Pollination is a key ecological process both in wild plant species and in economically important crops. Global land use change and urbanization are known to alter plant-pollinator interactions, but our understanding of how the local (i.e. size of green area, food resource availability) and landscape (surrounding green area) context affect pollinators in urban landscapes remains understudied. We selected two co-occurring clover species, Trifolium pratense and T. repens. to assess whether mixed stands of common wildflowers provide resources for a diverse pollinator assemblage by supporting differently adapted/specialized pollinator species. We further wanted to test how environmental factors (flower diversity, resource availability, size and percentage of green area) alter plant-pollinator interactions in urban environments. We studied the pollinator assemblage and visitation rate of pollinators in 1 m² plots in 21 green areas of different sizes in the city of Vienna (Austria). In addition, we assessed the surrounding landscape context by estimating the percentage of green area in perimeters of 100 m, 500 m and 1000 m around each study plot and measured local flower resource availability. We found that proportions of pollinator taxa differed significantly between white and red clover, with T. repens mainly pollinated by Apis mellifera, and T. pratense primarily pollinated by different bumblebee species. Visitation frequency was positively correlated to local resource availability (number of anthetic Trifolium inflorescences in each plot), but independent of the surrounding landscape context (i.e. percentage of green area). We conclude that the establishment and maintenance even of small patches of different common wildflowers help maintain a diverse bee community in urban environments. Particularly large-flowered species may be important for supporting long-tongued, late emerging pollinators such as certain bumblebee species.

Study sites

Our study was conducted in the city of Vienna, Austria, in June and July 2018. We selected a total of 21 sites (Table S1), each composed of mostly continuous vegetation, mainly grass. To investigate the effect of green area size on pollinator compositions and frequency, we studied three categories of sites: small patches (< 5 000 m², n = 8), intermediate parks (10 000 – 250 000 m², n = 7) and large green areas (> 400 000 m², n = 6), referred to as “study site categories” from here onwards. The percentage of green area in and around each site was further described (see sections on “Landscape context” below). Site locations were selected to achieve a balanced design of sites located close to the city centre, with higher percentage of sealed surfaces and at the outskirts of the city (Figure 1).

In each site, we selected a plot of 1 m² for pollinator observations, including at least eight blooming inflorescences of both Trifolium repens and T. pratense. We recorded the respective number of anthetic and withering inflorescences of both study species for further analyses on pollinator visitation frequency and seed set. We recorded the GPS coordinates of the observation plots on a smartphone using the application “My GPS coordinates” (TappiApps for Android Version 1.74 released February 2017).

Pollinator observations and collection

We conducted pollinator observations between June 7^th and July 17^th 2018. Each plot was visited on a single day between 10 am and 4 pm under good weather conditions (sunny, no permanent cloud cover, minimum temperature 18 °C). Once per hour, we additionally recorded cloud cover (proportion of sky covered by clouds, estimated in eighths). We alternated observations between study site categories to minimize effects of phenological turnover in pollinator community composition on our analyses of the impact of green area size (also see Figure S1, S2). Please note that visitation of each site only once does not allow for assessing potential differences in pollinator assemblages between sampling days, but was our method of choice in order to provide comparable and accurate data in the light of frequent and unpredictable mowing.

During observations, of both Trifolium species at the same time, one or two observers sat near the plot and recorded pollinators for 15 minutes per hour, for six hours, resulting in a total observation time of 1 ½ hours per plot. We recorded each insect that visited an inflorescence and counted the number of inflorescences it visited in the plot. Based on the insects’ behaviour, we differentiated visitors, which only landed or crawled on the inflorescence, from pollinators, probing flowers by inserting their head into the corolla and thereby contacting the reproductive parts of the flowers. Subsequently, for the statistical analyses we only looked at the potential pollinators. Pollinators showed high flower constancy so that we did not count shifts between the two Trifolium species. We took pictures of all visitors and pollinators and classified them into morpho-species for later identification (see below).

To identify pollinator morpho-species, we added a 15-minute collection round after each 15-min observation round. In each observation plot, we collected a maximum of five specimens per pollinator morpho-species. We caught the insects in small plastic tubes while they probed Trifolium flowers and immediately put them on ice in an insulation box. At the end of each observation day, we froze pollinators at -18 °C in the laboratory of the Department of Botany and Biodiversity Research (University of Vienna), and later mounted them for identification. We identified bumblebees using Gokcezade et al. (2017) and other bees with the help of specialists (Florian Etl and Martin Streinzer). When possible, we identified the pollinators to species level, otherwise to genus level or above. We chose to circumscribe pollinator taxa broadly (i.e. Bombus cf lapidarius) since we would have had to capture and kill all visiting insects for reliable identification. Given the decline of many insect taxa in urban environments, and the nature conservation aspect of our work, we refrained from the collection of all insects.

