Preservation and sustainable use of soil biological communities represent major challenges in the current agroecological context. Ho
w ever, to identify the agricultural practices/systems that match
w ith these challenges, innovative tools have to be developed to establish a diagnosis of the biological status of the soil. Here,
w e have developed a statistical polynomial model to predict the molecular biomass of the soil microbial community according to the soil physicochemical properties. For this,
w e used a dataset of soil molecular microbial biomass estimates and pedoclimatic properties derived from analyses of samples collected in the context of the “
French monitoring soil quality net
w ork = Réseau de Mesures de la qualité des Sols” (RMQS). This sampling net
w ork has provided 2115 soil samples covering the range of variability of soil type and land use at the scale of France. The best model obtained from the data sho
w ed that soil organic carbon content, clay content, altitude, and pH
w ere the best explanatory variables of soil microbial biomass
w hile other variables such as longitude, latitude and annual temperature
w ere negligeable. Based on these variables, the multilinear model developed allo
w ed very accurate prediction of the soil microbial biomass,
w ith an excellent adjusted coefficient of determination
w the MathML source" class="mathImg" data-mathURL="/science?_ob=MathURL&_method=retrieve&_eid=1-s2.0-S1470160X15007062&_mathId=si1.gif&_user=111111111&_pii=S1470160X15007062&_rdoc=1&_issn=1470160X&md5=2c859c00b5173d527741b18214b53f46"> width="25" alt="View the MathML source" title="View the MathML source" src="/sd/grey_pxl.gif" data-inlimgeid="1-s2.0-S1470160X15007062-si1.gif"> width="25" alt="View the MathML source" title="View the MathML source" src="http://origin-ars.els-cdn.com/content/image/1-s2.0-S1470160X15007062-si1.gif"> w="scroll">w>R w>adj w>2 w> of 0.6772 (
P < 10
−3 ). In addition to
w the MathML source" class="mathImg" data-mathURL="/science?_ob=MathURL&_method=retrieve&_eid=1-s2.0-S1470160X15007062&_mathId=si1.gif&_user=111111111&_pii=S1470160X15007062&_rdoc=1&_issn=1470160X&md5=2c859c00b5173d527741b18214b53f46"> width="25" alt="View the MathML source" title="View the MathML source" src="/sd/grey_pxl.gif" data-inlimgeid="1-s2.0-S1470160X15007062-si1.gif"> width="25" alt="View the MathML source" title="View the MathML source" src="http://origin-ars.els-cdn.com/content/image/1-s2.0-S1470160X15007062-si1.gif"> w="scroll">w>R w>adj w>2 w> , the model
w as further validated by results from cross validation and sensitivity analyses. The model provides a reference value for microbial biomass for a given pedoclimatic condition,
w hich can then be compared
w ith the corresponding measured data to provide for the first time a robust diagnosis of soil quality. Application of the model to a set of soil samples obtained at the scale of an agricultural landscape is presented and discussed, sho
w ing the suitability of the model to diagnose of the impact of particular agricultural practices such as tillage and catch crops in field conditions, at least over the French nation.