The interplay of forest stand and environmental factors shape soil organic C (SOC) storage in forest ecosystems but little is known about their relative impacts in different soil layers. Moreover, how environmental factors modulate the impact of stand factors, particularly species mixing, on SOC storage, is largely unexplored.  In this study conducted in 21 forest triplets (two-species mixed stand and respective monocultures nearby) distributed in Europe, we tested the hypothesis that stand factors (functional identity and diversity) have stronger effects on topsoil (FF+0-10 cm) C storage than environmental factors (climatic water availability, clay+silt content, oxalate-extractable Al - Al_ox) but that the opposite occurs in the subsoil (10-40 cm). We also tested the hypothesis that functional diversity improves SOC storage under high climatic water availability, clay+silt contents, Al_ox. We characterized functional identity as the proportion of broadleaved species (beech and/or oak), and functional diversity as the product of broadleaved and conifer (pine) proportions. The results show that functional identity was the main driver of topsoil C storage while climatic water availability had the largest control on subsoil C storage. Contrary to expectations, functional diversity decreased topsoil C storage under increasing climatic water availability but the opposite was observed in the subsoil. Functional diversity effects on topsoil C increased with increasing clay+silt content, while its effects on subsoil C was negative at increasing Al_ox content. This suggests that functional diversity effect on SOC storage along environmental gradients depends on the specific environmental factor and the soil depth under consideration.

This study was conducted in 21 forest triplets across Europe. A triplet consisted of two-species mixed stand and their corresponding monocultures at the same site. The three forest stands in each triplet were of similar ages (based on tree cores and forest archives) and had homogenous soil conditions based on texture analyses on soil samples in the 10-20 cm depth. The triplets were of three types: five beech-oak (Fagus sylvatica L. - Quercus petraea (Matt.) Liebl.), eight pine-beech (Pinus sylvestris L. - Fagus sylvatica L.), and eight pine-oak (Pinus sylvestris L. - Quercus robur L. / Quercus petraea (Matt.) Liebl.). These tree species are widely distributed in Europe and are very important for forestry.

We placed ten (10) sampling points in each mixed stand and five (5) points each in the corresponding monocultures. At each sampling point, we sampled the forest floor (organic layer above the mineral soil) with 30 cm x 30 cm metal frame. Subsequently, we dug sampling pits in 10 cm interval until 40 cm depth. We estimated total volume (soil + voids + stones) of soil samples in each 10 cm pit by the volume replacement method (Al-Shammary and others 2018) with glass beads. Samples were air-dried, crushed, then passed through 2 mm sieve to separate fine soil (<2 mm), coarse roots (>2 mm), and stones. We picked visible roots in fine soil to reduce their influence on C contents. We separately weighed all the fine soil and the stone fractions. We determined stone volume by water displacement method. Sub-samples of fine soils were ground into powder with Vibratory Disc Mill (Retsch RS 200, Germany) for C and N analyses on all samples (totaling 2080) using CN Analyzer (FlashEA® 1112, USA). Computation of SOC stocks have been described in Osei and others (2021). Soil pH, particle size distribution, and oxalate-extractable metals (Al_ox, Fe_ox) were determined on samples from the 10-20 cm depth. We determined soil pH in deionized water at a ratio of 1:10 using inoLab pH Level 1 (WTW GmbH, Germany). Particle size distribution was determined by sedimentation method following protocol NF X31-107. The oxalate-extractable metals (Al_ox, Fe_ox) were extracted by 0.2M ammonium-oxalate at pH 3 according to Blackmore and others (1981), and the concentrations of Al and Fe were determined by ICP. We characterized the combined effect of precipitation (P, mm) and temperature (T, °C) by the de Martonne aridity index (DMI; P/T+10)

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