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Do local and landscape context affect the attractiveness of flower gardens to bees?
Effects of context on pollinator garden attractiveness
Eldridge Devon S. Conceptualization Data curation Formal analysis Investigation Methodology Validation Visualization Writing – original draft Writing – review & editing 1
Khalil Amani Conceptualization Data curation Formal analysis Investigation Methodology Validation Visualization Writing – original draft Writing – review & editing 1
Moulton John K. Data curation Project administration Supervision Validation Writing – review & editing 2
https://orcid.org/0000-0002-7343-9837
Russo Laura Conceptualization Data curation Formal analysis Funding acquisition Investigation Methodology Project administration Resources Supervision Validation Visualization Writing – review & editing 1 *
1 Department of Ecology & Evolutionary Biology, University of Tennessee, Knoxville, TN, United States of America
2 Department of Entomology & Plant Pathology, University of Tennessee, Knoxville, TN, United States of America
Bossart Janice L. Editor
Southeastern Louisiana University, UNITED STATES OF AMERICA
Competing Interests: The authors have declared that no competing interests exist.

* E-mail: lrusso@utk.edu
4 9 2024
2024
19 9 e03090008 3 2024
2 8 2024
© 2024 Eldridge et al
2024
Eldridge et al
https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Planting floral resources is a common strategy for increasing the abundance and diversity of beneficial flower-visiting insects in human-modified systems. However, the context of the local area and surrounding landscape may affect the attractiveness of these floral resource provisioning plots. We compared the relative effects of local floral resources and surrounding urban land-use on the abundance of bees on flowering plants in common gardens in eastern Tennessee, USA. We planted four types of common garden plots at each of five different landscapes representing a variety of surrounding land use: 1) Urban Garden, 2) Forage Grassland, 3) Mixed Agriculture, 4) Forest, and 5) Organic Farm. Each common garden plot type had a fixed plant community representing one of three plant families (Asteraceae, Fabaceae, Lamiaceae) or a mix of all three, and all four common gardens were replicated at all the sites. We concurrently sampled bees in the garden plots and in a 50 m radius (local area) around the garden plots. We found that the size of the floral display (i.e. the visual display size of flowers) and diversity of flowers in the local area did not affect bee abundance or species richness in the garden plots. Although there was a significant positive association between developed land use in a 2 km radius and bee abundance in the gardens, the effect was small, and there was no relationship between land use and bee abundance or species richness in the local area. There were significant differences in the composition of the bee community between the local area and garden plots, but the largest determinants of bee community composition and species richness in the gardens were floral display size and variation in the garden plant species in bloom. This finding is promising for anyone wishing to promote pollinator populations by providing more floral resources.

http://dx.doi.org/10.13039/100007659 Bayer Corporation Feed A Bee https://orcid.org/0000-0002-7343-9837
Russo Laura Funding was provided by Bayer’s Feed-A-Bee grant to LR in 2019. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Data AvailabilityAll relevant data are within the manuscript and its Supporting Information files.
Data Availability

All relevant data are within the manuscript and its Supporting Information files.
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pmc1. Introduction

The conservation of beneficial biodiversity, such as pollinating insects, is a topic of significant concern, particularly because these organisms contribute to human health and well-being. For example, as the human population grows, so does the global production of food, both in terms of the extent and intensity of agricultural production [1]. Many crop species rely on insect pollination, and land-use intensification has been shown to reduce both pollinating insect species richness and abundance [2,3]. At the same time, insect biodiversity is key to pollination services [4]; for example, while native bees can provide sufficient pollination services on watermelon farms, continued agricultural intensification drastically decreases unmanaged pollination services [5–7]. In fact, land use changes have been implicated as a primary driver of insect declines worldwide [8]. Thus, better understanding the role of land-use change and how to mitigate its negative impacts on beneficial biodiversity is an important topic of research.

Another area of increased land-use change lies in developing, or urbanizing, landscapes. The extent of developed landscapes is accelerating globally and although they are considered by some to be refuges for bees [9–11], urban areas can have negative effects on pollinating insects [12,13]. Urban land-use is unique in the way it alters landscapes; cities are considered hotspots of biological invasion [14], including for invasive bees [15,16], and significantly alter abiotic factors by increasing temperatures and the extent of impervious surfaces [17], which then reduce the soil available for ground-nesting pollinators and floral resources [18]. Both agricultural and urban land-use have repeatedly been shown to affect pollinating insects [19,20]. For example, agricultural land use was shown to decrease phylodiversity of bee communities [3], and urban land use was shown to have a negative effect on gene flow in Bombus vosnesenskii [21] and to change the microbiome in Ceratina calcarata [22]. While the negative impacts of agricultural land use seem to depend on the intensity and extent of the management [23], urban land use does not always have clear negative effects on pollinating insects, and the impact can depend on taxa and traits [24,25]. It is possible that local floral resources, such as urban gardens, may be mediating the impact of urban land use [26]. Moreover, bees are central place foragers, meaning that they forage within a given area and return to provision their nest, making them more vulnerable to certain spatial stressors [27]. This may mean that the structure of habitat patches within landscapes may also affect bee abundance and diversity. The foraging range of bees, and therefore the potential for the broader landscape to influence their foraging decisions, is also affected by their adult body size [28], though there is a significant difference between the potential and realized foraging distances of bees [29].

As a way to ameliorate the impact of such intensive land-use on beneficial arthropods, those interested in protecting pollinating insects recommend floral resource provisioning strips [9,30–32]. These strips of floral resources, essentially flower gardens, have been shown to increase pollinator abundance and diversity in intensively managed systems [30,33,34], but their attractiveness to pollinators also seems to vary with landscape context [35–37]. Attractiveness is a concept that dictates the foraging preferences of pollinating insects. It is usually defined in relative terms: a plant is attractive relative to other plants if it receives a greater abundance of insect visitors given the size of its floral display, or the visual component of bloom [38]. The attractiveness of flowering gardens to pollinators may be affected by local factors, such as floral resources in the immediate area around the garden [35]. For example, at the local scale, the abundance of visitors to any given plant species might be affected by neighboring flowering plants [39]. There is evidence for both a magnet effect, where having an attractive neighbor increases visitation to a plant [40], and a competitive effect, where having an attractive neighbor decreases visitation to a plant [41]. These two effects may in part be moderated by the availability of resources or environmental filtering at a broader scale [37] and a recent review demonstrated prevalent scale-dependence in pollinator-mediated facilitation between plant species [42].

Environmental filtering is the concept that the species found in any given habitat are a subset of the species in the surrounding community [43]. Thus, the surrounding landscape may determine to some extent the pollinator species available to visit a given plant, while the local area may determine the relative attractiveness, or the relative abundance of insect visitors to the flowers [38]. This concept has been applied to other urban green space communities; for example, the composition of carabid communities in urban green spaces was found to be strongly structured by environmental filtering [43].

Our goal was to determine whether the attractiveness of flowering garden plots was affected by local or landscape factors, or an interaction between them. We established four different types of common garden plots at each of five different sites. Three of the common garden plots established at each site included six species each of the plant families Lamiaceae, Fabaceae, and Asteraceae, while the fourth included two species from each of those three plant families. The study sites varied in both the availability of local flowering resources and the surrounding land-use. Our hypotheses were that: 1) the abundance and diversity of bees visiting flowers in the garden plots would be mostly driven by the abundance and diversity of local flowering resources, 2) land-use at a broader scale would interact with local floral availability to affect bee abundance and richness in the gardens, and 3) the bee community in the gardens would be a subset of the surrounding bee community.

