Articles | Volume 13, issue 12
https://doi.org/10.5194/essd-13-5831-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-13-5831-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Global patterns and drivers of soil total phosphorus concentration
Xianjin He
Key Laboratory of the Three Gorges Reservoir Region's Eco-Environment, Ministry of Education, Chongqing University, Chongqing, 400045, China
Key Laboratory of Vegetation Restoration and Management of Degraded
Ecosystems, South China Botanical Garden, Chinese Academy of Sciences,
Guangzhou, 510650, China
Laurent Augusto
ISPA, Bordeaux Sciences Agro, INRAE, 33140 Villenave-d'Ornon, France
Daniel S. Goll
Laboratoire des Sciences du Climat et de l'Environnement, CEA-CNRS-UVSQ-Université Paris-Saclay, 91191 Gif-sur-Yvette, France
Bruno Ringeval
ISPA, Bordeaux Sciences Agro, INRAE, 33140 Villenave-d'Ornon, France
Yingping Wang
CSIRO Oceans and Atmosphere, Aspendale, Vic, Australia
Julian Helfenstein
Agroscope, 8046 Zurich, Switzerland
Yuanyuan Huang
Laboratoire des Sciences du Climat et de l'Environnement, CEA-CNRS-UVSQ-Université Paris-Saclay, 91191 Gif-sur-Yvette, France
CSIRO Oceans and Atmosphere, Aspendale, Vic, Australia
Kailiang Yu
High Meadows Environmental Institute, Princeton University, Princeton, NJ 08544, USA
Zhiqiang Wang
Sichuan Zoige Alpine Wetland Ecosystem National Observation and Research Station, Southwest Minzu University, Chengdu, 610041, China
Institute of Qinghai-Tibetan Plateau, Southwest Minzu University, Chengdu, 610041, China
Yongchuan Yang
CORRESPONDING AUTHOR
Key Laboratory of the Three Gorges Reservoir Region's Eco-Environment, Ministry of Education, Chongqing University, Chongqing, 400045, China
Key Laboratory of Vegetation Restoration and Management of Degraded
Ecosystems, South China Botanical Garden, Chinese Academy of Sciences,
Guangzhou, 510650, China
Related authors
Xianjin He, Laurent Augusto, Daniel S. Goll, Bruno Ringeval, Ying-Ping Wang, Julian Helfenstein, Yuanyuan Huang, and Enqing Hou
Biogeosciences, 20, 4147–4163, https://doi.org/10.5194/bg-20-4147-2023, https://doi.org/10.5194/bg-20-4147-2023, 2023
Short summary
Short summary
We identified total soil P concentration as the most important predictor of all soil P pool concentrations, except for primary mineral P concentration, which is primarily controlled by soil pH and only secondarily by total soil P concentration. We predicted soil P pools’ distributions in natural systems, which can inform assessments of the role of natural P availability for ecosystem productivity, climate change mitigation, and the functioning of the Earth system.
Kailiang Yu, Johan van den Hoogen, Zhiqiang Wang, Colin Averill, Devin Routh, Gabriel Reuben Smith, Rebecca E. Drenovsky, Kate M. Scow, Fei Mo, Mark P. Waldrop, Yuanhe Yang, Weize Tang, Franciska T. De Vries, Richard D. Bardgett, Peter Manning, Felipe Bastida, Sara G. Baer, Elizabeth M. Bach, Carlos García, Qingkui Wang, Linna Ma, Baodong Chen, Xianjing He, Sven Teurlincx, Amber Heijboer, James A. Bradley, and Thomas W. Crowther
Earth Syst. Sci. Data, 14, 4339–4350, https://doi.org/10.5194/essd-14-4339-2022, https://doi.org/10.5194/essd-14-4339-2022, 2022
Short summary
Short summary
We used a global-scale dataset for the surface topsoil (>3000 distinct observations of abundance of soil fungi versus bacteria) to generate the first quantitative map of soil fungal proportion across terrestrial ecosystems. We reveal striking latitudinal trends. Fungi dominated in regions with low mean annual temperature (MAT) and net primary productivity (NPP) and bacteria dominated in regions with high MAT and NPP.
Lei Zhu, Philippe Ciais, Yitong Yao, Daniel Goll, Sebastiaan Luyssaert, Isabel Martínez Cano, Arthur Fendrich, Laurent Li, Hui Yang, Sassan Saatchi, and Wei Li
Geosci. Model Dev., 18, 4915–4933, https://doi.org/10.5194/gmd-18-4915-2025, https://doi.org/10.5194/gmd-18-4915-2025, 2025
Short summary
Short summary
This study enhances the accuracy of modeling the carbon dynamics of the Amazon rainforest by optimizing key model parameters based on satellite data. Using spatially varying parameters for tree mortality and photosynthesis, we improved predictions of biomass, productivity, and tree mortality. Our findings highlight the critical role of wood density and water availability in forest processes, offering insights to use in refining global carbon cycle models.
Ke Yu, Yang Su, Ronny Lauerwald, Philippe Ciais, Yi Xi, Haoran Xu, Xianglin Zhang, Nicolas Viovy, Amie Pickering, Marie Collard, and Daniel S. Goll
EGUsphere, https://doi.org/10.5194/egusphere-2025-1861, https://doi.org/10.5194/egusphere-2025-1861, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
Coupling crop and land surface models helps quantify the climate effects of agriculture, but lacks crop-specific management processes. We enhanced a land surface model with time-varying albedo from foliar yellowing and residue cover, improving the simulation of energy and water fluxes. Results show cooler surfaces and slightly wetter soils during residue cover, highlighting how managements improve climate mitigation and adaptation, advancing the development of climate-smart agriculture.
Lingfei Wang, Gab Abramowitz, Ying-Ping Wang, Andy Pitman, Philippe Ciais, and Daniel S. Goll
EGUsphere, https://doi.org/10.5194/egusphere-2025-2545, https://doi.org/10.5194/egusphere-2025-2545, 2025
This preprint is open for discussion and under review for Biogeosciences (BG).
Short summary
Short summary
Accurate estimates of global soil organic carbon (SOC) content and its spatial pattern are critical for future climate change mitigation. However, the most advanced mechanistic SOC models struggle to do this task. Here we apply multiple explainable machine learning methods to identify missing variables and misrepresented relationships between environmental factors and SOC in these models, offering new insights to guide model development for more reliable SOC predictions.
Jianghao Tan, Muhammed Mustapha Ibrahim, Huiying Lin, Zhaofeng Chang, Conghui Guo, Zhimin Li, Xianzhen Luo, Yongbiao Lin, and Enqing Hou
EGUsphere, https://doi.org/10.5194/egusphere-2025-310, https://doi.org/10.5194/egusphere-2025-310, 2025
Preprint archived
Short summary
Short summary
Controlled experiments show that adding phosphorus (P) to soils relieves microbial P limitation to degrade soil organic carbon (SOC). No alternative explanation currently exists. We show increased desorption of OC with P supply in subtropical forests, which was used to satisfy microbial C-limitation induced while incorporating P into microbial biomass, and driving CO2 emission, without further SOC degradation. We provide newer an alternative mechanism vital for constraining land C models.
