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.
Data description paper
| 
20 Dec 2021
Data description paper |
| 20 Dec 2021
| 20 Dec 2021
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
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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
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Juhwan Lee, Raphael A. Viscarra Rossel, Mingxi Zhang, Zhongkui Luo, and Ying-Ping Wang
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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...
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