2. Materials and methods

Experimental design

We established garden plots with a fixed community of native perennial plants in eastern Tennessee, USA. Each of the gardens contained four individuals of each of six perennial wildflower species native to Tennessee. In each of five sites, we planted four 3m x 2m garden plots: 1) six species of the plant family Asteraceae (A), 2) six species of Fabaceae (F), 3) six species of Lamiaceae (L), and 4) a mixed garden plot two species of each of the aforementioned families (mixed plot, M) (Fig 1). These three plant families were selected due to the range of floral resources they provide, from primarily nectar-based resources in the Lamiaceae, to protein-rich pollen in the Fabaceae [44]. The plants also differed in their floral morphology and these traits did interact to affect pollinator visitation [45]. At each site, the garden plots were separated between 15m – 50m. Sites were all property owned by the University of Tennessee (Research and Education Centers, or RECs). The distance between sites ranged from 1 km to 106 km. We chose the plant composition (a total of 18 species) based on commercially available, insect-pollinated plant species native to the region and sourced them from a local native plant nursery (Overhill Gardens, Vonore, TN, S1 Table in S2 File).

10.1371/journal.pone.0309000.g001 Fig 1 A map of one of the study sites illustrating the sampling design.

The larger map illustrates the 2 km radius, from which we assessed land use. The inset show the four research gardens represented by squares (Lamiaceae = blue, Fabaceae = yellow, Asteraceae = green, Mixed = brown), which are surrounded by the 50-meter local sampling area. Base map from USGS EROS Earth Explorer (public domain: https://earthexplorer.usgs.gov/).

All of the gardens were established following the same methodology at five separate sites: 1) Urban Garden, 2) Forage Grassland, 3) Mixed Agriculture, 4) Forest, and 5) Organic Farm. These sites were selected because they represented a variety of local and landscape types, with land-use at a 2 km radius varying from primarily urban (Urban Garden) to primarily agricultural (Forage Grassland). The community of flowering plants immediately surrounding the gardens varied from frequently mown (Forage Grassland), to a high diversity of native (Forest) and ornamental (Urban Garden) flowering beds. Both the Mixed Agriculture and Organic Farm sites comprised a mixed community of taller grasses and some common non-native flowering weeds, that were mown twice a summer, alongside a mixture of research crops including blueberries, apples, and switchgrass (Mixed Agriculture) and lettuce, squash, and mint (Organic Farm). The fixed community of plants within the gardens allowed us to isolate the effects of local and landscape factors on changes in the flower-visiting insect communities.

Garden plot surveys

Each garden plot was visited weekly from July 13th–August 17th, 2020, or five complete rounds of sampling each plot in the study. This represented the peak bloom period of the research plants in our study plots. While some of the plant species in the plots bloomed outside this period, it represented the greatest proportion of co-flowering plants, and largest floral display of plants in the plots. The amount of time spent sampling in each garden varied depending on the number of plant species in flower (5 min per plant species in bloom, or up to 30 min per garden). For the gardens, floral diversity was represented by the number of plant species in bloom during the survey.

We collected all insects that contacted the reproductive parts of the inflorescences within the garden plots during standardized surveys. These weekly surveys involved sampling each plant species in bloom in each plot at a given site for five minutes, using a hand-held vacuum aspirator from BioQuip (Rancho Dominquez, CA). During each collection event, we also counted the number of inflorescences of each plant species and used the number of inflorescences per plot as a measure of overall floral display. There were three different plant families in the plots, with different floral morphologies. The Asteraceae all had composite inflorescences, or flowerheads, and each flowerhead was counted. For Fabaceae that presented large individual flowers (all but Amorpha herbacea), we counted these, and for Amorpha herbacea, we counted racemes of flowers as inflorescences. For the Lamiaceae that presented large individual flowers (all except Blephilia subnuda, Lycopus virginicus, and Pycnanthemum muticum), we counted these, while for B. subnuda, L. virginicus, and P. muticum, we counted the composite-like flowerheads as inflorescences. We kept track of this to determine how the background floral display within the plot affected its attractiveness to pollinating insects [46–48].

Local survey

We paired the garden plot surveys with surveys in the local area immediately around each plot, because we were interested in whether the local flowering plants affected visitation to the research plots. These local surveys were paired in time (July 13th–August 17th 2020) and space with the plots. An insect net was used to capture insects that contacted the reproductive parts of flowers within a 50m radius of each research plot once a week, for a total of five complete surveys (Fig 1). These local surveys were 10 minutes each, allowing the collector to walk the entirety of the area within the 50m radius, and the timer was paused after each insect was collected, while it was being transferred to a collection vial. Honeybees (Apis mellifera L) and carpenter bees (Xylocopa virginica L) were counted and recorded but not captured, as they could be identified on sight.

Flowering plant diversity (floral diversity) and floral display were surveyed before each pollinator survey was performed. In these local surveys, we did not identify the flowering plant species, but rather were interested in rapidly assessing how many different flower types were available (diversity) and how abundant they were (floral display), because our main goal was determining whether the abundance and diversity of floral resources around the gardens had any effect on bee visitation to the fixed plant communities within the gardens. The same surveyor ranked diversity and floral display on all of the local surveys, to ensure that the rankings would be consistent. We used a visual ranking method within the 50m radius around each research plot in the following manner. First, we ranked the floral diversity on a scale from 1–10, where 1 was the least diverse survey area (i.e. a single plant type in bloom), and 10 was the most diverse survey area (a variety of colors and floral morphologies in bloom). We used a mowed lawn as an example of a 0 on the floral diversity scale, and a botanical garden in bloom as a 10 on the floral diversity scale. Next, we ranked floral display on a scale from 1–10, where 1 was the smallest, and 10 was the largest floral display for the survey areas. Similarly, a mown lawn with no flowers was a 0 on this scale, and an apple orchard in full bloom was our example of a 10 on this scale. Our local surveys were ranked on these two scales by the same surveyor before each pollinator collection event. Such ranking methods have been shown to be consistent with other vegetation measures and respond consistently to treatments [49,50]. We chose this method of assessment over the Braun-Blanquet method because we wanted a rapid visual assessment of the entire local area around the gardens, rather than quadrat subsamples [51]. These measures allowed us to qualitatively compare the survey areas to one another.

Insect processing

Insects collected from both garden and local surveys were frozen, then pinned, labeled, identified, and databased. We focused our analysis on bee specimens (members of the superfamily Apoidea). Bees were identified to genus and species where possible, using the Discover Life interactive key [52]. Bee identifications were then verified by Sam Droege (USGS). Specimens are vouchered at the University of Tennessee.

