DOI: 10.5061/dryad.1vhhmgr5m
title: Data from: Tree functional strategies and soil microbial communities regulate forest ecosystem services

description: 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.
description: <strong>Experimental description </strong>
 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
 (H<sub>2</sub>O) of 4.53, total organic carbon of 3.40%, and
 total N of 0.16%. The experimental region was previously covered by
 Chinese fir (<em>Cunninghamia lanceolata</em> [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.
 <strong>Soil sampling and analysis
 </strong> 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 <em>et
 al</em>., 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 <em>et al</em>., 2022). Soil
 microbial composition was then described by principal coordinates analysis
 (PCoA) of Bray-Curtis distance matrices.
 <strong>Plant sampling and functional
 traits </strong> 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. <strong>Ecosystem
 </strong><strong>service indicators</strong>
 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 <em>et al</em>., 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 <em>et al</em>., 2012; Shi <em>et
 al</em>., 2021). Furthermore, we calculated multifunctionality by
 equally weighting all ecosystem services and functions to reduce the
 influence of highly correlated functions (Manning <em>et
 al</em>., 2018).
description: # Tree functional strategies and soil microbial communities regulate
 forest ecosystem services
 [https://doi.org/10.5061/dryad.1vhhmgr5m](https://doi.org/10.5061/dryad.1vhhmgr5m) ## Description of the data and file structure Author Information Jianqing Wang 1, 2, Peter Manning 3, Josep Peñuelas 4, 5, Francis Q. Brearley 6, Xiuzhen Shi 1, 2, *, Peng Leng 1, 2, Manuel Esteban Lucas-Borja 7, Samiran Banerjee 8, Manuel Delgado-Baquerizo 9, *, Zhiqun Huang 1, 2, * 1 Key Laboratory for Humid Subtropical Eco-geographical Processes of the Ministry of Education, Institute of Geography, Fujian Normal University, Fuzhou 350117, China 2 Fujian Provincial Key Laboratory for Subtropical Resources and Environment, School of Geographical Sciences, Fujian Normal University, Fuzhou 350117, China 3 Department of Biological Sciences, University of Bergen, Bergen, Norway 4 CREAF, Centre de Recerca Ecològica i Aplicacions Forestals, Cerdanyola del Vallès, Ctalonia, Spain 5 Global Ecology Unit, CREAF-CSIC-UAB, Bellaterra, Catalonia, Spain 6 Department of Natural Sciences, Manchester Metropolitan University, Manchester, UK 7 Higher Technical School of Agricultural and Forestry Engineering, Castilla-La Mancha University, Campus Universitario s/n, 02071 Albacete, Spain 8 Department of Microbiological Sciences, North Dakota State University, Fargo, North Dakota, USA 9 Laboratorio de Biodiversidad y Funcionamiento Ecosistémico. Instituto de Recursos Naturales y Agrobiología de Sevilla (IRNAS), CSIC, 41012, Sevilla, Spain *Corresponding authors: Xiuzhen Shi, Manuel Delgado-Baquerizo and Zhiqun Huang E-mail addresses: [shxzh87@hotmail.com](mailto:shxzh87@hotmail.com), [m.delgado.baquerizo@csic.es](mailto:m.delgado.baquerizo@csic.es), [zhiqunhuang@fjnu.edu.cn](mailto:zhiqunhuang@fjnu.edu.cn) Brief summary of dataset contents, contextualized in experimental procedures and results. 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 ℃. **Data Description：** | Variable | Description | units | | :---------------------- | :------------------------------- | :-------- | | Carbon\_stocks | Carbon stock function  | NA | | Soil\_activity  | Soil activity function  | NA | | Nutrient\_cycling | Nutrient cycling function | NA | | Water\_cycling | Water cycling function  | NA | | Ecosystem\_productivity | Ecosystem productivity function  | NA | | Multifunctionality | Ecosystem multifunctionality | NA | | Leaf\_N | Leaf nitrogen content  | % | | LDMC | Leaf dry matter content | mg g-1 | | SLA | Specific leaf area | m2 kg-1 | | Root\_N | Root nitrogen content  | % | | SRL | Specific root length | m g-1 | | F\_B | Ratio of fungi-bacteria  | NA | | M\_diversity | Soil microbial diversity  | NA | | M\_biomass | Soil microbial biomass  | nmol g-1  | | M\_composition | Soil microbial composition  | NA | | Soil\_TC | Soil total carbon  | % | | Soil\_TN | Soil total nitrogen  | % | | Soil\_pH | Soil pH | NA | | NA | No unit | -- | **Sharing/access Information** Links to other publicly accessible locations of the data: No Was data derived from another source? No