E-mail Address Invalid Input. Recipient Name Invalid Input. Recipient E-mail Invalid Input. Which plants are bees attracted to? Why is it important to plant honey plants? Which plants produce the most nectar? Carniolan honey bee For bees, the most important plants in nature are: spring vegetation, such as hazel, snowdrops, primroses, saffron, willow, hellebore, heather, wild cherry, dandelion; fruit trees; acacia, linden, maple, chestnut; woodland undergrowth and meadow flowers.
Bee-friendly ornamental plants Bees can also benefit from plants that we grow for decorative purposes. Nectar plants that we can plant in the garden include: Nectar-producing perennials : golden alyssum Alyssum saxatile , lilac or purple rock cress Aubrieta deltoidea , bellflower Campanula , carnation Dianthus , Phlox, candytuft Iberis , rice button aster or bushy aster Symphyotrichum dumosum , coneflowers Rudbeckia , columbine Aquilegia , peony Paeonia , common lady's mantle Alchemilla vulgaris , Leucanthemum, lily, daylily Hemerocallis , larkspur Delphinium , purple coneflower Echinacea purpurea , yarrow Achillea millefolium , speedwell Veronica , thimbleweed or windflower Anemone hupehensis , rockfoils Saxifraga , lily of the valley Convallaria majalis , cranesbill Geranium , showy stonecrop or ice plant Hylotelephium spectabile , stonecrop Sedum , Primula, common houseleek Sempervivum tectorum.
Nectar quantification followed one of two protocols see S2 File for detailed methods. When possible, nectar was collected directly using 1.
We sampled 9. Where volumes of nectar were too small or concentrations of nectar too high to use this approach, nectar sugar was harvested by using a fine Gilson pipette to flush flowers with a known volume of distilled water and the Brix sugar content of the resulting solution estimated using a sucrose refractometer [ 57 ].
The mass of sugar contained was estimated as above. Pollen per flower was estimated for all species using flowers collected in Edinburgh treatment meadows in and , for a total of 15, flowers across 64 species see S3 File for detailed methods. Pollen was harvested using sonication Dawe sonicleaner from flowers that opened and dehisced in the lab.
Sample size information for resource quantification in each species is provided in S1 Table , from a mean of Pollen resource per floral unit per 24h was estimated by dividing the pollen volume per floral unit by floral longevity in days.
This approach does not assume that pollen release is constant during the lifetime of each flower, but does assume that the proportion of flowers in the sampled population in each stage of pollen release if it varies through floral life was stable at the time longevity was measured see below. We explored the predictability of pollen volume per flower or per floret for Asteraceae from floral morphology, using a linear model incorporating anther size and number of stamens as predictors in the base R package [ 61 ].
Galium verum , Stellaria media ; to a maximum anther volume of ca. Ranunculus spp. The regression model was fitted and checked for non-violation of assumptions of linearity, normality and homoscedasticity by inspection of residuals, fitted values and quantile plots. We tested the predictive power of our model by estimating per-flower pollen volumes for a validation data set comprising 43 species quantified using the same lab protocol Baude et al.
Species in the validation data set were selected to span the same range of measured pollen volumes. We attempted to develop similar predictive models for nectar sugar per flower based on the floral morphology traits of corolla diameter and corolla length. No useful predictive model resulted from this approach. Floral unit longevity was estimated by scoring the numbers of newly opening and newly closed i.
To meet the assumptions of this approach as closely as possible, species were observed in the middle of their flowering period. Sampling included the full range of flower ages, totalling approximately 50 flowers distributed on at least five plants. Longevity data for almost all species were collected for plants from Edinburgh meadows, with additional data where necessary from sites specified in S1 Table , sampled using the same protocol.
We used quadrat surveys to quantify floral abundance in all meadows, at the level of individual flowers for all species except Asteraceae, which were sampled at the level of the capitulum. We sampled between 49 and 99 quadrats for each meadow, and then used computer simulations sampling actual transect values at random, without replacement to assess the impact of sampling increasing numbers of 1m 2 quadrats on the cumulative mean of nectar sugar mass and pollen volume per meadow S1 and S2 Figs.
In each meadow, variance in mean estimates declined sharply with increasing sample size, stabilising for each meadow and resource at a sample size of ca. We therefore sampled 20 x 1m 2 quadrats per treatment replicate per sampling interval for the Edinburgh meadows during the main survey season a total of quadrats over all treatments and sampling intervals.