Landscape analysis

To classify the landscape around our research sites, we used ArcGIS Pro 2.6 and the US National Land Cover Database (NLCD) (https://www.mrlc.gov/), with a 30 m resolution [53]. We classified land cover at 2000 m around the center of each site (Fig 1). Our goal in using this buffer radius was to determine how the broader landscape affected bee diversity and abundance in the gardens [54,55]. In our analysis, we detected 14 land cover classifications that we aggregated into four general land-use types: water (Open Water), developed (Developed High Intensity, Developed Low Intensity, Developed Medium Intensity, Developed Open Space), agriculture (Cultivated Crops, Grassland/Herbaceous, Pasture/Hay), and semi-natural (Deciduous Forest, Emergent Herbaceous Wetlands, Evergreen Forest, Mixed Forest, Shrub/Scrub, Woody Wetlands) (S2 Table in S2 File). The NLCD defined developed land as constructed materials and impervious surfaces such as commercial and residential housing, roadways, and lawn grasses. Areas classified as water included open water and areas with minimal soil and vegetation. Semi-natural land use included different forest types, wetlands, shrubland, and non-grassland herbaceous land cover. Agricultural land use comprised of pastureland, cultivated crops, or grasslands. We hypothesized that landscape context would interact with local floral resources to have an effect on bee diversity or abundance; specifically, that landscapes that increased bee diversity and abundance in the local surveys would also increase bee diversity and abundance in the garden plots. We selected 2000 m to provide a strong contrast with the local surveys; however, for completeness, we reran these analyses with land-use buffers calculated at 500 m and 1000 m.

Data analysis

All data analyses were conducted in R version 4.3.2 [56,57]. First, we compared the bee collections among the sites and surveys (garden or local). We used feature scaling to standardize the measures of floral display and diversity in the gardens and local area on a scale of 0–1. We used rescaling (aka min-max normalization) here, following the equation: x′=x−min(x)max(x)−min(x). We compared the average number of bees collected per minute sampling, and the relationship between bee abundance and the scaled floral display for both survey types. We used a rarefaction analysis (function iNEXT [58]) to test for differences in bee diversity among the sites and surveys. This function uses sample-size based integrations to calculate Hill numbers, or the effective number of species, to quantify the species diversity of an assemblage (58). We report the results for Hill numbers q = 0 (species richness) and q = 1 (Shannon diversity). Shannon diversity incorporates information on the relative abundances of different species, or species evenness, as a way to interpret the effective number of species in a community. Shannon diversity is often included as a way of measuring diversity beyond just the count of species (i.e. species richness). iNEXT has the added benefit of accounting for sample size, which is helpful in comparing communities of different sizes or where sampling effort is uneven. Where honeybees were especially prevalent, we ran the rarefaction analysis with and without honeybees. This species was of special interest because it is a non-native species that can potentially compete with wild bees for floral resources [16,59,60], but it is unlikely to be affected by the same environmental factors because honeybees are often kept in managed hives. For example, honeybee abundance may be positively associated with urban or agricultural beekeeping [53]. We also tested for sampling completeness of both survey types using iNEXT.

We built four separate models for bee abundance and species richness in the garden and local surveys. To test our first hypothesis, we then used generalized linear mixed effects models (GLMMs) using the function glmmTMB in the package “glmmTMB” [61] to test the effect of the scaled floral display and floral diversity in the garden and local area, and developed land use at a 2 km radius on bee abundance and species richness in the gardens, with sampling round nested in plot as the random effect. Because the floral display and floral diversity were correlated, we ran two sets of models for each response, one with display and one with diversity. We then used the function anova to compare the two models, and selected the model with the lower AIC value to include. We also used GLMMs to test whether the abundance and species richness of bees in the area around the gardens was affected by land use or local floral display and floral diversity. To test our second hypothesis about whether land use interacted with local floral display and floral diversity, we also tested for interactions between the land use effect and the other fixed effects. We removed non-significant interaction terms from the final models. For all count-based models, we used a negative binomial distribution due to overdispersion.

We used non-metric multidimensional scaling (NMDS) to compare the bee community composition among the sites and surveys [62]. NMDS is an ordination technique that allows for visualization of multivariate responses to treatments. In our case, we were looking for overlap, or non-overlap in the community structure of the bees. We used the function anosim in the package “vegan” [62] to test for significant differences in the bee community composition. We used 99 permutations and Bray-Curtis dissimilarity in this test. To determine which species were driving differences, we used the multipatt function in the package “indicspecies” [63] when the groups differed significantly.

3. Results

Garden plot surveys

We collected 1,470 specimens during 20.83 hours of sampling in the garden plots [53]. Most of the specimens (1,186 or 81%) were bees (Halictidae, Megachilidae, and Apidae) (S1A Fig in S2 File), of which 137 (9%) were honeybees (Apis mellifera). We were able to identify all specimens to species except for 157 Lasioglossum males and five Ceratina females, which were left at the genus level (11% of all specimens collected in the gardens). A total of 44 bee species were identified from the garden collections. Halictidae (791 specimens) was the most abundant bee family collected within the gardens during the sampling period. Apidae followed as the second most abundant bee family with 356 specimens. The largest number of specimens were collected from plots at the Forage Grassland (379) and the Organic Farm (318).

On average, 2.4 ± 0.13 (standard error) plant species were in bloom per plot during the surveys. We observed an average of 369.21 ± 39.8 inflorescences per plot per survey. We used feature scaling to standardize these measures to a 0–1 scale to compare to the floral diversity and floral display of the local surveys.

Local surveys

We collected or observed 3,324 flower-visiting insects during 16.67 hours of sampling the local areas surrounding the plots. Most of the specimens (2,917 or 88%) were bees (Halictidae, Megachilidae, Colletidae, Andrenidae, and Apidae) (S1B Fig in S2 File); 1,380 (42%) were A. mellifera (S1 Fig in S2 File). We were able to identify all specimens to the species level except for 92 Lasioglossum males and four Ceratina females (3% of the specimens collected in local surveys). We identified 52 species of bees (S3 Table in S2 File). We collected six species of bees not found in the plot surveys: Melissodes communis Cresson, Xenoglossa (Peponapis) pruinosa (Say), Hylaeus leptocephalus (Morawitz), Lasioglossum fattigi (Mitchell), Lasioglossum simplex (Robertson), and Hoplitis producta Cresson. Lasioglossum fattigi and L. simplex were both new occurrence records for the state of Tennessee (pers. comm., S. Droege, J. Ascher).

The average ranked floral display in the local survey was 4.25 ± 0.27 (standard error) and the average ranked floral diversity was 4.17 ± 0.29. We used feature scaling to standardize these ranked floral display and floral diversity measures from 0–1.

Comparing garden and local surveys

The Mixed Agriculture site had the highest bee abundance among the garden surveys, while the Urban Garden site had the highest abundance among the local surveys (Fig 2A). The local surveys found a higher bee abundance per minute spent sampling than the garden plots at four of the five sites (Fig 2A). The scaled floral display had a significant positive effect on bee abundance in both local and garden surveys (Fig 2B). With honeybees included in the rarefaction analysis, the Forage Grassland and Mixed Agriculture sites both had significantly higher bee Shannon diversity than the other sites, but all the sites had overlapping confidence intervals for bee species richness (S2A Fig in S2 File, S4 Table in S2 File) and when we excluded honeybees, only the Forage Grassland had higher Shannon diversity than the other sites. We also compared the local and garden surveys (S2B and S2C Fig in S2 File) and found that they did not differ in bee species richness, but that the gardens had a higher Shannon diversity than the local surveys due to a greater evenness. This difference was probably driven by the dominance of honeybees in the local surveys because, after removing honeybees from the rarefaction analysis, we found that the local surveys had a higher Shannon diversity than the garden plots (S2C Fig in S2 File). Our sample coverage was above 95% for all the sites we sampled, and above 98% for both survey types (S4 Table in S2 File, S2D and S2E Fig in S2 File).

