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Hierarchical pedotransfer functions to predict bulk density of highly weathered soils in Central Africa

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Project
BOF B/09517/02
Abstract
Bulk density (BD) is a key soil property for sustainable land management and C stock assessment. However, data on BD are often missing in various soil survey reports in Central Africa because its measurement is laborious, time consuming at large scales, and may pose expense and facilities challenges, particularly in resource-poor countries. Therefore, there was a need for developing pedotransfer functions (PTFs) to predict BD for soils of Central Africa as an alternative solution. To do so, two approaches, namely multiple linear regression (MLR) and a pattern-recognition approach (k-nearest neighbor [k-NN]) were tested to predict BD for 196 soils of the Lower Congo. Based on their needs and familiarity with one or both of the two approaches, potential users interested in predicting the BD of strongly weathered soils of Lower Congo in particular or of Central Africa in general can immediately use the proposed equations or later apply the k-NN algorithm. Using an independent data set of low-activity clay soils from different tropical countries, nine individual PTFs and three ensemble PTFs were tested for their predictive capability. The results showed that despite the use of various modeling approaches—MLR, k-NN, or ensembles—BD remains a soil property that is difficult to predict with a satisfactory level of reliability because it can have substantial short-term variability in response to natural as well as humaninduced causes. We achieved a minimum root mean square difference value of 0.179 Mg m−3.
Keywords
Highly Weathered Soils, Pedotransfer Functions, Central Africa, Prediction, Bulk Density, WATER-RETENTION, ORGANIC-MATTER, GEOGRAPHICAL-DISTRIBUTION, CARBON CONTENT, IRON-OXIDES, AGGREGATION

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Citation

Please use this url to cite or link to this publication:

Chicago
Botula Manyala, Yves-Dady, Attila Nemes, Eric Van Ranst, Paul Mafuka, Jan De Pue, and Wim Cornelis. 2015. “Hierarchical Pedotransfer Functions to Predict Bulk Density of Highly Weathered Soils in Central Africa.” Soil Science Society of America Journal 79 (2): 476–486.
APA
Botula Manyala, Yves-Dady, Nemes, A., Van Ranst, E., Mafuka, P., De Pue, J., & Cornelis, W. (2015). Hierarchical pedotransfer functions to predict bulk density of highly weathered soils in Central Africa. SOIL SCIENCE SOCIETY OF AMERICA JOURNAL, 79(2), 476–486.
Vancouver
1.
Botula Manyala Y-D, Nemes A, Van Ranst E, Mafuka P, De Pue J, Cornelis W. Hierarchical pedotransfer functions to predict bulk density of highly weathered soils in Central Africa. SOIL SCIENCE SOCIETY OF AMERICA JOURNAL. 2015;79(2):476–86.
MLA
Botula Manyala, Yves-Dady, Attila Nemes, Eric Van Ranst, et al. “Hierarchical Pedotransfer Functions to Predict Bulk Density of Highly Weathered Soils in Central Africa.” SOIL SCIENCE SOCIETY OF AMERICA JOURNAL 79.2 (2015): 476–486. Print.
@article{5851564,
  abstract     = {Bulk density (BD) is a key soil property for sustainable land management and C stock assessment. However, data on BD are often missing in various soil survey reports in Central Africa because its measurement is laborious, time consuming at large scales, and may pose expense and facilities challenges, particularly in resource-poor countries. Therefore, there was a need for developing pedotransfer functions (PTFs) to predict BD for soils of Central Africa as an alternative solution. To do so, two approaches, namely multiple linear regression (MLR) and a pattern-recognition approach (k-nearest neighbor [k-NN]) were tested to predict BD for 196 soils of the Lower Congo. Based on their needs and familiarity with one or both of the two approaches, potential users interested in predicting the BD of strongly weathered soils of Lower Congo in particular or of Central Africa in general can immediately use the proposed equations or later apply the k-NN algorithm. Using an independent data set of low-activity clay soils from different tropical countries, nine individual PTFs and three ensemble PTFs were tested for their predictive capability. The results showed that despite the use of various modeling approaches---MLR, k-NN, or ensembles---BD remains a soil property that is difficult to predict with a satisfactory level of reliability because it can have substantial short-term variability in response to natural as well as humaninduced causes. We achieved a minimum root mean square difference value of 0.179 Mg m\ensuremath{-}3.},
  author       = {Botula Manyala, Yves-Dady and Nemes, Attila and Van Ranst, Eric and Mafuka, Paul and De Pue, Jan and Cornelis, Wim},
  issn         = {0361-5995},
  journal      = {SOIL SCIENCE SOCIETY OF AMERICA JOURNAL},
  language     = {eng},
  number       = {2},
  pages        = {476--486},
  title        = {Hierarchical pedotransfer functions to predict bulk density of highly weathered soils in Central Africa},
  url          = {http://dx.doi.org/10.2136/sssaj2014.06.0238},
  volume       = {79},
  year         = {2015},
}

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