Forests provide key ecosystem services. However, the role of tree functional strategies and soil microbial communities in supporting multiple ecosystem services remains unclear. To bridge this gap, we conducted a field experiment involving monocultures of 28 tree species with diverse functional traits and their associated soil microbial communities. We assessed multiple indicators of ecosystem services to gain insights into their interrelationships. Our study revealed strong connections between tree functional traits, soil microbial communities, and ecosystem services such as nutrient cycling, water retention, and ecosystem productivity. Broadleaved trees had a negative impact on nutrient cycling rates but positively influenced ecosystem productivity compared to coniferous trees. Deciduous trees are positively associated with ecosystem water availability compared to evergreen trees. Tree species with resource-acquisitive strategies were associated with faster nutrient cycling rates. Furthermore, trees forming ectomycorrhizal associations increased nutrient cycling and multifunctionality (i.e. multiple ecological functions and services) compared to trees with arbuscular mycorrhizal associations. More importantly, leaf nitrogen content indirectly influenced multifunctionality by affecting the ratio of fungi-bacteria and soil microbial composition.

Synthesis and applications. This research highlights the role of tree functional strategies and soil microbial community composition in influencing the ecosystem services of subtropical forests, and provides important information on which functional groups may be planted to promote particular bundles of ecosystem services.

Experimental description 

This study aimed to investigate the relationships between tree species and ecosystem functioning in subtropical forests. The field experiment was conducted in Shanghang, Fujian Province, China (25°07′N, 116°32′E), which has a humid subtropical climate with a mean annual precipitation of 1,637 mm and a mean annual temperature of 19.8 ℃, based on data from 1971 to 2020. The soil is derived from sandstone and is classified as red soil according to the Chinese Soil Classification System, which corresponds to an Ultisol in the USDA Soil Taxonomy. The basic chemical properties of the topsoil are as follows: pH (H₂O) of 4.53, total organic carbon of 3.40%, and total N of 0.16%. The experimental region was previously covered by Chinese fir (Cunninghamia lanceolata [Lamb.] Hook; Cupressaceae) plantations. In March 2019, following the clear-cutting of the Chinese fir plantations, a total of 28 common subtropical tree species were planted in monoculture as saplings in 81 randomly selected plots, with 2 to 4 replicates for each tree species (Table 1). The trees were planted at a density of 256 trees per plot, each covering an area of 12 m × 12 m, with approximately 0.75 m spacing between rows. To limit cross-over effects, all plots were separated by a buffer zone of at least 2 m. Of the 28 species, 7 were deciduous and 21 evergreen, 5 were coniferous 23 broadleaved, and 20 were AM and 8 EM (Table S1). Field experiment permissions were obtained from landowners and the forestry department under applicable local regulations.

Soil sampling and analysis

Soil sampling was conducted in August 2021 when the trees had been growing for 2.5 years. Ten topsoil cores (0-10 cm depth) were randomly collected from the center of the plot, surrounding each tree stem. Cores were extracted using a 3.5 cm diameter auger after carefully removing the litter layer. The collected soil cores were thoroughly mixed to form a composite sample. The 81 soil samples were divided into two portions for subsequent analysis. One was stored at 4 °C for soil physical and chemical analyses, while the other was stored at -20 °C for microbial analyses.

Soil water content (SWC) was measured by oven-drying subsamples at 105 °C for 24 hours. Soil nitrification and mineralization rates were determined by differences in total nitrate N and mineral N concentrations between the beginning and end of a 28-day incubation at 25 ℃ in an incubator, respectively.

Soil enzyme activities: β-glucosidase, cellobiohydrolase, acid phosphatase, and N-acetylglucosaminidase, were determined using MUB (4-methylumbelliferone)-linked substrates (Saiya-Cork et al., 2002). Soil phospholipid fatty acids analysis (PLFA) was employed to assess the Shannon-wiener diversity and biomass of soil microbial communities. This technique characterizes microbial populations, including bacteria, fungi, and actinomycetes, by examining fatty acid profiles in the soil samples (Wan et al., 2022). Soil microbial composition was then described by principal coordinates analysis (PCoA) of Bray-Curtis distance matrices.

Plant sampling and functional traits 

In 2020, litterfall mass were measured from all individual trees within the experimental plots. Litterfall was collected once a month in each experimental plot using five litter traps (47 cm × 47 cm) for one year. The collected litter was dried at 65 ℃ for 72 hours to determine its dry weight. The litter's maximum water-holding capacity was evaluated by immersing dry litter in water for 24 hours. In May 2021, leaf samples were collected from at least three representative trees of each species from each plot. The sampling involved selecting one south-facing branch from the canopy, and leaves were carefully collected from this branch ensuring representative samples for analysis. LDMC was calculated by dividing water-saturated fresh leaf mass by the corresponding dry leaf mass. SLA was calculated by dividing the dry weight of the leaf by the corresponding fresh leaf area. Leaf N content was analyzed using finely ground dry leaf samples (8-10 mg) on a CNS Macro Elemental Analyzer. Root branches with intact terminal branch orders were selected and cut, and 5 g of fresh biomass from first-order roots was collected as the representative sample. Root N content was quantified by analyzing finely ground dry root samples, as above.

Ecosystem service indicators

Multiple aspects of ecosystem service provision were captured by using several indicator measures for each to form what we refer to as ecosystem service classes. These aspects were: ecosystem productivity, carbon stocks, nutrient cycling (faster rates equated to greater ecosystem service supply), water retention (more water retention considered greater service supply), and soil health (greater soil enzyme activity considered indicative of more health soil). These capture multiple aspects of ecosystem functioning with strong links to service provision (Table 1). Ecosystem productivity was evaluated using litterfall mass. Nutrient cycling was assessed using soil mineralization rates and nitrification rates. Carbon stocks were represented by soil microbial biomass carbon and dissolved organic carbon, the most rapidly changing pools over the timeframe considered. Soil health was represented by soil enzyme activities. Water retention was indicated by SWC and litter maximum water-holding capacity. Within each service class, standardized ecosystem variables were converted into individual services using the formula: ecosystem services = (species value - minimum value) / (maximum value - minimum value) (Wang et al., 2019). Each transformed ecosystem variable had a minimum value of zero and a maximum value of one. The normalized individual services, averaged across the indicators of each, were then averaged to calculate the overall multifunctionality score (Maestre et al., 2012; Shi et al., 2021). Furthermore, we calculated multifunctionality by equally weighting all ecosystem services and functions to reduce the influence of highly correlated functions (Manning et al., 2018).