Hostname: page-component-cd9895bd7-gxg78 Total loading time: 0 Render date: 2024-12-24T17:56:10.013Z Has data issue: false hasContentIssue false

Auxin herbicides, halosulfuron, sulfentrazone, and topramezone disparately affect morphology and ultraviolet features of weedy flowers and associated pollinator foraging

Published online by Cambridge University Press:  30 October 2024

Navdeep Godara
Affiliation:
Graduate Assistant, School of Plant and Environmental Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA
Shawn D. Askew*
Affiliation:
Professor, School of Plant and Environmental Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA
*
Corresponding author: Shawn D. Askew; Email: [email protected]
Rights & Permissions [Opens in a new window]

Abstract

Pollinators risk exposure to insecticide residue when visiting weedy flowers in urban landscapes. Previous research shows that pollinators are routinely exposed to a variety of pesticides, but herbicides have exhibited minimal toxicity and did not contribute to the modeled risk quotients. Herbicides from different modes of action may deter pollinators from visiting turfgrass weeds, but their temporal influence on floral quality and pollinator foraging is unaddressed. Research experiments were conducted at Blacksburg, VA, in 2023 to assess the effect of four herbicides on floral morphology and ultraviolet (UV) reflectance of three different UV floral classes of weeds and associated pollinator foraging visits. Among 1,080 assessments per weed species, honeybees (Apis mellifera), bumble bees (Bombus spp.), solitary bees (Chelostoma florisomne), and flies (Diptera spp.) accounted for 94%, 2%, 3%, and 1%, respectively, of the total pollinator visitations on white clover (Trifolium repens L.) inflorescences; 71%, 2%, 0%, and 27%, respectively, on dandelion (Taraxacum officinale F.H. Wigg.) flowers; and 0%, 0%, 78%, and 22%, respectively, on bulbous buttercup (Ranunculus bulbosus L.) flowers. Pollinator visitation and floral quality were temporarily affected by herbicide application, with some herbicides eliminating food resources, while others transiently impacted floral quality and density. The combination of 2,4-D + dicamba + MCPP and topramezone eliminated pollinator foraging visits, but on differing temporal scales of 3 d for auxins and 14 d for topramezone. Halosulfuron and sulfentrazone transiently suppressed floral quality and density, with varying degrees of deterrence on pollinators depending on the weed species. All evaluated herbicides reduced radiometric UV reflectance of T. officinale petal apices, but only synthetic auxin and topramezone reduced digitally assessed floral UV-reflecting area. Petal UV reflectance appears to contribute but not solely influence pollinator foraging behavior. UV-absorbing and UV-reflecting flowers differed in UV-reflectance response to herbicides, but pollinators were similarly deterred. Results suggest that herbicides may offer a variety of management solutions to pollinator deterrence in areas slated for insecticide treatment, including long-term or transient deterrence with potential food-resource preservation.

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2024. Published by Cambridge University Press on behalf of Weed Science Society of America

Introduction

The recent decline in pollinator abundance is a cause of concern for sustaining global food production (Koh et al. Reference Koh, Lonsdorf, Williams, Brittain, Isaacs, Gibbs and Ricketts2015; USDA 2016), eliciting calls for land management policy (Dicks et al. Reference Dicks, Breeze, Ngo, Senapathi, An, Aizen, Basu, Buchori, Galetto, Garibaldi, Gemmill-Herren, Howlett, Imperatriz-Fonseca, Johnson and Kovacs-Hostyanszki2021). Pesticides have been cited as a likely abiotic contributor that negatively interacts with other biotic stressors, adversely affecting pollinator abundance (Goulson et al. Reference Goulson, Nicholls, Botias and Rotheray2015). Synthetic insecticides are primarily utilized to prevent damage from foliar- or root-feeding insects in managed turfgrass systems (Held and Potter Reference Held and Potter2012). The most widely used insecticides in turfgrass pest management are neonicotinoids such as clothianidin, dinotefuran, imidacloprid, and thiamethoxam, which pose a severe threat to pollinators and natural enemies foraging on weedy flowers for floral resources (Larson et al. Reference Larson, Dale, Held, McGraw, Richmond, Wickings and Williamson2017). Preventive insecticide treatments in turf are applied between March and June, aligning with the periodicity of weedy flower bloom, therefore increasing insecticide-associated risk to pollinators (Larson et al. Reference Larson, Dale, Held, McGraw, Richmond, Wickings and Williamson2017).

Weeds provide floral resources to pollinators (Bretagnolle and Gaba Reference Bretagnolle and Gaba2015; Hicks et al. Reference Hicks, Ouvrard, Baldock, Baude, Goddard and Kunin2016). In urban landscapes, dandelion (Taraxacum officinale F.H. Wigg.) and white clover (Trifolium repens L.) were visited by 50 different species of pollinators, including 37 species of bees (Larson et al. Reference Larson, Kesheimer and Potter2014). This convergence of turfgrass weeds and pollinators in urban landscapes increases the risk of pollinator exposure to toxic insecticide residues (Gels et al. Reference Gels, Held and Potter2002; Larson et al. Reference Larson, Redmond and Potter2013). Instructions on insecticide labels for pollinator protection mention “Do not apply this product while bees are foraging” (Anonymous 2022), which does not provide specific directions to practitioners for the prevention of pollinator exposure. Existing best practices for reducing pollinator exposure include not spraying areas potentially visited by pollinators, spraying in the morning or during times that pollinators are inactive, mowing the area to remove weedy flowers before insecticide treatment, and controlling flowering weeds with herbicides (Godara et al. Reference Godara, Williamson, Koo and Askew2023; Larson et al. Reference Larson, Redmond and Potter2015; NCIPMC 2019).

