DOI: 10.5061/dryad.zs7h44j7m
title: Seasonality of floral resources in relation to bee activity in agroecosystems

description: The contribution of wild insects to crop pollination is becoming
 increasingly important as global demand for crops dependent on animal
 pollination increases. If wild insect populations are to persist in
 agricultural landscapes, there must be sufficient resources over time and
 space. The temporal, within‐season component of floral resource
 availability has rarely been investigated, despite growing recognition of
 its likely importance for pollinator populations. Here, we examined the
 visitation rates of common bee genera and the spatiotemporal availability
 of floral resources in agroecosystems over one season to determine whether
 local wild bee activity was limited by landscape floral resource
 abundance, and if so, whether it was limited by the present or past
 abundance of landscape floral resources. Visitation rates and landscape
 floral resources were measured in 27 agricultural sites in Ontario and
 Québec, Canada, across four time periods and three spatial scales. Floral
 resources were determined based on species‐specific floral volume
 measurements, which we found to be highly correlated with published
 measurements of nectar sugar mass and pollen volume. Total floral volume
 at varying spatial scales predicted visits for commonly observed bee
 genera. We found Lasioglossum and Halictus visits were highest in
 landscapes that provided either a stable or increasing amount of floral
 resources over the season. Andrena visits were highest in landscapes with
 high floral resources at the start of the season, and Bombus visits
 appeared to be positively related to greater cumulative seasonal abundance
 of floral resources. These findings together suggest the importance of
 early‐season floral resources to bees. Megachile visits were negatively
 associated with the present abundance of floral resources, perhaps
 reflecting pollinator movement or dilution. Our research provides insight
 into how seasonal fluctuations in floral resources affect bee activity and
 how life history traits of bee genera influence their responses to food
 availability within agroecosystems.
description: <strong>Study sites and landscape
 structure</strong> The study was conducted in 27
 farms growing fruit or vegetable crops in Eastern Ontario and the
 Outaouais region of Québec, Canada (map of sites in Figure S1). Farms
 planning to grow cucurbit crops were chosen initially for inclusion
 because we wished to focus on pollinator‐dependent, late‐season crops;
 however, many farms were not able to grow cucurbits due to drought
 conditions experienced throughout the region. To maximize independence
 among farm sites (i.e., to minimize the chance that an individual bee
 could move between farms), chosen farms were 4–211 km apart. Across all
 farm sites, 102 locations were sampled for bees and floral resource
 abundance (as described below), with one to six locations per farm,
 depending on the number of distinct land patches in which
 resource‐providing flowers were present, and when permission was given
 from landowners. Sampling locations within patches of land were selected
 based on the estimated location of the patch's centre or, if the
 patch was over 25 m wide, was located at least 10 m from an edge. In three
 patches wider than 25 m, sampling locations less than 10 m from the edge
 were used due to a complete absence of flowers in bloom in the centre. The
 distance between sampling locations within a farm ranged from 3.8 m to
 1,040 m. Sites were visited in rotation over four time periods during one
 season in 2016: the first took place in late spring, between May 20 and
 June 10 (n = 38 sampling locations), the second in early summer, from June
 10 to July 4 (n = 33), the third in mid‐summer, from July 5 to August 1 (n
 = 37), and the fourth in late summer, from August 1 to September 1 (n =
 39). If sampling locations contained open flowers during more than one
 sampling period, the same location was sampled in multiple time
 periods. The composition of the landscape within 250,
 500, and 750 m radii of each sampling location was quantified to estimate
 landscape‐scale floral resource abundance. The 250–750 m scale has been
 found in previous studies to be the range at which
 non‐<em>Apis</em> bees respond to landscape structure
 (Steffan‐Dewenter et al., 2002), and 500 m was chosen as an intermediate
 spatial scale. Sampling locations within the same farm site (and with
 overlapping radii at the 750 m scale) were not treated as independent (see
 Statistical analysis). Within a 750 m radius around each sampling
 location, the boundaries between land patches were manually digitized in
 QGIS version 2.18.7, using both waypoints taken on‐site with a Trimble®
 Juno SD handheld GPS unit (Trimble Navigation Limited), and from Google
 Earth and Bing Aerial satellite imagery. Each land
 patch was then categorized by the type of land‐use (hereafter, “land
 type”), through ground‐truthing and raster imagery from Agriculture and
 Agri‐Food Canada's (AAFC) 2016 Annual Crop Inventory. Land types fell
 into three categories: non‐resource land, resource‐providing land, and
 unknown land (see Table S1 for detailed descriptions of each land type).