The 20 quadrats were sampled at 4 m intervals along the length of the plot, alternating between edge quadrats i. For the three other cities, time constraints restricted sampling to a subset of the quadrat scheme, comprising seven edge quadrats per treatment replicate per sampling interval located at 8m intervals along the plot length. We compare the consequences of adopting the seven or quadrat scheme below using the Edinburgh data. In short, we consider the seven-quadrat estimates adequate for comparison of mean differences between treatments, and all comparisons among cities are based on data for the seven-quadrat scheme.
In , over the four cities, 80 plots and six sampling intervals, we recorded over two million flowers of plant species, from a total of quadrats. To illustrate variation among replicates we present detailed data summaries for each of the Edinburgh treatment replicates, and present the data for each meadow location in the other three cities in S4 and S5 Figs.
To allow comparison between cities, treatments and sampling time points, we use means calculated for each treatment across all time points, replicates and cities, as appropriate. We excluded from these values data for four sites at which management issues detailed below led to complete failure of the treatment relative to others in the same group.
These comprise two perennial sites and two A1 annual sites S2 Table. Resources per meadow nectar sugar mass or pollen volume were calculated as the sum across plant species of resource per flower x the number of flowers in the treatment replicate.
Statistical analyses were carried out in R version 3. Flower counts per species and summed across species and resource values showed non-normality and heteroscedasticity that could not be corrected using standard data transformations.
Variation of floral resource estimates among treatments was therefore tested using global Kruskal-Wallis tests on means calculated across all surveys for a given type i. This approach allows identification of multivariate patterns and fitting of a separate Generalised Linear Model GLM for each flowering species using a common set of explanatory variables. Resampling-based hypothesis testing within mvabund was then used to make community-level and taxon-specific inferences about which factors were associated with the multivariate abundance patterns.
For this dataset we specified a negative binomial error distribution, and checked assumptions of mean-variance and log-linearity as detailed in [ 67 ], both by plotting directly and by plotting residuals versus fitted values. We used Monte Carlo bootstrapping to estimate p-values adjusted to control the family-wise error rate across species, at the default setting of resamples. Meadows with fewer than 10 flowers or capitula in total per m 2 were excluded from the analysis.
Because NMDS only uses rank information and maps ranks non-linearly onto ordination space, it can handle non-linear species responses of any shape and robustly find underlying gradients. As the final ordination is partly dependent on the initial configuration, we used up to 99 consecutive NMDS iterations with random starting configurations to test for stability of the result. Nectar sugar estimates per 24h for the seed mix species and associated weeds are shown in Fig 1 and S1 Table.
Most of the highest values were for Asteraceae, for which a floral unit comprises an inflorescence capitulum rather than a single flower Fig 1. Both the annual and perennial mixes contained species with very low nectar sugar rewards per floral unit, including species with large individual flowers such as Papaver rhoeas 0.
Values shown are ranked means in each group mean values and standard errors are provided in S1 Table. Images of the top ranked species in each group are shown, with the highest-ranked at right. Total pollen rewards per floral unit were highest in Asteraceae sampled at the level of the entire capitulum Leucanthemum vulgare , Myosotis arvensis , 0.
Of species sampled at the level of a single flower, by far the most rewarding were the poppies, Papaver rhoeas Among weed species, values were again highest for Asteraceae, including Glebionis segetum 5.
Quantifying the contribution of each species to daily pollen resource provision at the meadow level requires scaling of total pollen volume by floral longevity, which ranged from mean values of a single day e. Cerastium fontanum , Veronica persica , Vicia hirsuta to In the annual mix, Coreopsis picta 0. The top-ranked perennial mix species by floral unit were Malva moschata 2.
The top-ranked weed species in our meadows were native Taraxacum agg. Values shown are ranked means in each group. For half of the 59 species in our modelling dataset S3 Table , fitted values were within the confidence limits of laboratory estimates. This suggests that the statistical model could be used to estimate values where no direct measurement is possible or available, and to identify outlying measured values that should perhaps be confirmed.
Examination of the single species analyses S4A Table shows that for perennial meadows, among-city differences were primarily due to varying floral abundance of three of the sown species in declining rank of deviance explained, Achillea millefolium 4. The seed mix species Achillea millefolium and Echium vulgare and the weed species Taraxacum agg.