Herbicides affect pollinator foraging by reducing weedy flower density and floral resources (King Reference King1964; MacRae et al. Reference MacRae, Mitchem, Monks and Parker2005; Schmitz et al. Reference Schmitz, Schafer and Bruhl2013). Sublethal drift of synthetic auxin herbicides reduced the floral density and pollinator foraging frequency on alfalfa (Medicago sativa L.) and common boneset (Eupatorium perfoliatum L.) despite similar pollen protein concentrations in herbicide-treated and nontreated flowers (Bohnenblust et al. Reference Bohnenblust, Vaudo, Egan, Mortensen and Tooker2016). Glyphosate applied at sublethal rates reduced floral density and delayed flowering of common tansy (Tanacetum vulgare L.), leading to a decline in insect visitation (Dupont et al. Reference Dupont, Strandberg and Damgaard2018). Herbicides could be utilized in managed turfgrass systems before insecticide applications, as weedy flowers are not typically desired (Godara et al. Reference Godara, Williamson, Koo and Askew2023). However, these management practices may limit future food resources for pollinators for several months, if not years.

Herbicides from different modes of action (MOAs), including acetolactate synthase inhibitors, carotenoid biosynthesis inhibitors, protoporphyrinogen oxidase (PPO) inhibitors, and synthetic auxins were classified as practically nontoxic to honeybee (Apis mellifera) (Bunch et al. Reference Bunch, Gervais, Buhl and Stone2012; Gervais et al. Reference Gervais, Luukinen, Buhl and Stone2008; PMRA 2014; USEPA 2012, 2014). Acute contact and oral toxicity (LD50) to honeybees from the herbicides 2,4-D, dicamba, sulfentrazone, topramezone, and halosulfuron exceed 100,000 and 10,000 ng ai per bee, respectively (APVMA 2011; PMRA 2014; USEPA 2012, 2014). The insecticide imidacloprid, by comparison, has contact and oral LD50 for honeybees of 60 to 243 ng and 4 to 41 ng ai per bee, respectively (Gervais et al. Reference Gervais, Luukinen, Buhl and Stone2010), which are at least 412 and 244 times more toxic than the above-mentioned herbicides following contact or oral exposure, respectively. A statewide study conducted in Maine demonstrated that fungicide and herbicide residues were detected at a higher frequency in pollen of 32 apiaries compared with insecticides, but insecticides constituted the highest risk quotient via contact or oral exposure and herbicides comprised none of the risk quotient (Drummond et al. Reference Drummond, Ballman, Eitzer, Du Clos and Dill2018).

Herbicides pose little risk to pollinators, so their incorporation into efforts to protect pollinators from insecticide exposure through weedy floral suppression should be explored. Herbicides of differing MOAs influence weed physiology differently with regard to temporal plant phytotoxicity and mortality (Duke Reference Duke1990; Shaner Reference Shaner2014); therefore, one would expect variable degrees of pollinator deterrence and impact on long-term food resources between herbicides. Pollinators vacated auxin-treated turfgrass within 2 d after treatment; however, T. repens flower quality persisted up to 5 d after treatment (Godara et al. Reference Godara, Williamson, Koo and Askew2023). This rapid pollinator evacuation from treated lawn weeds suggests a viable practice for preventing the exposure of pollinators to insecticides. However, no literature exists to explain why pollinator evacuation following auxin herbicide treatments to T. repens was so rapid despite the persistence of floral quality. Likely causes may include reduced nectar production, as has been observed following some herbicide treatments (Kearns et al. Reference Kearns, Inouye and Waser1998; King Reference King1964), or changes in ultraviolet (UV) floral features that are invisible to humans.

Previous researchers documented that UV floral features affect pollinator foraging behavior (DeMarche et al. Reference DeMarche, Miller and Kay2015; Koski and Ashman Reference Koski and Ashman2014; Papiorek et al. Reference Papiorek, Junker, Alves-Dos-Santos, Melo, Amaral-Neto, Sazime, Wolowski, Freitas and Lunau2016; Rae and Vamosi Reference Rae and Vamosi2012). A study that investigated 43 taxa of Hymenoptera observed that insects have a trichromatic color vision system with photoreceptors that peak at 340, 430, and 535 nm (Peitsch et al. Reference Peitsch, Fietz, Hertel, de Souza, Ventura and Menzel1992), emphasizing the importance of UV reflectance in insect vision. Johnson and Andersson (Reference Johnson and Andersson2002) observed that African honeybee (Apis mellifera scutellata) foraging on African potato (Hypoxis hemerocallidea Fisch. & C.A. Mey.), a UV-reflecting flower, was decreased when the flower surface was coated with sunscreen containing UV-absorbing compounds. Although UV floral features have been characterized by plant species in some ecosystems (Tunes et al. Reference Tunes, Camargo and Guimaraes2021), no studies have reported the effect of herbicides on these features.

Through the exploration of how herbicides of differing MOAs influence floral responses and associated insect foraging behavior, we aim to expand potential best practices for pollinator deterrence in areas that would receive insecticide treatments. Such practices not only protect pollinators, but may reduce regulatory pressure on important insecticide chemistries. We hypothesized that weedy flowers will vary in magnitude and temporal floral periodicity following disparate herbicide treatments, and that insect visitation will likewise vary depending on herbicide. Our first objective was to evaluate the effect of four herbicides from different MOAs on pollinator foraging visits and relate these temporally to floral quality and density metrics. Our second objective was to measure the posttreatment impacts of four herbicides on UV floral features of weedy flowers or inflorescences that can be characterized as UV-absorbing, UV-reflecting at petal apex with bullseye patterns, and UV-reflecting petals with contrasting reproductive parts.