10.1371/journal.pone.0309000.g002 Fig 2 A) Box and whisker plots of the average number of bees collected per minute sampled at all five sites (1: Urban Garden, 2: Forage Grassland, 3: Mixed Agriculture, 4: Forest, and 5: Organic Farm) for the landscape (red) and plot (blue) surveys. B) Number of bees collected per sample compared to the scaled floral display of the local (red) and garden (blue) surveys. The lines are drawn with the function “geom_smooth(method = lm)” in the package ggplot2 and the shaded area around each line indicates the 95% confidence interval. C) Rarefaction analysis (excluding honeybees) showing bee species richness and Shannon diversity at the five sites (1 = red, 2 = yellow, 3 = green, 4 = blue, 5 = purple). Interpolated data are represented with a solid line and extrapolated data are represented with a dashed line. The shaded area around each line is the 95% confidence interval.

We did not find any significant interactions between developed land use at a 2 km radius and any of the other fixed effects and thus removed the interaction terms from the models. The best model for bee abundance in the gardens included the floral diversity in the local area and gardens, along with development. Bee abundance in the gardens was significantly associated with the flower species richness in the gardens (i.e. the number of plant species in bloom at the time of the sample), along with developed land use at a 2 km radius (Table 1, Fig 3A and 3B). However, the effect of development was much lower in magnitude than the effect of the floral richness in the gardens. Bee abundance in the gardens was not associated with local floral diversity. The best model for bee species richness in the gardens included the floral display in the gardens and local area, along with developed land use at a 2 km radius. Bee species richness in the gardens was significantly associated with floral richness in the gardens, but not local floral diversity or development (Table 1, Fig 3D).

10.1371/journal.pone.0309000.g003 Fig 3 Significant relationships between bee abundance and species richness in the gardens and local area and fixed effects in the models.

We found that bee abundance in the gardens was driven most strongly by the developed land use in a 2 km radius (A) and floral species richness in the gardens (B). Bee richness in the gardens was driven mostly by the floral display in the gardens (D). The local bee abundance (C) and local bee richness (E) were both driven by the local floral display. The points on the graph represent raw data and the solid lines are predicted relationships from the models. The dashed lines around the solid lines represent the 95% confidence intervals.

10.1371/journal.pone.0309000.t001 Table 1 Results from generalized linear mixed effects models (GLMMs) for bee abundance and species richness in the gardens and local area.

Significant effects are bolded. Due to overdispersion, we used negative binomial models for the count-based responses.

Response	Fixed effects	Contrasts	Family	Random effects	Observations	Estimate	z value	P value	
Garden Bee Abundance	Garden Floral Species Richness	continuous	Negative Binomial	Round|Plot	100 obs, 4 plot types, 5 rounds	3.84	6.03	<0.001	
	Local Floral Diversity					-1.12	-1.71	0.09	
 	Development (2km)	 	 	 	 	0.02	2.07	0.04	
Local Bee Abundance	Local Floral Display	continuous	Negative Binomial	Round|Plot	100 obs, 4 plot types, 5 rounds	1.29	2.09	0.04	
 	Development (2km)	 	 	 	 	0.01	1.66	0.1	
Garden Bee Species Richness	Garden Floral Display	continuous	Negative Binomial	Round|Plot	100 obs, 4 plot types, 5 rounds	1.59	4.86	<0.001	
	Local Floral Display					-0.4	-1.01	0.31	
 	Development (2km)	 	 	 	 	0.01	1.94	0.05	
Local Bee Species Richness	Local Floral Display	continuous	Negative Binomial	Round|Plot	100 obs, 4 plot types, 5 rounds	0.89	3.36	<0.001	
 	Development (2km)	 	 	 	 	0.002	0.53	0.6	

The best model for bee abundance in the local surveys included the local floral display and developed land use at a 2 km radius. Bee abundance in the local surveys was significantly associated with local floral display, but not development (Table 1, Fig 3C). The best model for bee species richness in the local surveys included local floral display and developed land use at a 2 km radius. Bee species richness in the local surveys was only associated with local floral display (Table 1, Fig 3E). We reran these models with the land-use buffer calculated at 500 m and 1000 m, but the results did not differ qualitatively from the original analyses (S5 Table in S2 File).

The NMDS ordination plots (Fig 4, stress = 0.196) showed community overlap between the sites, plot types, and surveys. All three groups differed significantly from one another, but with low R values, suggesting some overlap in community composition (sites R = 0.19, p = 0.01; plot types R = 0.08, p = 0.04, survey types R = 0.19, p = 0.01). For this analysis, R values close to 1 would suggest complete dissimilarity in groups, while values close to zero would suggest community overlap. The indicator species analysis identified bee species that were found more often at a given site or plot type. This analysis suggested that the greatest variation in bee species composition was at the site level (S6 Table in S2 File). There were many bee species found significantly more often at the Urban Garden site; these significantly associated bee species were Bombus impatiens, B. pensylvanicus, B. griseocollis, Megachile pusilla, M. rotundata, M. mendica, Xylocopa virginica, Lasioglossum apocyni, Anthidium manicatum, and Agapostemon virescens. Megachile rotundata and A. manicatum are both non-native bee species often associated with urban habitat [14,64]. The bee species found to be associated with the Organic Farm site were Lasioglossum zephyrum, L. admirandum, L. tegulare. Only one bee species was found more often at the Forage Grassland site (Ceratina dupla), and the Forest site (Lasioglossum lustrans) (S6 Table in S2 File). For the plot types, the only significantly associated bee species was Halictus ligatus/poeyi, which was significantly associated with the Asteraceae plots (S6 Table in S2 File). Between the two survey methods, there were seven species significantly associated with the local surveys (Apis mellifera, Lasioglossum hitchensi, L. callidum, L. imitatum, L. trigeminum, L. apocyni, and Calliopsis andreniformis) and none associated with the gardens (S6 Table in S2 File).

10.1371/journal.pone.0309000.g004 Fig 4 Non-metric multidimensional scaling (NMDS) ordination plots of the different sites (A), plot types (B), and surveys (C). Overlap in the shapes indicates overlap in the communities in the sites or surveys. Color indicates landscape (A): Urban Garden (red), Forage Grassland (yellow), Mixed Agriculture (green), Forest (light blue), and Organic Farm (dark blue); plot type: Lamiaceae (dark blue), Fabaceae (yellow), Asteraceae (red), and Mixed (green); and survey type: garden (blue) and local (red).

4. Discussion

In our study of the relative effects of local and landscape characteristics on the attractiveness of flower gardens to visiting bees, we found strong positive relationships between floral display and bee abundance and species richness, but also that the effect was mostly constrained to the sample area, whether it be the common garden itself or the local area. Similar relationships have been previously documented in agricultural ecosystems [65,66] and strong background effects of floral display on pollinator visitation are well-documented [48,67]. We observed the highest local floral diversity and floral display in the site managed as a public garden (Urban Garden site). This site was well manicured, with many flower beds for display. At the same time, this high floral display and diversity in the local area did not significantly increase the abundance or species richness of the bees in our garden plots. Our first hypothesis, that local floral display and diversity would be the primary driver of bee abundance and species richness in the garden plots, was therefore not supported by our results. This contrasts with other studies that have shown that the surrounding floral resources and landscape context can significantly affect bee abundance and diversity in wildflower gardens [35,68].