Yi Xi, Philippe Ciais, Dan Zhu, Chunjing Qiu, Yuan Zhang, Shushi Peng, Gustaf Hugelius, Simon P. K. Bowring, Daniel S. Goll, and Ying-Ping Wang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-206, https://doi.org/10.5194/gmd-2024-206, 2025
Revised manuscript accepted for GMD
Short summary
Short summary
Including high-latitude deep carbon is critical for projecting future soil carbon emissions, yet it’s absent in most land surface models. Here we propose a new carbon accumulation protocol by integrating deep carbon from Yedoma deposits and representing the observed history of peat carbon formation in ORCHIDEE-MICT. Our results show an additional 157 PgC in present-day Yedoma deposits and a 1–5 m shallower peat depth, 43 % less passive soil carbon in peatlands against the convention protocol.
Thi Lan Anh Dinh, Daniel Goll, Philippe Ciais, and Ronny Lauerwald
Geosci. Model Dev., 17, 6725–6744, https://doi.org/10.5194/gmd-17-6725-2024, https://doi.org/10.5194/gmd-17-6725-2024, 2024
Short summary
Short summary
The study assesses the performance of the dynamic global vegetation model (DGVM) ORCHIDEE in capturing the impact of land-use change on carbon stocks across Europe. Comparisons with observations reveal that the model accurately represents carbon fluxes and stocks. Despite the underestimations in certain land-use conversions, the model describes general trends in soil carbon response to land-use change, aligning with the site observations.
Lingfei Wang, Gab Abramowitz, Ying-Ping Wang, Andy Pitman, and Raphael A. Viscarra Rossel
SOIL, 10, 619–636, https://doi.org/10.5194/soil-10-619-2024, https://doi.org/10.5194/soil-10-619-2024, 2024
Short summary
Short summary
Effective management of soil organic carbon (SOC) requires accurate knowledge of its distribution and factors influencing its dynamics. We identify the importance of variables in spatial SOC variation and estimate SOC stocks in Australia using various models. We find there are significant disparities in SOC estimates when different models are used, highlighting the need for a critical re-evaluation of land management strategies that rely on the SOC distribution derived from a single approach.
Mengjie Han, Qing Zhao, Xili Wang, Ying-Ping Wang, Philippe Ciais, Haicheng Zhang, Daniel S. Goll, Lei Zhu, Zhe Zhao, Zhixuan Guo, Chen Wang, Wei Zhuang, Fengchang Wu, and Wei Li
Geosci. Model Dev., 17, 4871–4890, https://doi.org/10.5194/gmd-17-4871-2024, https://doi.org/10.5194/gmd-17-4871-2024, 2024
Short summary
Short summary
The impact of biochar (BC) on soil organic carbon (SOC) dynamics is not represented in most land carbon models used for assessing land-based climate change mitigation. Our study develops a BC model that incorporates our current understanding of BC effects on SOC based on a soil carbon model (MIMICS). The BC model can reproduce the SOC changes after adding BC, providing a useful tool to couple dynamic land models to evaluate the effectiveness of BC application for CO2 removal from the atmosphere.
Xianjin He, Laurent Augusto, Daniel S. Goll, Bruno Ringeval, Ying-Ping Wang, Julian Helfenstein, Yuanyuan Huang, and Enqing Hou
Biogeosciences, 20, 4147–4163, https://doi.org/10.5194/bg-20-4147-2023, https://doi.org/10.5194/bg-20-4147-2023, 2023
Short summary
Short summary
We identified total soil P concentration as the most important predictor of all soil P pool concentrations, except for primary mineral P concentration, which is primarily controlled by soil pH and only secondarily by total soil P concentration. We predicted soil P pools’ distributions in natural systems, which can inform assessments of the role of natural P availability for ecosystem productivity, climate change mitigation, and the functioning of the Earth system.
Yongzhe Chen, Xiaoming Feng, Bojie Fu, Haozhi Ma, Constantin M. Zohner, Thomas W. Crowther, Yuanyuan Huang, Xutong Wu, and Fangli Wei
Earth Syst. Sci. Data, 15, 897–910, https://doi.org/10.5194/essd-15-897-2023, https://doi.org/10.5194/essd-15-897-2023, 2023
Short summary
Short summary
This study presented a long-term (2002–2021) above- and belowground biomass dataset for woody vegetation in China at 1 km resolution. It was produced by combining various types of remote sensing observations with adequate plot measurements. Over 2002–2021, China’s woody biomass increased at a high rate, especially in the central and southern parts. This dataset can be applied to evaluate forest carbon sinks across China and the efficiency of ecological restoration programs in China.
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.
Yuan Zhang, Devaraju Narayanappa, Philippe Ciais, Wei Li, Daniel Goll, Nicolas Vuichard, Martin G. De Kauwe, Laurent Li, and Fabienne Maignan
Geosci. Model Dev., 15, 9111–9125, https://doi.org/10.5194/gmd-15-9111-2022, https://doi.org/10.5194/gmd-15-9111-2022, 2022
Short summary
Short summary
There are a few studies to examine if current models correctly represented the complex processes of transpiration. Here, we use a coefficient Ω, which indicates if transpiration is mainly controlled by vegetation processes or by turbulence, to evaluate the ORCHIDEE model. We found a good performance of ORCHIDEE, but due to compensation of biases in different processes, we also identified how different factors control Ω and where the model is wrong. Our method is generic to evaluate other models.
Kailiang Yu, Johan van den Hoogen, Zhiqiang Wang, Colin Averill, Devin Routh, Gabriel Reuben Smith, Rebecca E. Drenovsky, Kate M. Scow, Fei Mo, Mark P. Waldrop, Yuanhe Yang, Weize Tang, Franciska T. De Vries, Richard D. Bardgett, Peter Manning, Felipe Bastida, Sara G. Baer, Elizabeth M. Bach, Carlos García, Qingkui Wang, Linna Ma, Baodong Chen, Xianjing He, Sven Teurlincx, Amber Heijboer, James A. Bradley, and Thomas W. Crowther
Earth Syst. Sci. Data, 14, 4339–4350, https://doi.org/10.5194/essd-14-4339-2022, https://doi.org/10.5194/essd-14-4339-2022, 2022
Short summary
Short summary
We used a global-scale dataset for the surface topsoil (>3000 distinct observations of abundance of soil fungi versus bacteria) to generate the first quantitative map of soil fungal proportion across terrestrial ecosystems. We reveal striking latitudinal trends. Fungi dominated in regions with low mean annual temperature (MAT) and net primary productivity (NPP) and bacteria dominated in regions with high MAT and NPP.
Shuang Ma, Lifen Jiang, Rachel M. Wilson, Jeff P. Chanton, Scott Bridgham, Shuli Niu, Colleen M. Iversen, Avni Malhotra, Jiang Jiang, Xingjie Lu, Yuanyuan Huang, Jason Keller, Xiaofeng Xu, Daniel M. Ricciuto, Paul J. Hanson, and Yiqi Luo
Biogeosciences, 19, 2245–2262, https://doi.org/10.5194/bg-19-2245-2022, https://doi.org/10.5194/bg-19-2245-2022, 2022
Short summary
Short summary
The relative ratio of wetland methane (CH4) emission pathways determines how much CH4 is oxidized before leaving the soil. We found an ebullition modeling approach that has a better performance in deep layer pore water CH4 concentration. We suggest using this approach in land surface models to accurately represent CH4 emission dynamics and response to climate change. Our results also highlight that both CH4 flux and belowground concentration data are important to constrain model parameters.
