A geospatial approach for evaluating impact and potentiality of conservation farming for soil health improvement at regional and farm scale

Soil organic matter (SOM) is a key factor in sustaining soil fertility, sequestering greenhouse gases and reducing soil erosion, in this regard, an accurate estimation and monitoring of the SOM content is crucial for sustainable land management and climate change mitigation strategies. In recent years, there has been a growing consciousness of the need to better understand the dynamics of SOM across different farm management in time and space. In this context, the main objective of the study is to improve understanding regarding the relationship between SOM and the main farming systems adopted in Italy by taking spatial correlation into account. For this purpose, a large dataset consisting of topsoil SOM values (0–20 cm) and environmental and farming information was collected in 597 locations (145 fields and 62 farms) representative of the whole agricultural area of Po Valley in Italy. This sizable dataset was analyzed by a novel geospatial analysis using a de-clustering approach in combination with polygon kriging for detecting and understanding the SOM variability over the different fields characterized by irregular shapes and different farming systems. The results provided clear evidences of the spatial correlation between SOM, farming systems and soil types. Higher SOM contents were detected in Cambisols (3.11 %) and in field managed according conservation agriculture practices (3.22 %) as compared to other farming systems. Moreover the inclusion of fodder crops in the rotation and the use of no-tillage are two of the most effective practices for increasing and preserving SOM according to our findings. Spatial information, such those provided in this study, could facilitate the delineation of tailored solutions for each European Member State for targeting future actions related to carbon farming, and offering crucial insights to support advancements in agriculture for enhancing soil fertility and health and for fostering sustainable agricultural practices. • SOM estimation and monitoring is crucial for sustainable land management • Spatial information facilitates tailored solutions for enhancing soil health • A geospatial approach allowed to compare SOM content for the main farming systems • SOM content, farming systems and soil types are significant spatially correlated • Significant higher SOM content in field managed according conservation agriculture