Spatio-temporal dynamics of topsoil moisture and the influence of tree species on pattern persistence

Soil moisture (SM) in the topsoil horizon is a key variable in terrestrial ecosystems, regulating water and energy exchange at the interface between the soil and the atmosphere. In forest ecosystems, SM exhibits pronounced spatio-temporal variability within the active root zone as a result of complex interactions among multiple factors including soil properties, topography, climate and vegetation. Formulating broadly reliable statements about spatio-temporal soil moisture characteristics and its effects remains challenging. Existing research is limited and sometimes contradictory regarding when and to what extent controls such as tree species influence topsoil SM variability across space and time.

This study investigates spatio-temporal dynamics of topsoil SM and their controls in different forest ecosystems. The objectives are to quantify the spatial variability at the plot scale and its temporal evolution from event to seasonal scale, thereby improving our understanding of SM dynamics between wet and dry states and across different mono- and mixed-species forest stands. We investigate the variables governing spatial soil moisture variability and how they modulate SM patterns over time, with a focus on how ecohydrological processes amplify or mitigate SM variability.

SM was recorded in four stands in the ECOSENSE forest in southwestern Germany, using 400 time domain transmissometry sensors (SMT100, Truebner GmbH, Germany) installed at 12 cm depth in a tree-centered design across stands of mixed and pure Douglas fir, Beech and Silver fir. A continuous 2.5-year dataset (2023 – 2025) was analysed using statistical and geostatistical approaches to identify dominating spatial SM patterns during wet and dry periods. Temporal stability was evaluated to determine the pattern persistence. Spatial SM differed significantly among plots during most of the observation period. Mean SM followed a similar annual cycle throughout all plots, with typical maxima in late winter and minima in early fall. Despite comparable soil properties and topography, the pure Beech and Douglas fir plots revealed significant seasonal differences in mean SM. Beech has more prominent autumn wetting, while Douglas fir has stronger spring drying, likely reflecting changes in evapotranspiration dynamics. The individual probability density functions of spatial soil moisture distribution transitioned between wet- or dry-preferential unimodal states and intermediate bimodal states. Across plots, spatial mean SM and the coefficient of variation exhibited an upward-convex relationship: variability was low under dry and wet (<10% or > 30% mean SM) and high under intermediate moisture conditions. The geostatistical variogram analyses showed short autocorrelation lengths, and pronounced spatial variability at few meters’ distance. Temporal stability of SM varied across plots with a range of persistently wet and dry spots. Individual locations deviated by up to 50% from temporally averaged SM at the Beech, Douglas fir and mixed plot, and up to 75% for the Silver fir plot.

Combined with LiDAR derived canopy structure metrics, micro topographic maps, soil properties, and continuous ecohydrological- and meteorological observation, the presented soil moisture dataset provides a unique framework to investigate jointly modulating factors of soil moisture. It enables detailed analysis of wetting-drying cycles, including seasonal and species-specific differences.