Zhu Deng, Philippe Ciais, Zitely A. Tzompa-Sosa, Marielle Saunois, Chunjing Qiu, Chang Tan, Taochun Sun, Piyu Ke, Yanan Cui, Katsumasa Tanaka, Xin Lin, Rona L. Thompson, Hanqin Tian, Yuanzhi Yao, Yuanyuan Huang, Ronny Lauerwald, Atul K. Jain, Xiaoming Xu, Ana Bastos, Stephen Sitch, Paul I. Palmer, Thomas Lauvaux, Alexandre d'Aspremont, Clément Giron, Antoine Benoit, Benjamin Poulter, Jinfeng Chang, Ana Maria Roxana Petrescu, Steven J. Davis, Zhu Liu, Giacomo Grassi, Clément Albergel, Francesco N. Tubiello, Lucia Perugini, Wouter Peters, and Frédéric Chevallier
Earth Syst. Sci. Data, 14, 1639–1675, https://doi.org/10.5194/essd-14-1639-2022, https://doi.org/10.5194/essd-14-1639-2022, 2022
Short summary
Short summary
In support of the global stocktake of the Paris Agreement on climate change, we proposed a method for reconciling the results of global atmospheric inversions with data from UNFCCC national greenhouse gas inventories (NGHGIs). Here, based on a new global harmonized database that we compiled from the UNFCCC NGHGIs and a comprehensive framework presented in this study to process the results of inversions, we compared their results of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O).
Lina Teckentrup, Martin G. De Kauwe, Andrew J. Pitman, Daniel S. Goll, Vanessa Haverd, Atul K. Jain, Emilie Joetzjer, Etsushi Kato, Sebastian Lienert, Danica Lombardozzi, Patrick C. McGuire, Joe R. Melton, Julia E. M. S. Nabel, Julia Pongratz, Stephen Sitch, Anthony P. Walker, and Sönke Zaehle
Biogeosciences, 18, 5639–5668, https://doi.org/10.5194/bg-18-5639-2021, https://doi.org/10.5194/bg-18-5639-2021, 2021
Short summary
Short summary
The Australian continent is included in global assessments of the carbon cycle such as the global carbon budget, yet the performance of dynamic global vegetation models (DGVMs) over Australia has rarely been evaluated. We assessed simulations by an ensemble of dynamic global vegetation models over Australia and highlighted a number of key areas that lead to model divergence on both short (inter-annual) and long (decadal) timescales.
Juhwan Lee, Raphael A. Viscarra Rossel, Mingxi Zhang, Zhongkui Luo, and Ying-Ping Wang
Biogeosciences, 18, 5185–5202, https://doi.org/10.5194/bg-18-5185-2021, https://doi.org/10.5194/bg-18-5185-2021, 2021
Short summary
Short summary
We performed Roth C simulations across Australia and assessed the response of soil carbon to changing inputs and future climate change using a consistent modelling framework. Site-specific initialisation of the C pools with measurements of the C fractions is essential for accurate simulations of soil organic C stocks and composition at a large scale. With further warming, Australian soils will become more vulnerable to C loss: natural environments > native grazing > cropping > modified grazing.
Alexander J. Winkler, Ranga B. Myneni, Alexis Hannart, Stephen Sitch, Vanessa Haverd, Danica Lombardozzi, Vivek K. Arora, Julia Pongratz, Julia E. M. S. Nabel, Daniel S. Goll, Etsushi Kato, Hanqin Tian, Almut Arneth, Pierre Friedlingstein, Atul K. Jain, Sönke Zaehle, and Victor Brovkin
Biogeosciences, 18, 4985–5010, https://doi.org/10.5194/bg-18-4985-2021, https://doi.org/10.5194/bg-18-4985-2021, 2021
Short summary
Short summary
Satellite observations since the early 1980s show that Earth's greening trend is slowing down and that browning clusters have been emerging, especially in the last 2 decades. A collection of model simulations in conjunction with causal theory points at climatic changes as a key driver of vegetation changes in natural ecosystems. Most models underestimate the observed vegetation browning, especially in tropical rainforests, which could be due to an excessive CO2 fertilization effect in models.
Yuanyuan Huang, Phillipe Ciais, Maurizio Santoro, David Makowski, Jerome Chave, Dmitry Schepaschenko, Rose Z. Abramoff, Daniel S. Goll, Hui Yang, Ye Chen, Wei Wei, and Shilong Piao
Earth Syst. Sci. Data, 13, 4263–4274, https://doi.org/10.5194/essd-13-4263-2021, https://doi.org/10.5194/essd-13-4263-2021, 2021
Short summary
Short summary
Roots play a key role in our Earth system. Here we combine 10 307 field measurements of forest root biomass worldwide with global observations of forest structure, climatic conditions, topography, land management and soil characteristics to derive a spatially explicit global high-resolution (~ 1 km) root biomass dataset. In total, 142 ± 25 (95 % CI) Pg of live dry-matter biomass is stored belowground, representing a global average root : shoot biomass ratio of 0.25 ± 0.10.
Xin Huang, Dan Lu, Daniel M. Ricciuto, Paul J. Hanson, Andrew D. Richardson, Xuehe Lu, Ensheng Weng, Sheng Nie, Lifen Jiang, Enqing Hou, Igor F. Steinmacher, and Yiqi Luo
Geosci. Model Dev., 14, 5217–5238, https://doi.org/10.5194/gmd-14-5217-2021, https://doi.org/10.5194/gmd-14-5217-2021, 2021
Short summary
Short summary
In the data-rich era, data assimilation is widely used to integrate abundant observations into models to reduce uncertainty in ecological forecasting. However, applications of data assimilation are restricted by highly technical requirements. To alleviate this technical burden, we developed a model-independent data assimilation (MIDA) module which is friendly to ecologists with limited programming skills. MIDA also supports a flexible switch of different models or observations in DA analysis.
Elisa Bruni, Bertrand Guenet, Yuanyuan Huang, Hugues Clivot, Iñigo Virto, Roberta Farina, Thomas Kätterer, Philippe Ciais, Manuel Martin, and Claire Chenu
Biogeosciences, 18, 3981–4004, https://doi.org/10.5194/bg-18-3981-2021, https://doi.org/10.5194/bg-18-3981-2021, 2021
Short summary
Short summary
Increasing soil organic carbon (SOC) stocks is beneficial for climate change mitigation and food security. One way to enhance SOC stocks is to increase carbon input to the soil. We estimate the amount of carbon input required to reach a 4 % annual increase in SOC stocks in 14 long-term agricultural experiments around Europe. We found that annual carbon input should increase by 43 % under current temperature conditions, by 54 % for a 1 °C warming scenario and by 120 % for a 5 °C warming scenario.
