Data from: The contributions of flower strips to wild bee conservation in agricultural landscapes can be predicted using pollinator habitat suitability models
Data files
Sep 01, 2023 version files 1.48 GB
Abstract
Sowing flower strips along field edges is a widely adopted method for conserving pollinating insects in agricultural landscapes. To maximize the effect of flower strips given limited resources, we need spatially explicit tools that can prioritize their placement, and for identifying plant species to include in seed mixtures.
We sampled bees and plant species as well as their interactions in a semi-controlled field experiment with roadside/field edge pairs with/without a sown flower strip at 31 sites in Norway and used a regional spatial model of solitary bee species richness to test if the effect of flower strips on bee species richness was predictable from the modelled solitary bee species richness.
We found that sites with flower strips were more bee species rich compared to sites without flower strips and that this effect was greatest in areas that the regional solitary bee species richness model had identified to be particularly important for bees. Spatial models revealed that even within small landscapes there were pronounced differences between field edges in the predicted effect of sowing flower strips.
Of the plant species that attracted the most bee species, the majority mainly attracted bumblebees and only few species also attracted solitary bees. Considering both the taxonomic diversity of bees and the species richness of bees attracted by plants we suggest that seed mixes containing Hieracium spp. such as Hieracium umbellatum and Pilosella officinarum; Taraxacum spp; Trifolium repens; Lotus corniculatus; Stellaria graminea; and Achillea millefolium would provide resources for diverse bee communities in our region.
Spatial prediction models of bee diversity can be used to identify locations where flower strips are likely to have the largest effect and can thereby provide managers with an important tool for prioritizing how funding for agri-environmental schemes such as flower strips should be allocated. Such flower strips should contain plant species that are attractive to both solitary and bumblebees, and do not need to be particularly plant species rich as long as the selected plants complement each other.
README: Title of Dataset: The contributions of flower strips to wild bee conservation in agricultural landscapes can be predicted using pollinator habitat suitability models
The data contain data collected from surveys, spatial data showing the location of study sites, and raster maps and R code. The R code allows running the analyses in the manuscript and testing for the effects of flower strips on bee species richness and for using an existing spatial model of solitary bee species richness to predict the spatial effects of sowing flower strips.
The data include R code and raw data (.csv, .shp, .tif) files required to reproduce the analyses in the manuscript and print figures 2-4.
Description of the Data and file structure
R_script_for_Sydenham_et_al_2023_Ecological_Solutions_and_Evidence.R
> R script for running analyses and producing figures.
Site transect lines.shp (with: .shx,.prj,.dbf):
> Shapefile with study sites as 50m spatial lines along road sides and fieldedges.
> Contains site names for each line.
MetaData_bee_surveys.csv:
> MetaData with information on survey dates at each study site.
> Columns
> > Site: Site name
> > Collector: Initials of fieldworker
> > TransectDate: Data survey was conducted
> > TransectCut: If vegetation along road side had been cut prior to survey (TRUE) or not (FALSE)
> > Treatment: If the roadside+field edge combination contained a flowerstrip along the field edge (Flwstrp) or if the site was a control (Cntrl)
> > TransectType: If the transect was in the field edge or roadside.
Plant_survey_data.csv:
> data table containing results from plant surveys containing the columns:
> > Site: Site name.
> > SurveyDate: Date vegetation survey was conducted.
> > Collector: Initials of fieldworker.
> > PlantSpecies: Name of recorded plant species.
> > RoadPlot1: Integer ranging from 0 to 4 depending on the number of 25cm*25cm subplots the plant species was recorded in within the 1m vegetation plot located along the road side transect.RoadPlot2: Integer ranging from 0 to 4 depending on the number of 25cm*25cm subplots the plant species was recorded in within the 1m vegetation plot located along the road side transect.
> > RoadPlot3: Integer ranging from 0 to 4 depending on the number of 25cm*25cm subplots the plant species was recorded in within the 1m vegetation plot located along the road side transect.RoadPlot4: Integer ranging from 0 to 4 depending on the number of 25cm*25cm subplots the plant species was recorded in within the 1m vegetation plot located along the road side transect.
> > RoadPlot5: Integer ranging from 0 to 4 depending on the number of 25cm*25cm subplots the plant species was recorded in within the 1m vegetation plot located along the road side transect.FieldPlot1: Integer ranging from 0 to 4 depending on the number of 25cm*25cm subplots the plant species was recorded in within the 1m vegetation plot located along the field edge transect.