Materials and Methods

Field Assessment of Floral Features and Insect Visitation

Field experiments were conducted as a single-factor, randomized complete block design with four replications and two temporal runs at the Virginia Tech Glade Road Research Facility (37.23°N, 80.43°W), Blacksburg, VA, the Virginia Tech Turfgrass Research Center (37.22°N, 80.41°W), Blacksburg, VA, and a private residence (37.28°N, 80.44°W), Blacksburg, VA. Separate studies were conducted for each of the two floral classifications for a total of 4 site-years (2 per floral class). The floral classifications (Godara and Askew Reference Godara and Askew2023) included “UV-absorbing inflorescence” (represented by T. repens) at two sites and “UV-reflecting at petal apex with bullseye-pattern flowers” (represented by T. officinale and R. bulbosus) at two sites. Studies were initiated on April 21, May 20, May 31, and June 12 of 2023 for UV-reflecting site 1 (37.22°N, 80.41°W), UV-reflecting site 2 (37.28°N, 80.44°W), UV-absorbing site 1 (37.23°N, 80.43°W), and UV-absorbing site 2 (37.23°N, 80.43°W), respectively. Plots were 3.2, 3.2, and 6.5 m2 for T. repens, R. bulbosus, and T. officinale, respectively. Plot size was varied to achieve at least 30 inflorescences per plot. The resulting floral density at study initiation was 30, 10, and 5 inflorescences m−2 for T. repens, R. bulbosus, and T. officinale, respectively. A buffer zone of 3 m between plots and 6 m between blocks ensured that adjacent plots did not serve as the primary insect attractant.

Treatments included a nontreated control; a premix of 2,4-D, dicamba, and MCPP; halosulfuron; sulfentrazone; and topramezone. A detailed list of treatments with product names, manufacturer descriptions, herbicide MOAs, and rates is provided in Table 1. All herbicides were applied using a CO2-pressurized backpack sprayer equipped with four extended-range (XR11006VS) flat-fan spray nozzles (TeeJet® Technologies, Wheaton, IL), calibrated to deliver 468 L ha−1 at a speed of 4.8 km h−1. Herbicides were applied to weedy flowers at 8:00 AM 1 d after experiment initiation. Mowing and fertilizer applications were withheld throughout the study duration to prevent any alteration to flower density. Baseline floral density and plot size for each study were chosen based on preliminary work to have sufficient pollinator visitation on weedy flowers (data not shown).

Table 1. List of treatments with trade names, manufacturer details, herbicide modes of action, and rates evaluated in experiments assessing ultraviolet (UV)-absorbing inflorescence, UV-reflecting at petal apex with bullseye-pattern, and UV-reflecting petals with contrasting reproductive part weedy flowers.

a Nonionic surfactant at 0.25% v/v was added.

b Crop oil concentrate at a rate of 0.5% v/v was added.

Flower density data were collected by counting all flowers in each plot, and three representative flowers in each plot were photographed to assess the flower quality every day at 9:00 AM. Flowers were counted toward the density metric if apparently “healthy” tissue was visually perceived from a standing position. Flower images were batch processed through the object selection tool in Adobe Photoshop (Adobe, San Jose, CA) to select flowers based on color and shape and eliminate background elements before digital analysis. Processed images were analyzed using TurfAnalyzer (Green Research Services, Fayetteville, AR) to quantify flower discoloration. Insect visitation was assessed by counting unique foragers that physically interacted with flowers that were encountered over a 1-min assessment period in each plot three times each day (∼10:00 AM, ∼12:00 PM, and ∼2:00 PM), similar to other researchers (Bohnenblust et al. Reference Bohnenblust, Vaudo, Egan, Mortensen and Tooker2016; Boyle et al. Reference Boyle, Wisdom and Richardson2020; Larson et al. Reference Larson, Redmond and Potter2013). Insect foragers were separated into honeybees, bumble bees (Bombus spp.), solitary bees (Osmia spp.), hoverflies (Syrphidae), wasps (Vespula spp.), and butterflies (Hesperiidae, Nymphalidae, Papilionidae, Lycaenidae). Insect visitation, floral density, and flower quality data for all floral species were taken on 1 d before and 0, 1, 2, 3, 4, 7, 10, and 14 d after treatment (DAT).

Floral reflectance via radiometry, UV images, visible-light images, and fluorescent-light images were collected from three random flower samples from each plot at 4, 24, and 72 h after treatment (HAT). Flowers were harvested from experimental sites in test tubes (Falcon 15-ml centrifuge tube, Corning, Tewksbury, MA) containing 5 ml L−1 of Miracle-Gro solution for fresh cut flowers (Scotts, Miracle-Gro, Marysville, OH) and moved to an indoor studio with controlled lighting at the Virginia Tech Glade Road Research Facility. UV floral features were captured with an EOS 5D Mark IV camera (Canon, Tokyo, Japan) in which an internal hot mirror was modified with a UV band-pass filter (Life Pixel Infrared, Mukilteo, WA) (Klomberg et al. Reference Klomberg, Dywou Kouede, Bartos, Mertens, Tropek, Fokam and Janecek2019) and utilizing a non–UV coated Levnoc Helios 44-mm lens and remote digital viewing screen (Shinobi 4K HDMI Monitor, Atomos, Carlton, Australia). Light images and UV-light images were captured with a nonmodified version of a similar camera, Canon EOS 5D Mark IV with a Canon EF 105-mm lens under a UV light (Everbeam®, Surrey, BC, Canada) that emits 315 to 405 nm with a peak at 365 nm or bright white light (Craftsman®, Towson, MD) that emits 400 to 700 nm. Reflectance standards were used for UV photography, including a WS-1 (Ocean Insight, Orlando, FL) diffuse reflectance standard, which reflects >98% of light ranging from 250 to 1,500 nm; a custom-made barium sulfate standard reflecting 100% of UV light; a custom-made barium sulfate and charcoal mixture, uniformly reflecting 50% of incident UV light; and a custom-made charcoal standard absorbing all UV light (Garcia et al. Reference Garcia, Greentree, Shrestha, Dorin and Dyer2014). All images also included a ruler and color standard (DGK-Pro Multifunction Color Chart, DGK Color Tools, Boston, MA). UV photographs were exposure corrected to achieve a uniform hue of UV-reflecting areas by visual evaluation of barium sulfate and charcoal mixture standards. Photographs were subjected to an object selection tool in Adobe Photoshop to select flowers based on color and shape (described earlier) before digital analysis to quantify UV-reflecting area based on hue/saturation-based thresholds using TurfAnalyzer.

