Articles | Volume 21, issue 2
https://doi.org/10.5194/bg-21-625-2024
© Author(s) 2024. 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-21-625-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
30 Jan 2024
Research article |
| 30 Jan 2024
| 30 Jan 2024
Evaluation of five models for constructing forest NPP–age relationships in China based on 3121 field survey samples
Peng Li
Key Laboratory of Humid Subtropical Eco-Geographical Process of Ministry of Education, School of Geographical Sciences, Fujian Normal University, Fuzhou, 350117, China
Academy of Carbon Neutrality, Fujian Normal University, Fuzhou, 350117, China
Key Laboratory of Humid Subtropical Eco-Geographical Process of Ministry of Education, School of Geographical Sciences, Fujian Normal University, Fuzhou, 350117, China
Academy of Carbon Neutrality, Fujian Normal University, Fuzhou, 350117, China
Jing M. Chen
CORRESPONDING AUTHOR
Key Laboratory of Humid Subtropical Eco-Geographical Process of Ministry of Education, School of Geographical Sciences, Fujian Normal University, Fuzhou, 350117, China
Department of Geography and Planning, University of Toronto, Ontario, ON M5S 3G3, Canada
Mingzhu Xu
Key Laboratory of Humid Subtropical Eco-Geographical Process of Ministry of Education, School of Geographical Sciences, Fujian Normal University, Fuzhou, 350117, China
Academy of Carbon Neutrality, Fujian Normal University, Fuzhou, 350117, China
Xudong Lin
Key Laboratory of Humid Subtropical Eco-Geographical Process of Ministry of Education, School of Geographical Sciences, Fujian Normal University, Fuzhou, 350117, China
Academy of Carbon Neutrality, Fujian Normal University, Fuzhou, 350117, China
Guirui Yu
Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
Nianpeng He
Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
Li Xu
Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
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Huajie Zhu, Mousong Wu, Fei Jiang, Michael Vossbeck, Thomas Kaminski, Xiuli Xing, Jun Wang, Weimin Ju, and Jing M. Chen
Geosci. Model Dev., 17, 6337–6363, https://doi.org/10.5194/gmd-17-6337-2024, https://doi.org/10.5194/gmd-17-6337-2024, 2024
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In this work, we developed the Nanjing University Carbon Assimilation System (NUCAS v1.0). Data assimilation experiments were conducted to demonstrate the robustness and investigate the feasibility and applicability of NUCAS. The assimilation of ecosystem carbonyl sulfide (COS) fluxes improved the model performance in gross primary productivity, evapotranspiration, and sensible heat, showing that COS provides constraints on parameters relevant to carbon-, water-, and energy-related processes.
Wei Zhang, Xunhua Zheng, Siqi Li, Shenghui Han, Chunyan Liu, Zhisheng Yao, Rui Wang, Kai Wang, Xiao Chen, Guirui Yu, Zhi Chen, Jiabing Wu, Huimin Wang, Junhua Yan, and Yong Li
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-141, https://doi.org/10.5194/gmd-2024-141, 2024
Preprint under review for GMD
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Process-oriented biogeochemical models are promising tools for estimating the carbon fluxes of forest ecosystems. In this study, the hydro-biogeochemical model of CNMM-DNDC was improved by incorporating a new forest growth module derived from the Biome-BGC. The updated model was validated using the multiple-year observed carbon fluxes and showed better performance in capturing the daily dynamics and annual variations. The sensitive eco-physiological parameters were also identified.
Jiye Leng, Jing M. Chen, Wenyu Li, Xiangzhong Luo, Mingzhu Xu, Jane Liu, Rong Wang, Cheryl Rogers, Bolun Li, and Yulin Yan
Earth Syst. Sci. Data, 16, 1283–1300, https://doi.org/10.5194/essd-16-1283-2024, https://doi.org/10.5194/essd-16-1283-2024, 2024
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We produced a long-term global two-leaf gross primary productivity (GPP) and evapotranspiration (ET) dataset at the hourly time step by integrating a diagnostic process-based model with dynamic parameterizations. The new dataset provides us with a unique opportunity to study carbon and water fluxes at sub-daily time scales and advance our understanding of ecosystem functions in response to transient environmental changes.