Perennial meadows across all cities, separated by survey round. Annual meadows across all cities, separated by survey round. Perennial meadows across all survey rounds, separated by city. Annual meadows across all survey rounds, separated by city. The mix species Centaurea cyanus achieved higher floral unit densities in the north Edinburgh, Leeds than in the south Reading and Bristol , while Malcolmia maritima and the non-mix species Sonchus oleraceus and Coreopsis spp.
Differences between the A2 and A1 annual treatments S4C Table were due to significantly greater weed intrusion in A2 meadows, particularly Veronica spp. The significant treatment x city interaction for annual meadows was predominantly due to variable performance of the sown species Calendula officinalis , which had higher floral density in A1 than A2 meadows in Edinburgh and Leeds, while showing the opposite pattern in Bristol and Reading. A general pattern across mixes and replicates is that flower counts were commonly dominated by high values for a small number of species, with a distribution tail of species with very low counts.
For example, the highest number of flowers recorded for any single m 2 in a perennial meadow was 34 Edinburgh, Pilrig Park perennial meadow on 30 July , of which The highest values recorded for a single m 2 in an annual meadow was 23 Bristol, Hengrove Farm on 9 August , of which Mean flower densities for the rarest seed mix species were 3—4 orders of magnitude lower perennials Stachys sylvatica 0.
Many of the weed species recorded in our surveys had a mean density over all sampled quadrats of less than 0. Variation in meadow composition between cities and time points as revealed by NMDS and the two dominant axes of floral variation is shown in Fig 3. Stress values for these analyses were 0. Repeated iterations of NMDS nevertheless produce very similar patterns in each dataset.
No clear divergence among cities is apparent, although for annual meadows Bristol and Leeds group more closely with each other than with Edinburgh. Regional drought aside, the implication is that for each seed mix treatment, variation in meadow composition and abundance depends strongly on season and less on geographical position in the UK. All planted meadow treatments produced significantly more nectar sugar than amenity grassland controls Table 1.
Perennial meadows produced significantly more nectar than both A1 and A2 annual meadow treatments, which did not differ significantly from one another Table 1. Changes in meadow-level nectar sugar mass through the season are shown for the five Edinburgh replicates in each of the A1, A2 and P treatments in Fig 4 ; equivalent plots for the other three cities are shown in S4 Fig.
One perennial meadow Saughton, excluded from statistical analyses performed very poorly due to accidental mowing. The maximum value for any control site was for the late June survey at Morningside Park, with a mean value of Nectar productivity of perennial meadows peaked earlier in the year early August for all replicates than for annual A1 meadows which all peaked in late August or September. Annual meadows produced little or no nectar in June and July.
Data were sampled at three-week intervals through The poor performance of the Saughton perennial meadow was due to accidental mowing, and this replicate was excluded from statistical analyses. The contribution by individual species to nectar sugar in each Edinburgh meadow treatment is shown in Fig 5.
Most of the nectar sugar was provided by one or a few species at a given seasonal time point. A high proportion of early season nectar production in all treatments was contributed by native weed species—particularly Taraxacum agg. The high early August peak in nectar production of perennial meadows was largely due to abundant flowering of Daucus carota , and to a lesser extent Achillea millefolium and Echium vulgare. The percentage of total meadow nectar sugar mass attributable to each species is indicated by the height of the filled polygon for that species at a given seasonal time point.
Values at each time point are based on x 1m 2 quadrats across 5 replicate meadows at each time point for each meadow treatment. Consideration of the other three cities Fig 6 and S4 Fig shows that perennial meadows again had higher nectar abundance than both A1 and A2 annual treatments in Bristol and Leeds, and that nectar productivity in perennial meadows again peaked earlier in the year than in A1 meadows.
Perennial meadows in Reading performed poorly relative to other cities, and showed no clear seasonal peak in nectar production see Discussion. There is some evidence of a latitudinal effect in the annual meadow treatments, with nectar production increasing earlier in the year in southern cities June and July in Bristol and Reading than further north early August in Edinburgh and Leeds.
Whilst per-species estimates using the seven-quadrat sampling regime are subject to the stochastic patterns shown in S1 and S2 Figs, the same species that dominated perennial nectar sugar production in Edinburgh also dominated in the other three cities: over all cities, replicates and time points, Daucus carota contributed The annual meadows showed more heterogeneous patterns of species abundance and resource contribution, with Centaurea cyanus making the greatest contribution overall to nectar Each mix contained some species that contributed very little nectar sugar.