Spectral reflectance data ranging from 200 to 950 nm with 1.6-nm optical resolution were collected from each of the three random flower samples harvested from each plot with a QEPRO-XR spectrometer (Ocean Insight). The QEPRO-XR spectrometer was equipped with a UV-sensitive fiber-optic probe (QR400-7-SR, Ocean Insight) and connected to a PX-2 Pulsed Xenon light source (Ocean Insight) having a 200- to 750-nm light output. The fiber-optic probe was fixed at 45° and 2 cm above the target for collecting reflectance data. As established by previous researchers (Camargo et al. Reference Camargo, Lunau, Batalha, Brings, de Brito and Morellato2019; Tunes et al. Reference Tunes, Camargo and Guimaraes2021), reflectance data were collected on each flower at the petal apex, petal base, and reproductive structures. Pollinator visitation and floral quality data over time were converted to the area under progress curve (AUPC) using

([1]) $$\partial = \sum\nolimits_{i = 1}^{n_{i - 1}} {\left( {{{\left( {{y_i} + {y_{\left( {i - 1} \right)}}} \right)} \over 2}\left({t_{\left( {i + 1} \right)}} - {t_{\left( i \right)}}\right)} \right)} $$

where $$\partial $$ is the AUPC of floral quality or pollinator visitation, i is the ordered sampling date, n_i is the number of sampling dates, y is pollinator visitation or floral quality expressed as a percent of the nontreated control at a given assessment date, and t is the time in days. AUPC data were subjected to ANOVA using PROC GLM in SAS v. 9.3 (SAS Institute, Cary, NC). Means were separated using Fisher’s protected LSD (α = 0.05). Based on the significance of experimental run by treatment or treatment effect, data were subjected to nonlinear regression (Table 2) using SigmaPlot software (v. 13.0, Systat software, San Jose, CA). Other response variables were also subjected to ANOVA using the same procedure, and means were separated using Fisher’s protected LSD (α = 0.05).

Table 2. Nonlinear and polynomial regression equations with parameters utilized for pollinator visitation and floral quality of ultraviolet (UV)-absorbing inflorescence and UV-reflecting at petal apex with bullseye-pattern flowers.

Additional UV-Reflectance Assessment

Two additional experiments were conducted to evaluate the effect of herbicides on an alternate floral UV-reflectance class that reflects more UV than “bullseye”-type flowers. Foxglove beardtongue (Penstemon digitalis Nutt. ex Sims) flowers reflect UV throughout the petals, but have contrasting reproductive organs that absorb UV (Godara and Askew Reference Godara and Askew2023). Penstemon digitalis flowers were collected from the Virginia Tech Glade Road Research Facility (37.23°N, 80.43°W), Blacksburg, VA, on June 20, 2023, and July 6, 2023. The experiment was conducted as a randomized block design with two temporal runs and four replications. Each experimental unit had three subsample flowers for a total of 12 flowers per treatment for each experimental run. Flowers were collected from volunteer plants growing in a 4-yr-old pollinator garden and moved to test tubes, as previously described. These studies differed from the aforementioned field studies in that flowers were treated with herbicides on June 20 and July 6, 2023, after being separated from plants rather than spraying plants in situ. Similar to these previous studies, flowers were subjected to digital photography and radiometric reflectance analysis at 4 HAT. Thus, these studies only evaluated floral reflectance metrics soon after treatment and did not assess the impact of herbicide treatments on pollinator visitation, floral density, and floral quality. Our goal was to compare an alternate class of UV-reflecting flowers for impact on UV reflectance soon after herbicide treatment. Previous research demonstrated that P. digitalis plant height was 76 cm and 13 cm for inflorescence (Parachnowitsch and Kessler Reference Parachnowitsch and Kessler2010), so it is unlikely to occur in managed turfgrass situations, but is found in managed beds and reduced management sites in urban settings. Penstemon digitalis offers floral rewards to a broad diversity of pollinators (Clinebell and Bernhardt Reference Clinebell and Bernhardt1998) and is an important component of pollinator gardens (Anonymous 2024). Because its inflorescences could be subjected to insecticide drift in urban settings, it was deemed a viable candidate for this research despite its differences from R. bulbosus, T. officinale, and T. repens. Reflectance and UV-reflecting area data were subjected to ANOVA using PROC GLM in SAS v. 9.3, and means were separated using Fisher’s protected LSD (α = 0.05).

Results and Discussion

UV-absorbing Inflorescence and Pollinator Response to Herbicides

Honeybees comprised 94% over the total pollinator visitations on T. repens inflorescences followed by bumble bees (2%), solitary bees (3%), and flies (1%) when averaged over 1,080 assessments comprising 27 assessment times, 5 treatments, 4 replicates, and 2 experimental runs (data not shown). Honeybees have been documented as primary insect visitors on T. repens blooms (Goodman and Williams Reference Goodman and Williams1994; Larson et al. Reference Larson, Kesheimer and Potter2014; Wolfin et al. Reference Wolfin, Watkins, Lane, Portman and Spivak2023). Temporal response of UV-absorbing floral quality and pollinator visitation averaged over experimental runs exhibited mostly nonlinear trends (Table 2). Visual association of the temporal trends (Figure 1) and correlations ranging from 0.56 for synthetic auxins to 0.86 for sulfentrazone (data not shown) suggested that the dependency between these two variables varies with herbicide. In the case of auxin herbicides, pollinator visitation declined more rapidly than floral quality (Figure 1A). Pollinator visitation was eliminated at 2 DAT, while floral quality took 7 d to decline by 95% (Figure 1A). Pollinator vacancy in advance of T. repens floral quality decline following auxin herbicide treatment has occurred in other studies (Godara et al. Reference Godara, Williamson, Koo and Askew2023).

Figure 1. Effect of herbicides 2,4-D + dicamba + MCPP (A); halosulfuron (B); sulfentrazone (C); and topramezone (D) on floral quality of ultraviolet (UV)-absorbing inflorescence and pollinator visitation.

