Simultaneous negative changes in soil electrical resistivity and porosity in two Carpathian mixed forests induced by rubber-tyred skidder traffic

While the impact of forestry machinery on soil structure is well documented, large-scale monitoring of soil compaction in managed forests is hindered by the high spatial variability of soils, the labour intensity of conventional methods, and their time-consuming and destructive nature. These challenges obstruct the implementation of preventive strategies, such as optimised skid-trail design, to mitigate soil degradation. Meanwhile, efficient, non-destructive soil assessment techniques suitable for operational forestry remain underdeveloped. Here, we evaluate the potential of electrical resistivity tomography for detecting skidder-induced compaction in forest soils. Conducted in two Carpathian forests, the study employed two approaches: successive and spatially aligned soil electrical resistivity (ER) measurements before and after two loaded skidder passes in locality 1, and parallel ER measurements on a skid road formed by approximately forty passes alongside a non-trafficked area in Locality 2. Decreases of approximately 10 Ω m were observed after just two passes in locality 1 and > 200 Ω m after approximately forty passes in Locality 2, respectively. This study provides the first assessment of ER changes along forest skid trail sections almost 10 m long, accompanied by a soil porosity (φ) reduction of up to 13%. Significant effects of skidder traffic and locality on φ were indicated by two-way ANOVA ( p = 0.013, R 2 = 0.335). Partial evidence for a significant co-occurrence of negative changes in both soil ER and φ was indicated by a probabilistic analysis under the assumption of independence ( p < 0.01). However, higher φ sampling density, spatially aligned with soil ER variation, is required for a robust correlation analysis. These findings support the integration of ER tomography into forest operations as a decision-support tool while highlighting the necessity for diverse environmental conditions.