Abstract
Detailed knowledge of agricultural soil properties is a key element for high-quality food production. However, high-resolution soil data covering a large agricultural region are generally unavailable. This study explores a demand-driven cooperative framework for soil data sourcing that connects individual farmers to several stakeholders by means of a centralised database containing more than 16,000 records of soil information collected within the framework of an integrated production program for intensively managed permanent crops in the Adige/Etsch and Venosta/Vinschgau valleys in South Tyrol, Italy. Data for soil pH, soil organic matter (SOM), and soil texture were used to produce digital soil maps with a RMSE of 0.21, 1.25% and a cross-validation of 43%, respectively. Spatialisation was conducted using either regression-kriging or multinomial logistic regression. Collaboration among farmers, public administrators, and researchers provided a successful cooperative framework for digital soil mapping. The maps highlight the complex interplay of the postglacial evolution of these valleys due to the presence of a cluster of large alluvial fans and the anthropogenic influences of intense farming on pH, SOM, and soil texture. This study regarded a subset of the available soil properties, which can be dealt with using the geostatistical approaches presented herein. Thus, a long-term soil monitoring program and the combination of all available variables will allow digital assessment of the spatial patterns of nutrient availability, ecological risk assessments, change detection studies, and an overall long-term plan for soil security at larger spatial scales.
•Demand-driven cooperative framework for farmer soil data sourcing.•High density soil database provide an ideal dataset for digital soil mapping.•Postglacial landforms strongly influence soil property spatial pattern.•The long-term monitoring plan open new paths for digital soil assessment.