Articles | Volume 15, issue 6
https://doi.org/10.5194/essd-15-2465-2023
© Author(s) 2023. 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-15-2465-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description article
| 
14 Jun 2023
Data description article |
| 14 Jun 2023
| 14 Jun 2023
Digital soil mapping of lithium in Australia
Sydney Institute of Agriculture, School of Life and Environmental
Sciences, The University of Sydney, Eveleigh, NSW 2015, Australia
Budiman Minasny
Sydney Institute of Agriculture, School of Life and Environmental
Sciences, The University of Sydney, Eveleigh, NSW 2015, Australia
Alex McBratney
Sydney Institute of Agriculture, School of Life and Environmental
Sciences, The University of Sydney, Eveleigh, NSW 2015, Australia
Patrice de Caritat
Geoscience Australia, Canberra, ACT 2601, Australia
John Wilford
Geoscience Australia, Canberra, ACT 2601, Australia
Related authors
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Anthony Dosseto, Florian Dux, Clément Bataille, and Patrice de Caritat
Earth Syst. Sci. Data, 17, 4865–4880, https://doi.org/10.5194/essd-17-4865-2025, https://doi.org/10.5194/essd-17-4865-2025, 2025
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We created the first detailed map of bioavailable strontium isotope ratios in Australian soils that are taken up by plants and animals. These ratios vary depending on local geology and are useful for tracing the origins of people, animals, and food. By combining new data from across Australia with global datasets and a machine learning model, we produced a national prediction that supports research in archaeology, ecology, and forensic science.
Yin-Chung Huang, José Padarian, Budiman Minasny, and Alex B. McBratney
SOIL, 11, 553–563, https://doi.org/10.5194/soil-11-553-2025, https://doi.org/10.5194/soil-11-553-2025, 2025
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Uncertainty quantification plays a crucial role in reporting machine learning models in soil spectroscopy. This study introduces Monte Carlo conformal prediction (MC-CP), a novel method for uncertainty quantification in deep-learning soil spectral models. MC-CP outperformed two established methods, providing the most reliable results. Its efficiency and robustness make it a practical choice for implementing soil spectral models in decision making.
Marliana Tri Widyastuti, José Padarian, Budiman Minasny, Mathew Webb, Muh Taufik, and Darren Kidd
SOIL, 11, 287–307, https://doi.org/10.5194/soil-11-287-2025, https://doi.org/10.5194/soil-11-287-2025, 2025
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This work aims to predict soil water content at a fine spatiotemporal resolution (80 m grids, daily) to support agricultural management in Tasmania. It proves that transfer learning can improve the accuracy of deep learning models to predict multilevel soil moisture. We address the challenge of mapping soil moisture at field-scale resolution and integrate the model into a near-real-time monitoring system.
Patrice de Caritat, Anthony Dosseto, and Florian Dux
Earth Syst. Sci. Data, 17, 79–93, https://doi.org/10.5194/essd-17-79-2025, https://doi.org/10.5194/essd-17-79-2025, 2025
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This new, extensive dataset from southwestern Australia contributes considerable new data and knowledge to Australia’s strontium isotope coverage. The data are discussed in terms of the lithology and age of the source lithologies. This dataset will reduce Northern Hemisphere bias in future global strontium isotope models. Potential applications of the new data include mineral exploration, hydrogeology, food tracing, dust provenancing, and historic migrations of people and animals.
Claudia Hird, Morgane M. G. Perron, Thomas M. Holmes, Scott Meyerink, Christopher Nielsen, Ashley T. Townsend, Patrice de Caritat, Michal Strzelec, and Andrew R. Bowie
Aerosol Research, 2, 315–327, https://doi.org/10.5194/ar-2-315-2024, https://doi.org/10.5194/ar-2-315-2024, 2024
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Dust deposition flux was investigated in lutruwita / Tasmania, Australia, between 2016–2021. Results show that the use of direct measurements of aluminium, iron, thorium, and titanium in aerosols to estimate average dust deposition fluxes limits biases associated with using single elements. Observations of dust deposition fluxes in the Southern Hemisphere are critical to validate model outputs and better understand the seasonal and interannual impacts of dust deposition on biogeochemical cycles.
Marliana Tri Widyastuti, Budiman Minasny, José Padarian, Federico Maggi, Matt Aitkenhead, Amélie Beucher, John Connolly, Dian Fiantis, Darren Kidd, Yuxin Ma, Fraser Macfarlane, Ciaran Robb, Rudiyanto, Budi Indra Setiawan, and Muh Taufik
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-333, https://doi.org/10.5194/essd-2024-333, 2024
Preprint withdrawn
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PEATGRIDS, the first dataset containing maps of global peat thickness and carbon stock at 1 km resolution. The dataset has been publicly available at Zenodo to support further analyses and modelling of peatlands across the globe. This work employed the random forest machine learning model to provide spatially explicit peat carbon stock at pixel basis.
