Data from: Tree species and genetic diversity increase productivity via functional diversity and trophic feedbacks

This data was collected in the species × genetic diversity experiment of the Biodiversity–Ecosystem Functioning Experiment China Platform (BEF-China, www.bef-china.com). This data set includes four species (Alniphyllum fortunei, Cinnamanum camphora, Daphniphyllum oldhamii, and Idesia polycarpa) with the mother trees of all tree individuals known, and the offspring from the same mother tree was defined as a seed family. In total, 92 subplots with 4 tree diversity levels were included: species diversity (1 or 4 species) and genetic diversity (1 or 4 seed families per species) which resulted in four tree diversity levels: one species with one seed family (1.1), one species with four seed families (1.4), four species with one seed family per species (4.1) and four species with four seed families per species (4.4). For tree functional traits, five leaf functional traits were measured in 2017 and 2018, including leaf area (LA), specific leaf area (SLA), chlorophyll content (CHL), leaf nitrogen content (LN), and leaf carbon content (LC). Herbivory was visually recorded as leaf damage in 2017. Soil fungal diversity was used as proxies for unspecified trophic interactions. Soil samples were taken on subplot level for the 1.1 and 1.4 diversity treatments, but on plot level for the 4.1 and 4.4 diversity treatments in 2017. Tree community productivity was summed by the biomass of individual trees in each subplot and individual tree biomass (kg) was calculated using the biomass equation (H × BA × CV) of the BEF-China experiment, where CV is a correction factor for stem shape and wood density.Funding provided by: National Natural Science Foundation of ChinaCrossref Funder Registry ID: http://dx.doi.org/10.13039/501100001809Award Number: 31870409Funding provided by: Strategic Priority Research Program of the Chinese Academy of Sciences*Crossref Funder Registry ID: Award Number: XDB31000000Funding provided by: National Natural Science Foundation of ChinaCrossref Funder Registry ID: http://dx.doi.org/10.13039/501100001809Award Number: 32161123003Funding provided by: Younth Innovation Promotion Association CAS*Crossref Funder Registry ID: Award Number: 201908