Canopy cover at the crown-scale best predicts spatial heterogeneity of soil moisture within a temperate Atlantic forest

• We examined soil moisture relationships with forest structure at three spatial scales. • Our three study sites on sandy soils in the Netherlands include four density treatments. • We used terrestrial laser scanning to derive canopy cover, plant area index, and other attributes. • The crown-scale explained most variation in soil moisture across structures and time. Managing forest openness can enhance drought resilience during dry, hot summer periods by reducing competition for soil moisture among trees. The purpose of our study was to better understand how different components of forest structure influence soil moisture variability. In our study, we utilized Terrestrial Laser Scanning to quantify the relationships between five forest structural attributes and the spatial distribution of soil moisture within experimental forest plots dominated by Douglas fir, Scots pine, and common beech in The Netherlands. In these plots the canopy openness ranged from 0, 20, 80 to 100 %. Observations were conducted during the hot and dry summer of 2022. Our findings revealed that all forest structural attributes related negatively with soil moisture and that the crown features canopy cover and plant area index predicted between 30 and 60 % of the spatial variability of soil moisture. In addition, these crown features consistently predicted 17 % more variation than the trunk-centred features basal area, stem density, and a density-dependent competition index. The crown -scale, corresponding to the crown radius of the dominant tree species, consistently explained most variation in soil moisture across species and time. We expect that tree water uptake is the primary factor influencing the spatial variability of soil moisture, rather than throughfall or interception, yet direct measurements of these processes are needed to substantiate this. This study suggests that forest management could benefit from information on forest structural attributes to guide tree harvest and improve soil moisture availability, contributing to developing a climate-smart forest management strategy.