Halosulfuron similarly reduced pollinator foraging more rapidly than floral quality, but approximately 35% of pollinators were undeterred (Figure 1B). Sulfentrazone decreased pollinator foraging visits to approximately 25% of nontreated plots in step with floral quality decline (Figure 1C). Both halosulfuron and sulfentrazone exhibited a trend of recovery in pollinator visitation during the assessment, with near-complete recovery following sulfentrazone treatment at 14 DAT (Figure 1B and 1C). These trends suggest that some herbicides may be viable methods to transiently deter pollinator visitation without causing long-term loss of food resources. MacRae et al. (Reference MacRae, Culpepper, Batts and Lewis2008) found that halosulfuron injured watermelon 34% at 2 wk after treatment (WAT), but did not affect fruit production at a later stage, showing that plants recovered from herbicidal injury. Halosulfuron injured broadleaf weeds at 7 to 14 DAT (Anonymous 2018), but McCurdy et al. (Reference McCurdy, McElroy, Flessner, Hoyle and Parker2016) observed that T. repens floral density increased by 65% at 28 DAT. Transient pollinator deterrence could be attributed to the residual attractiveness of halosulfuron-treated flowers or temporary suppression of nectar production in T. repens. Topramezone floral quality persisted for more than 1 WAT and declined sharply thereafter (Figure 1D). Pollinator foraging following topramezone decreased more rapidly than floral quality but required 2 wk to reach peak decline, which completely eliminated pollinator visitation, similar to auxin herbicides (Figure 1D). Thus, if topramezone is to be used as a deterrent to pollinator foraging, insecticide treatment must be delayed for at least 2 WAT of herbicide. Larson et al. (Reference Larson, Redmond and Potter2015) demonstrated that imidacloprid residues were >99% lower in the nectar of newly formed T. repens blooms at 1 WAT, which suggests that translocation of insecticide residue to new blooms is practically nontoxic to pollinators after eliminating the existing blooms with herbicides.

The herbicidal treatment effect was significant for AUPC of pollinator visitation (P < 0.0001) and floral quality (P = 0.0003) of UV-absorbing inflorescence and did not interact with the experimental run, so data were pooled over both experimental runs (Table 3). It should be noted that AUPC is a unitless, relative comparison that reflects the quantity of pollinator foraging visits over the assessment period from 1 to 14 DAT. Thus, in a scenario in which an herbicide was applied to serve as a deterrent to pollinator foraging and an insecticide was applied concurrently, greater AUPC is predictive of greater potential insecticide exposure. The herbicides 2,4-D + dicamba + MCPP reduced the AUPC of pollinator visitation to 0.5 from the nontreated value of 14 (Table 3). Thus, 2,4-D + dicamba + MCPP would allow for insecticide treatment to occur more rapidly with respect to herbicide treatment and effectively eliminate pollinator foraging visits for the 2-wk, posttreatment duration (Table 3). Only one other study has evaluated the temporal trend of pollinator deterrence following herbicide treatment (Godara et al. Reference Godara, Williamson, Koo and Askew2023), wherein pollinator decline following T. repens treatment with 2,4-D + dicamba + MCPP was similar to the current study (Figure 1A). Halosulfuron, sulfentrazone, and topramezone reduced pollinator visitation AUPC to 8.7, 7.4, and 7.2, respectively, which were more than the auxin herbicides AUPC for pollinator visitation (Table 3). These values of pollinator visitation AUPC appear to imply that these herbicides only reduced pollinator visitation by approximately 50% compared with the nontreated control (Table 3), but the temporal trends show that the maximum reduction in pollinator decline was 35%, 25%, and 0% of the nontreated control for halosulfuron, sulfentrazone, and topramezone, respectively (Figure 1B–D). Trends in AUPC of flower quality generally mirrored those of pollinator visitation AUPC (Table 3). During the duration of the experiment, total reduction in floral quality differed between each herbicide and can be ordered greatest to least floral quality reduction based on AUPC for 2,4-D + dicamba + MCPP, sulfentrazone, halosulfuron, and topramezone (Table 3). As with insect visitation AUPC, floral quality AUPC numbers reflect cumulative quality over the entire period and do not necessarily reflect peak floral quality reduction. Herbicides from similar MOAs evaluated in other studies also reduced floral quality. Clopyralid, halosulfuron, and mesotrione caused 73%, 88%, and 45% phytotoxicity to garden coreopsis (Coreopsis lanceolata L.) flowers (Henry et al. Reference Henry, Tucker and McCurdy2023).

Table 3. Effect of herbicides on area under progress curve (AUPC) for pollinator visitation and flower quality of ultraviolet (UV)-absorbing inflorescence and UV-reflecting at petal apex with bullseye-pattern flowers. a

a Means followed by the same letter within each column are not significantly different based on Fisher’s protected LSD (α = 0.05).

In turfgrass systems, floral density changes over time and is transiently reduced by mowing (Fetridge et al. Reference Fetridge, Ascher and Langellotto2008; Lerman et al. Reference Lerman, Contosta, Milam and Bang2018), typically declining over time when mowing is withheld (Kőrösi et al. Reference Kőrösi, Szentirmai, Batáry, Kövér, Örvössy and Peregovits2014). Such was the case in our study, where mowing was withheld from a turf sward infested with T. repens for approximately 21 d starting 7 d before herbicide treatment. The nontreated control lost 1% and 7% T. repens floral density at 7 and 14 DAT, respectively (Table 4). Zaleski (Reference Zaleski1964) also documented a 14% natural decline in T. repens floral density, which was attributed to retarded vegetative and reproductive growth due to lower levels of light intensity at the base of high-density T. repens. Another possible cause of the decline in T. repens floral density is that several inflorescences present in the subcanopy (<5 cm) were not subjected to mowing, and maximum T. repens bloom occurred ∼4 wk after the mowing event, which suggests unmowed blooms reached floral longevity (SAREP 2024). Herbicides may reduce floral density by phytotoxic effect on the whole inflorescence or by delaying the production of new inflorescences (Carpenter et al. Reference Carpenter, Mathiassen, Boutin, Strandberg, Casey and Damgaard2020). Furthermore, synthetic auxin herbicide triggers the biosynthesis of ethylene, a known hormone that influences floral induction and evocation (Askew Reference Askew2017). These herbicides also cause epinasty, tissue swelling, and inhibition of auxin transport, which delays flowering time and reduces floral display (Ramos et al. Reference Ramos, Bakhtiari, Castañeda-Zárate, Iriart and Ashman2023). For all herbicides, T. repens floral density at 7 and 14 DAT (Table 4) generally mirrored trends in floral quality (Figure 1), and only the 2,4-D + dicamba + MCPP treatment reduced floral density 100% at 14 DAT (Table 4). MacRae et al. (Reference MacRae, Mitchem, Monks and Parker2005) also found that synthetic auxins reduced T. repens floral density 100% and suggested herbicides as a measure of pollinator protection from insecticide treatment in apple (Malus spp.) orchards.

