DOI: 10.5061/dryad.zs7h44jjm
title: Tree diversity drives multiple facets of bee diversity via microenvironment

description: Wild bees are widely distributed and effective pollinators, yet they face
 significant threats such as degradation of forests. Forest restoration has
 been advocated as a strategy to mitigate these threats and stabilize
 biodiversity. However, there is a lack of understanding of the ecological
 consequences of forest restoration on bee diversity, particularly
 regarding interactions with tree diversity and microenvironment. Using
 data from the world’s largest tree diversity experiment (BEF-China), this
 study examines how tree species richness, canopy cover, understory
 vegetation, and microclimatic conditions affect bee diversity in the
 context of forest restoration. Our analysis of bee diversity data (8,341
 individuals from 79 species) revealed that these biotic factors had
 distinct effects on three dimensions of bee diversity. Specifically,
 canopy cover had a negative effect on bee taxonomic diversity but a
 positive effect on phylogenetic and functional diversity. However, these
 patterns were reversed when cover of understory vegetation was accounted
 for. Moreover, tree species richness exerted an indirect influence on bee
 diversity through understory microenvironment. Our findings provide nuance
 into how tree species richness shapes bee communities via vegetation cover
 and microclimate, which is informative on habitat characteristics in
 forest restoration and conservation that better enable the safeguarding of
 pollinators.
description: <em>Study sites</em> The study was
 carried out in the BEF-China Biodiversity Experiment which is located in
 forests of Jiangxi province, a subtropical region (29°08′–29°11′N,
 117°90′–117°93′E). For this study, 66 plots were selected randomly for the
 two sites (33 plots for each site), which covered a tree species richness
 gradient from 0 to 24 (for each site, 1 plot without artificial planted
 trees, 16 plots with monocultures, 8 plots with 2 species, 4 plots with 4
 species, 2 plots with 8 species, 1 plot with 16 species and 1 plot with 24
 species). <em>Environmental
 factors</em> Four quadrats were set on the
 diagonal (next to the traps) and one was set in the centre of each plot to
 measure the coverage of understory vegetation, of which the size was 1 m*1
 m (see Fig S1). Above each quadrat, canopy cover was recorded through
 hemispherical pictures taken at 1 m above ground with a 180-mm fish eye
 lens and then calculated as percentage of black area of total image size
 using Gap Light Analyzer 2.0 (Frazer et al., 1999). Then, the mean of the
 canopy cover and understory coverage were calculated for each plot. For
 microclimate, temperature and humidity data were recorded in 15-minute
 intervals with sensors mounted 1 m above ground (Shandong Renke Control
 Technology Co., Ltd., China). The monthly temperature and humidity during
 the sampling events were calculated to represent understory
 microclimate. <em>Bee sampling and molecular
 work</em> Blue vane traps and three-colored pan
 traps were both used to collect bees in June and September of 2022, and
 April, June and September of 2023. Two vane traps were put at a distance
 of 1.5 m from ground, while two groups of pan traps (yellow, white and
 blue) were placed at a distance of 0.5 m on the second diagonal of each
 plot. Each trap was partially filled with water, with few drops of
 detergent to break the water surface tension. For each collection event,
 samples in the traps were collected after about 24 hours, conducted three
 times (totally 72 h). COI DNA barcode region (~650 bp) was amplified using
 universal primer pairs (LCO1490: GGTCA ACAAA TCATA AAGAT ATTGG and HCOout:
 CCAGG TAAAA TTAAA ATATA AACTT C). Molecular delimitation and taxonomic
 assignment followed the pipeline of Xie et at. (2023) (Xie et al.,
 2023). <em>Bee functional
 traits</em> Functional traits of our captured
 bees were determined either by new measurement (e.g. morphological traits)
 or phylogeny-based prediction using species-level reference data of
 phylogeny terminals and life history records. We measured morphometric
 traits of bee individuals using a Zeiss Discovery V20 stereomicroscope. If
 the length exceeded the microscope range, we used a digital calliper. Five
 such traits were used, body length (BL), head width (HW), hair length
 (HL), inter-tegular distance (ITD) and fore-wing length (fWL). Life
 history traits were also integrated via literature records, and then
 assigned to MOTU. These included lecty (floral range), sociality,
 parasitism and nest location (implicated in the utilization of resources).
 Missing traits were predicted and assigned by modeling trait evolution
 along branches of the phylogeny. A more comprehensive description of trait
 prediction for phylogenetically placed MOTU can be found in Xie et al.
 (2023).
description: # Tree diversity drives multiple facets of bee diversity via
 microenvironment Dataset DOI:
 [10.5061/dryad.zs7h44jjm](https://doi.org/10.5061/dryad.zs7h44jjm) ##
 Description of the data and file structure ### Files and variables ####
 File: diversity.csv **Description:** the diversity indices used in this
 study ##### Variables * hill.shann: bee taxonomic diversity; estimation
 using hill numbers (hereafter TD, ' q' = 1: Shannon diversity )
 in the R package ‘hilldiv’ * PD.ses: standardized effect size of bee
 phylogenetic diversity (Value~obs~ - Value~mean~) / Valuesd); Faith’s
 phylogenetic diversity * FDiv.ses: standardized effect size of bee
 functional diversity (Value~obs~ - Value~mean~) / Valuesd); Functional
 divergence;  * Site: sampling site (A or B) * Plot: sampling plots * Year:
 sampling year * Month: sampling month #### File: env.csv
 **Description:** the environmental factors considered in this study #####
 Variables * Site: sampling site (A or B) * Plot: sampling plots * Month:
 sampling month * under_cover: cover of understory vegetation (%) *
 canopy_cover: canopy cover (%) * MT: monthly temperature (℃) * MH: monthly
 humidity (%) * TREE_R: tree species richness  (number of species)