Our second hypothesis was that the surrounding landscape would interact with local floral resources to drive bee abundance and species richness in the gardens. However, we found no significant interactions between our land use variable and the other factors in our analysis. While developed land use at a 2 km radius did have a significant positive effect on bee abundance in the gardens, the effect size was orders of magnitude smaller than the effect of the floral display in the gardens themselves. Moreover, developed land use had no effect on the bee abundance or species richness in the local surveys. Thus, our second hypothesis was also not supported. Overall, local factors seemed to be the major drivers of the bee community, at least in this study. It is possible that other land-uses, such as agricultural land or natural areas, may have had an undetected influence on the pollinator communities in these systems. Further, our sites were in patchy landscapes and this patchy, heterogenous habitat may influence bee species composition and abundance [69,70]. Measuring landscape heterogeneity and patch structure in the landscape might show different patterns.

It is also possible that more extreme landscapes would have shown stronger effects. Our sites varied between roughly 5% and 60% developed land-use at a 2 km radius, whereas one previous study found non-linear effects on homogenization in Lepidoptera above 60% agricultural land-use [71]. Our findings might therefore not be representative of more homogenous landscapes. However, even if this were true, we would at least expect to see some difference between the two extreme ends of our gradient. Instead, we saw a mild positive effect of developed land use on overall bee abundance and species richness in the gardens. Previous studies similarly found multiple non-linearities and significant variation in patterns of community similarity [72].

Our third hypothesis was that the bee community in the research gardens would be a subset of the local bee community. Overall, the sites and surveys had relatively similar total bee species richness, but the evenness of the species varied, leading to a greater difference in the Shannon diversity. For example, although there were not significant differences in the total bee species richness of the two surveys, the garden survey had a higher Shannon diversity until we removed honeybees from the analysis. Proportionally, far fewer honeybees were collected in the gardens (~9%) than in the surrounding local surveys (~53%), which may have been due to the plant species composition of the garden plots relative to the local area. Eusocial bee species like the honeybee may be capable of competitively excluding solitary bee species [59,60,73], but may also exhibit distinct foraging preferences [74] and may not be affected by the same land-use factors [16,53]. Although on a per minute sampling basis, the local surveys collected a higher abundance of bees, from a bee community composition perspective, the differences among sites, plot types, and survey types were relatively minor. Similarly, though these groups differed significantly, there was substantial overlap in the community composition. We were able to identify significant indicator species among the different groups, and found that the Urban Garden and the local surveys had the largest number of significantly associated species, while there were no bee species significantly associated with the research gardens. From these results, we find mixed support for the hypothesis that the bees in the garden plots were a subset of the surrounding bee community.

5. Conclusions

Our study provides promising findings for anyone that wishes to promote diverse pollinator communities. Along with other research, this study supports strategies for promoting pollinators by increasing floral diversity and floral display [75], especially when these plants provide a diverse range of floral resources [45]. Our findings did not show support for our hypotheses that bee abundance and species richness in experimental gardens would be driven by a mixture of local and landscape effects. Instead, we saw that these gardens attracted a diverse bee community largely through the size of their floral display and the identity of the blooming plants within them. We found minor effects of developed land use but no large effects across a range of land use. We show that local floral resources are stronger predictors of bee abundance than surrounding land-use and that managed landscapes can maintain high abundances of bees. Whether undisturbed or managed, landowners have the power to promote their local pollinator communities by conserving existing natural patches or increasing the availability of floral resources.

Supporting information

S1 File Supporting information appendix: Data collected for the analyses in this study.

(XLSX)

S2 File Supporting information appendix 2: Supplemental tables and figures, including six additional tables and two additional figures.

(DOCX)

We would like to thank the University of Tennessee (UT), the UT Institute of Agriculture, the UT Gardens, and the UT Ag Research and Education Centers, including the Plateau AgResearch Center, the Organic Crops Unit, and the Forest Research and Education Center, for allowing us to do research on their lands, especially K. Hoyt, B. Simpson, W. Hitch, H. Jones, J. Newburn, and W. Lively. We would also like to thank D. Matheson, S. Collins, and A. Murray for field assistance and N. Oldham for assisting with hoverfly identification. Thanks also go to S. Droege for lending his expertise in bee identification. Thank you to the Department of Ecology & Evolutionary Biology at the University of Tennessee for the support of this project.

10.1371/journal.pone.0309000.r001
Decision Letter 0
Bossart Janice L. Academic Editor
© 2024 Janice L. Bossart
2024
Janice L. Bossart
https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Submission Version0
9 May 2024

PONE-D-24-09528Do local and landscape context affect the attractiveness of flower gardens to bees?PLOS ONE

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Reviewer #1: This paper presents a study on the interplay between landscape and local-scale factors in shaping the attractiveness (in terms of plant-pollinator interactions and alpha diversity metrics) of floral bee gardens. This study considers two relevant spatial scales and investigates how important factors, such as resource availability and habitat amount, shape bee communities across human-dominated landscapes. The paper seems to be based on the master work of one of the authors, and thus, the limitations regarding sampling size (e.g., replicates per treatment) can be understood regarding the (probaly) limited humanpower and existing time constraints. The paper is well-written, structured, and organized. The authors have made the data available as declared.

Having said that, we have a number of major concerns regarding the (1) statistical analyses (families used and model assumptions, colinearity in the variables, definition of variables, model assembly, assumptions), (2) some of the methods, (3) some rationals regarding the conceptualisation of the study, and (4) the available datasets, which seem to have not been properly cleaned and are not sufficiently documented to reproduce and re-use the data (we have tried ourself and wasn’t able to reproduce the work). Thus, together, these points question the study as a whole and prevent to recommend the paper for publication in its current form. We think that there might be potential for publication, but this will require work.

I have added my comments below, which we hope will be useful for the authors

### Major comments: ###

- Statistical analyses:

o Correlations among predictors: The authors do not mention any collinearity check on their predictors, but this is a basic standard check. We’ve check the correlations of some of the predictors and they are quite high: floral display at the local scale vs. development; floral display at the local vs. plant richness at the local, plant richness at the local vs. development. The authors checked collinearity before building the models and checked the variance inflation factor (VIF) of the model. We guess the authors are familiar with it, but there is a large number of problems related to colinearity. This issue raises questions regarding the validity of the models.

o Statistical families of the models: The authors seem to have used Gaussian families for all their variables, despite working with count data (i.e., the assumptions of Gaussian do not necessarily work when you have count data, which is limited to countable values). While gaussian families are adequate when count data is faily large, it shouldn’t be used when the counts are “small” and there are zeros. This violates the assumption of constance variance. In your case, I think you should use “Poisson” family if there is no overdispersion, or using a negative binomial if overdispersion. This puts all models and results into question, as they are now.

o Model specifications and Table 1: The random effect structure specified in the method section and the one presented in table 1 do not match. In the methods, it is said that the random effects were site and sampling date nested in the site. However, in Table 1, it appears that garden type (or plot) was used in the random effect. It makes sense to use plot and sampling data as random effect to account for the lack of independence of these two factors, so perhaps there was an error in the method section.

Another problem is that there are five sampling rounds, but in Table 1, it appears that there are only four rounds. Please clarify this discrepancy.