 Non‐resource land was defined as any area that did not provide floral
 resources, which included crops with exclusively wind‐pollinated flowers
 and crops with anecdotal or no evidence of bees collecting resources from
 flowers. Urban and developed land, which comprised approximately 8.5% of
 all area surrounding sampling locations, was also included in non‐resource
 land; although residential gardens may provide floral resources for bees,
 the amount is inconsistent over time and space (Cane, 2005; Matteson et
 al., 2008) and appeared in our study to be highly variable across
 locations. Furthermore, other components of urban and developed land
 (e.g., pavement, mown lawns) are often devoid of floral resources.
 Resource‐providing land was defined as land areas that provided floral
 resources for bees at some point during the season and was categorized
 into 14 different land types (Table S1). Sampling locations were located
 only within resource‐providing land, and at least one of each
 resource‐providing land type was sampled during each time period. Unknown
 land was comprised of areas where we could not determine the crop grown
 (2.3% of all area surrounding sampling locations); hedgerow (1.8%); crop
 land where potentially resource‐providing crops were grown, but floral
 resources were not measured (0.7%); and soybean (10%), which is of
 uncertain value as a floral resource for bees. There is some anecdotal
 evidence for cross‐pollination by honey bees resulting in increased
 soybean yields (Ahrent & Caviness, 1994; Erickson et al., 1978),
 and 29 species of wild bees (including eight of the species observed in
 this study) have been found visiting soybean in Delaware, Wisconsin, and
 Missouri, USA (Rust et al., 1980). However, many varieties of soybean are
 cleistogamous, or self‐fertilize before flowers open, and insect
 pollination of Ontario‐grown varieties is not expected to increase yields
 (OMAFRA, 2015). <strong>Bee
 observations</strong> Bee
 observation methods were adapted from frequently used pollinator surveying
 designs (Alarcón et al., 2008; Gibson et al., 2011; Memmott, 1999). At
 each sampling location, a transect was set up to survey bee activity
 within a 30 m × 4 m area (89 transects); a 30 m × 2 m area was surveyed
 when only one crop row (&lt; 4 m wide) was present (eight transects);
 and 25 m × 4 m (one transect) or 24 m × 4m areas (four transects) were
 surveyed when crop rows were shorter than 30 m. Bee observations occurred
 over 1 min per 4 m2 of transect intervals by slowly walking the length of
 the transect. The shaded and unshaded temperature, maximum wind speed, and
 average wind speed were recorded for at least 1 min using a Kestrel® 2000
 Pocket Weather® Meter (Nielsen‐Kellerman) held at approximately 1.5 m
 above ground preceding each observation period. If there was a noticeable
 change in conditions during the observation period, temperature and wind
 speed were recorded again at the end of the period and averages were
 recorded. All bee observations were conducted when shaded temperatures
 were above 11.9°C (mean ± SD = 25.3°C ± 4°C), average wind speeds were
 below 1.9 m/s, and maximum wind speeds were below 4 m/s.
 During observation periods, all occurrences of bees visiting open
 flowers were recorded by two observers, standing on either side of the
 transect width, and recording all visits within 2 m each. A visit was
 counted when a bee was seen contacting sexual organs of an entomophilous
 flower or was probing a flower for nectar. All visited flowers were
 identified to genus (9 out of 77 taxa) or species (68 out of 77 taxa), and
 bees were identified on the wing to genus or species. When identification
 was not possible on the wing, observations were paused and both observers
 attempted to catch the bee to take a photograph from inside a glass vial
 or to collect it as a voucher (79 specimens total). Vouchers were then
 identified to species or genus and are stored in the Forrest
 laboratory's collection at the University of Ottawa (Ottawa, ON,
 Canada). Overall, 82% of bees were identified to species, 17% to genus,
 0.1% to family, and 1% as Anthophila. The full list of bee taxa can be
 found in Table S2. Floral
 resources Floral density was recorded at
 each sampling location, using three quadrats of 1.5 m × 1.5 m. Quadrats
 were placed in random locations within the same transect used for bee
 observations, immediately following the observation period. If no open
 flowers were present in all three quadrat locations, an additional
 location was randomly selected and the mean count across the four quadrats
 was recorded. Within a quadrat, the number of open flowers was counted for
 each nongraminoid species encountered; for species with many‐flowered
 inflorescences, five individuals were haphazardly selected, and the number
 of flowers was counted on a randomly selected inflorescence. The mean
 number of flowers per inflorescence for many‐flowered species was then
 multiplied by the number of inflorescences in a quadrat to obtain the
 number of flowers per quadrat. In members of the Asteraceae family,
 capitula were treated as single flowers (see Table S3 for descriptions of
 floral units used for counts of each species). For 29 out of 96 species