Wolfgang A. Obermeier, Julia E. M. S. Nabel, Tammas Loughran, Kerstin Hartung, Ana Bastos, Felix Havermann, Peter Anthoni, Almut Arneth, Daniel S. Goll, Sebastian Lienert, Danica Lombardozzi, Sebastiaan Luyssaert, Patrick C. McGuire, Joe R. Melton, Benjamin Poulter, Stephen Sitch, Michael O. Sullivan, Hanqin Tian, Anthony P. Walker, Andrew J. Wiltshire, Soenke Zaehle, and Julia Pongratz
Earth Syst. Dynam., 12, 635–670, https://doi.org/10.5194/esd-12-635-2021, https://doi.org/10.5194/esd-12-635-2021, 2021
Short summary
Short summary
We provide the first spatio-temporally explicit comparison of different model-derived fluxes from land use and land cover changes (fLULCCs) by using the TRENDY v8 dynamic global vegetation models used in the 2019 global carbon budget. We find huge regional fLULCC differences resulting from environmental assumptions, simulated periods, and the timing of land use and land cover changes, and we argue for a method consistent across time and space and for carefully choosing the accounting period.
Zichong Chen, Junjie Liu, Daven K. Henze, Deborah N. Huntzinger, Kelley C. Wells, Stephen Sitch, Pierre Friedlingstein, Emilie Joetzjer, Vladislav Bastrikov, Daniel S. Goll, Vanessa Haverd, Atul K. Jain, Etsushi Kato, Sebastian Lienert, Danica L. Lombardozzi, Patrick C. McGuire, Joe R. Melton, Julia E. M. S. Nabel, Benjamin Poulter, Hanqin Tian, Andrew J. Wiltshire, Sönke Zaehle, and Scot M. Miller
Atmos. Chem. Phys., 21, 6663–6680, https://doi.org/10.5194/acp-21-6663-2021, https://doi.org/10.5194/acp-21-6663-2021, 2021
Short summary
Short summary
NASA's Orbiting Carbon Observatory 2 (OCO-2) satellite observes atmospheric CO2 globally. We use a multiple regression and inverse model to quantify the relationships between OCO-2 and environmental drivers within individual years for 2015–2018 and within seven global biomes. Our results point to limitations of current space-based observations for inferring environmental relationships but also indicate the potential to inform key relationships that are very uncertain in process-based models.
Yan Sun, Daniel S. Goll, Jinfeng Chang, Philippe Ciais, Betrand Guenet, Julian Helfenstein, Yuanyuan Huang, Ronny Lauerwald, Fabienne Maignan, Victoria Naipal, Yilong Wang, Hui Yang, and Haicheng Zhang
Geosci. Model Dev., 14, 1987–2010, https://doi.org/10.5194/gmd-14-1987-2021, https://doi.org/10.5194/gmd-14-1987-2021, 2021
Short summary
Short summary
We evaluated the performance of the nutrient-enabled version of the land surface model ORCHIDEE-CNP v1.2 against remote sensing, ground-based measurement networks and ecological databases. The simulated carbon, nitrogen and phosphorus fluxes among different spatial scales are generally in good agreement with data-driven estimates. However, the recent carbon sink in the Northern Hemisphere is substantially underestimated. Potential causes and model development priorities are discussed.
Bruno Ringeval, Christoph Müller, Thomas A. M. Pugh, Nathaniel D. Mueller, Philippe Ciais, Christian Folberth, Wenfeng Liu, Philippe Debaeke, and Sylvain Pellerin
Geosci. Model Dev., 14, 1639–1656, https://doi.org/10.5194/gmd-14-1639-2021, https://doi.org/10.5194/gmd-14-1639-2021, 2021
Short summary
Short summary
We assess how and why global gridded crop models (GGCMs) differ in their simulation of potential yield. We build a GCCM emulator based on generic formalism and fit its parameters against aboveground biomass and yield at harvest simulated by eight GGCMs. Despite huge differences between GGCMs, we show that the calibration of a few key parameters allows the emulator to reproduce the GGCM simulations. Our simple but mechanistic model could help to improve the global simulation of potential yield.
Erqian Cui, Chenyu Bian, Yiqi Luo, Shuli Niu, Yingping Wang, and Jianyang Xia
Biogeosciences, 17, 6237–6246, https://doi.org/10.5194/bg-17-6237-2020, https://doi.org/10.5194/bg-17-6237-2020, 2020
Short summary
Short summary
Mean annual net ecosystem productivity (NEP) is related to the magnitude of the carbon sink of a specific ecosystem, while its inter-annual variation (IAVNEP) characterizes the stability of such a carbon sink. Thus, a better understanding of the co-varying NEP and IAVNEP is critical for locating the major and stable carbon sinks on land. Based on daily NEP observations from eddy-covariance sites, we found local indicators for the spatially varying NEP and IAVNEP, respectively.
Yuan Zhang, Ana Bastos, Fabienne Maignan, Daniel Goll, Olivier Boucher, Laurent Li, Alessandro Cescatti, Nicolas Vuichard, Xiuzhi Chen, Christof Ammann, M. Altaf Arain, T. Andrew Black, Bogdan Chojnicki, Tomomichi Kato, Ivan Mammarella, Leonardo Montagnani, Olivier Roupsard, Maria J. Sanz, Lukas Siebicke, Marek Urbaniak, Francesco Primo Vaccari, Georg Wohlfahrt, Will Woodgate, and Philippe Ciais
Geosci. Model Dev., 13, 5401–5423, https://doi.org/10.5194/gmd-13-5401-2020, https://doi.org/10.5194/gmd-13-5401-2020, 2020
Short summary
Short summary
We improved the ORCHIDEE LSM by distinguishing diffuse and direct light in canopy and evaluated the new model with observations from 159 sites. Compared with the old model, the new model has better sunny GPP and reproduced the diffuse light fertilization effect observed at flux sites. Our simulations also indicate different mechanisms causing the observed GPP enhancement under cloudy conditions at different times. The new model has the potential to study large-scale impacts of aerosol changes.
Cited articles
Achat, D. L., Augusto, L., Gallet-Budynek, A., and Loustau, D.: Future challenges in coupled C-N-P cycle models for terrestrial ecosystems under global change: a review, Biogeochemistry, 131, 173–202, https://doi.org/10.1007/s10533-016-0274-9, 2016a.
Achat, D. L., Pousse, N., Nicolas, M., Brédoire, F., and Augusto, L.: Soil
properties controlling inorganic phosphorus availability: general results
from a national forest network and a global compilation of the literature,
Biogeochemistry, 127, 255–272, https://doi.org/10.1007/s10533-015-0178-0,
2016b.
Adams, J., Tipping, E., Thacker, S. A., and Quinton, J. N.: Phosphorus, carbon and nitrogen concentrations in UK soil mineral fractions, 2013–2014, NERC Environmental Information Data Centre, https://doi.org/10.5285/e6e9a85c-b537-4110-899f-2c1498bc826c, 2020.
Alewell, C., Ringeval, B., Ballabio, C., Robinson, D. A., Panagos, P., and
Borrelli, P.: Global phosphorus shortage will be aggravated by soil erosion,
Nat. Commun., 11, 4546, https://doi.org/10.1038/s41467-020-18326-7, 2020.
Amberger, A.: Pflanzenernährung. Ökologische und physiologische
Grundlagen, Dynamik und Stoffwechsel der Nährelemente, 4th edn., Eugen
Ulmer, Stuttgart, Germany, 1996 (in German).