Yang Liu, Ronggao Liu, and Rong Shang
Earth Syst. Sci. Data, 14, 4505–4523, https://doi.org/10.5194/essd-14-4505-2022, https://doi.org/10.5194/essd-14-4505-2022, 2022
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Surface water has been changing significantly with high seasonal variation and abrupt change, making it hard to capture its interannual trend. Here we generated a global annual surface water cover frequency dataset during 2000–2020. The percentage of the time period when a pixel is covered by water in a year was estimated to describe the seasonal dynamics of surface water. This dataset can be used to analyze the interannual variation and change trend of highly dynamic inland water extent.
Jing M. Chen, Rong Wang, Yihong Liu, Liming He, Holly Croft, Xiangzhong Luo, Han Wang, Nicholas G. Smith, Trevor F. Keenan, I. Colin Prentice, Yongguang Zhang, Weimin Ju, and Ning Dong
Earth Syst. Sci. Data, 14, 4077–4093, https://doi.org/10.5194/essd-14-4077-2022, https://doi.org/10.5194/essd-14-4077-2022, 2022
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Green leaves contain chlorophyll pigments that harvest light for photosynthesis and also emit chlorophyll fluorescence as a byproduct. Both chlorophyll pigments and fluorescence can be measured by Earth-orbiting satellite sensors. Here we demonstrate that leaf photosynthetic capacity can be reliably derived globally using these measurements. This new satellite-based information overcomes a bottleneck in global ecological research where such spatially explicit information is currently lacking.
Fei Jiang, Weimin Ju, Wei He, Mousong Wu, Hengmao Wang, Jun Wang, Mengwei Jia, Shuzhuang Feng, Lingyu Zhang, and Jing M. Chen
Earth Syst. Sci. Data, 14, 3013–3037, https://doi.org/10.5194/essd-14-3013-2022, https://doi.org/10.5194/essd-14-3013-2022, 2022
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A 10-year (2010–2019) global monthly terrestrial NEE dataset (GCAS2021) was inferred from the GOSAT ACOS v9 XCO2 product. It shows strong carbon sinks over eastern N. America, the Amazon, the Congo Basin, Europe, boreal forests, southern China, and Southeast Asia. It has good quality and can reflect the impacts of extreme climates and large-scale climate anomalies on carbon fluxes well. We believe that this dataset can contribute to regional carbon budget assessment and carbon dynamics research.
Fei Jiang, Hengmao Wang, Jing M. Chen, Weimin Ju, Xiangjun Tian, Shuzhuang Feng, Guicai Li, Zhuoqi Chen, Shupeng Zhang, Xuehe Lu, Jane Liu, Haikun Wang, Jun Wang, Wei He, and Mousong Wu
Atmos. Chem. Phys., 21, 1963–1985, https://doi.org/10.5194/acp-21-1963-2021, https://doi.org/10.5194/acp-21-1963-2021, 2021
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We present a 6-year inversion from 2010 to 2015 for the global and regional carbon fluxes using only the GOSAT XCO2 retrievals. We find that the XCO2 retrievals could significantly improve the modeling of atmospheric CO2 concentrations and that the inferred interannual variations in the terrestrial carbon fluxes in most land regions have a better relationship with the changes in severe drought area or leaf area index, or are more consistent with the previous estimates about drought impact.
Yi Zheng, Ruoque Shen, Yawen Wang, Xiangqian Li, Shuguang Liu, Shunlin Liang, Jing M. Chen, Weimin Ju, Li Zhang, and Wenping Yuan
Earth Syst. Sci. Data, 12, 2725–2746, https://doi.org/10.5194/essd-12-2725-2020, https://doi.org/10.5194/essd-12-2725-2020, 2020
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Accurately reproducing the interannual variations in vegetation gross primary production (GPP) is a major challenge. A global GPP dataset was generated by integrating the regulations of several major environmental variables with long-term changes. The dataset can effectively reproduce the spatial, seasonal, and particularly interannual variations in global GPP. Our study will contribute to accurate carbon flux estimates at long timescales.
