plant responses to elevated CO2. This framework is useful in revealing both the consequences and the mechanisms through which different assumptions affect predictions. We therefore recommend the use of this framework to analyze the likely outcomes of new assumptions before introducing them to complex model structures.
S. Caldararu, D. W. Purves, and P. I. Palmer
Biogeosciences, 11, 763–778, https://doi.org/10.5194/bg-11-763-2014, https://doi.org/10.5194/bg-11-763-2014, 2014
Tea Thum, Tuuli Miinalainen, Outi Seppälä, Holly Croft, Cheryl Rogers, Ralf Staebler, Silvia Caldararu, and Sönke Zaehle
EGUsphere, https://doi.org/10.5194/egusphere-2024-2802, https://doi.org/10.5194/egusphere-2024-2802, 2024
Short summary
Short summary
Climate change has potential to influence the carbon sequestration potential of terrestrial ecosystems and here also nitrogen cycle is important. We used a terrestrial biosphere model QUINCY at mixed deciduous forest in Canada. We investigated the usefulness of using leaf area index and leaf chlorophyll content to improve the parameterization of the model. This work paves way for using spaceborn observations in the model parameterization, also including information on the nitrogen cycle.
Gabriela Sophia, Silvia Caldararu, Benjamin David Stocker, and Sönke Zaehle
Biogeosciences, 21, 4169–4193, https://doi.org/10.5194/bg-21-4169-2024, https://doi.org/10.5194/bg-21-4169-2024, 2024
Short summary
Short summary
Through an extensive global dataset of leaf nutrient resorption and a multifactorial analysis, we show that the majority of spatial variation in nutrient resorption may be driven by leaf habit and type, with thicker, longer-lived leaves having lower resorption efficiencies. Climate, soil fertility and soil-related factors emerge as strong drivers with an additional effect on its role. These results are essential for comprehending plant nutrient status, plant productivity and nutrient cycling.
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
Short summary
Short summary
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.
Gab Abramowitz, Anna Ukkola, Sanaa Hobeichi, Jon Cranko Page, Mathew Lipson, Martin De Kauwe, Sam Green, Claire Brenner, Jonathan Frame, Grey Nearing, Martyn Clark, Martin Best, Peter Anthoni, Gabriele Arduini, Souhail Boussetta, Silvia Caldararu, Kyeungwoo Cho, Matthias Cuntz, David Fairbairn, Craig Ferguson, Hyungjun Kim, Yeonjoo Kim, Jürgen Knauer, David Lawrence, Xiangzhong Luo, Sergey Malyshev, Tomoko Nitta, Jerome Ogee, Keith Oleson, Catherine Ottlé, Phillipe Peylin, Patricia de Rosnay, Heather Rumbold, Bob Su, Nicolas Vuichard, Anthony Walker, Xiaoni Wang-Faivre, Yunfei Wang, and Yijian Zeng
EGUsphere, https://doi.org/10.5194/egusphere-2023-3084, https://doi.org/10.5194/egusphere-2023-3084, 2024
Short summary
Short summary
This paper evaluates land models – computer based models that simulate ecosystem dynamics, the land carbon, water and energy cycles and the role of land in the climate system. It uses machine learning / AI approaches to show that despite the complexity of land models, they do not perform nearly as well as they could, given the amount of information they are provided with about the prediction problem.
Richard Nair, Yunpeng Luo, Tarek El-Madany, Victor Rolo, Javier Pacheco-Labrador, Silvia Caldararu, Kendalynn A. Morris, Marion Schrumpf, Arnaud Carrara, Gerardo Moreno, Markus Reichstein, and Mirco Migliavacca
EGUsphere, https://doi.org/10.5194/egusphere-2023-2434, https://doi.org/10.5194/egusphere-2023-2434, 2023
Preprint archived
Short summary
Short summary
We studied a Mediterranean ecosystem to understand carbon uptake efficiency and its controls. These ecosystems face potential nitrogen-phosphorus imbalances due to pollution. Analysing six years of carbon data, we assessed controls at different timeframes. This is crucial for predicting such vulnerable regions. Our findings revealed N limitation on C uptake, not N:P imbalance, and strong influence of water availability. whether drought or wetness promoted net C uptake depended on timescale.