Andersson, H., Bergström, L., Djodjic, F., Ulén, B., and Kirchmann,
H.: Topsoil and Subsoil Properties Influence Phosphorus Leaching from Four
Agricultural Soils, J. Environ. Qual., 42, 455–463, https://doi.org/10.2134/jeq2012.0224, 2013.
Arenberg, M. R. and Arai, Y.: Uncertainties in soil physicochemical factors
controlling phosphorus mineralization and immobilization processes, Adv.
Agron., 154, 153–200, https://doi.org/10.1016/bs.agron.2018.11.005, 2019.
Augusto, L., Bakker, M. R., Morel, C., Meredieu, C., Trichet, P., Badeau, V.,
Arrouays, D., Plassard, C., Achat, D. L., Gallet-Budynek, A., Merzeau, D.,
Canteloup, D., Najar, M., and Ranger, J.: Is “grey literature” a reliable
source of data to characterize soils at the scale of a region? A case study
in a maritime pine forest in southwestern France, Eur. J. Soil Sci., 61,
807–822, https://doi.org/10.1111/j.1365-2389.2010.01286.x, 2010.
Augusto, L., Achat, D. L., Jonard, M., Vidal, D., and Ringeval, B.: Soil
parent material – A major driver of plant nutrient limitations in
terrestrial ecosystems, Glob. Change Biol., 23, 3808–3824, https://doi.org/10.1111/gcb.13691, 2017.
Ballabio, C., Lugato, E., Fernández-Ugalde, O., Orgiazzi, A., Jones, A.,
Borrelli, P., Montanarella, L., and Panagos, P.: Mapping LUCAS topsoil
chemical properties at European scale using Gaussian process regression,
Geoderma, 355, 113912, https://doi.org/10.1016/j.geoderma.2019.113912, 2019.
Baribault, T. W., Kobe, R. K., and Finley, A. O.: Data from: Tropical tree
growth is correlated with soil phosphorus, potassium, and calcium, though
not for legumes, Dryad [data set], https://doi.org/10.5061/dryad.r9p70, 2012.
Beusen, A. H. W., Van Beek, L. P. H., Bouwman, A. F., Mogollón, J. M., and Middelburg, J. J.: Coupling global models for hydrology and nutrient loading to simulate nitrogen and phosphorus retention in surface water – description of IMAGE–GNM and analysis of performance, Geosci. Model Dev., 8, 4045–4067, https://doi.org/10.5194/gmd-8-4045-2015, 2015.
Brédoire, F., Bakker, M. R., Augusto, L., Barsukov, P. A., Derrien, D., Nikitich, P., Rusalimova, O., Zeller, B., and Achat, D. L.: What is the P value of Siberian soils? Soil phosphorus status in south-western Siberia and comparison with a global data set, Biogeosciences, 13, 2493–2509, https://doi.org/10.5194/bg-13-2493-2016, 2016.
Buendía, C., Kleidon, A., and Porporato, A.: The role of tectonic uplift, climate, and vegetation in the long-term terrestrial phosphorous cycle, Biogeosciences, 7, 2025–2038, https://doi.org/10.5194/bg-7-2025-2010, 2010.
Bui, E. N. and Henderson, B. L.: C:N:P stoichiometry in Australian soils with
respect to vegetation and environmental factors, Plant Soil, 373, 553–568,
https://doi.org/10.1007/s11104-013-1823-9, 2013.
Butcher, S. S., Charlson, R. J., Orians, G. H., and Wolfe, G. V.: Global
Biogeochemical Cycles, Academic Press (Harcourt Brace Jovanovich), London, UK, 1992.
Cheng, Y., Li, P., Xu, G., Li, Z., Cheng, S., and Gao, H.: Spatial
distribution of soil total phosphorus in Yingwugou watershed of the Dan
River, China, Catena, 136, 175–181, https://doi.org/10.1016/j.catena.2015.02.015, 2016.
Cheng, Y., Li, P., Xu, G., Li, Z., Yu, K., Cheng, S., Zhao, B., and Wang, F.:
Factors that influence soil total phosphorus sources on dam fields that are
part of ecological construction programs on the Loess Plateau, China,
Catena, 171, 107–114, https://doi.org/10.1016/j.catena.2018.07.006, 2018.
Cleveland, C. C. and Liptzin, D.: C : N : P stoichiometry in soil: is there a “Redfield Ratio” for the microbial biomass?, Biogeochemistry, 85, 235–252, https://doi.org/10.1007/s10533-007-9132-0, 2007.
Cross, A.: Phosphorus Fractions in Grassland and Shrubland Soils at the Sevilleta National Wildlife Refuge, New Mexico (1989) ver 154704, Environmental Data Initiative [data set], https://doi.org/10.6073/pasta/5986a5885f621dd9659da99576341f5b, 2013.
Cross, A. F. and Schlesinger, W. H.: A literature review and evaluation of
the. Hedley fractionation: Applications to the biogeochemical cycle of soil
phosphorus in natural ecosystems, Geoderma, 64, 197–214, https://doi.org/10.1016/0016-7061(94)00023-4, 1995.
Deiss, L., de Moraes, A., and Maire, V.: Environmental drivers of soil phosphorus composition in natural ecosystems, Biogeosciences, 15, 4575–4592, https://doi.org/10.5194/bg-15-4575-2018, 2018.
Delgado-Baquerizo, M., Reich, P. B., Bardgett, R. D., Eldridge, D. J., Lambers,
H., Wardle, D. A., Reed, S. C., Plaza, C., Png, G. K., Neuhauser, S., Berhe,
A. A., Hart, S. C., Hu, H., He, J., Bastida, F., Abades, S., Alfaro, F. D.,
Cutler, N. A., Gallardo, A., García-Velázquez, L., Hayes, P. E.,
Hseu, Z., Pérez, C. A., Santos, F., Siebe, C., Trivedi, P., Sullivan,
B. W., Weber-Grullon, L., Williams, M. A., and Fierer, N.: The influence of
soil age on ecosystem structure and function across biomes, Nat. Commun.,
11, 4721–4721, https://doi.org/10.1038/s41467-020-18451-3, 2020.
Delmas, M., Saby, N., Arrouays, D., Dupas, R., Lemercier, B., Pellerin, S., and Gascuel-Odoux, C.: Explaining and mapping total phosphorus content in
French topsoils, Soil Use Manage, 31, 259–269, https://doi.org/10.1111/sum.12192,
2015.
Deng, Q., McMahon, D. E., Xiang, Y., Yu, C. L., Jackson, R. B., and Hui, D.: A global meta-analysis of soil phosphorus dynamics after afforestation, New
Phytol., 213, 181–192, https://doi.org/10.1111/nph.14119, 2017.
De Schrijver, A., Vesterdal, L., Hansen, K., De Frenne, P., Augusto, L.,
Achat, D. L., Staelens, J., Baeten, L., De Keersmaeker, L., De Neve, S., and
Verheyen, K.: Four decades of post-agricultural forest development have
caused major redistributions of soil phosphorus fractions, Oecologia, 169,
221–234, https://doi.org/10.1007/s00442-011-2185-8, 2012.
Dieter, D., Elsenbeer, H., and Turner, B. L.: Phosphorus fractionation in
lowland tropical rainforest soils in central Panama, Catena, 82, 118–125,
https://doi.org/10.1016/j.catena.2010.05.010, 2010.