Hengmao Wang, Fei Jiang, Jun Wang, Weimin Ju, and Jing M. Chen
Atmos. Chem. Phys., 19, 12067–12082, https://doi.org/10.5194/acp-19-12067-2019, https://doi.org/10.5194/acp-19-12067-2019, 2019
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The differences in inverted global and regional carbon fluxes from GOSAT and OCO-2 XCO2 from 1 January to 31 December 2015 are studied. We find significant differences for inverted terrestrial carbon fluxes on both global and regional scales. Overall, GOSAT XCO2 has a better performance than OCO-2, and GOSAT data can effectively improve carbon flux estimates in the Northern Hemisphere, while OCO-2 data, with the specific version used in this study, show only slight improvement.
Zhiwei Xu, Guirui Yu, Qiufeng Wang, Xinyu Zhang, Ruili Wang, Ning Zhao, Nianpeng He, and Ziping Liu
Biogeosciences, 16, 3333–3349, https://doi.org/10.5194/bg-16-3333-2019, https://doi.org/10.5194/bg-16-3333-2019, 2019
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Plant functional traits have increasingly been studied as determinants of ecosystem properties. While the relationships between biological community structures and ecological functions remain poorly understood at the large scale, we found that there was considerable variation in the profiles of different substrate uses along the NSTEC. The soil silt content and plant functional traits together shaped the biogeographical pattern of the soil microbial substrate use.
Xiaojin Qian, Liangyun Liu, Holly Croft, and Jingming Chen
Biogeosciences Discuss., https://doi.org/10.5194/bg-2019-228, https://doi.org/10.5194/bg-2019-228, 2019
Preprint withdrawn
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The leaf maximum carboxylation rate (Vcmax) is a key photosynthesis parameter. We attempt to investigate whether a universal and stable relationship exists between leaf Vcmax25 and chlorophyll content across different C3 plant types from a plant physiological perspective and verify it using field experiments. The results confirm that leaf chlorophyll can be a reliable proxy for estimating Vcmax25, providing an operational approach for the global mapping of Vcmax25 across different plant types.
Jun Wang, Ning Zeng, Meirong Wang, Fei Jiang, Jingming Chen, Pierre Friedlingstein, Atul K. Jain, Ziqiang Jiang, Weimin Ju, Sebastian Lienert, Julia Nabel, Stephen Sitch, Nicolas Viovy, Hengmao Wang, and Andrew J. Wiltshire
Atmos. Chem. Phys., 18, 10333–10345, https://doi.org/10.5194/acp-18-10333-2018, https://doi.org/10.5194/acp-18-10333-2018, 2018
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Based on the Mauna Loa CO2 records and TRENDY multi-model historical simulations, we investigate the different impacts of EP and CP El Niños on interannual carbon cycle variability. Composite analysis indicates that the evolutions of CO2 growth rate anomalies have three clear differences in terms of precursors (negative and neutral), amplitudes (strong and weak), and durations of peak (Dec–Apr and Oct–Jan) during EP and CP El Niños, respectively. We further discuss their terrestrial mechanisms.
Xiaoli Ren, Honglin He, Li Zhang, and Guirui Yu
Earth Syst. Sci. Data, 10, 1217–1226, https://doi.org/10.5194/essd-10-1217-2018, https://doi.org/10.5194/essd-10-1217-2018, 2018
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A spatial radiation dataset of China from 1981 to 2010, including global radiation, diffuse radiation, photosynthetically active radiation (PAR), and diffuse PAR, is generated and shared based on several estimation models and observations of the China Meteorology Administration and the Chinese Ecosystem Research Network. This is an integral and consistent radiation dataset for ecological modeling and the analysis of the effects of diffuse radiation on terrestrial ecosystem productivity.
Zhiwei Xu, Guirui Yu, Xinyu Zhang, Nianpeng He, Qiufeng Wang, Shengzhong Wang, Xiaofeng Xu, Ruili Wang, and Ning Zhao
Biogeosciences, 15, 1217–1228, https://doi.org/10.5194/bg-15-1217-2018, https://doi.org/10.5194/bg-15-1217-2018, 2018
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Forest types with specific soil conditions supported the development of distinct soil microbial communities with variable functions. Our results indicate that the main controls on soil microbes and functions vary across forest ecosystems in different climatic zones. This information will add value to the modeling of microbial processes and will contribute to carbon cycling on a large scale.
