DOI: 10.5061/dryad.z34tmpgcf
title: Red and white clover provide food resources for honeybees and wild bees in urban environments

description: 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.
description: <b>Study sites</b> 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 (&lt; 5 000 m², n = 8), intermediate parks (10 000 –
 250 000 m², n = 7) and large green areas (&gt; 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 <i>Trifolium repens</i>
 and <i>T. pratense</i>. 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). <b>Pollinator
 observations and collection</b> We conducted pollinator
 observations between June 7<sup>th</sup> and July
 17<sup>th</sup> 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 <i>Trifolium</i> 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
 <i>Trifolium</i> 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 <i>Trifolium </i>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. <i>Bombus </i>cf
 <i>lapidarius</i>) 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.
  
 <b>Pollinator frequency and total visitation frequency of
 the two <i>Trifolium</i> species</b> For each <i>Trifolium
 </i>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
 <i>Trifolium</i> 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 <i>Trifolium</i>
 species.  
 <b>Assessing differences within the pollinator
 community</b> We divided all observed
 pollinators into six taxonomic groups: <i>Apis mellifera</i>,
 <i>Bombus </i>cf.<i> lapidarius</i>,
 <i>Bombus </i>cf.<i> pascuorum</i>,
 <i>Bombus </i>sp., “other Apoidea”, and “other insects”. The
 group “<i>Bombus </i>sp.” included different
 <i>Bombus</i> species observed in lower abundances (e.g.
 <i>Bombus </i>cf. <i>hortorum</i>, <i>Bombus
 </i>cf.<i> terrestris</i>, <i>Bombus </i>cf.
 <i>humilis</i>) and may have also included additional
 individuals of <i>B. </i>cf.<i> pascuorum</i> and
 <i>B. </i>cf.<i> lapidarius</i>, which could not
 be identified with certainty, as well as other or unidentified individuals
 of the genus <i>Bombus</i>. The group “other Apoidea” included
 individuals of the superfamily Apoidea (e.g. genera:
 <i>Hylaeus</i>, <i>Andrena</i>) or individuals of
 the family Halictidae (e.g. genera: <i>Halictus</i>,
 <i>Lasioglossum</i>). The group “other insects” included
 infrequent insect pollinators, including Lepidoptera, Coleoptera and
 Syrphidae as well as other unidentified Hymenoptera.
 <b>Seed set</b> 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
 <i>Trifolium</i> 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
 <i>Trifolium</i> 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.   <b>Local
 scale: recording flower resource availability and
 diversity</b> To assess local flower resource
 availability, we recorded the number of anthetic and withered
 <i>Trifolium</i> 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).
   <b>Landscape context: recording the
 percentage of surrounding green area</b> 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").