- Other methods

o Ranking floral diversity and floral abundance: The authors used a scale of to 1-10 to quantify floral diversity and floral abundance. As presented in the Methods section, it is unclear what criteria were used to attribute the different scale values to the existing features. It feels that this is a purely subjective guess from the observer. It is also strange that no method based on coverage (E.g., Braun-blanquet scale or similar) was used. The authors should better explain how the assessment of their scale was done, how they dealt with the potential subjectivity of the observer, etc. As it is now, it leaves too many doubts on a variable that is key for the analyses.

o Estimation of floral abundance: the authors state that they counted inflorescens to assess floral abundance at both plot and local scales. They did not mention how they assessed single flowers (and they should mention it), but one can assume that they were counted individually. However, the major problem I see here is the lack of detail on the definition of inflorescences. Surprisingly, the authors did not use standard methods based on floral units (references). For example, how did you consider compound umbellas, compound capitulums, etc? A classification criteria for the different types of inflorescences and they way they were counted is necessary (e.g., see https://doi.org/10.1016/j.dib.2021.107243, https://doi.org/10.1038/s41559-018-0769-y for examples).

- Conceptual aspects:

o Definition of pollinator-friendly plants: The authors mention that they used pollinator-friendly plant species native to the study area. However, it is unclear what is used to define plant species as pollinator-friendly. Was this based on what nurseries and plant providers say? Is this based on actual research? This is crucial, as it has been found that what is reported by nurseries does not always reflect the reality.

o Functional ecology aspects: While the study stands as it is, I think it is difficult to justify why the authors did not use any functional metrics and quantify resources (and resource quality) solely using taxonomic metrics. In conclusion, the authors suggest increasing plant diversity and floral display, but we know that this is a poor recommendation without actually considering the value of plants for pollinators (one could add many grasses, plant varieties that do not provide rewards, or plants that have mismatches in their flowering season with the phenology of the pollinators). This can be achieved by integrating the functional traits of plants, which are quite widely available (TRY database, datapapers), such as blossom class, symmetry, flowering start and duration, growth form, and even nutritional metrics (e.g., sugar in pollen or nectar). Computing functional metrics could really better underpin your results and provide strong support for your conclusions, which at the moment feel vague and unspecific.

e.g.,: https://www.sciencedirect.com/science/article/pii/S2352340921005278,

https://doi.org/10.1002/2688-8319.12248, https://esajournals.onlinelibrary.wiley.com/doi/10.1002/ecy.3705,

- Problems with the provided data: The authors made the data available. However, we found a number of problems that prevented reuse and reproduced the results:

o In general, you should provide a read-me file (separated as a text document or as a new sheet in the excel), where you clearly explain the columns of both sheets. It is unclear what site and block are (one has four levels, the other has five). You should define all variables, their column names, units, etc. So an external user can understand everything

o Sheet “specimens’: There is something wrong with this sheet. For example, between rows 39-72, the plant species and plant long columns are wong: it says local and UT Arboretum. There is no information on the block, plot type, local-garden scale, and so on. No columns with full site names.

o Sheet for data analyses: You should add the development metric here, so it simplifies reproducing the analyses. The differences between the site and the block are unclear.

### Other comments: ###

INTRODUCTION

- The introduction does not provide sufficient information on key concepts. The authors should devote some text and references to them.

o Central place foragers: This is critical because we know that most bees forage within the proximity of their nest, with some exceptions. Thus, the local-scale factors may be significant. There is plenty of literature in that regard: 10.1002/ecy.3809, https://doi.org/10.1002/eap.2727, https://www.sciencedirect.com/science/article/abs/pii/S0065250415000367

o Filtering: The third hypothesis of this study refers to filtering. However, the term is not adequately introduced, even though there is literature on the topic for bees: https://onlinelibrary.wiley.com/doi/abs/10.1111/jbi.13772, 10.1098/rspb.2014.2849 , 10.1038/s41467-020-14496-6

o Attractiveness: The authors disclose the drivers of attractiveness without properly defining the term and provide an overview of what has been found to influence it. E.g.: https://doi.org/10.1111/1365-2435.12178, 10.7717/peerj.3066

o Honeybees and their effects on wildbees: It would be beneficial to explain the potential effects of managed pollinators, such as honeybees, on wild bees, especially where they are not native. It will also help understanding why some analyses were done excluding honeybees. https://peerj.com/articles/14699/ , https://esajournals.onlinelibrary.wiley.com/doi/10.1002/ecy.3939

- L94: The phrasing of the sentences is a bit unusual, and it is difficult to understand what was done.

METHODS

- Experimental design: How far were the sites? What criteria were used to select them? (permisions and special features??). Please clarify.

- L106: here it is said there are 5 sites, in the data, the column “site” has only 4 levels…

- L166: provide the version of ArcGIUS

- L167: provide the resolution of the NLCD

- L186: Provide the version of R. If you used Rstudio, provide citation and version as well

- You should provide a list of packages and versions used in the supplementary

- L188: Predictors were scaled only or centered.

- L193-204: This paragraph could be better written and explained; that is, the information could be presented in a more efficient way. For us, it is not clear that local- and garden-scale models were done separately. This can be said earlier, and is better specified. The random effects did not match those presented in Table 1. There was no mention of how assumptions for the model were checked (e.g., spatial autocorrelation).

DISCUSSION

- L326-330: The authors discuss evenness here, but this is a metric that has not been presented before in the introduction or methods. Please integrate this into the manuscript.

- The authors could add some information regarding the following aspects, which are not unfamiliar to them:

o Nutritional aspects of floral resources: In addition to discussing the effects of resources based on alpha-diversity metrics, the authors could make use of the existing literature (including the work of the senior author) to add depth to the discussion of how floral resources shape bee communities (niche partitioning, health, etc.), the role of nutritional landscapes in floral restoration, etc.

- It feels more references could be integrated, e.g.,: https://advaudo.weebly.com/uploads/1/2/6/8/126897510/current_opinion_in_insect_science_2015_vaudo.pdf, http://www.woodardlab.com/uploads/6/4/9/6/64969235/1-s2.0-s2214574517300615-main.pdf,

CONCLUSIONS

- L347: What does “healthy” mean here? This concept has not been previously addressed. The authors could use previous work to develop it more: https://www.cell.com/trends/ecology-evolution/fulltext/S0169-5347(21)00333-5?_returnURL=https://linkinghub.elsevier.com/retrieve/pii/S0169534721003335?showall=true,

- L349: What are the specific traits of plants? It is always the more the better?

- L359: What do you mean by “high quality”? I think you can develop this much more in the Introduction and Discussion, and as mentioned before, even include it by using plant traits.

TABLE 1

- Effect size: The authors report effect size, but do not explain what metric was used in the methods. If this is the estimate of the predictor, why is it not called an estimate? Otherwise, please define the effect size. The estimate with the standard error is provided in Table 1.

FIGURES:

- Figure 1: You can add a map and a better representation of the nested design.

- Figure 2: (b) explain what was used for the smooth line (lm?); (C) state again what the shaded bands indicate

- Figure 3: The points represent the raw data? Are the smooth lines based on the model predictions? If not, they should be based on your models, so that we can see how they fit the data. Again, explain how the lines are calculated (linear models?) and shaded bands, respectively.

- Figre 4: what was the stress of the NDMS? Maybe add it to the supplementary.

Reviewer #2: This is an interesting study and the methods are solid. The taxonomic resolution of bee species is especially impressive. Also, the discussion was well-organized and effective. I left many comments in the attached document. None are "make or break" for the paper, but some of them may (1) suggest easy modifications to the analysis (considering more radii than just 2000m, considering quasipoisson or negative binomial models) or (2) improve how the statistical methods are described.

**********

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Reviewer #1: No

Reviewer #2: No

**********

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Attachment Submitted filename: PONE-D-24-09528_reviewer.pdf

10.1371/journal.pone.0309000.r002
Author response to Decision Letter 0
Submission Version1
20 Jun 2024

PONE-D-24-09528

Do local and landscape context affect the attractiveness of flower gardens to bees?