Yang Liu, Ronggao Liu, Jan Pisek, and Jing M. Chen
Biogeosciences, 14, 1093–1110, https://doi.org/10.5194/bg-14-1093-2017, https://doi.org/10.5194/bg-14-1093-2017, 2017
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Forest overstory and understory layers differ in carbon and water cycle regimes and phenology, as well as ecosystem functions. In this paper, overstory and understory LAI values were estimated separately for global needleleaf and deciduous broadleaf forests. This work would help us better understand the seasonal patterns of forest structure, evaluate the ecosystem functions and improve the modeling of the forest carbon and water cycles.
S. Zhang, X. Zheng, J. M. Chen, Z. Chen, B. Dan, X. Yi, L. Wang, and G. Wu
Geosci. Model Dev., 8, 805–816, https://doi.org/10.5194/gmd-8-805-2015, https://doi.org/10.5194/gmd-8-805-2015, 2015
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A Global Carbon Assimilation System based on the Ensemble Kalman filter (GCAS-EK) is developed for assimilating atmospheric CO2 data into an ecosystem model to simultaneously estimate the surface carbon fluxes and atmospheric CO2 distribution. This assimilation approach is similar to CarbonTracker, but with several new developments. The results showed that this assimilation approach can effectively reduce the biases and uncertainties of the carbon fluxes simulated by the ecosystem model.
H. Zheng, Y. Li, J. M. Chen, T. Wang, Q. Huang, W. X. Huang, L. H. Wang, S. M. Li, W. P. Yuan, X. Zheng, S. P. Zhang, Z. Q. Chen, and F. Jiang
Biogeosciences, 12, 1131–1150, https://doi.org/10.5194/bg-12-1131-2015, https://doi.org/10.5194/bg-12-1131-2015, 2015
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Ecological models often suffer from substantial biases due to inaccurate simulations of complex ecological processes. We introduce a set of scaling factors (parameters) for an ecological model on the basis of plant functional type (PFT) and latitudes. A global carbon assimilation system (GCAS-DOM) is developed by employing a dual optimization method (DOM) to invert the time-dependent ecological model parameter state and the net carbon flux state on 1 degree grid cells simultaneously.
F. Jiang, H. M. Wang, J. M. Chen, T. Machida, L. X. Zhou, W. M. Ju, H. Matsueda, and Y. Sawa
Atmos. Chem. Phys., 14, 10133–10144, https://doi.org/10.5194/acp-14-10133-2014, https://doi.org/10.5194/acp-14-10133-2014, 2014
M. Liu, H. Wang, H. Wang, T. Oda, Y. Zhao, X. Yang, R. Zang, B. Zang, J. Bi, and J. Chen
Atmos. Chem. Phys., 13, 10873–10882, https://doi.org/10.5194/acp-13-10873-2013, https://doi.org/10.5194/acp-13-10873-2013, 2013
F. Jiang, H. W. Wang, J. M. Chen, L. X. Zhou, W. M. Ju, A. J. Ding, L. X. Liu, and W. Peters
Biogeosciences, 10, 5311–5324, https://doi.org/10.5194/bg-10-5311-2013, https://doi.org/10.5194/bg-10-5311-2013, 2013
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Field heterogeneity of soil texture controls leaf water potential spatial distribution in non-irrigated vineyards
Remote sensing reveals fire-driven enhancement of a C4 invasive alien grass on a small Mediterranean volcanic island
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Synergistic use of Sentinel-2 and UAV-derived data for plant fractional cover distribution mapping of coastal meadows with digital elevation models
Data-based investigation of the effects of canopy structure and shadows on chlorophyll fluorescence in a deciduous oak forest
Reviews and syntheses: Remotely sensed optical time series for monitoring vegetation productivity
Geographically divergent trends in snow disappearance timing and fire ignitions across boreal North America
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Louis Delval, Jordan Bates, François Jonard, and Mathieu Javaux
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The accurate quantification of grapevine water status is crucial for winemakers as it significantly impacts wine quality. It is acknowledged that within a single vineyard, the variability of grapevine water status can be significant. Within-field spatial distribution of soil hydraulic conductance and weather conditions are the primary factors governing the leaf water potential spatial heterogeneity and extent observed in non-irrigated vineyards, and their effects are concomitants.
