A dataset of nectar sugar production for flowering plants found in urban green spaces

1. Nectar and pollen are floral resources that provide food for insect pollinators, so quantifying their supplies can help us to understand and mitigate pollinator declines. However, most existing datasets of floral resource measurements focus on native plants found in rural landscapes, so cannot be used effectively for estimating supplies in urban green spaces, where non- native ornamental plants often predominate. 2. We sampled floral nectar sugar in 225 plant taxa found in UK residential gardens and other urban green spaces, focussing on the most common species. The vast majority (94%) of our sampled taxa are non- native, filling an important research gap and ensuring these data are also relevant outside of the United Kingdom. 3. Our dataset includes values of daily nectar sugar production for all 225 taxa and nectar sugar concentration for around half (102) of those sampled. Nectar extraction was conducted according to published methods, ensuring our values can be combined with other datasets. 4. We anticipate that the two main uses of these data are (1) to estimate the nectar production of habitats and landscapes and (2) to identify high- nectar plants of conservation importance. To increase the utility of our data, we provide guidance for scaling nectar values up from single flowers to floral units, as is commonly done in field studies.


| INTRODUC TI ON
In an attempt to understand and mitigate insect pollinator declines (Biesmeijer et al., 2006;Powney et al., 2019;Soroye et al., 2020), some research has focussed on measuring the supplies of the floral resources on which they feed (e.g. Baude et al., 2016;Flo et al., 2018;Timberlake et al., 2019). Quantifying nectar sugar (and occasionally also pollen) production has allowed researchers to estimate floral resources at a landscape or even national scale Flo et al., 2018;Tew et al., 2021), describe temporal trends and identify However, most existing datasets of floral resource measurements focus on native plants found in rural landscapes, so cannot be used effectively for estimating supplies in urban green spaces, where non-native ornamental plants often predominate.
2. We sampled floral nectar sugar in 225 plant taxa found in UK residential gardens and other urban green spaces, focussing on the most common species. The vast majority (94%) of our sampled taxa are non-native, filling an important research gap and ensuring these data are also relevant outside of the United Kingdom.
3. Our dataset includes values of daily nectar sugar production for all 225 taxa and nectar sugar concentration for around half (102) of those sampled. Nectar extraction was conducted according to published methods, ensuring our values can be combined with other datasets. 4. We anticipate that the two main uses of these data are (1) to estimate the nectar production of habitats and landscapes and (2) to identify high-nectar plants of conservation importance. To increase the utility of our data, we provide guidance for scaling nectar values up from single flowers to floral units, as is commonly done in field studies.

K E Y W O R D S
conservation, floral resources, flowers, gardens, nectar, pollinators, urban seasonal gaps in their supply (Jachuła et al., 2021;Tew et al., 2022;Timberlake et al., 2019), predict the impact of management interventions (Hicks et al., 2016;Timberlake et al., 2021), investigate factors limiting pollinator populations (Timberlake et al., 2021) and characterise the accessibility of resources to different insect groups (Tew et al., 2022). In addition, floral resource data are used by other stakeholders, including non-governmental organisations and conservation practitioners, with the aim of improving habitats for foraging pollinators. For example, Plantlife's 'Every Flower Counts' is a citizen science initiative which encourages participants to count the flowers of different species in their garden lawn, combining these values with floral resource measurements to give a 'Personal Nectar Score', along with suggestions for its improvement. There is an increasing appreciation of the importance of flowering plant communities in urban green spaces for insect pollinators (Baldock, 2020;Baldock et al., 2019;Lowenstein & Minor, 2016), but we cannot quantify the supply of floral resources without empirical measurements of nectar or pollen production for the appropriate species. These flower-level assessments are also valuable in identifying particularly resource-rich plants which should be prioritised in pollinator-friendly planting schemes (Hicks et al., 2016).
Here, we present a dataset of floral nectar sugar production values for 225 plant taxa found in UK residential gardens and other urban green spaces (where a taxon is either a species, hybrid or cultivar). Many of these plants are also common in urban landscapes in other countries. We focus on nectar rather than pollen sampling because nectar is the main energy source in the diets of adult pollinators and has a less complex nutritional profile than pollen (Vaudo et al., 2015). Our methods for measuring nectar sugar production follow those of Baude et al. (2016) and Hicks et al. (2016), allowing our datasets to be combined (as in Tew et al., 2021Tew et al., , 2022. After describing the dataset and the sampling methods, we subsequently provide usage notes and explore some general patterns.