Across all cities, replicates and time points, seven species in the perennial mix Galium verum 0. Across all four cities, pollen production varied significantly among treatments global Kruskal-Wallis test, 3 d.
All planted meadows produced significantly more pollen than amenity grassland controls Table 2. Across the season, perennial meadows produced significantly more pollen than annual A1 meadows, while A1 and A2 annual treatments produced did not differ significantly Table 2. Changes in meadow-level pollen volume through the season are shown for the five Edinburgh replicates in each of the A1, A2 and perennial treatments in Fig 7 ; equivalent plots for the other three cities are shown in S5 Fig.
The Edinburgh meadows show the following patterns Fig 7 : i Productivity per square metre was highest in the perennial meadows, with a mean of approx. Peak values for both annual treatments were an order of magnitude lower at 0. Peak values for amenity grassland control sites were usually two to three orders of magnitude lower than for any planted sites: for 29 of the 30 Edinburgh control site surveys five sites x six sampling points through the season, mean pollen volumes were less than 0.
The highest value for any control site of 0. Pollen productivity of perennial meadows peaked earlier in the year early or late August than for annual A1 meadows late August or September. Low pollen production at two Edinburgh A2 meadows Sighthill and West Pilton was associated with high abundance of weeds, particularly Rumex spp. The contribution by individual species to pollen volumes in Edinburgh meadow treatments is shown in Fig 8. As for nectar, most pollen was provided by a few species at a given seasonal time point, particularly in perennial and A2 meadows.
Native weeds contributed almost all early-season pollen production in all treatments—particularly Taraxacum agg. Later in the summer, perennial meadow pollen production was dominated by Leucanthemum vulgare and Achillea millefolium , while pollen production in the annual meadows particularly A2 was dominated by the poppies Papaver rhoeas and Eschscholzia californica.
The percentage of estimated total meadow pollen volume attributable to each species is indicated by the height of the filled polygon for that species at a given seasonal time point. Consideration of the other three cities Fig 9 and S5 Fig shows that, in contrast to Edinburgh, meadow pollen production was more comparable across perennial and annual meadow treatments. In Bristol and Leeds, productivity of perennial meadows again peaked before annual A1 meadows.
There is some evidence of earlier A1 pollen production peaks in southern Bristol and Reading than in northern Edinburgh and Leeds cities, though this is less clear than for nectar. Whilst per-species estimates using the seven-quadrat sampling regime are subject to the stochastic patterns shown in S1 and S2 Figs, most of the same species that dominated pollen production in Edinburgh also dominated in the other three cities: over all cities, replicates and time points, dominant contributions to total perennial pollen volume were made by Leucanthemum vulgare However, Bristol did not show the high peak of Achillea millefolium seen in Edinburgh, highlighting between-site variation in the spectrum of species contributing pollen from a given seed mix.
Both seed mixes contained species making very low contributions to pollen volume at the meadow level. Low values were due to low numbers of available flowers e.
Galium verum. In A1 treatments the lowest value was substantially higher, at 0. Sampling of up to 99 x 1m 2 quadrats in individual meadows followed by in silico resampling showed variance in estimates of floral abundance and hence nectar and pollen resources to decline with increasing numbers of quadrats.
For the Edinburgh perennial replicate that failed Saughton , inclusion of 20 quadrats meant the difference between a mean value of zero seven quadrats and a very low value of 3. Similar magnitudes of difference were observed for other Edinburgh treatments and time points. We thus consider the seven-quadrat estimates adequate for comparison of mean differences between treatments. Note that data have been log e transformed. The fitted lines are least squares regressions of the transformed data, with the darker shaded area showing standard errors of fitted values.
Our aims in this study were to quantify per-flower nectar sugar and pollen rewards for species in two seed mixes, and weeds from the seed bank that commonly grow with them in UK urban environments, and to estimate the total floral rewards these seed mixes provide per unit area when grown as urban meadows.
We first discuss methodological issues related to our approach, before focussing on per species and per meadow resource estimates.
Finally, we consider what more is needed to better estimate floral resource provision in urban and other habitats, and implications for urban green space managers. Quantification of floral resources involves two key steps: estimation of nectar and pollen resources per flower per species and estimation of numbers of flower per species per unit area.
