@article{fdi:010055780,
  title = {{P}edotransfer functions to estimate soil bulk density for {N}orthern {A}frica : {T}unisia case},
  author = {{B}rahim, {N}. and {B}ernoux, {M}artial and {G}allali, {T}.},
  editor = {},
  language = {{ENG}},
  abstract = {{C}ountries should provide regularly national inventories of greenhouse gas emissions and sinks and, and for the agriculture and forestry sectors this comprise national estimates of soil organic carbon ({C}) stocks. {E}stimation of soil {C} stock requires soil bulk density ({D}-b) values. {H}owever, direct measurement of {D}-b is often lacking mainly for soils in arid and semi-arid conditions. {M}uch effort has been made in finding alternative solution to predict {D}-b, either improving in situ determinations, either improving estimation procedures based on other soil properties. {R}egression models or pedotransfer functions ({PTF}s) based on easily measured soil properties constitute an adequate tool to assess {D}-b, since it needs a minimum data set of indicators. {A} forward stepwise multiple linear regression routine was used to predict {D}-b from physico-chemical soil properties. {I}n this study, a soil database was organised from published and unpublished data from {T}unisia. {T}he database consisted of 238 soil profiles corresponding to 707 soil horizons from {T}unisia. {A} general regression model fitted with all the data showed that {CC}, {C}lay, coarse-{S}and and p{H} were the principal contributors to {D}-b prediction ({R}-2 = 0.55, standard error of prediction = 0.14). {A}dditional models based on different set of variables are also provided providing alternative solutions for different levels of soil information. {P}redictions of the models were often improved when the data were partitioned into groups by soil depth (0-40 and 40-100 cm) and soil orders. {T}his study also showed that {C}a{CO}3 might be an important predictor for deeper soil horizon. {T}he proposed {PTF}s for {T}unisia might be useful for a larger range of soil from arid and sub arid regions.},
  keywords = {{B}ulk density ; {P}edotransfer functions ; {M}ultiple linear regressions ; {M}editerranean region ; {C}arbon stock estimates ; {C}arbonate},
  booktitle = {},
  journal = {{J}ournal of {A}rid {E}nvironments},
  volume = {81},
  numero = {},
  pages = {77--83},
  ISSN = {0140-1963},
  year = {2012},
  DOI = {10.1016/j.jaridenv.2012.01.012},
  URL = {https://www.documentation.ird.fr/hor/fdi:010055780},
}