DOI: 10.5061/dryad.m905qfv27
title: Data from: Seasonal bee communities vary in their responses to resources at local and landscape scales: Implication for land managers

description: Context: There is great interest in land management practices for
 pollinators; however, a quantitative comparison of landscape and local
 effects on bee communities is necessary to determine if adding small
 habitat patches can increase bee abundance or species richness. The value
 of increasing floral abundance at a site is undoubtedly influenced by the
 phenology and magnitude of floral resources in the landscape, but due to
 the complexity of measuring landscape-scale resources, these factors have
 been understudied. Objectives: To address this knowledge gap, we
 quantified the relative importance of local versus landscape scale
 resources for bee communities, identified the most important metrics of
 local and landscape quality, and evaluated how these relationships vary
 with season. Methods: We studied season-specific relationships between
 local and landscape quality and wild-bee communities at 33 sites in the
 Finger Lakes region of New York, USA. We paired site surveys of wild bees,
 plants, and soil characteristics with a multi-dimensional assessment of
 landscape composition, configuration, insecticide toxic load, and a
 spatio-temporal evaluation of floral resources at local and landscape
 scales. Results: We found that the most relevant spatial scale and
 landscape factor varied by season. Early-season bee communities responded
 primarily to landscape resources, including the presence of flowering
 trees and wetland habitats.  In contrast, mid to late-season bee
 communities were more influenced by local conditions, though bee diversity
 was negatively impacted when sites were embedded in highly agricultural
 landscapes. Soil composition had complex impacts on bee communities, and
 likely reflects effects on plant community flowering. 
 Conclusions: Early-season bees can be supported by adding flowering trees
 and wetlands, while mid to late-season bees can be supported by local
 addition of summer and fall flowering plants. Sites embedded in landscapes
 with a greater proportion of natural areas will host a greater bee species
 diversity.
description: Data file
 <strong>'bee_abundance_richness_all_predictors_toarchive.csv':  </strong>abundance and richness of wild bees at 33 sites in the Ithaca region of New York, USA with 68 variables of site and landscape quality. Landscape quality variables include topography, landscape-scale floral resources, landscape configuration and composition, and insecticide toxic load. Site quality variables include soil characteristics (texture, fertility, bulk density, water content), plant species richness, plant community composition, and site-scale floral resources. Please see README for a description of column headings in the data file ('bee_abundance_richness_all_predictors_toarchive_Mar2024.csv'). Missing values: For analyses of species richness, we excluded sites with zero abundance of wild bees (either due to compromised traps or poor-quality habitat). In the data file, these instances are indicated as richness of zero.
description: # Data from: Seasonal bee communities vary in their responses to resources
 at local and landscape scales: Implication for land managers
 [https://doi.org/10.5061/dryad.m905qfv27](https://doi.org/10.5061/dryad.m905qfv27) This dataset accompanies the publication "Seasonal bee communities vary in their responses to resources at local and landscape scales: Implication for land managers." For a complete description of how the data were collected, please see the referenced, open-access publication. In brief, we sampled abundance and richness of wild bees at 33 sites in the Ithaca region of New York, USA for two years and generated 72 variables of site and landscape quality. Landscape quality variables include topography, landscape-scale floral resources, landscape configuration and composition, and insecticide toxic load. Site quality variables include soil characteristics (texture, fertility, bulk density, water content), plant species richness, plant community composition, and site-scale floral resources. ### Contact Information: For any questions about these data, please contact Melanie Kammerer ([melanie.a.kammerer@gmail.com](mailto:melanie.a.kammerer@gmail.com)) or Christina Grozinger ([cmgrozinger@psu.edu](mailto:cmgrozinger@psu.edu)) ### Date of data collection: 2018-2019 (for each data point, start of sampling indicated in 'date_set' variable) ### Geographic location of data collection: Tompkins, Ontario, Seneca, Cayuga, Onondaga, Schuyler counties, New York, USA ### File list: bee_abundance_richness_all_predictors_toarchive_Mar2024.csv (updated March 11, 2024) ### **Accompanying code:** To replicate the analyses described in the manuscript, complete code is available at [https://zenodo.org/doi/10.5281/zenodo.5598051](https://zenodo.org/doi/10.5281/zenodo.5598051) ### General abbreviations used in column headings: FA floral area .land variable calculated at landscape-scale .site variable measured or calculated at site-scale .all variable represents all plant species .IP variable represents only insect-pollinated plant species (see Iverson et al, unpublished manucscript) ### Description of specific column headings #### Sampling information: SiteName site identifier Year year of data collection Season spring or summer collection time date_set date pan trap were placed at each site NTrapsSuccessful number of pan traps per site at the end of the sampling round (not cracked, tipped over, or missing) NDaysTrapsSet number of days pan traps were deployed #### Bee abundance/richness: Abundance number of individual bees AbundTrap number of bees per trap AbundDayTrap number of bees per trap per day richness number of bee species estimated by coverage-based rarefaction (Chao and Jost 2012) S.obs number of bee species observed in the sample (not rarified) habitat type of habitat (as defined by Iverson et al, unpublished manuscript) #### Topography: elevation Elevation at wild-bee sampling location (m) slope_pct Slope at wild-bee sampling location (%) aspectEW East/West component of aspect at wild-bee sampling location (USGS 2014) aspectNS North/South component of aspect at wild-bee sampling location (USGS 2014) distance_to_water distance from bee sampling location to nearest stream, pond, or lake (m) #### Floral resources: total_FA sum of floral resources for the entire year (spring, summer, and fall) max_FA maximum value of floral-resource cuve (whole year) CV_FA coefficient of variation of floral resource curve (whole year) min_FA minimum value of floral-resource cuve (whole year) spring_total_FA sum of floral resources in spring summer_total_FA sum of floral resources in summer fall_total_FA sum of floral resources in fall #### Landscape composition and configuration: PctLand_Agriculture percentage of the landscape in agriculture (%) PctLand_Developed percentage of the landscape developed land (%) PctLand_Forest percentage of the landscape in forest land (%) PctLand_Successional percentage of the landscape in successional habitat (%) PctLand_Water percentage of the landscape covered in open water (%) PctLand_Wetland percentage of the landscape in wetland habitat (%) PctLand_Natural percentage of the landdscape in forest, successional, water, or wetland habitat (%) ITL_mean_landscape insecticide toxic load, mean of oral and contact toxicity (Douglas et al 2021) para_mn mean perimeter-area ratio (Hesselbarth et al 2019) enn_cv Coefficient of variation of euclidean nearest-neighbor distance (Hesselbarth et al 2019) ed edge density (Hesselbarth et al 2019) iji Interspersion and Juxtaposition index (Hesselbarth et al 2019) shdi Shannon's diversity of land use types (Hesselbarth et al 2019) sidi Simpson's diversity of land use types (Hesselbarth et al 2019) area_mn Mean of patch area (Hesselbarth et al 2019) #### Soil characteristics Grav_WaterContent_g.g_mean gravimetric water content (g water per g of soil, mean of 2 samples) pH_mean mean soil pH (mean of 5 samples) P_ppm_mean soil phosphorus (ppm, mean of 5 samples) K_ppm_mean soil potassium (ppm, mean of 5 samples) Mg_ppm_mean soil magnesium (ppm, mean of 5 samples) Ca_ppm_mean soil calcium (ppm, mean of 5 samples) CEC_meq_per_100g_mean cation exchange capacity of soil (meq per 100g, mean of 5 samples) Zn_ppm_mean soil zinc (ppm, mean of 5 samples) Cu_ppm_mean soil copper (ppm, mean of 5 samples) S_ppm_mean soil sulfur (ppm, mean of 5 samples) OM_Pct_mean soil organic matter (%, mean of 5 samples) Total_N_Pct_mean soil nitrogen content by combustion (%, mean of 5 samples) Sand_Pct_mean soil texture (% sand, mean of 5 samples) Silt_Pct_mean soil texture (% silt, mean of 5 samples) Clay_Pct_mean soil texture (% clay, mean of 5 samples) bulk_density_mean soil bulk density (mean of 2 samples) #### Plant community richness.plants number of plant species at the site mean_pct_cover vegetative cover (%, mean of 10 quadrats) NMDS_mmt NMDS ordination of plant community composition (axis one representing gradient in management intensity) NMDS_water NMDS ordination of plant community composition (axis one representing gradient in water availability)