Silvia Caldararu, Victor Rolo, Benjamin D. Stocker, Teresa E. Gimeno, and Richard Nair
Biogeosciences, 20, 3637–3649, https://doi.org/10.5194/bg-20-3637-2023, https://doi.org/10.5194/bg-20-3637-2023, 2023
Short summary
Short summary
Ecosystem manipulative experiments are large experiments in real ecosystems. They include processes such as species interactions and weather that would be omitted in more controlled settings. They offer a high level of realism but are underused in combination with vegetation models used to predict the response of ecosystems to global change. We propose a workflow using models and ecosystem experiments together, taking advantage of the benefits of both tools for Earth system understanding.
Lin Yu, Silvia Caldararu, Bernhard Ahrens, Thomas Wutzler, Marion Schrumpf, Julian Helfenstein, Chiara Pistocchi, and Sönke Zaehle
Biogeosciences, 20, 57–73, https://doi.org/10.5194/bg-20-57-2023, https://doi.org/10.5194/bg-20-57-2023, 2023
Short summary
Short summary
In this study, we addressed a key weakness in current ecosystem models regarding the phosphorus exchange in the soil and developed a new scheme to describe this process. We showed that the new scheme improved the model performance for plant productivity, soil organic carbon, and soil phosphorus content at five beech forest sites in Germany. We claim that this new model could be used as a better tool to study ecosystems under future climate change, particularly phosphorus-limited systems.
Tea Thum, Silvia Caldararu, Jan Engel, Melanie Kern, Marleen Pallandt, Reiner Schnur, Lin Yu, and Sönke Zaehle
Geosci. Model Dev., 12, 4781–4802, https://doi.org/10.5194/gmd-12-4781-2019, https://doi.org/10.5194/gmd-12-4781-2019, 2019
Short summary
Short summary
To predict the response of the vegetation to climate change, we need global models that describe the relevant processes taking place in the vegetation. Recently, we have obtained more in-depth understanding of vegetation processes and the role of nutrients in the biogeochemical cycles. We have developed a new global vegetation model that includes carbon, water, nitrogen, and phosphorus cycles. We show that the model is successful in evaluation against a wide range of observations.
Mingkai Jiang, Sönke Zaehle, Martin G. De Kauwe, Anthony P. Walker, Silvia Caldararu, David S. Ellsworth, and Belinda E. Medlyn
Geosci. Model Dev., 12, 2069–2089, https://doi.org/10.5194/gmd-12-2069-2019, https://doi.org/10.5194/gmd-12-2069-2019, 2019
Short summary
Short summary
Here we used a simple analytical framework developed by Comins and McMurtrie (1993) to investigate how different model assumptions affected plant responses to elevated CO2. This framework is useful in revealing both the consequences and the mechanisms through which different assumptions affect predictions. We therefore recommend the use of this framework to analyze the likely outcomes of new assumptions before introducing them to complex model structures.
Silvia Caldararu, Drew W. Purves, and Matthew J. Smith
Geosci. Model Dev., 10, 1679–1701, https://doi.org/10.5194/gmd-10-1679-2017, https://doi.org/10.5194/gmd-10-1679-2017, 2017
Short summary
Short summary
We developed a new general model for predicting the growth and development of annual crops to help improve food security worldwide. We explore how accurately such a model can predict wheat and maize crop growth in Europe and the US when we use commonly used public datasets to calibrate the model. Satellite measurements of crop greenness and ground measurements of carbon dioxide exchange improve prediction accuracy substantially, whereas regional measurements of crop yields are less important.