Doetterl, S., Stevens, A., Six, J., Merckx, R., Van Oost, K., Casanova
Pinto, M., Casanova-Katny, A., Muñoz, C., Boudin, M., Zagal Venegas, E., and Boeckx, P.: Soil carbon storage controlled by interactions between
geochemistry and climate, Nat. Geosci., 8, 780–783, https://doi.org/10.1038/ngeo2516,
2015.
Dokuchaev, V. V.: The Russian chernozem, Report to the Free Economic Society, Imperial Univ. of St. Petersburg, St. Petersburg, Russia,
1883 (in Russian).
Elser, J. J., Bracken, M. E. S., 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, https://doi.org/10.1111/j.1461-0248.2007.01113.x, 2007.
Fleischer, K., Rammig, A., Kauwe, D. M. G., Walker, A. P., Domingues, T. F.,
Fuchslueger, L., Garcia, S., Goll, D. S., Grandis, A., Jiang, M., Haverd, V.,
Hofhansl, F., Holm, J. A., Kruijt, B., Leung, F., Medlyn, B. E., Mercado,
L. M., Norby, R. J., Pak, B., Randow, V. C., Quesada, C. A., Schaap, K. J.,
Valverde-Barrantes, O. J., Wang, Y. P., Yang, X., Zaehle, S., Zhu, Q., Lapola, D. M., and Oak Ridge National Lab: Amazon forest response to
CO2 fertilization dependent on plant phosphorus acquisition, Nat. Geosci., 12, 736–741, https://doi.org/10.1038/s41561-019-0404-9, 2019.
Gama-Rodrigues, A. C., Sales, M. V. S., Silva, P. S. D., Comerford, N. B.,
Cropper, W. P., and Gama-Rodrigues, E. F.: An exploratory analysis of
phosphorus transformations in tropical soils using structural equation
modeling, Biogeochemistry, 118, 453–469, https://doi.org/10.1007/s10533-013-9946-x,
2014.
Goll, D. S., Brovkin, V., Parida, B. R., Reick, C. H., Kattge, J., Reich, P. B., van Bodegom, P. M., and Niinemets, Ü.: Nutrient limitation reduces land carbon uptake in simulations with a model of combined carbon, nitrogen and phosphorus cycling, Biogeosciences, 9, 3547–3569, https://doi.org/10.5194/bg-9-3547-2012, 2012.
Goll, D. S., Moosdorf, N., Hartmann, J., and Brovkin, V.: Climate-driven
changes in chemical weathering and associated phosphorus release since 1850:
Implications for the land carbon balance, Geophys. Res. Lett., 41,
3553–3558, https://doi.org/10.1002/2014GL059471, 2014.
Goll, D. S., Vuichard, N., Maignan, F., Jornet-Puig, A., Sardans, J., Violette, A., Peng, S., Sun, Y., Kvakic, M., Guimberteau, M., Guenet, B., Zaehle, S., Penuelas, J., Janssens, I., and Ciais, P.: A representation of the phosphorus cycle for ORCHIDEE (revision 4520), Geosci. Model Dev., 10, 3745–3770, https://doi.org/10.5194/gmd-10-3745-2017, 2017.
Hahm, W. J., Riebe, C. S., Lukens, C. E., and Araki, S.: Bedrock composition
regulates mountain ecosystems and landscape evolution, P. Natl. Acad. Sci. USA, 111, 3338–3343, https://doi.org/10.1073/pnas.1315667111, 2014.
He, X., Augusto, L., Goll, D. S., Ringeval, B., Wang, Y., Helfenstein, J., Huang, Y., Yu, K., Wang, Z., Yang, Y., and Hou, E.: Global patterns and drivers of soil total phosphorus concentration, figshare [data set], https://doi.org/10.6084/m9.figshare.14583375, 2021.
Helfenstein, J., Tamburini, F., von Sperber, C., Massey, M. S., Pistocchi,
C., Chadwick, O. A., Vitousek, P. M., Kretzschmar, R., and Frossard, E.:
Combining spectroscopic and isotopic techniques gives a dynamic view of
phosphorus cycling in soil, Nat. Commun., 9, 3226, https://doi.org/10.1038/s41467-018-05731-2, 2018.
Hengl, T., Leenaars, J. G. B., Shepherd, K. D., Walsh, M. G., Heuvelink, G. B. M., Mamo, T., Tilahun, H., Berkhout, E., Cooper, M., Fegraus, E., Wheeler, I., and Kwabena, N. A.: Soil nutrient maps of Sub-Saharan Africa: assessment of soil nutrient content at 250 m spatial resolution using machine learning,
Nutr. Cycl. Agroecosys., 109, 77–102, https://doi.org/10.1007/s10705-017-9870-x, 2017a.
Hengl, T., Mendes, D. J. J., Heuvelink, G. B., Ruiperez, G. M., Kilibarda, M., Blagotic, A., Shangguan, W., Wright, M. N., Geng, X., Bauer-Marschallinger, B., Guevara, M. A., Vargas, R., MacMillan, R. A., Batjes, N. H., Leenaars, J. G., Ribeiro, E., Wheeler, I., Mantel, S., and Kempen, B.: SoilGrids250m: Global gridded soil information based on machine learning, PLoS One, 12, e0169748, https://doi.org/10.1371/journal.pone.0169748, 2017b.
Hou, E., Chen, C., Luo, Y., Zhou, G., Kuang, Y., Zhang, Y., Heenan, M., Lu,
X., and Wen, D.: Effects of climate on soil phosphorus cycle and availability
in natural terrestrial ecosystems, Glob. Change Biol., 24, 3344–3356, https://doi.org/10.1111/gcb.14093, 2018a.
Hou, E., Tan, X., Heenan, M., and Wen, D.: A global dataset of plant
available and unavailable phosphorus in natural soils derived by Hedley
method, Scientific Data, 5, 180166, https://doi.org/10.1038/sdata.2018.166, 2018b.
Hou, E., Luo, Y., Kuang, Y., Chen, C., Lu, X., Jiang, L., Luo, X., and Wen,
D.: Global meta-analysis shows pervasive phosphorus limitation of
aboveground plant production in natural terrestrial ecosystems, Nat.
Commun., 11, 637, https://doi.org/10.1038/s41467-020-14492-w, 2020.
Hou, E., Wen, D., Jiang, L., Luo, X., Kuang, Y., Lu, X., Chen, C., Allen,
K. T., He, X., Huang, X., and Luo, Y.: Latitudinal patterns of terrestrial
phosphorus limitation over the globe, Ecol. Lett., 24, 1420–1431, https://doi.org/10.1111/ele.13761, 2021.
Huston, M. A.: Precipitation, soils, NPP, and biodiversity: resurrection of
Albrecht's curve, Ecol. Monogr., 82, 277–296, https://doi.org/10.1890/11-1927.1, 2012.
Huston, M. A. and Wolverton, S.: The global distribution of net primary
production: resolving the paradox, Ecol. Monogr., 79, 343–377, https://doi.org/10.1890/08-0588.1, 2009.
Jenny, H.: Factors of soil formation; a system of quantitative pedology,
McGraw-Hill, New York, USA, 1941.