 encountered, the number of flowers per inflorescence was obtained from
 either literature sources or digital images of herbarium specimens because
 of the large number of flowers encountered in the field or because (in a
 few cases) the species was inadvertently overlooked in the field (see
 Table S3 for literature values for each species). To
 estimate the amount of floral resources (nectar and pollen) provided by a
 species, floral dimensions were measured on five haphazardly selected
 individuals of each species. The length and width of the receptacle (or
 capitulum in Asteraceae species) were measured at right angles to each
 other, as well as the height from the receptacle to the end of the longest
 sexual organ (stamen or pistil); in species with sexual organs completely
 hidden within a corolla, height was measured from the receptacle to the
 end of the corolla. Measurements were made using calipers and were rounded
 to the nearest 1 mm. Thirty‐one of 96 species were not measured in the
 field, and floral measurements were instead obtained from literature
 sources or digital images of herbarium specimens (see Table S3 for
 measurements and literature sources for each species). Floral measurements
 were used to calculate both the surface area of flowers (<i>A
 </i>= π<i>ab</i>) and the volume of flowers
 (<i>V</i> = π<i>abh</i>), where a is the
 semi‐major axis, or half the length or width (whichever was longest) of a
 flower's receptacle or capitulum, b is the semi‐minor axis, or half
 the length or width (whichever was shortest) of a flower's receptacle
 or capitulum, and h is the height of a flower or inflorescence (Figure 2c
 and Table S3). To determine which measurement of floral
 dimensions was the best proxy for floral resource amount, literature
 searches for daily nectar sugar mass (µg/day) and pollen volume (in
 µl/flower) were conducted for all flowering species encountered; these
 measurements have been previously used to assess floral resources
 available to pollinators (Baude et al., 2016; Hicks et al., 2016).
 Literature sources that provided counts of pollen grains per flower and
 volumes of individual pollen grains were used to calculate an estimate of
 pollen volume per flower for species for which we could not find
 measurements of total pollen volume. Nectar sugar mass was obtained for 46
 species and pollen volume for 33 species of the 96 encountered (see Tables
 S4–S5 for full species lists). Pearson correlations between nectar sugar
 mass or pollen volume and the length, width, height, surface area, and
 volume measurements of each species (all variables log‐transformed to
 approximate normal distributions) were used to determine which floral
 dimension could best estimate the amount of floral resources. In addition,
 to determine whether the source of floral volume measurements (literature,
 in‐field measurements, or combination of both; see Table S3) influenced
 the relationship between floral volume and either nectar or pollen, we ran
 ANCOVAs on daily nectar sugar mass and pollen volume as functions of
 floral volume, measurement source, and their interaction. The interaction
 was nonsignificant for both nectar (F<sub>2,40</sub> = 0.82, p
 = .45) and pollen (F<sub>2,28</sub> = 0.18, p = .83),
 indicating that it was reasonable to combine data sources.
 For all bee genera other than <em>Peponapis</em>, the
 abundance of floral resources in the landscape surrounding each sampling
 location was calculated by determining the mean floral resource value per
 flower of each species and multiplying this value by the count of each
 flower in a quadrat. <em>Peponapis</em> collect pollen
 exclusively from squash (<em>Cucurbita</em> spp.; Hurd et al.,
 1974), and we only observed <em>Peponapis</em> visiting squash
 and cucumber (<em>Cucumis</em> <em>sativus</em>)
 flowers (both Cucurbitaceae). Therefore, in models of
 <em>Peponapis</em> visits, the abundance of floral resources
 in the landscape surrounding each sampling location was calculated from
 the mean floral resource value per squash or cucumber flower. While other
 bee genera such as <em>Andrena</em> likely included some
 oligolectic (pollen‐specialist) species, we included all rewarding plant
 taxa in calculations of floral resources for genera other than
 <em>Peponapis</em>, as oligolectic species would make up a
 much smaller proportion of the total than in
 <em>Peponapis</em>. Furthermore, collectively, all oligolectic
 species within other genera would likely be specialized on pollen from
 multiple taxonomic groups, rather than a single family as in
 <em>Peponapis</em>. The mean abundance of floral resources per
 1 m2 was then calculated across quadrats for each transect, and the median
 of the transect‐level values was calculated for each land type during each
 time period. This number was then multiplied by the total area of each
 land type within 250, 500, and 750 m around a sampling location to obtain
 an estimate of the total floral resources at a given spatial scale during
 a given time period.
description: Guezen_Forrest_shapefiles_2021 folder: See ReadMe file
 included. Bee_visits.csv, Floral_counts.csv,
 Full_dataset.csv: See ReadMe_for_CSV_files.csv for description of all
 columns.