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Seasonality of floral resources in relation to bee activity in agroecosystems


Guezen, Jessica M.; Forrest, Jessica R. K. (2021), Seasonality of floral resources in relation to bee activity in agroecosystems, Dryad, Dataset,


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.


Study sites and landscape structure

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‐Apis 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).

Bee observations

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 (< 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 (A = πab) and the volume of flowers (V = πabh), 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 (F2,40 = 0.82, p = .45) and pollen (F2,28 = 0.18, p = .83), indicating that it was reasonable to combine data sources.

For all bee genera other than Peponapis, 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. Peponapis collect pollen exclusively from squash (Cucurbita spp.; Hurd et al., 1974), and we only observed Peponapis visiting squash and cucumber (Cucumis sativus) flowers (both Cucurbitaceae). Therefore, in models of Peponapis 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 Andrena likely included some oligolectic (pollen‐specialist) species, we included all rewarding plant taxa in calculations of floral resources for genera other than Peponapis, as oligolectic species would make up a much smaller proportion of the total than in Peponapis. 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 Peponapis. 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.

Usage Notes

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.


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