Yiqi Luo, Zheng Shi, Xingjie Lu, Jianyang Xia, Junyi Liang, Jiang Jiang, Ying Wang, Matthew J. Smith, Lifen Jiang, Anders Ahlström, Benito Chen, Oleksandra Hararuk, Alan Hastings, Forrest Hoffman, Belinda Medlyn, Shuli Niu, Martin Rasmussen, Katherine Todd-Brown, and Ying-Ping Wang
Biogeosciences, 14, 145–161, https://doi.org/10.5194/bg-14-145-2017, https://doi.org/10.5194/bg-14-145-2017, 2017
Short summary
Short summary
Climate change is strongly regulated by land carbon cycle. However, we lack the ability to predict future land carbon sequestration. Here, we develop a novel framework for understanding what determines the direction and rate of future change in land carbon storage. The framework offers a suite of new approaches to revolutionize land carbon model evaluation and improvement.
Johannes Meyerholt, Sönke Zaehle, and Matthew J. Smith
Biogeosciences, 13, 1491–1518, https://doi.org/10.5194/bg-13-1491-2016, https://doi.org/10.5194/bg-13-1491-2016, 2016
Short summary
Short summary
We investigated how today's state-of-the-art terrestrial biosphere models represent biological nitrogen fixation and what the consequences of varying representation are for model predictions under ambient conditions and under scenarios of elevated atmospheric carbon dioxide concentrations. We found that varying global nitrogen fixation rates are simulated under ambient conditions and that the responses of the simulated carbon and nitrogen cycles are significantly affected under perturbation.
Y. P. Wang, J. Jiang, B. Chen-Charpentier, F. B. Agusto, A. Hastings, F. Hoffman, M. Rasmussen, M. J. Smith, K. Todd-Brown, Y. Wang, X. Xu, and Y. Q. Luo
Biogeosciences, 13, 887–902, https://doi.org/10.5194/bg-13-887-2016, https://doi.org/10.5194/bg-13-887-2016, 2016
Short summary
Short summary
Comparing two nonlinear microbial models, we found that,
in response to warming, soil C decreases in one model but can increase or decrease in the other model, and sensitivity of priming response to carbon input increases with soil T in one model but decreases in the other model
Significance: these differences in the responses can be used to discern which model is more realistic, which will improve our understanding of the significance of soil microbial processes in the terrestrial C cycle.
S. Caldararu, D. W. Purves, and P. I. Palmer
Biogeosciences, 11, 763–778, https://doi.org/10.5194/bg-11-763-2014, https://doi.org/10.5194/bg-11-763-2014, 2014
M. J. Smith, D. W. Purves, M. C. Vanderwel, V. Lyutsarev, and S. Emmott
Biogeosciences, 10, 583–606, https://doi.org/10.5194/bg-10-583-2013, https://doi.org/10.5194/bg-10-583-2013, 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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Arora, V. K. and Boer, G. J.: Simulating Competition and Coexistence between
Plant Functional Types in a Dynamic Vegetation Model, Earth Interact., 10,
1–30, 2006.
Baltzer, J. and Thomas, S.: Physiological and morphological correlates of
whole-plant light compensation point in temperate deciduous tree seedlings,
Oecologia, 153, 209–223, 2007.
Bey, I., Jacob, D., Yantosca, R., Logan, J., Field, B., Fiore, A., Li, Q.,
Liu,
H., Mickley, L., and Schultz, M.: Global modeling of tropospheric chemistry
with assimilated meteorology: Model description and evaluation, J.
Geophys. Res., 106, 23073–23095, 2001.
Bi, J., Knyazikhin, Y., Choi, S., Park, T., Barichivich, J., Ciais, P., Fu,
R.,
Ganguly, S., Hall, F., Hilker, T., Huete, A., Jones, M., Kimball, J.,
Lyapustin, A. I., Mõttus, M., Nemani, R. R., Piao, S., Poulter, B., Saleska,
S. R., Saatchi, S. S., Xu, L., Zhou, L., 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.
Box, E. O.: Plant Functional Types and Climate at the Global Scale, J.
Vegetat. Sci., 7, 309–320,
1996.
Brock, T. D.: Calculating solar radiation for ecological studies, Ecol.
Modell., 14, 1–19,
1981.
Bustamante, M. M. C., Medina, E., Asner, G. P., Nardoto, G. B., and
Garcia-Montiel, D. C.: Nitrogen cycling in tropical and temperate savannas,
in: Nitrogen Cycling in the Americas: Natural and Anthropogenic Influences
and Controls, edited by: Martinelli, L. A. and Howarth, R. W.,
Springer Netherlands, 209–237, 2006.