PLOS ONE

Dear Dr. Russo,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

The reviewers had widely split perspectives on your manuscript. That said, reviewer 2 mirrored some of the concerns identified by reviewer 1, e.g. aspects of the model and areas where clarity was lacking. Please carefully consider concerns raised by both reviewers; for any you disagree with, please clearly detail why in your response.

Please submit your revised manuscript by Jun 23 2024 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

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If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

We look forward to receiving your revised manuscript.

Kind regards,

Dr. Janice L. Bossart

Academic Editor

PLOS ONE

***We would like to thank the editor and two anonymous reviewers for their helpful feedback on our manuscript. We have significantly revised the manuscript according to these recommendations and feel that it is much improved. Some significant changes included updating and clarifying the methods, improving the attached data file, redoing all the statistical analyses with new model distributions and adding different landscape buffers to the supplemental materials, remaking figures 1 and 3, and adding 24 new references suggested by the reviewers. We hope that the revised manuscript meets your standards.

We address the reviewer comments on a point-by-point basis below. Our responses are demarcated with three asterisks (***).***

Journal requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

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2. Thank you for stating the following financial disclosure:

“LR received funding from Bayer in 2019 ($5000 Feed A Bee).”

Please state what role the funders took in the study. If the funders had no role, please state: "The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript."

If this statement is not correct you must amend it as needed.

Please include this amended Role of Funder statement in your cover letter; we will change the online submission form on your behalf.

***We amended the role of funder as advised. This now reads “Funding was provided by Bayer’s Feed-A-Bee grant to LR in 2019. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.”***

3. Thank you for stating the following in the Acknowledgments Section of your manuscript:

“We would like to thank the University of Tennessee (UT), the UT Institute of Agriculture, the UT Gardens, and the UT Ag Research and Education Centers, including the Plateau AgResearch Center, the Organic Crops Unit, and the Forest Research and Education Center, for allowing us to do research on their lands, especially K. Hoyt, B. Simpson, W. Hitch, H. Jones, J. Newburn, and W. Lively. We would also like to thank D. Matheson, S. Collins, and A. Murray for field assistance and N. Oldham for assisting with hoverfly identification. Thanks also go to S. Droege for lending his expertise in bee identification. We are also grateful to Bayer, for the Feed-A-Bee grant that funded our Feed-A-Bee research plots. Thank you to the Department of Ecology & Evolutionary Biology at the University of Tennessee for the support of this project.”

We note that you have provided funding information that is currently declared in your Funding Statement. However, funding information should not appear in the Acknowledgments section or other areas of your manuscript. We will only publish funding information present in the Funding Statement section of the online submission form.

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“LR received funding from Bayer in 2019 ($5000 Feed A Bee).”

Please include your amended statements within your cover letter; we will change the online submission form on your behalf.

***We removed the statement from the acknowledgements section. It now reads “We would like to thank the University of Tennessee (UT), the UT Institute of Agriculture, the UT Gardens, and the UT Ag Research and Education Centers, including the Plateau AgResearch Center, the Organic Crops Unit, and the Forest Research and Education Center, for allowing us to do research on their lands, especially K. Hoyt, B. Simpson, W. Hitch, H. Jones, J. Newburn, and W. Lively. We would also like to thank D. Matheson, S. Collins, and A. Murray for field assistance and N. Oldham for assisting with hoverfly identification. Thanks also go to S. Droege for lending his expertise in bee identification. Thank you to the Department of Ecology & Evolutionary Biology at the University of Tennessee for the support of this project.”***

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***We removed the figures from the manuscript file.***

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5. Review Comments to the Author

Reviewer #1: This paper presents a study on the interplay between landscape and local-scale factors in shaping the attractiveness (in terms of plant-pollinator interactions and alpha diversity metrics) of floral bee gardens. This study considers two relevant spatial scales and investigates how important factors, such as resource availability and habitat amount, shape bee communities across human-dominated landscapes. The paper seems to be based on the master work of one of the authors, and thus, the limitations regarding sampling size (e.g., replicates per treatment) can be understood regarding the (probaly) limited humanpower and existing time constraints. The paper is well-written, structured, and organized. The authors have made the data available as declared.

***We thank the reviewer for their thorough and helpful comments. We have addressed your comments on a point-by-point basis, demarcated by three asterisks (***).***

Having said that, we have a number of major concerns regarding the (1) statistical analyses (families used and model assumptions, colinearity in the variables, definition of variables, model assembly, assumptions), (2) some of the methods, (3) some rationals regarding the conceptualisation of the study, and (4) the available datasets, which seem to have not been properly cleaned and are not sufficiently documented to reproduce and re-use the data (we have tried ourself and wasn’t able to reproduce the work). Thus, together, these points question the study as a whole and prevent to recommend the paper for publication in its current form. We think that there might be potential for publication, but this will require work.

I have added my comments below, which we hope will be useful for the authors

### Major comments: ###

- Statistical analyses:

o Correlations among predictors: The authors do not mention any collinearity check on their predictors, but this is a basic standard check. We’ve check the correlations of some of the predictors and they are quite high: floral display at the local scale vs. development; floral display at the local vs. plant richness at the local, plant richness at the local vs. development. The authors checked collinearity before building the models and checked the variance inflation factor (VIF) of the model. We guess the authors are familiar with it, but there is a large number of problems related to colinearity. This issue raises questions regarding the validity of the models.

***To address this concern, we ran separate models for the plant diversity and abundance terms, and then used AIC to select the better model.***

o Statistical families of the models: The authors seem to have used Gaussian families for all their variables, despite working with count data (i.e., the assumptions of Gaussian do not necessarily work when you have count data, which is limited to countable values). While gaussian families are adequate when count data is faily large, it shouldn’t be used when the counts are “small” and there are zeros. This violates the assumption of constance variance. In your case, I think you should use “Poisson” family if there is no overdispersion, or using a negative binomial if overdispersion. This puts all models and results into question, as they are now.

***The Poisson models were overdispersed. In the revised manuscript, we now use glmmTMB to build negative binomial models.***

o Model specifications and Table 1: The random effect structure specified in the method section and the one presented in table 1 do not match. In the methods, it is said that the random effects were site and sampling date nested in the site. However, in Table 1, it appears that garden type

10.1371/journal.pone.0309000.r003
Decision Letter 1
Bossart Janice L. Academic Editor
© 2024 Janice L. Bossart
2024
Janice L. Bossart
https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Submission Version1
11 Jul 2024

PONE-D-24-09528R1Do local and landscape context affect the attractiveness of flower gardens to bees?PLOS ONE

Dear Dr. Russo, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Aug 25 2024 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Dr. Janice L. Bossart

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Additional Editor Comments:

The revised version has corrected most of the problems identified by reviewers.  Thank you for your efforts to address their concerns.  Below I list remaining issues that need attention.

Line 124.  Missing 'the'.  Three of the...

Line 439.  Missing word.  There 'was' ?

Line 728.  Please spell out linear model(s) so it's not confused with 1m, and either make model plural or add an 'a' before linear.

Table 1.  Delete the extraneous 's' at the end.

Figure S1.  The legend struck me as a bit odd given 'Bees' aren't an Order.  Maybe Hymenoptera-Bees and Hymenoptera-Non Bees?  Or maybe you can think of some other way that all terms fit.