Nectar measurements of the 225 flowering plant taxa took place in
March-October 2018 (220 taxa) or February-April 2019 (five taxa) at field sites in southern England, which included public and private gardens, allotments, garden centres and road verges (Table 1). Sites typically comprised a variety of urban land uses, including ornamental borders and shrubberies, lawns, paths and hard standing. Where possible (97 taxa), taxa were sampled at two or three locations on different days to account for variation due to site, weather and plant variety. We selected the plant taxa for sampling primarily based on a study by Baldock et al. (2019), who surveyed floral abundance from April to September in 360 sites spanning nine land use types in four UK cities. Our dataset focuses on the plants they recorded with the highest overall floral counts (with 88% of our sampled genera found in their study), supplemented with some common taxa which flower outside of their survey period.
Following Baude et al. (2016), insects were excluded from the flowers to be sampled by mesh bags (pore size 1.4 mm × 1.7 mm) for 24 ± 2 h, providing a measure of nectar accumulation over a one-day period ( Figure 1). After bagging, and between the hours of 08:30 to 18:00, flowers were removed and nectar extracted by one of two methods using glass microcapillaries (0.5 to 20 μL Minicaps, Hirshmann; Figure 1). Where possible (102 taxa), we removed nectar directly from flowers until no more could be extracted. Alternatively, where the direct extraction of nectar was not possible as the quantity was too small or viscous (123 taxa), we rinsed nectaries with 0.5-10 μL of distilled water, added with a pipette. Sugar residues were left to dissolve for 1 min before all the solution was removed using microcapillaries and the process repeated one further time.
The concentration of the extracted solution (C; g of sugars per 100 g solution) was measured using a handheld refractometer with a lid

| USAG E NOTE S
For each of the 225 plant taxa, the dataset associated with this article includes its native status, life form, the nectar extraction method and sites where flowers were sampled, the nectar sugar mass per flower, the nectar sugar concentration (where applicable, see Section 2), the floral unit category, the number of flowers per floral unit and the nectar sugar mass per floral unit. The two main uses of these data are (1) to estimate nectar production at larger spatial scales (e.g. quadrats, habitat patches or entire landscapes), which requires multiplying by values of floral abundance (e.g. Hicks et al., 2016;Tew et al., 2021Tew et al., , 2022, or (2) to identify particularly nectar-rich species to include in pollinator-friendly planting schemes. In addition, researchers could investigate how phylogeny and floral traits predict nectar production or nectar sugar concentration using statistical models (e.g. Tew et al., 2021Tew et al., , 2022. Two important limitations of our presented nectar values are that (1) taxa are often represented by only one or a few different sampled varieties (see Tew et al., 2021) and (2) measures of 24-h nectar accumulation may underestimate the potential maximum secretion under repeated insect visitation (Carisio et al., 2022).
When recording floral abundance in the field, researchers often count floral units, which are commonly defined as single flowers or collections of flowers that insect pollinators can walk within but must fly between (Baldock et al., 2015;Carvalheiro et al., 2008). The sites used for nectar sampling in the field in this study. Each taxon was sampled at either one (128), two (88) or three (9) different sites. before taking a mean value by which to multiply. In this dataset, we assign floral units following Baldock et al. (2015Baldock et al. ( , 2019 and report the daily nectar sugar production value at both the flower and floral unit levels.

F I G U R E 3
Mean daily nectar sugar production of taxa (n = 225) at the flower level (bin width = 500 μg).

F I G U R E 4
Mean nectar sugar concentration of taxa (n = 102) at the flower level (bin width = 5%).
contributing critically to the drafts; Jane Memmott, Katherine C. R.
Baldock, Stephanie Bird and Ian P. Vaughan acquired funding. All authors gave final approval for publication.

This work was supported by the Natural Environment Research
Council through the NERC GW4 + Doctoral Training Partnership (NE/L002434/1) and by a grant from the Royal Horticultural Society (RHS). We would also like to thank all the landowners who gave us permission to sample flowers and Dr Jordan Bilsborrow (RHS) for help with plant taxonomy.

CO N FLI C T O F I NTE R E S T S TATE M E NT
The authors have no conflict of interest to declare.

PE E R R E V I E W
The peer review history for this article is available at https:// w w w.w e b o f s c i e n c e . c o m /a p i /g a t e w a y/ w o s /p e e r-r e v i e w/10.1002/2688-8319.12248.

DATA AVA I L A B I L I T Y S TAT E M E N T
The dataset associated with this publication, along with information for its use, is available from the Dryad Digital Repository https://doi.