The major challenge in estimating resources per flower lies in effective sampling of very small volumes of nectar or pollen in very small individual flowers or florets. Extraction of pollen through sonication is widely used and generally effective [ 69 ] and anthers can be visually checked to have released their pollen after sonication. In contrast it is much more difficult to be sure that very tiny volumes of nectar have been harvested: even when flowers of florets are flushed with a known volume of water, we cannot be sure that effective mixing of nectar and added water has occurred deep within the flower.
We recorded zero values for nectar secretion using floret flushing in four species: Crepis capillaris , Matricaria discoidea , Plantago lanceolata , and Senecio vulgaris.
Nectar has been collected from Senecio vulgaris by centrifuging individual capitula [ 70 ], and butterflies are known to feed presumably on nectar from Matricaria discoidea [ 71 ]. Previous studies have confirmed our finding of zero or very low nectar production in some species, including Papaver rhoeas low but non-zero in [ 58 ], zero in [ 72 ] , Eschscholzia californica [ 73 ] and Plantago lanceolata [ 73 ]. Given the likelihood of failing to remove all resources from flowers, and possibility of false zeros for some taxa, we regard our floral resource estimates as underestimates.
More detailed examination of nectar secretion in each flower type e. Quantification of floral resources per unit area required estimation of flower densities for each species in each survey. Surveys of Edinburgh meadows using a range of sampling intensities showed sampling variance to decline with increased sampling effort, a pattern that reflects better sampling of spatial variation in sampled taxa among quadrats [ 75 ].
Nevertheless, comparison of results for seven and 20 quadrats across all of the Edinburgh surveys shows similar treatment-mean resource values with no systematic directional bias.
Given that effects of flower sampling strategy and errors in estimation of resources per flower and floral longevity are compounded in estimation of floral resources per unit area, we see our approach as providing an order of magnitude estimate of meadow resource provision, rather than exact values.
An additional issue to address is the possibility of between-city variation in the resources provided by floral units of a given species drawn, as in our study, from the same mix of seed provenances. Variation in growth conditions e. In natural systems, such environmental variation is compounded by any population- or cultivar-associated genetic variation in floral resources e.
We illustrate the combined impact of these effects by comparing our resource values with nectar values generated for other populations of the same species in different locations, sampled using the same protocols by Baude et al.
Quantitative and qualitative see below variation in floral resource provision is an important area for future study. In part this reflects differences in the scale of our sampling; it is unsurprising that we found the multi-floret capitula of Asteraceae to contain more resources than a single-flower floral unit of other taxa all of the top 10 ranked floral units for nectar sugar mass and seven of the top ten for pollen volume were Asteraceae; Figs 1 and 2.
Single flowers of Papaver rhoeas and Eschscholzia californica Papaveraceae offered the highest per unit pollen rewards, providing as much pollen per day as ca. Our data confirm high levels of nectar annual Centaurea spp. Relatively few species were highly rewarding for both pollen and nectar; the best joint performer was Calendula officinalis.
It is striking that non-mix and native weed species contribute the top five ranked nectar producers per floral unit including Senecio jacobaea , Cirsium vulgare , C. These results support previous studies showing the value of some weed species for bees and other taxa [ 81 — 83 ]. Even low numbers of floral units of any of the highly ranked seed mix or weed species would significantly increase floral resource quantity relative to amenity grassland.
There is growing evidence that resource quality, as well as quantity, matters for flower visitors. Pollens vary widely in their percentage protein by mass, and also in the amino acid composition of proteins present [ 53 , 84 , 85 ]. Flower visitors respond to this variation [ 54 , 84 , 86 ], and pollens rich in essential amino acids are associated with improved bee health [ 87 ] and population growth [ 88 , 89 ]. Protein percentage by mass, and the percentage of essential amino acids, are given for 23 of our study species in S1 Table.
In each of these cases, nutmeg plays an important supporting role. Likewise, its pollinators—nocturnal flower beetles that look like ants—are unassuming but essential.
Nutmeg trees are dioecious with creamy-white, fragrant flowers on both male and female trees. Flowers open at night when other insects are not active.
Pollen is the reward from male trees, and ant-mimicking beetles consistently depart male nutmeg trees carrying large loads of pollen. Female flowers lack a reward altogether. Beetles are tricked into visiting stigmas by an enticing fragrance. Orange Citrus x sinensis is pollinated by honey bees Apis mellifera. Citrus and humans have a long history, from citron and lemons serving as a status symbol in the Roman Empire to orange production becoming a multi-billion dollar industry in Florida during the 20 th century.