Ji, H., Wen, J., Du, B., Sun, N., Berg, B., and Liu, C.: Comparison of the
nutrient resorption stoichiometry of Quercus variabilis Blume growing in two
sites contrasting in soil phosphorus content, Ann. Forest Sci., 75, 59, https://doi.org/10.1007/s13595-018-0727-5, 2018.
Kitayama, K., Majalap-Lee, N., and Aiba, S.: Soil Phosphorus Fractionation
and Phosphorus-Use Efficiencies of Tropical Rainforests along Altitudinal
Gradients of Mount Kinabalu, Borneo, Oecologia, 123, 342–349, https://doi.org/10.1007/s004420051020, 2000.
Kuhn, M.: caret: Classification and Regression Training, R package version
6.0-86, available at: https://github.com/topepo/caret/ (last access: 15 December 2021), 2020.
Li, P., Yang, Y., Han, W., and Fang, J.: Global patterns of soil microbial
nitrogen and phosphorus stoichiometry in forest ecosystems, Global Ecol.
Biogeogr., 23, 979–987, https://doi.org/10.1111/geb.12190, 2014.
Li, X., Li, Y., Peng, S., Chen, Y., and Cao, Y.: Changes in soil phosphorus
and its influencing factors following afforestation in Northern China, Land
Degrad. Dev., 30, 1655–1666, https://doi.org/10.1002/ldr.3345, 2019.
Liaw, A. and Wiener, M.: Classification and Regression by randomForest, R
News, 2, 18–22, 2002.
Mage, S. M. and Porder, S.: Parent Material and Topography Determine Soil
Phosphorus Status in the Luquillo Mountains of Puerto Rico, Ecosystems, 16,
284–294, https://doi.org/10.1007/s10021-012-9612-5, 2013.
Malone, B. P., Minasny, B., and McBratney, A. B.: Using R for Digital Soil Mapping, Springer, Cham, Switzerland, https://doi.org/10.1007/978-3-319-44327-0, 2017.
McGroddy, M. E.: LBA-ECO TG-07 Forest Soil P, C, and N Pools, km 83 Site,
Tapajos National Forest, Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge, Tennessee, USA [data set], https://doi.org/10.3334/ORNLDAAC/1085, 2012.
Mehmood, A., Akhtar, M. S., Imran, M., and Rukh, S.: Soil apatite loss rate
across different parent materials, Geoderma, 310, 218–229, https://doi.org/10.1016/j.geoderma.2017.09.036, 2018.
Meinshausen, N.: Quantile Regression Forests, J. Mach. Learn. Res., 7,
983–999, 2006.
Meinshausen, N.: quantregForest: Quantile Regression Forests, available at:
https://CRAN.R-project.org/package=quantregForest (last access: 15 December 2021), 2017.
Ploton, P., Mortier, F., Réjou-Méchain, M., Barbier, N., Picard, N.,
Rossi, V., Dormann, C., Cornu, G., Viennois, G., Bayol, N., Lyapustin, A.,
Gourlet-Fleury, S., and Pélissier, R.: Spatial validation reveals poor
predictive performance of large-scale ecological mapping models, Nat.
Commun., 11, 4540, https://doi.org/10.1038/s41467-020-18321-y, 2020.
Porder, S. and Chadwick, O. A.: Climate and Soil-Age Constraints on Nutrient
Uplift and Retention by Plants, Ecology, 90, 623–636, https://doi.org/10.1890/07-1739.1, 2009.
Porder, S. and Ramachandran, S.: The phosphorus concentration of common
rocks – a potential driver of ecosystem P status, Plant Soil, 367, 41–55,
https://doi.org/10.1007/s11104-012-1490-2, 2013.
R Core Team: R: A language and environment for statistical computing, R
Foundation for Statistical Computing, Vienna, Austria, available at:
https://www.R-project.org/ (last access: 15 December 2021), 2018.
Reed, S. C., Yang, X., and Thornton, P. E.: Incorporating phosphorus cycling
into global modeling efforts: a worthwhile, tractable endeavor, New
Phytol., 208, 324–329, https://doi.org/10.1111/nph.13521, 2015.
Reich, P. B. and Oleksyn, J.: Global patterns of plant leaf N and P in
relation to temperature and latitude, P. Natl. Acad. Sci. USA, 101, 11001–11006, https://doi.org/10.1073/pnas.0403588101, 2004.
Ringeval, B., Augusto, L., Monod, H., van Apeldoorn, D., Bouwman, L., Yang,
X., Achat, D. L., Chini, L. P., Van Oost, K., Guenet, B., Wang, R., Decharme,
B., Nesme, T., and Pellerin, S.: Phosphorus in agricultural soils: drivers of
its distribution at the global scale, Glob. Change Biol., 23, 3418–3432,
https://doi.org/10.1111/gcb.13618, 2017.
Rodionov, A., Bauke, S. L., von Sperber, C., Hoeschen, C., Kandeler, E.,
Kruse, J., Lewandowski, H., Marhan, S., Mueller, C. W., Simon, M., Tamburini,
F., Uhlig, D., von Blanckenburg, F., Lang, F., and Amelung, W.:
Biogeochemical cycling of phosphorus in subsoils of temperate forest
ecosystems, Biogeochemistry, 150, 313–328, https://doi.org/10.1007/s10533-020-00700-8,
2020.
Shangguan, W., Dai, Y., Duan, Q., Liu, B., and Yuan, H.: A global soil data
set for earth system modeling, J. Adv. Model. Earth Syst., 6, 249–263, https://doi.org/10.1002/2013MS000293, 2014.
Shangguan, W., Hengl, T., Mendes De Jesus, J., Yuan, H., and Dai, Y.: Mapping
the global depth to bedrock for land surface modeling, J. Adv. Model. Earth
Syst., 9, 65–88, https://doi.org/10.1002/2016MS000686, 2017.
Siqueira, R. G., Schaefer, C. E. G. R., Fernandes Filho, E. I., Corrêa, G. R., Francelino, M. R., Souza, J. J. L. L., and Rocha, P. D. A.: Weathering and pedogenesis of sediments and basaltic rocks on Vega Island, Antarctic
Peninsula, Geoderma, 382, 114707, https://doi.org/10.1016/j.geoderma.2020.114707, 2021.
Smeck, N. E.: Phosphorus dynamics in soils and landscapes, Geoderma, 36,
185–199, https://doi.org/10.1016/0016-7061(85)90001-1, 1985.
Smil, V.: Phosphorus in the environment: natural flows and human
interferences, Annu. Rev. Energ. Env., 25, 53–88, https://doi.org/10.1146/annurev.energy.25.1.53, 2000.
Spohn, M.: Increasing the organic carbon stocks in mineral soils sequesters
large amounts of phosphorus, Glob. Change Biol., 26, 4169–4177, https://doi.org/10.1111/gcb.15154, 2020.
Strobl, C., Boulesteix, A., Kneib, T., Augustin, T., and Zeileis, A.:
Conditional variable importance for random forests, BMC Bioinformatics, 9,
307, https://doi.org/10.1186/1471-2105-9-307, 2008.