Caldararu, S., Palmer, P. I., and Purves, D. W.: Inferring Amazon leaf
demography from satellite observations of leaf area index, Biogeosciences, 9,
1389–1404, https://doi.org/10.5194/bg-9-1389-2012,
2012.
Caldararu, S., Purves, D. W., and Palmer, P. I.: Phenology as a strategy for
carbon optimality: a global model, Biogeosciences, 11, 763–778,
https://doi.org/10.5194/bg-11-763-2014,
2014.
Chen, J., Menges, C., and Leblanc, S.: Global mapping of foliage clumping
index
using multi-angular satellite data, Remote Sens. Environ., 97,
447–457, https://doi.org/10.1016/j.rse.2005.05.003,
2005.
Chen, J. M., Mo, G., Pisek, J., Liu, J., Deng, F., Ishizawa, M., and Chan,
D.:
Effects of foliage clumping on the estimation of global terrestrial gross
primary productivity, Global Biogeochem. Cy., 26, GB1019,
https://doi.org/10.1029/2010GB003996, 2012.
da Rocha, H. R., Goulden, M. L., Miller, S. D., Menton, M. C., Pinto, L.,
de Freitas, H. C., and Figueira, A.: Seasonality of water and heat fluxes
over a tropical forest in eastern Amazonia, Ecol. Appl., 14,
S22–S32, 2004.
dePury, D. G. G. and Farquhar, G. D.: Simple scaling of photosynthesis from
leaves to canopies without the errors of big-leaf models, Plant Cell
Environ., 20, 537–557, 1997.
Elser, J. J., Bracken, M. E., Cleland, E. E., Gruner, D. S., Harpole, W. S.,
Hillebrand, H., Ngai, J. T., Seabloom, E. W., Shurin, J. B., and Smith,
J. E.: Global analysis of nitrogen and phosphorus limitation of primary
producers in freshwater, marine and terrestrial ecosystems, Ecol. Lett.,
10, 1135–1142, 2007.
Farquhar, G. D., Caemmerer, S., and Berry, J. A.: A biochemical model of
photosynthetic CO2 assimilation in leaves of C3 species, Planta, 149,
78–90, 1980.
Fisher, J. B., Badgley, G., and Blyth, E.: Global nutrient limitation in
terrestrial vegetation, Global Biogeochem. Cy., 26, GB3007,
https://doi.org/10.1029/2011GB004252, 2012.
Fisher, R. A., Muszala, S., Verteinstein, M., Lawrence, P., Xu, C., McDowell,
N. G., Knox, R. G., Koven, C., Holm, J., Rogers, B. M., Spessa, A., Lawrence,
D., and Bonan, G.: Taking off the training wheels: the properties of a
dynamic vegetation model without climate envelopes, CLM4.5(ED), Geosci. Model
Dev., 8, 3593–3619, https://doi.org/10.5194/gmd-8-3593-2015, 2015.
Givnish, T. J., Montgomery, R. A., and Goldstein, G.: Adaptive radiation of
photosynthetic physiology in the Hawaiian lobeliads: light regimes, static
light responses, and whole-plant compensation points, Am. J.
Bot., 91, 228–246, 2004.
Goulden, M. L., Miller, S. D., da Rocha, H. R., Menton, M. C., de Freitas,
H. C., Figueira, A., and de Sousa, C. A. D.: Diel and seasonal patterns of
tropical forest CO2 exchange, Ecol. Appl., 14, S42–S54,
2004.
Haxeltine, A. and Prentice, I. C.: A General Model for the Light-Use
Efficiency
of Primary Production, Funct. Ecol., 10, 551–561,
1996.
Hayden, B. P.: Ecosystem feedbacks on climate at the landscape scale,
Philosophical Transactions of the Royal Society of London, Series B,
Biol. Sci., 353, 5–18,
1998.