Table 4. Effect of herbicides on weedy floral density at 7 and 14 d after treatment (DAT). a

a Floral density is expressed as a percent reduction of initial flower density. Means followed by the same letter within each column are not different based on Fisher’s protected LSD (α = 0.05).

UV-reflecting at Petal Apex with “Bullseye” Pattern Flower and Pollinator Response to Herbicides

Honeybees, bumblebees, and hoverflies (Syrphidae) accounted for 71%, 2%, and 27%, respectively, of total pollinator foraging visits on T. officinale flowers, while solitary bees (Chelostoma florisomne) and flies (Diptera) accounted for 78% and 22%, respectively, of total insect visitors on R. bulbosus flowers (data not shown). Previous research also documented honeybees and hoverflies as primary visitors on T. officinale flowers (Larson et al. Reference Larson, Kesheimer and Potter2014), and solitary bees on R. bulbosus flowers (Westrich Reference Westrich, Matheson, Buchmann, O’Toole, Westrich and Williams1996). The temporal response of UV reflecting at petal apex with “bullseye” pattern floral quality and associated pollinator visitation averaged over experimental runs exhibited nonlinear trends (Table 2). Response variables differed by herbicidal effect, and floral quality persisted longer after herbicide treatment compared with pollinator visitation, which declined rapidly (Figure 2).

Figure 2. Effect of herbicides 2,4-D + dicamba + MCPP (A); halosulfuron (B); sulfentrazone (C); and topramezone (D) on floral quality of ultraviolet (UV)-reflecting at petal apex with bullseye-pattern flower and pollinator visitation.

Pollinators completely evacuated bullseye flowers 3 d after auxin herbicide treatment but complete floral quality decline required 14 d (Figure 2A). Halosulfuron-treated flower quality declined at each assessment timing such that 25% of floral quality persisted at 14 DAT and 4 d later than complete pollinator evacuation, which occurred by 10 DAT (Figure 2B). Sulfentrazone reduced the quality of bullseye flowers by half at 4 DAT, but floral quality rebounded by 14 DAT (Figure 2C). Sulfentrazone applied at 280 g ha−1 transiently injured cranberry (Vaccinium macrocarpon Aiton) but no differences in reproductive structures were observed at 8 WAT (Besançon et al. Reference Besançon, Ghantous and Sandler2021). Sulfentrazone causes rapid necrosis (Shaner Reference Shaner2014) of herbicide-exposed floral tissues but likely does not inhibit new blooms that develop after treatment. Similarly, pollinator visitation on sulfentrazone-treated flowers also exhibited a rapid decline to as low as 25% of visits on nontreated flowers (Figure 2C) but did not recover over time, as observed in the case of T. repens (Figure 1C). Pollinator visitation on topramezone-treated bullseye flowers declined at each evaluation timing, with no visitors observed at 14 DAT (Figure 2D). Bullseye floral quality also declined, but 48% of floral quality still persisted at 14 d after topramezone treatment (Figure 2D). Previous research conducted in New Jersey, USA, did not measure floral quality but showed that herbicides reduced floral density, resulting in lower abundance, richness, and diversity of pollinator visitation (McDougall et al. Reference McDougall, DiPaola, Blaauw and Nielsen2021). The treatment effect was significant for AUPC of pollinator visitation (P = 0.0009) and floral quality (P = 0.0161) and not dependent on the experimental run (Table 3). Both response variables were pooled over experimental runs that included R. bulbosus and T. officinale sites (Table 3). Synthetic auxin herbicide reduced the AUPC of pollinator visitation to 0.7, but other assessed herbicides had ≥4.4 AUPC (Table 3). All evaluated herbicides reduced the AUPC of bullseye floral quality, but the severity of damage varied with herbicide (Table 3).

The experimental run by treatment effect was significant for floral density reduction of bullseye species at 7 DAT (P = 0.0087) and 14 DAT (P = 0.0054), so data are presented by R. bulbosus and T. officinale sites (Table 4). 2,4-D + MCPP + dicamba reduced T. officinale density 100% at 7 DAT, but other assessed herbicides reduced floral density <50% (Table 4). However, synthetic auxins and topramezone reduced R. bulbosus floral density by at least 74% at 7 DAT (Table 4). At 14 DAT, herbicides reduced T. officinale floral density by at least 73%, with a complete reduction in floral density after 2,4-D + MCPP + dicamba and halosulfuron treatment (Table 4). Similarly, herbicide treatment reduced R. bulbosus floral density ≥93% at 14 DAT, but nontreated control plots also had a 75% reduction in floral density at 14 DAT (Table 4). Schmitz et al. (Reference Schmitz, Schafer and Bruhl2013) also observed that sulfonylurea herbicide reduced Ranunculus spp. floral density by 85% at 2 WAT. Ranunculus bulbosus peak flowering occurs in early June (Sarukhan Reference Sarukhan1974), which explains the 75% reduction in nontreated R. bulbosus flowers in late June, as no new flowers were produced.