Pollinator frequency and total visitation frequency of the two Trifolium species

For each Trifolium species, we calculated pollinator frequency as the number of visits of a potential pollinator taxon per inflorescence per hour. We further calculated the total visitation frequency for each Trifolium species as the total number of pollinating insects visiting each species per inflorescence per hour. From here onwards, we use the term “pollinator frequency” when referring to single insect taxa, and “total visitation frequency” when comparing frequencies summed across all pollinators for each Trifolium species.

Assessing differences within the pollinator community

We divided all observed pollinators into six taxonomic groups: Apis mellifera, Bombus cf. lapidarius, Bombus cf. pascuorum, Bombus sp., “other Apoidea”, and “other insects”. The group “Bombus sp.” included different Bombus species observed in lower abundances (e.g. Bombus cf. hortorum, Bombus cf. terrestris, Bombus cf. humilis) and may have also included additional individuals of B. cf. pascuorum and B. cf. lapidarius, which could not be identified with certainty, as well as other or unidentified individuals of the genus Bombus. The group “other Apoidea” included individuals of the superfamily Apoidea (e.g. genera: Hylaeus, Andrena) or individuals of the family Halictidae (e.g. genera: Halictus, Lasioglossum). The group “other insects” included infrequent insect pollinators, including Lepidoptera, Coleoptera and Syrphidae as well as other unidentified Hymenoptera.

Seed set

Our one-day pollinator observations only give a snapshot idea of potential differences in pollinator frequencies at each site and may be influenced by current conditions such as recent mowing or weather. Since each Trifolium plant produces many flowers per inflorescence and flowers for several days, we also assessed seed set to obtain a second measure of pollinator performance in the different sites. On the same day as when performing the pollinator observations, we harvested and dried a total of three, at least ⅔ withered, inflorescences per Trifolium species and site. Whenever enough withered inflorescences where available, we took them from the 1m² plot, otherwise collected them in the immediate surrounding. We randomly chose 10 withered flowers per inflorescence (n = 630 flowers per species) and removed the seeds from the ovaries by gently grinding each withered flower between the fingers. We then examined them under a stereomicroscope to differentiate aborted from developing seeds, and calculated the average number of initiated seeds per flower. We further counted the number of flowers per inflorescence and extrapolated the averaged seed set to the inflorescence level. This way we obtained an averaged seed set per inflorescence for the respective plot.

Local scale: recording flower resource availability and diversity

To assess local flower resource availability, we recorded the number of anthetic and withered Trifolium inflorescences of both study species in each observation plot (Table S2). To further characterize flowering resources in the immediate surroundings of each observation plot, we recorded flower diversity along 5 m transects starting at the four edges of each plot and extending in the four cardinal directions. We included all plant species flowering on the day of observations and potentially offering pollinator rewards, thereby excluding wind-pollinated graminoids. We counted all inflorescences in a 10 cm wide strip along these transects. From these data, we calculated the Shannon diversity index (Shannon and Weaver 1949) of each plot as an estimate of resource diversity (Table S2).

Landscape context: recording the percentage of surrounding green area

To quantify the urban aspects of the landscape context, we used the OpenStreetMap data with land-use information for Vienna (GeofabrikGmbH and OpenStreetMap Contributors 2018, Stadt Wien 2014) as data basis in ArcGIS 10.5 (ESRI 2016). We loaded the GPS-points of our observation plots into the map. Around each observation plot, we conducted a buffer-analysis to characterize the relative amounts of different land cover types, using the geoprocessing tool “Buffer”. We characterized the types of land cover in perimeters of 100 m, 500 m and 1 000 m around each observation plot (Fig. 1B). We distinguished green areas (vegetated surfaces like gardens, parks, grass areas along roads, sport courts) from other landcover types (i.e. sealed surface, traffic, and waterbodies). We then calculated the percentage of green area in the given perimeter around each observation plot (Fig. 1B, Table S1). All data files are in the projected coordinate system MGI_Austria_GK_M34.

The provided datasets consist of the data on pollinator frequency (per taxon per plot per hour) that were used to assess differences in the pollinator assemblages between the two Trifolium species ("poll_diversity.xlsx"), and total visitation frequency or seed set, together with the environmental variables (local resource availability, shannon diversity index, percentage of green areas, "visitrate_environment.xlsx").