Hikosaka, K.: A Model of Dynamics of Leaves and Nitrogen in a Plant Canopy:
An
Integration of Canopy Photosynthesis, Leaf Life Span, and Nitrogen Use
Efficiency, Am. Nat., 162, 149–164,
2003.
Huete, A. R., Didan, K., Shimabukuro, Y. E., Ratana, P., Saleska, S. R.,
Hutyra, L. R., Yang, W. Z., Nemani, R. R., and Myneni, R.: Amazon
rainforests green-up with sunlight in dry season, Geophys. Res.
Lett., 33, L06405, https://doi.org/10.1029/2005GL025583, 2006.
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.
Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., Gandin, L.,
Iredell, M., Saha, S., White, G., Woollen, J., Zhu, Y., Chelliah, M.,
Ebisuzaki, W., Higgins, W., Janowiak, J., Mo, K., Ropelewski, C., Wang, J.,
Leetmaa, A., Reynolds, R., Jenne, R., and Joseph, D.: The NCEP/NCAR 40-year
reanalysis project, Bull. Am. Meteorol. Soc.,
77, 437–471, 1996.
Knyazikhin, Y., J., G., Privette, J. L., Tian, Y., Lotsch, A., Zhang., Y.,
Wang, Y., Morisette, J. T., P.Votava, Myneni, R., Nemani, R. R., and Running,
S. W.: MODIS Leaf Area Index (LAI) and Fraction of Photosynthetically
Active Radiation Absorbed by Vegetation (FPAR) Product (MOD15) Algorithm
Theoretical Basis Document,
http://modis.gsfc.nasa.gov/data/atbd/, 1999.
Kucharik, C. J., Foley, J. A., Delire, C., Fisher, V. A., Coe, M. T.,
Lenters,
J. D., Young-Molling, C., Ramankutty, N., Norman, J. M., and Gower, S. T.:
Testing the performance of a dynamic global ecosystem model: Water balance,
carbon balance, and vegetation structure, Global Biogeochem. Cy., 14,
795–825, 2000.
Lewis, J. D., McKane, R. B., Tingey, D. T., and Beedlow, P. A.: Vertical
gradients in photosynthetic light response within an old-growth Douglas-fir
and western hemlock canopy, Tree Physiol., 20, 447–456,
2000.
Morton, D. C., Nagol, J., Carabajal, C. C., Rosette, J., Palace, M., Cook,
B. D., Vermote, E. F., Harding, D. J., and North, P. R. J.: Amazon forests
maintain consistent canopy structure and greenness during the dry season,
Nature, 506, 221–224,
2014.
Myneni, R. B., Yang, W. Z., Nemani, R. R., Huete, A. R., Dickinson, R. E.,
Knyazikhin, Y., Didan, K., Fu, R., Juarez, R. I. N., 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, Proc. Natl. Acad. Sci. USA, 104, 4820–4823, 2007.
Pavlick, R., Drewry, D. T., Bohn, K., Reu, B., and Kleidon, A.: The Jena
Diversity-Dynamic Global Vegetation Model (JeDi-DGVM): a diverse approach to
representing terrestrial biogeography and biogeochemistry based on plant
functional trade-offs, Biogeosciences, 10, 4137–4177,
https://doi.org/10.5194/bg-10-4137-2013, 2013.
Prentice, I. C., Cramer, W., Harrison, S. P., Leemans, R., Monserud, R. A.,
and
Solomon, A. M.: A Global Biome Model Based on Plant Physiology and Dominance,
Soil Properties and Climate, J. Biogeogr., 19, 117–134,
1992.
Reich, P. B., Wright, I. J., and Lusk, C. H.: Predicting leaf physiology from
simple plant and climate attributes: A global GLOPNET analysis, Ecol.
Appl., 17, 1982–1988, 2007.
Riddoch, I., Lehto, T., and Grace, J.: Photosynthesis of Tropical Tree
Seedlings in Relation to Light and Nutrient Supply, New Phytol., 119,
137–147, 1991.
Sakschewski, B., von Bloh, W., Boit, A., Rammig, A., Kattge, J., Poorter, L.,
Peñuelas, J., and Thonicke, K.: Leaf and stem economics spectra drive
diversity of functional plant traits in a dynamic global vegetation model,
Glob. Change Biol., 21, 2711–2725, 2015.
