Mapping soil diversity in mountain areas in a temperate climate: methods to analyse a complex environment. A case study in the Northern Apennines (Italy)

Monitoring and evaluating ecosystems and their interactions are essential for the effective management of both natural and agricultural landscapes. Soil, a crucial component of terrestrial ecosystems, is globally acknowledged for its complexity and diversity. It serves as a vital medium where key processes such as nutrient cycling, water regulation, and carbon storage take place. Despite its fundamental role in sustaining biodiversity and delivering critical ecosystem services, soil often receives limited attention in ecological research and environmental policies. Soil formation is a complex process shaped by environmental factors such as climate, organisms, parent material, morphology, and time. The interplay of these factors, along with inherent properties, results in a wide variety of soils across different scales. Geographic Information Systems (GIS) tools can help analyze these interactions and “unpack the mosaic” that defines a given landscape, thereby aiding soil surveys and data collection in complex environments like mountainous regions. Mountainous areas cover more than a third of Italy’s land area and provide numerous invaluable ecosystem services, from water regulation and carbon storage to recreation, timber, and high-quality food production. They also support diverse habitats and preserve Italy’s historical and cultural heritage. However, climate change, land use changes, and hydrogeological instability present significant threats to mountain ecosystems and the adjacent hills and lowlands, with frequent landslides, floods, and wildfires damaging forests, crops, and communities. Despite their importance, mountain soils in Italy remain poorly understood and largely neglected in environmental policies. With this study, we present a digital soil mapping approach to optimize soil survey campaigns in complex environments, and a Random Forest to transition from the sampled points to the final map. After sampling and soil classification is completed, a set of remotely sensed and topographic covariates related to soil forming factors is selected. A subset of covariates is chosen by recursively eliminating the least performing layers, and is then used to perform an iterative Random Forest which yields the final map. This method not only delivers accurate results for this study area, but it also provides important information regarding the intensity with which soil forming factors affect it. It can also be used to plan new sampling campaigns in unsurveyed areas, making it a powerful tool in the whole process of soil mapping in mountainous environments, which is fundamental to provide useful information and directions for the management of these vulnerable but critically important lands.