Tobias Karl David Weber, Lutz Weihermüller, Attila Nemes, Michel Bechtold, Aurore Degré, Efstathios Diamantopoulos, Simone Fatichi, Vilim Filipović, Surya Gupta, Tobias L. Hohenbrink, Daniel R. Hirmas, Conrad Jackisch, Quirijn de Jong van Lier, John Koestel, Peter Lehmann, Toby R. Marthews, Budiman Minasny, Holger Pagel, Martine van der Ploeg, Shahab Aldin Shojaeezadeh, Simon Fiil Svane, Brigitta Szabó, Harry Vereecken, Anne Verhoef, Michael Young, Yijian Zeng, Yonggen Zhang, and Sara Bonetti
Hydrol. Earth Syst. Sci., 28, 3391–3433, https://doi.org/10.5194/hess-28-3391-2024, https://doi.org/10.5194/hess-28-3391-2024, 2024
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Pedotransfer functions (PTFs) are used to predict parameters of models describing the hydraulic properties of soils. The appropriateness of these predictions critically relies on the nature of the datasets for training the PTFs and the physical comprehensiveness of the models. This roadmap paper is addressed to PTF developers and users and critically reflects the utility and future of PTFs. To this end, we present a manifesto aiming at a paradigm shift in PTF research.
Frisa Irawan Ginting, Rudiyanto Rudiyanto, Fatchurahman, Ramisah Mohd Shah, Norhidayah Che Soh, Sunny Goh Eng Giap, Dian Fiantis, Budi Indra Setiawan, Sam Schiller, Aaron Davitt, and Budiman Minasny
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-90, https://doi.org/10.5194/essd-2024-90, 2024
Preprint withdrawn
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This study is the first to map rice cropping intensity and the harvested area across Southeast Asia at a spatial resolution of 10 m (SEA-Rice-Ci10). We have developed a geospatial inventory of paddy rice parcels and rice cropping intensity by integrating Sentinel-1 and 2 time-series data in a framework called LUCK-PALM, based on local phenological expert interpretation. According to our best knowledge, it is the finest-resolution and most accurate database of paddy rice in Southeast Asia.
Candan U. Desem, Patrice de Caritat, Jon Woodhead, Roland Maas, and Graham Carr
Earth Syst. Sci. Data, 16, 1383–1393, https://doi.org/10.5194/essd-16-1383-2024, https://doi.org/10.5194/essd-16-1383-2024, 2024
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Lead (Pb) isotopes form a potent tracer in studies of provenance, mineral exploration and environmental remediation. Previously, however, Pb isotope analysis has rarely been deployed at a continental scale. Here we present a new regolith Pb isotope dataset for Australia, which includes 1119 large catchments encompassing 5.6 × 106 km2 or close to ~75 % of the continent. Isoscape maps have been produced for use in diverse fields of study.
Mercedes Román Dobarco, Alexandre M. J-C. Wadoux, Brendan Malone, Budiman Minasny, Alex B. McBratney, and Ross Searle
Biogeosciences, 20, 1559–1586, https://doi.org/10.5194/bg-20-1559-2023, https://doi.org/10.5194/bg-20-1559-2023, 2023
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Soil organic carbon (SOC) is of a heterogeneous nature and varies in chemistry, stabilisation mechanisms, and persistence in soil. In this study we mapped the stocks of SOC fractions with different characteristics and turnover rates (presumably PyOC >= MAOC > POC) across Australia, combining spectroscopy and digital soil mapping. The SOC stocks (0–30 cm) were estimated as 13 Pg MAOC, 2 Pg POC, and 5 Pg PyOC.
Patrice de Caritat, Anthony Dosseto, and Florian Dux
Earth Syst. Sci. Data, 15, 1655–1673, https://doi.org/10.5194/essd-15-1655-2023, https://doi.org/10.5194/essd-15-1655-2023, 2023
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This new, extensive (~1.5×106 km2) dataset from northern Australia contributes considerable new information on Australia's strontium (Sr) isotope coverage. The data are discussed in terms of lithology and age of the source areas. This dataset will reduce Northern Hemisphere bias in future global Sr isotope models. Other potential applications of the new data include mineral exploration, hydrology, food tracing, dust provenancing, and examining historic migrations of people and animals.
Patrice de Caritat, Anthony Dosseto, and Florian Dux
Earth Syst. Sci. Data, 14, 4271–4286, https://doi.org/10.5194/essd-14-4271-2022, https://doi.org/10.5194/essd-14-4271-2022, 2022
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Strontium isotopes are useful in geological, environmental, archaeological, and forensic research to constrain or identify the source of materials such as minerals, artefacts, or foodstuffs. A new dataset, contributing significant new data and knowledge to Australia’s strontium isotope coverage, is presented from an area of over 500 000 km2 of inland southeastern Australia. Various source areas for the sediments are recognized, and both fluvial and aeolian transport processes identified.
José Padarian, Budiman Minasny, Alex B. McBratney, and Pete Smith
SOIL Discuss., https://doi.org/10.5194/soil-2021-73, https://doi.org/10.5194/soil-2021-73, 2021
Manuscript not accepted for further review
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Soil organic carbon sequestration is considered an attractive technology to partially mitigate climate change. Here, we show how the SOC storage potential varies globally. The estimated additional SOC storage potential in the topsoil of global croplands (29–67 Pg C) equates to only 2 to 5 years of emissions offsetting and 32 % of agriculture's 92 Pg historical carbon debt. Since SOC is temperature-dependent, this potential is likely to reduce by 18 % by 2040 due to climate change.
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Short summary
With a higher demand for lithium (Li), a better understanding of its concentration and spatial distribution is important to delineate potential anomalous areas. This study uses a framework that combines data from recent geochemical surveys and relevant environmental factors to predict and map Li content across Australia. The map shows high Li concentration around existing mines and other potentially anomalous Li areas. The same mapping principles can potentially be applied to other elements.
With a higher demand for lithium (Li), a better understanding of its concentration and spatial...
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