Sitch, S., Smith, B., Prentice, I. C., Arneth, A., Bondeau, A., Cramer, W.,
Kaplan, J. O., Levis, S., Lucht, W., Sykes, M. T., Thonicke, K., and
Venevsky, S.: Evaluation of ecosystem dynamics, plant geography and
terrestrial carbon cycling in the LPJ dynamic global vegetation model,
Glob.
Change Biol., 9, 161–185, 2003.
Smith, T. M.: Plant functional types :their relevance to ecosystem properties
and global change, edited by: Smith, T. M., Shugart, H. H., and Woodward, F. I.,
Cambridge University Press, Cambridge, 1997.
Stockli, R., Rutishauser, T., Dragoni, D., O'Keefe, J., Thornton, P. E.,
Jolly,
M., Lu, L., and Denning, A. S.: Remote sensing data assimilation for a
prognostic phenology model, J. Geophys. Res.-Biogeo.,
113, G04021, https://doi.org/10.1029/2008JG000781,
2008.
Van Bodegom, P. M., Douma, J. C., Witte, J. P. M., Ordonez, J. C.,
Bartholomeus, R. P., and Aerts, R.: Going beyond limitations of plant
functional types when predicting global ecosystem – atmosphere fluxes:
exploring the merits of traits-based approaches, Glob. Ecol.
Biogeogr., 21, 625–636,
2012.
van Bodegom, P. M., Douma, J. C., and Verheijen, L. M.: A fully traits-based
approach to modeling global vegetation distribution, Proc.
Natl. Acad. Sci., 111, 13733–13738, 2014.
Verheijen, L. M., Brovkin, V., Aerts, R., Bönisch, G., Cornelissen, J.
H. C.,
Kattge, J., Reich, P. B., Wright, I. J., and van Bodegom, P. M.: Impacts of
trait variation through observed trait-climate relationships on performance
of an Earth system model: a conceptual analysis, Biogeosciences, 10,
5497–5515, https://doi.org/10.5194/bg-10-5497-2013,
2013.
White, M. A., Running, S. W., and Thornton, P. E.: The impact of
growing-season
length variability on carbon assimilation and evapotranspiration over 88
years in the eastern US deciduous forest, Internat. J.
Biometeorol., 42, 139–145, 1999.
Wilson, K. B. and Baldocchi, D. D.: Seasonal and interannual variability of
energy fluxes over a broadleaved temperate deciduous forest in North
America, Agr. Forest Meteorol., 100, 1–18,
2000.
Wright, I. J., Reich, P. B., Westoby, M., Ackerly, D. D., Baruch, Z.,
Bongers,
F., Cavender-Bares, J., Chapin, T., Cornelissen, J. H. C., 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.
Wullschleger, S. D., Epstein, H. E., Box, E. O., Euskirchen, E. S., Goswami,
S., Iversen, C. M., Kattge, J., Norby, R. J., van Bodegom, P. M., and Xu, X.:
Plant functional types in Earth system models: past experiences and future
directions for application of dynamic vegetation models in high-latitude
ecosystems, Ann. Bot., mcu077, https://doi.org/10.1093/aob/mcu077,
2014.
Zaehle, S. and Friend, A. D.: Carbon and nitrogen cycle dynamics in the O-CN
land surface model: 1. Model description, site-scale evaluation, and
sensitivity to parameter estimates, Global Biogeochem. Cy., 24, Gb1005,
https://doi.org/10.1029/2009GB003521, 2010.
Short summary
The plant functional type (PFT) concept is widely used in global vegetation models but recent studies have attempted to replace this with a more biologically representative formulation by using plant traits. In this study we aim to quantify the performance of a data-constrained leaf phenology model that uses PFTs when compared to one that uses local traits. We show that the PFT model performs relatively poorly but we can identify a small number of traits that improve model performance.
The plant functional type (PFT) concept is widely used in global vegetation models but recent...
Altmetrics
Final-revised paper
Preprint