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Developing global pedotransfer functions to estimate available soil phosphorus

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Developing global pedotransfer functions to estimate available soil phosphorus. / Khaledian, Yones; Quinton, John Norman; Brevik, Eric C. et al.
In: Science of the Total Environment, Vol. 644, 10.12.2018, p. 1110-1116.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Khaledian, Y, Quinton, JN, Brevik, EC, Pereira, P & Zeraatpisheh, M 2018, 'Developing global pedotransfer functions to estimate available soil phosphorus', Science of the Total Environment, vol. 644, pp. 1110-1116. https://doi.org/10.1016/j.scitotenv.2018.06.394

APA

Khaledian, Y., Quinton, J. N., Brevik, E. C., Pereira, P., & Zeraatpisheh, M. (2018). Developing global pedotransfer functions to estimate available soil phosphorus. Science of the Total Environment, 644, 1110-1116. https://doi.org/10.1016/j.scitotenv.2018.06.394

Vancouver

Khaledian Y, Quinton JN, Brevik EC, Pereira P, Zeraatpisheh M. Developing global pedotransfer functions to estimate available soil phosphorus. Science of the Total Environment. 2018 Dec 10;644:1110-1116. Epub 2018 Jul 11. doi: 10.1016/j.scitotenv.2018.06.394

Author

Khaledian, Yones ; Quinton, John Norman ; Brevik, Eric C. et al. / Developing global pedotransfer functions to estimate available soil phosphorus. In: Science of the Total Environment. 2018 ; Vol. 644. pp. 1110-1116.

Bibtex

@article{f53b4ea7d7874cb1a914a34742d89c03,
title = "Developing global pedotransfer functions to estimate available soil phosphorus",
abstract = "There are a large number of investigations that estimate available soil phosphorous (P), but a paucity of global data on available soil P. One significant modern challenge is developing low cost, accurate approaches to predict available soil P that are useful to scientists around the world. We conducted a global meta-analysis using data on available soil P from 738 sites, 640 in the USA and 149 in 14 other countries. Four different methods of determining available soil P, New Zealand (NZ), acid oxalate, Bray and Mehlich 3 were represented in the dataset. Inputs evaluated for inclusion in the pedotransfer functions to predict available soil P were clay (C), fine silt, (FSi) coarse silt (CSi), very fine sand (VFS), fine sand (FS), medium sand (MS), coarse sand (CS), very coarse sand (VCS), organic carbon (OC), pH, calcium (Ca), magnesium (Mg), potassium (K), iron (Fe), aluminum (Al), and manganese (Mn). Available soil P was estimated for: 1) the entire dataset, 2) only the USA, and 3) the non-USA dataset. The best models to estimate available soil P were obtained for the NZ method (using the co-variates C, FSi, CSi, VFS, MS, CS, OC, Fe, Al, Mn, Ca, Mg, and pH) and for the acid oxalate method (using the co-variates C, FSi, Fe, Al, Mn, Ca, and Mg). Although estimation of available soil P determined with the acid oxalate method was poor for the entire dataset, good estimates were obtained for the USA and non-USA datasets separately. Models for the Bray and Mehlich 3 methods only predicted available soil P well for the non-USA dataset. Using pedotransfer function models to estimate available soil P could provide an efficient and cost effective way to estimate global distributions of a soil property that is important for a number of agricultural and environmental reasons.",
author = "Yones Khaledian and Quinton, {John Norman} and Brevik, {Eric C.} and Paulo Pereira and Mojtaba Zeraatpisheh",
year = "2018",
month = dec,
day = "10",
doi = "10.1016/j.scitotenv.2018.06.394",
language = "English",
volume = "644",
pages = "1110--1116",
journal = "Science of the Total Environment",
issn = "0048-9697",
publisher = "Elsevier Science B.V.",

}

RIS

TY - JOUR

T1 - Developing global pedotransfer functions to estimate available soil phosphorus

AU - Khaledian, Yones

AU - Quinton, John Norman

AU - Brevik, Eric C.

AU - Pereira, Paulo

AU - Zeraatpisheh, Mojtaba

PY - 2018/12/10

Y1 - 2018/12/10

N2 - There are a large number of investigations that estimate available soil phosphorous (P), but a paucity of global data on available soil P. One significant modern challenge is developing low cost, accurate approaches to predict available soil P that are useful to scientists around the world. We conducted a global meta-analysis using data on available soil P from 738 sites, 640 in the USA and 149 in 14 other countries. Four different methods of determining available soil P, New Zealand (NZ), acid oxalate, Bray and Mehlich 3 were represented in the dataset. Inputs evaluated for inclusion in the pedotransfer functions to predict available soil P were clay (C), fine silt, (FSi) coarse silt (CSi), very fine sand (VFS), fine sand (FS), medium sand (MS), coarse sand (CS), very coarse sand (VCS), organic carbon (OC), pH, calcium (Ca), magnesium (Mg), potassium (K), iron (Fe), aluminum (Al), and manganese (Mn). Available soil P was estimated for: 1) the entire dataset, 2) only the USA, and 3) the non-USA dataset. The best models to estimate available soil P were obtained for the NZ method (using the co-variates C, FSi, CSi, VFS, MS, CS, OC, Fe, Al, Mn, Ca, Mg, and pH) and for the acid oxalate method (using the co-variates C, FSi, Fe, Al, Mn, Ca, and Mg). Although estimation of available soil P determined with the acid oxalate method was poor for the entire dataset, good estimates were obtained for the USA and non-USA datasets separately. Models for the Bray and Mehlich 3 methods only predicted available soil P well for the non-USA dataset. Using pedotransfer function models to estimate available soil P could provide an efficient and cost effective way to estimate global distributions of a soil property that is important for a number of agricultural and environmental reasons.

AB - There are a large number of investigations that estimate available soil phosphorous (P), but a paucity of global data on available soil P. One significant modern challenge is developing low cost, accurate approaches to predict available soil P that are useful to scientists around the world. We conducted a global meta-analysis using data on available soil P from 738 sites, 640 in the USA and 149 in 14 other countries. Four different methods of determining available soil P, New Zealand (NZ), acid oxalate, Bray and Mehlich 3 were represented in the dataset. Inputs evaluated for inclusion in the pedotransfer functions to predict available soil P were clay (C), fine silt, (FSi) coarse silt (CSi), very fine sand (VFS), fine sand (FS), medium sand (MS), coarse sand (CS), very coarse sand (VCS), organic carbon (OC), pH, calcium (Ca), magnesium (Mg), potassium (K), iron (Fe), aluminum (Al), and manganese (Mn). Available soil P was estimated for: 1) the entire dataset, 2) only the USA, and 3) the non-USA dataset. The best models to estimate available soil P were obtained for the NZ method (using the co-variates C, FSi, CSi, VFS, MS, CS, OC, Fe, Al, Mn, Ca, Mg, and pH) and for the acid oxalate method (using the co-variates C, FSi, Fe, Al, Mn, Ca, and Mg). Although estimation of available soil P determined with the acid oxalate method was poor for the entire dataset, good estimates were obtained for the USA and non-USA datasets separately. Models for the Bray and Mehlich 3 methods only predicted available soil P well for the non-USA dataset. Using pedotransfer function models to estimate available soil P could provide an efficient and cost effective way to estimate global distributions of a soil property that is important for a number of agricultural and environmental reasons.

U2 - 10.1016/j.scitotenv.2018.06.394

DO - 10.1016/j.scitotenv.2018.06.394

M3 - Journal article

VL - 644

SP - 1110

EP - 1116

JO - Science of the Total Environment

JF - Science of the Total Environment

SN - 0048-9697

ER -