Sun, Y., Peng, S., Goll, D. S., Ciais, P., Guenet, B., Guimberteau, M.,
Hinsinger, P., Janssens, I. A., Peñuelas, J., Piao, S., Poulter, B.,
Violette, A., Yang, X., Yin, Y., and Zeng, H.: Diagnosing phosphorus
limitations in natural terrestrial ecosystems in carbon cycle models,
Earth's Future, 5, 730–749, https://doi.org/10.1002/2016EF000472, 2017.
Tipping, E., Somerville, C. J., and Luster, J.: The C:N:P:S stoichiometry of
soil organic matter, Biogeochemistry, 130, 117–131, https://doi.org/10.1007/s10533-016-0247-z, 2016.
Turner, B. L. and Engelbrecht, B. M. J.: Soil organic phosphorus in lowland
tropical rain forests, Biogeochemistry, 103, 297–315, https://doi.org/10.1007/s10533-010-9466-x, 2011.
Viscarra Rossel, R. A. and Bui, E. N.: A new detailed map of total phosphorus
stocks in Australian soil, Sci. Total Environ., 542, 1040–1049, https://doi.org/10.1016/j.scitotenv.2015.09.119, 2016.
Vitousek, P. M. and Chadwick, O. A.: Pedogenic Thresholds and Soil Process
Domains in Basalt-Derived Soils, Ecosystems, 16, 1379–1395, https://doi.org/10.1007/s10021-013-9690-z, 2013.
Vitousek, P. M., Porder, S., Houlton, B. Z., and Chadwick, O. A.: Terrestrial
phosphorus limitation: mechanisms, implications, and nitrogen–phosphorus
interactions, Ecol. Appl., 20, 5–15, https://doi.org/10.1890/08-0127.1, 2010.
Walker, T. W. and Syers, J. K.: The fate of phosphorus during pedogenesis,
Geoderma, 15, 1–19, https://doi.org/10.1016/0016-7061(76)90066-5, 1976.
Wang, Y., Zhang, X., and Huang, C.: Spatial variability of soil total
nitrogen and soil total phosphorus under different land uses in a small
watershed on the Loess Plateau, China, Geoderma, 150, 141–149, https://doi.org/10.1016/j.geoderma.2009.01.021, 2009.
Wang, Y., Zhang, Q., Pitman, A. J., and Dai, Y.: Nitrogen and phosphorous
limitation reduces the effects of land use change on land carbon uptake or
emission, Environ. Res. Lett., 10, 14001, https://doi.org/10.1088/1748-9326/10/1/014001, 2015.
Wang, Y. P., Law, R. M., and Pak, B.: A global model of carbon, nitrogen and phosphorus cycles for the terrestrial biosphere, Biogeosciences, 7, 2261–2282, https://doi.org/10.5194/bg-7-2261-2010, 2010.
Wang, Z., Tian, H., Yang, J., Shi, H., Pan, S., Yao, Y., Banger, K., and
Yang, Q.: Coupling of Phosphorus Processes With Carbon and Nitrogen Cycles
in the Dynamic Land Ecosystem Model: Model Structure, Parameterization, and
Evaluation in Tropical Forests, J. Adv. Model. Earth Syst., 12, e2020MS002123,
https://doi.org/10.1029/2020MS002123, 2020.
Wang, Z., Wang, M., Yu, K., Hu, H., Yang, Y., Ciais, P., Ballantyne, A. P.,
Niklas, K. J., Huang, H., Yao, B., and Wright, S. J.: Global synthesis for the scaling of soil microbial nitrogen to phosphorus in terrestrial ecosystems, Environ. Res. Lett., 16, 044034, https://doi.org/10.1088/1748-9326/abed78, 2021.
Wardle, D. A., Walker, L. R., Bardgett, R. D., and Sveriges, L.: Ecosystem
Properties and Forest Decline in Contrasting Long-Term Chronosequences,
Science, 305, 509–513, https://doi.org/10.1126/science.1098778, 2004.
Wassen, M. J., Schrader, J., van Dijk, J., and Eppinga, M. B.: Phosphorus
fertilization is eradicating the niche of northern Eurasia's threatened
plant species, Nature Ecology & Evolution, 5, 67–73, https://doi.org/10.1038/s41559-020-01323-w, 2021.
Wieder, W. R., Cleveland, C. C., Smith, W. K., and Todd-Brown, K.: Future
productivity and carbon storage limited by terrestrial nutrient
availability, Nat. Geosci., 8, 441–444, https://doi.org/10.1038/ngeo2413, 2015.
Xu, X., Thornton, P. E., and Post, W. M.: A global analysis of soil microbial
biomass carbon, nitrogen and phosphorus in terrestrial ecosystems, Global
Ecol. Biogeogr., 22, 737–749, https://doi.org/10.1111/geb.12029, 2013.
Yan, T., Zhu, J., and Yang, K.: Leaf nitrogen and phosphorus resorption of
woody species in response to climatic conditions and soil nutrients: a
meta-analysis, J. Forestry Res., 29, 905–913, https://doi.org/10.1007/s11676-017-0519-z, 2018.
Yanai, R. D.: The effect of whole-tree harvest on phosphorus cycling in a
northern hardwood forest, Forest Ecol. Manag., 104, 281–295, https://doi.org/10.1016/S0378-1127(97)00256-9, 1998.
Yang, X., Post, W. M., Thornton, P. E., and Jain, A.: The distribution of soil phosphorus for global biogeochemical modeling, Biogeosciences, 10, 2525–2537, https://doi.org/10.5194/bg-10-2525-2013, 2013.
Yang, X., Thornton, P. E., Ricciuto, D. M., and Post, W. M.: The role of phosphorus dynamics in tropical forests – a modeling study using CLM-CNP, Biogeosciences, 11, 1667–1681, https://doi.org/10.5194/bg-11-1667-2014, 2014.
Zhang, C., Tian, H., Liu, J., Wang, S., Liu, M., Pan, S., and Shi, X.: Pools
and distributions of soil phosphorus in China, Global Biogeochem. Cy., 19,
GB1020, https://doi.org/10.1029/2004GB002296, 2005.
Zhang, Q., Wang, Y. P., Pitman, A. J., and Dai, Y. J.: Limitations of nitrogen
and phosphorous on the terrestrial carbon uptake in the 20th century,
Geophys. Res. Lett., 38, L22701, https://doi.org/10.1029/2011GL049244, 2011.
Zhang, Y.-W., Guo, Y., Tang, Z., Feng, Y., Zhu, X., Xu, W., Bai, Y., Zhou, G., Xie, Z., and Fang, J.: Patterns of nitrogen and phosphorus pools in terrestrial ecosystems in China, Earth Syst. Sci. Data, 13, 5337–5351, https://doi.org/10.5194/essd-13-5337-2021, 2021.
Short summary
Our database of globally distributed natural soil total P (STP) concentration showed concentration ranged from 1.4 to 9630.0 (mean 570.0) mg kg−1. Global predictions of STP concentration increased with latitude. Global STP stocks (excluding Antarctica) were estimated to be 26.8 and 62.2 Pg in the topsoil and subsoil, respectively. Our global map of STP concentration can be used to constrain Earth system models representing the P cycle and to inform quantification of global soil P availability.
Our database of globally distributed natural soil total P (STP) concentration showed...
Altmetrics
Final-revised paper
Preprint