Like much of the citrus we eat, oranges are a genetic tangle. They are the result of natural and artificial tinkering between citrus varieties that resulted in the perfectly sweet fruit we enjoy at breakfast. Unfortunately, this perfection comes at a cost. All oranges are essentially clones of one another, meaning they are highly susceptible to disease and the future of oranges as we know them is in jeopardy.
But, having bees on farms can increase yield and, for beekeepers, the nectar produced by orange flowers is an important food source for their colonies. Plus, orange blossom honey is delicious! Pear Pyrus communis is pollinated by mason bees Osmia spp.
Each variety arose from a chance mutation in a pear ancestor that produced a desirable quality such as improved flavor or longer shelf life. To maintain these traits, growers cloned the varieties. Thus, all trees of a particular variety, like Anjou or Bartlett, are genetically identical. Each of these varieties requires non-self pollen —pollen that is not genetically identical to the stigma—to set fruit, and therefore must be cross-pollinated with a different pear variety.
Solitary mason bees get the job done. They are good pear pollinators because they are active during the short bloom season and will fly in cold spring conditions. Furthermore, mason bees have a preference for pear pollen over other spring flowers like dandelions and, for that reason, ensure a higher fruit set compared to other bees. Quince Cydonia oblonga is pollinated by honey bees Apis mellifera. Quince are an odd fruit.
They share no immediate relatives, though they are part of the apple and rose family. They are oblong, bruise easily, and have a tough, starchy flesh that can only be made edible by long poaching. Once softened, however, quince are a real treat. Spoon them over yogurt or cook them down into preserves. Choose ones in the grocery store that have a sweet fragrance. Quince flowers are highly attractive to honey bees and they are its chief pollinator throughout the world, though many varieties are also self-compatible.
Raspberry Rubus spp. Raspberries are highly attractive to pollinating insects and require pollination to set fruit. These solitary bees hollow out old, broken raspberry canes into long, linear tunnels. This behavior does not damage the raspberry plant.
In addition to small carpenter bees, mason bees Osmia aglaia are highly capable raspberry pollinators and are under experimentation to manage them commercially. Strawberry Fragraria spp. The strawberries we eat today are a far cry from their pithy, woodland ancestors. Humans have domesticated the tiny, wild strawberry into the behemoths we find in stores, selecting for sweetness, juiciness, and fruit size along the way.
Strawberries are not technically berries. Botanically speaking, a berry is a single ripened ovary like in watermelons or cucumbers. In strawberries, each bumpy seed on the surface of a fruit is actually a ripened ovary. For this reason, strawberries are termed aggregate fruits because they contain many ripened ovaries. Strawberries have perfect flowers that are varietally self-incompatible. Bee pollination is needed to increase fruit set and produce high quality, uniform fruits.
Sweat bees have been found to be superior pollinators of strawberry to honey bees because they are better at depositing compatible pollen on stigmas. Tomato Solanum lycopersicum is pollinated by bumble bees Bombus spp. Few fruits are as recognizable as tomatoes. Native to Central and South America, tomatoes have taken over the world thanks to our love for the fresh fruits and tomato-based sauces, stews, and curries. Tomatoes are grown in two ways—field and greenhouse—but always require buzz-pollination to set fruit.
Field tomatoes are produced by a diverse suite of wild bees. Greenhouse tomatoes, instead, are exclusively pollinated by bumble bees. Bumble bees are reared in boxes suitable for global transport and easily deployed inside a greenhouse. Most of your grocery store tomatoes are produced this way. Even in places with native bumble bees, exotic managed bumble bees are still imported for the greenhouse pollination of tomatoes.
A pollinator is an animal that transfers pollen from one flower to another flower. More than 90 percent of flowering plants depend on pollinators.
To survive, pollinators need more than just flowers as sources of pollen and nectar. They also need water, bare ground for nesting, shelter and nesting materials. In natural areas, these items are readily available.
But in urban and residential areas, these resources are often limited. Landscapes with manicured turfgrass and ornamental shrubs, while very attractive, are often not welcoming habitats for pollinators. To help pollinators thrive in home landscapes, homeowners need to provide them with water for drinking, evaporative cooling and reproduction purposes. If there are no ponds or streams nearby, add a couple of birdbaths or shallow dishes of water in numerous locations to provide fresh, clean water for pollinators.
Change the water often or unwelcome mosquitoes will use it to lay eggs. Treating birdbaths with Bacillus thuringiensis B.
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