Response of Petal UV Reflectance and UV-reflecting Area of Flowers to Herbicides

The treatment effect (P = 0.0194) was significant for UV-A reflectance from the petal apex of P. digitalis at 4 HAT and was not dependent on treatment by experimental run interaction (Table 5). All herbicide treatments reduced UV-A reflectance from the petal apex of P. digitalis flowers to at least 25%, except topramezone (Table 5), which exhibited UV-A reflectance (29%) similar to the nontreated flowers (Table 5). The experimental run by treatment effect was significant for UV-A (P = 0.0015) and UV-B (P = 0.0087) reflectance from petal apex of bullseye flowers at 4 HAT, so data are shown by R. bulbosus and T. officinale flowers (Table 5). Herbicide-treated T. officinale flowers reflected ≤10% of UV-A and UV-B from petal apex at 4 HAT, but nontreated flowers reflected 14% and 13% of UV-A and UV-B, respectively (Table 5). Herbicide treatment did not affect UV-A and UV-B reflectance from the petal apex of the R. bulbosus (Table 5), which could be attributed to the upper epidermal layer of the flower (van der Kooi et al. Reference van der Kooi, Elzenga, Dijksterhuis and Stavenga2017). Ranunculus spp. flowers reflect the incident light to the center of the flower to heat the reproductive parts, which enhances seed and pollen maturation to attract pollinators (van der Kooi et al. Reference van der Kooi, Elzenga, Dijksterhuis and Stavenga2017).

Table 5. Effect of herbicides on ultraviolet (UV) reflectance from petal apex of weedy flowers assessed via radiometry at 4 h after treatment. a

a Values followed by the same letter within each column do not differ based on Fisher’s protected LSD (α = 0.05).

b UV-A = 315–400 nm.

c UV-B = 280–315 nm.

Digitally assessed UV-reflecting area at 4 HAT was insignificant for UV-absorbing T. repens flowers (P > 0.05; data not shown), exhibited a treatment main effect for the UV-reflecting petals with contrasting reproductive organs of P. digitalis (P = 0.0419), and exhibited an experimental run by treatment interaction for UV-reflecting petal apex with bullseye-pattern flowers of T. officinale and R. bulbosus (P = 0.0114) (Table 6). Herbicide treatment reduced the UV-reflecting area of P. digitalis to ≤0.56 cm2, except for topramezone-treated flowers (Table 5). Previous research also showed that the floral disk diameter of T. vulgare and oxeye daisy (Leucanthemum vulgare Lam.) was reduced after glyphosate application (Strandberg et al. Reference Strandberg, Boutin, Mathiassen, Damgaard, Dupont, Carpenter and Kudsk2017), and this physical change in floral size can also reduce UV-reflecting area compared with nontreated petals. Herbicides did not affect the UV-reflecting area of R. bulbosus (Table 6), but physically altered T. officinale flowers, such that UV-reflecting area was reduced by 2,4-D + dicamba + MCPP and topramezone (Table 6).

Table 6. Effect of herbicides on digitally assessed ultraviolet (UV)-reflecting area of weedy flowers at 4 hours after treatment. a

a Means within each column followed by the same letter are not significantly different based on Fisher’s protected LSD (α = 0.05).

Pollinator visitation and floral quality are temporarily dependent on herbicide chemistry, with some herbicides eliminating food resources and others transiently impacting floral quality and density, thus supporting our hypothesis. Weedy floral quality and density reductions generally lag behind insect evacuation from herbicide-treated sites. Petal UV reflectance exhibited characteristics that suggest this factor contributes to but does not solely influence pollinator foraging behavior after herbicide treatment. Herbicides did not affect UV reflectance of T. repens and R. bulbosus flowers in contrast to effects on T. officinale flowers that mirror pollinator deterrence. Pollinator deterrence by these four herbicides was consistent across both UV-absorbing and UV-reflecting floral classifications in contrast with herbicidal effects on UV reflectance, which were dependent on floral UV-reflectance classification and even varied between species within UV-reflecting bullseye floral types. These data suggest that herbicides of differing MOAs may offer a variety of management solutions to pollinator deterrence in areas slated for insecticide treatment, as recommended by other researchers (Godara et al. Reference Godara, Williamson, Koo and Askew2023; MacRae et al. Reference MacRae, Mitchem, Monks and Parker2005; McDougall et al. Reference McDougall, DiPaola, Blaauw and Nielsen2021). These solutions range from long-term removal of food resources in areas that receive frequent insecticide treatments to transient floral suppression and sustained food resources in areas that rarely need insecticides. Nectar depletion after herbicide treatment (Kearns et al. Reference Kearns, Inouye and Waser1998; King Reference King1964) is speculated to be a major driver in reducing pollinator visitation. Future research will assess the effect of different herbicides on the temporal response of nectar production of weedy flowers and in situ bee exposure to pesticide and UV tracer dye following deterrent treatments.

Acknowledgments

The authors want to acknowledge Daewon Koo and Juan R. Cubas for their technical support. We also want to thank Annu Kumari for her assistance in making figures.

Funding

The authors thank the PBI Gordon Corporation for partially funding this study under the 2022 PBI-Gordan Turfgrass Pest Management Research Grant Program and also Virginia’s Agricultural Council for partial funding.

Competing interests

The authors declare no conflicts of interest.