> > FieldPlot2: Integer ranging from 0 to 4 depending on the number of 25cm*25cm subplots the plant species was recorded in within the 1m vegetation plot located along the field edge transect.FieldPlot3: Integer ranging from 0 to 4 depending on the number of 25cm*25cm subplots the plant species was recorded in within the 1m vegetation plot located along the field edge transect.
> > FieldPlot4: Integer ranging from 0 to 4 depending on the number of 25cm*25cm subplots the plant species was recorded in within the 1m vegetation plot located along the field edge transect.FieldPlot5: Integer ranging from 0 to 4 depending on the number of 25cm*25cm subplots the plant species was recorded in within the 1m vegetation plot located along the field edge transect.
> > PlantAbundance: Sum of subplots the plant species occured in.
Bee survey data:
> data table containing results from bee surveys containing the columns:
> > Site: Site name.
> > DateR: Date survey was conducted.
> > Treatment: If the study site contained a flowerstrip (FLWRSTRP) or not (CONTRL) along its field edge.
> > Specimen_ID: Unique identifier of the collected bee specimen.
> > Plant: Plant species the bee specimen was collected on.
> > Species: Bee species.
PolliLandPredictionMap.tif
> Rastermap with regional prediction model of solitary bee species richness. For reference see Sydenham et al., 2022. High resolution prediction maps of solitary bee diversity can guide conservation measures. Landscape and Urban Planning, 217, p.104267.
Predicted_flower_strip_effect_size_map.tif
> Rastermap showing the predicted effect of adding a flowerstrip.
The folowing files are included in order to produce figure 3 in the manuscript:
Predicted_flower_strip_effect_size_map_masked_to_field_edges.tif
Cropped_field_edges_raster.tif (and Cropped_field_edges_raster.tif.aux.xml)
Sat_image_for_figure_3.tif (and Sat_image_for_figure_3.tfw)
Sat_image_w_edges_for_figure_3.tif (and Sat_image_w_edges_for_figure_3.tfw)
Sat_image_w_edges_w_preds_for_figure_3.tif (and Sat_image_w_edges_w_preds_for_figure_3.tfw)
Sharing/access Information
> Not applicable
Was data derived from another source?
> Not applicable
Methods
We used a paired design of study sites located in Southeastern Norway consisting of a field edge and an adjacent vegetated roadside, with or without a sown flower strip in the field. During early spring (April) 2022, we used data from Vestfold/Telemark County Governor’s office to identify sites where farmers had previously (in 2021 and sometimes also in 2020) sown a flower strip along the field edge. We included sites in our study if farmers were also planning to sow a flower strip along the same field edge in 2022. Species composition of the flower strips varied, but Phacelia tanacetifolia, Trifolium pratense and Trifolium repens were commonly used in the seed mixtures. We paired each flower strip site with a control site (i.e. study site without flower strip) with a road side of similar width, located between one and five kilometers from the flower strip site. We considered our samples as independent, i.e. that they sampled different bee communities, because distances of one km or greater are beyond the typical foraging range of most wild bees in our region. At one of the indended control sites, the farmer did sow a flower strip in 2022 and for another site we did not find a suitable control site. Our resulting study design consisted of 17 flower strip sites with a vegetated roadside and a flower strip, and 14 control sites with a vegetated roadside and without a flower strip.
At each site we sampled wild flower-visiting bees with an entomological net by walking slowly for 20 minutes along two 50m transects placed in the vegetated road- and field edge, respectively. To account for handling time, we added 30 seconds sampling time per collected specimen. For our samples to cover seasonally distinct parts of the local bee communities, we conducted three surveys during the summer of 2022: in late May (early summer), late June/early July (summer), and late July (late summer). Because of unstable weather we were only able to sample 25 of the 31 sites during the first survey. All flower-visiting bees collected were kept in 50ml falcon tubes filled with 96% ethanol, labelled according to date, collector identification, site, habitat (roadside vs. field edge), and plant species. Collected bees were identified by the lead author. Voucher specimens are stored in the entomological collections at the Norwegian Institute for Nature Research in Oslo. In July, we placed five 1m2 square vegetation plots regularly along the 50m transects with one plot per ten meters. In each 1m2 vegetation plot we recorded the occurrence of forb and shrub species in four 25 by 25 cm sub-plots. We recorded all species regardless of growth stage so that our single plant survey provided estimates of the relative frequency of plant flowering during and outside the survey period.
Usage notes
Data and associated R script can be opened and run using R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.