Riccardo Guarino, Daniele Cerra, Renzo Zaia, Alessandro Chiarucci, Pietro Lo Cascio, Duccio Rocchini, Piero Zannini, and Salvatore Pasta
Biogeosciences, 21, 2717–2730, https://doi.org/10.5194/bg-21-2717-2024, https://doi.org/10.5194/bg-21-2717-2024, 2024
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The severity and the extent of a large fire event that occurred on the small volcanic island of Stromboli (Aeolian archipelago, Italy) on 25–26 May 2022 were evaluated through remotely sensed data to assess the short-term effect of fire on local plant communities. For the first time, we documented the outstanding after-fire resilience of an invasive alien species, Saccharum biflorum, which is a rhizomatous C4 perennial grass introduced on the island in the nineteenth century.
Surendra Shrestha, Christopher A. Williams, Brendan M. Rogers, John Rogan, and Dominik Kulakowski
Biogeosciences, 21, 2207–2226, https://doi.org/10.5194/bg-21-2207-2024, https://doi.org/10.5194/bg-21-2207-2024, 2024
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Ricardo Martínez Prentice, Miguel Villoslada, Raymond D. Ward, Thaisa F. Bergamo, Chris B. Joyce, and Kalev Sepp
Biogeosciences, 21, 1411–1431, https://doi.org/10.5194/bg-21-1411-2024, https://doi.org/10.5194/bg-21-1411-2024, 2024
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Despite hosting a wide range of ecosystem services, coastal wetlands face threats from global changes. This study models the plant fractional cover of plant communities in Estonian coastal meadows with a synergistic use of drone, satellite imagery and digital elevation models. This approach highlights the significant contribution of digital elevation models to multispectral data, enabling the modelling of heterogeneous plant community distributions in such wetlands.
Hamadou Balde, Gabriel Hmimina, Yves Goulas, Gwendal Latouche, Abderrahmane Ounis, and Kamel Soudani
Biogeosciences, 21, 1259–1276, https://doi.org/10.5194/bg-21-1259-2024, https://doi.org/10.5194/bg-21-1259-2024, 2024
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Lammert Kooistra, Katja Berger, Benjamin Brede, Lukas Valentin Graf, Helge Aasen, Jean-Louis Roujean, Miriam Machwitz, Martin Schlerf, Clement Atzberger, Egor Prikaziuk, Dessislava Ganeva, Enrico Tomelleri, Holly Croft, Pablo Reyes Muñoz, Virginia Garcia Millan, Roshanak Darvishzadeh, Gerbrand Koren, Ittai Herrmann, Offer Rozenstein, Santiago Belda, Miina Rautiainen, Stein Rune Karlsen, Cláudio Figueira Silva, Sofia Cerasoli, Jon Pierre, Emine Tanır Kayıkçı, Andrej Halabuk, Esra Tunc Gormus, Frank Fluit, Zhanzhang Cai, Marlena Kycko, Thomas Udelhoven, and Jochem Verrelst
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Biogeosciences, 20, 3803–3825, https://doi.org/10.5194/bg-20-3803-2023, https://doi.org/10.5194/bg-20-3803-2023, 2023
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Arthur Bayle, Bradley Z. Carlson, Anaïs Zimmer, Sophie Vallée, Antoine Rabatel, Edoardo Cremonese, Gianluca Filippa, Cédric Dentant, Christophe Randin, Andrea Mainetti, Erwan Roussel, Simon Gascoin, Dov Corenblit, and Philippe Choler
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Short summary
The amount of carbon that forests gain from the atmosphere, called net primary productivity (NPP), changes a lot with age. These forest NPP–age relationships could be modeled from field survey data, but we are not sure which model works best. Here we tested five different models using 3121 field survey samples in China, and the semi-empirical mathematical (SEM) function was determined as the optimal. The relationships built by SEM can improve China's forest carbon modeling and prediction.
The amount of carbon that forests gain from the atmosphere, called net primary productivity...
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