Short-range and regional spatial variability of soil chemical properties in an agro-ecosystem in eastern Croatia

Abstract

Spatial and temporal characterization of soil properties in agro-ecosystems is crucial for monitoring the evolution of soil functions and for understanding the main influential processes. Moreover, the objective mapping of soil properties in agro-ecosystems is urgently needed for regional planning purposes and the proper choice of land management practices. In this work, the geostatistical analysis of a dataset of soil properties, derived from 2411 soil samples collected in Vukovar-Srijem County (Croatia), highlighted the multiple benefits of a spatial-statistical approach. The main aim of this paper is to jointly examine short-range (i.e., within-field) and regional spatial variability of several soil chemical properties: soil pH, organic matter (OM), plant available phosphorus (AP) and potassium (AK). The available sampling network, characterized by a set of 2411 (0–30cm depth) irregularly and field-clustered soil samples, allowed to derivate of two typologies of soil nutrient maps by means of ordinary block kriging: within-field high-resolution maps (block size 250m) and regional low-resolution maps (block size 2000m). Soil pH and OM had lower variability compared to AP and AK. The OM content and pH ranged from 1.24% to 5.25% and from 3.69 to 7.84, respectively. Almost 94% of all samples had an OM content below 3%, indicating the need for future adoption of environmentally friendly soil management in this county. The mean values of AP and AK were 173mgkg−1 and 238mgkg−1, respectively, indicating a moderate supply of these nutrients. Geostatistical analysis revealed that the best-fit models were spherical for pH and AP, with moderate spatial dependency, and exponential for OM and AK, with strong spatial dependency. The within-field high-resolution soil property maps can be used as guidance for site-specific fertilization and liming. In addition, the regional maps derived for larger interpolation support provide quantitative information for regional planning and environmental monitoring and protection purposes. Consequently, the multi-resolution mapping of soil properties and the analysis of their spatial variability highlighted possible connections with influential factors and processes, including the relationships with different soil types. Finally, quantification of the spatial variability of soil properties by means of variogram models constitutes a basis for optimizing soil sample spacing for mapping purposes in the studied region.