Figure 3C.  Given the overlap of confidence intervals of 'Mixed' and at least 'Organic', I'm not sure I buy the interpretation that both 'Forage' and 'Mixed' had higher Shannon Diversity than all others.

--Mismatch between Figure 3 and Figure 3 caption.  Letter designations in the Figure caption don't match letter designations associated with plots in the actual figure.  Also, there is no plot of local bee abundance and land development (I'm guessing it's the caption that's incorrect given what is stated in the Results section).  

--Mismatch between Table 1 and text in the Methods.  Is sampling round nested within Site or nested within Plot?  The Table says Plot, the text says Site (Line 273).  Regardless of which is correct, the text would read better if you delete 'identity'.

--Loose use of 'diversity' throughout.  Given diversity can be used in multiple ways, please don't use it when you are referring specifically to species richness of either bees or flowers.  Otherwise, readers can't be sure whether you mean diversity, in terms of both richness and evenness, or simply richness.  Please carefully go through the manuscript, including figures and tables, and replace your use of 'diversity' with 'richness' anywhere you are explicitly referring to richness.

--Be consistent across Text, Figures, Tables, etc. including supplemental.  For example, Figure S2 uses Shannon Diversity and Figure 2C uses Shannon Index.  I didn't check every use, but Shannon diversity is often used in the text so perhaps that would be the way to go throughout.  Also, Figure S2C is unnecessary given it is identical to Figure 2C.  

--Rarefaction & Coverage methods. There is insufficient information in this section of the manuscript, e.g. approx. 256-267, to understand data shown in the resultant Figures.  iNEXT calculates Hill numbers, which at least needs to be pointed out as these are different calculations than other methods use.  Also, your figures don't correspond with figures generated by iNEXT for sample coverage or completeness, e.g. I'm expecting coverage or completeness to be an axis label.  No doubt I'm missing something, but if I am then others will likely also be confused.  Please add a bit of text to clarify how coverage was estimated and depicted.

[Note: HTML markup is below. Please do not edit.]

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

10.1371/journal.pone.0309000.r004
Author response to Decision Letter 1
Submission Version2
25 Jul 2024

PONE-D-24-09528R1

Do local and landscape context affect the attractiveness of flower gardens to bees?

PLOS ONE

Dear Dr. Russo,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Aug 25 2024 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

• A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

• A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

• An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Dr. Janice L. Bossart

Academic Editor

PLOS ONE

***We would like to thank the editors for the helpful comments. We have addressed all the comments on a point by point basis below, demarcated with three asterisks.***

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Additional Editor Comments:

The revised version has corrected most of the problems identified by reviewers. Thank you for your efforts to address their concerns. Below I list remaining issues that need attention.

**Thank you for these helpful comments!***

Line 124. Missing 'the'. Three of the...

***Fixed.***

Line 439. Missing word. There 'was' ?

***Fixed.***

Line 728. Please spell out linear model(s) so it's not confused with 1m, and either make model plural or add an 'a' before linear.

***We changed this to “The lines are drawn with the function “geom_smooth(method = lm)” in the package ggplot2...” to clarify this sentence.***

Table 1. Delete the extraneous 's' at the end.

***Fixed.***

Figure S1. The legend struck me as a bit odd given 'Bees' aren't an Order. Maybe Hymenoptera-Bees and Hymenoptera-Non Bees? Or maybe you can think of some other way that all terms fit.

***We changed “Order” to “Taxa” in this figure to correct for the different categories.***

Figure 3C. Given the overlap of confidence intervals of 'Mixed' and at least 'Organic', I'm not sure I buy the interpretation that both 'Forage' and 'Mixed' had higher Shannon Diversity than all others.

***For the supplemental figure showing the results of the rarefaction analyses, we realized it should be labeled as Figure S2, instead of S3, so we corrected that. The Forage and Mixed had higher Shannon Diversity, but only when honeybees are included, whereas the figure in the main text shows the honeybees removed, so we clarified this in text. We also added a new supplemental table with the raw data output from the rarefaction analysis showing the estimated diversity and its confidence intervals, and the sample coverage for the sites and surveys.***

--Mismatch between Figure 3 and Figure 3 caption. Letter designations in the Figure caption don't match letter designations associated with plots in the actual figure. Also, there is no plot of local bee abundance and land development (I'm guessing it's the caption that's incorrect given what is stated in the Results section).

***Thank you for catching that! We corrected the figure caption to match the figure.***

--Mismatch between Table 1 and text in the Methods. Is sampling round nested within Site or nested within Plot? The Table says Plot, the text says Site (Line 273). Regardless of which is correct, the text would read better if you delete 'identity'.

***The table was correct, so we modified the main text to match. We deleted “identity” in the text.***

--Loose use of 'diversity' throughout. Given diversity can be used in multiple ways, please don't use it when you are referring specifically to species richness of either bees or flowers. Otherwise, readers can't be sure whether you mean diversity, in terms of both richness and evenness, or simply richness. Please carefully go through the manuscript, including figures and tables, and replace your use of 'diversity' with 'richness' anywhere you are explicitly referring to richness.

***Thank you for this, we have revised the text throughout, and checked the figures in the main text and supplement. We include “diversity” rather than “species richness” under the following circumstances: 1) for bee diversity when we are referring both to species richness and Shannon diversity, 2) for the plant diversity where we ranked floral diversity on a scale of 1-10 rather than quantifying species richness of the flowering plants. In addition to these edits, we reviewed our use of floral display throughout to make it more consistent.***

--Be consistent across Text, Figures, Tables, etc. including supplemental. For example, Figure S2 uses Shannon Diversity and Figure 2C uses Shannon Index. I didn't check every use, but Shannon diversity is often used in the text so perhaps that would be the way to go throughout. Also, Figure S2C is unnecessary given it is identical to Figure 2C.

***We changed Shannon Index to Shannon Diversity throughout and checked the figures as well. We agree that is the more appropriate term. We removed Figure S2C (it was replaced with sample coverage graphs).***

--Rarefaction & Coverage methods. There is insufficient information in this section of the manuscript, e.g. approx. 256-267, to understand data shown in the resultant Figures. iNEXT calculates Hill numbers, which at least needs to be pointed out as these are different calculations than other methods use. Also, your figures don't correspond with figures generated by iNEXT for sample coverage or completeness, e.g. I'm expecting coverage or completeness to be an axis label. No doubt I'm missing something, but if I am then others will likely also be confused. Please add a bit of text to clarify how coverage was estimated and depicted.

***Thank you for pointing out this omission. We added detail about the methods used (and Hill numbers) to the methods. We also add new graphs to the supplemental figure to show the sampling completeness of the surveys and sites.***

[Note: HTML markup is below. Please do not edit.]

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

Attachment Submitted filename: Response to Reviewers.docx

10.1371/journal.pone.0309000.r005
Decision Letter 2
Bossart Janice L. Academic Editor
© 2024 Janice L. Bossart
2024
Janice L. Bossart
https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Submission Version2
5 Aug 2024

Do local and landscape context affect the attractiveness of flower gardens to bees?

PONE-D-24-09528R2

Dear Dr. Russo,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.  Congratulations!

There are two minor issues that first need to be corrected.  I have alerted the journal editor that these should be corrected before publication:

Line 754.  Figure 3 Caption.  Move (E) forward to follow 'richness' versus where you currently have it.

Figure S2 Caption, line 5. Should be '...abundant species affects...', i.e. affect should be plural.

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10.1371/journal.pone.0309000.r006
Acceptance letter
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