Footnotes

Associate Editor: Te-Ming Paul Tseng, Mississippi State University

References

Anonymous (2018) Halo 75 WDG Select™ specimen label. Middlesex, NC: Prime Source, LLC. 6 pGoogle Scholar
Anonymous (2022) Imidacloprid 2F Turf & Ornamental Insecticide specimen label. Pasadena, TX: Control Solutions, Inc. 32 pGoogle Scholar
Anonymous (2024) Penstemon digitalis. North Carolina Extension Gardener Plant Toolbox. https://plants.ces.ncsu.edu/plants/penstemon-digitalis. Accessed: February 14, 2024Google Scholar
Askew, SD (2017) Plant growth regulators applied in winter improve annual bluegrass (Poa annua) seedhead suppression on golf greens. Weed Technol 31:701713 CrossRefGoogle Scholar
[APVMA] Australian Pesticides and Veterinary Medicines Authority (2011) Public Release Summary of the Evaluation by the NRA of the New Active Constituent Halosulfuron-Methyl. Sydney NSW, Australia: APVMA. 169 p. https://www.apvma.gov.au/sites/default/files/publication/13806-prs-halosulfuron-methyl.pdf Google Scholar
Besançon, TE, Ghantous, KM, Sandler, HA (2021) Cranberry response to sulfentrazone rate, timing, and application volume. Weed Technol 35:574581 CrossRefGoogle Scholar
Bohnenblust, EW, Vaudo, AD, Egan, JF, Mortensen, DA, Tooker, JF (2016) Effects of the herbicide dicamba on nontarget plants and pollinator visitation. Environ Toxicol Chem 35:144151 CrossRefGoogle ScholarPubMed
Boyle, PE, Wisdom, MM, Richardson, MD (2020) Testing flowering plants in a bermudagrass (Cynodon spp.) lawn. HortScience 55:16421646 CrossRefGoogle Scholar
Bretagnolle, V, Gaba, S (2015) Weeds for bees? A review. Agron Sustain Dev 35:891909 CrossRefGoogle Scholar
Bunch, TR, Gervais, JA, Buhl, K, Stone, D (2012) Dicamba Technical Fact Sheet. Corvallis: National Pesticide Information Center, Oregon State University Extension ServicesGoogle Scholar
Camargo, MGG, Lunau, K, Batalha, MA, Brings, S, de Brito, VLG, Morellato, LPC (2019) How flower colour signals allure bees and hummingbirds: a community-level test of the bee avoidance hypothesis. New Phytol 222:11121122 CrossRefGoogle ScholarPubMed
Carpenter, DJ, Mathiassen, SK, Boutin, C, Strandberg, B, Casey, CS, Damgaard, C (2020) Effects of herbicides on flowering. Environ Toxicol Chem 39:12441256 CrossRefGoogle ScholarPubMed
Clinebell, RR, Bernhardt, P (1998) The pollination ecology of five species of Penstemon (Scrophulariaceae) in the tallgrass prairie. Ann Mo Bot Garden 85:126136 Google Scholar
DeMarche, ML, Miller, TJ, Kay, KM (2015) An ultraviolet floral polymorphism associated with life history drives pollinator discrimination in Mimulus guttatus . Am J Bot 102:396406 CrossRefGoogle Scholar
Dicks, LV, Breeze, TD, Ngo, HT, Senapathi, D, An, J, Aizen, MA, Basu, P, Buchori, D, Galetto, L, Garibaldi, LA, Gemmill-Herren, B, Howlett, BG, Imperatriz-Fonseca, VL, Johnson, SD, Kovacs-Hostyanszki, A, et al. (2021) A global-scale expert assessment of drivers and risks associated with pollinator decline. Nat Ecol Eval 5:14531461 CrossRefGoogle ScholarPubMed
Drummond, FA, Ballman, ES, Eitzer, BD, Du Clos, B, Dill, J (2018) Exposure of honey bee (Apis mellifera L.) colonies to pesticides in pollen, a statewide assessment in Maine. Environ Entomol 47:378387 CrossRefGoogle Scholar
Duke, SO (1990) Overview of herbicide mechanisms of action. Environ Health Perspect 87:263271 CrossRefGoogle ScholarPubMed
Dupont, YL, Strandberg, B, Damgaard, C (2018) Effects of herbicide and nitrogen fertilizer on non-target plant reproduction and indirect effects on pollination in Tanacetum vulgare (Asteraceae). Agric Ecosyst Environ 262:7682 CrossRefGoogle Scholar
Fetridge, ED, Ascher, JS, Langellotto, GA (2008) The bee fauna of residential gardens in a suburb of New York City (Hymenoptera: Apoidea). Ann Entomol Soc Am 101:10671077 CrossRefGoogle Scholar
Garcia, JE, Greentree, AD, Shrestha, M, Dorin, A, Dyer, AG (2014) Flower colours through the lens: quantitative measurement with visible and ultraviolet digital photography. PLoS ONE 9:e96646 CrossRefGoogle ScholarPubMed
Gels, JA, Held, DW, Potter, DA (2002) Hazards of insecticides to the bumble bees Bombus impatiens (Hymenoptera: Apidae) foraging on flowering white clover in turf. J Econ Entomol 95:722728 CrossRefGoogle Scholar
Gervais, J, Luukinen, B, Buhl, K, Stone, D (2008) 2,4-D Technical Fact Sheet. Corvallis: National Pesticide Information Center, Oregon State University Extension ServicesGoogle Scholar
Gervais, J, Luukinen, B, Buhl, K, Stone, D (2010) Imidacloprid Technical Fact Sheet. Corvallis: National Pesticide Information Center, Oregon State University Extension ServicesGoogle Scholar
Godara, N, Askew, SD (2023) Ultraviolet floral characteristics of volunteer plants in urban landscapes. In ASA, CSSA, SSSA International Annual Meeting, St Louis, MO, October 29 to November 1, 2023. https://scisoc.confex.com/scisoc/2023am/meetingapp.cgi/Paper/150081. Accessed: March 2, 2024Google Scholar
Godara, N, Williamson, RC, Koo, D, Askew, SD (2023) Effect of herbicides on pollinator foraging behavior and floral morphology in white clover (Trifolium repens L.)-infested turfgrass. Weed Technol 37:221225 CrossRefGoogle Scholar
Goodman, RD, Williams, AE (1994) Honeybee pollination of white clover (Trifolium repens L.) cv. Haifa. Aust J Exp Agric 34:11211123 CrossRefGoogle Scholar
Goulson, D, Nicholls, E, Botias, C, Rotheray, EL (2015) Bee declines driven by combined stress from parasites, pesticides, and lack of flowers. Science 347:1255957 CrossRefGoogle ScholarPubMed
Held, DW, Potter, DA (2012) Prospects for managing turfgrass pests with reduced chemical inputs. Annu Rev Entomol 57:329354 CrossRefGoogle ScholarPubMed
Henry, G, Tucker, K, McCurdy, J (2023) Response of common wildflower species to postemergence herbicides. HortScience 58:660665 CrossRefGoogle Scholar
Hicks, DM, Ouvrard, P, Baldock, KCR, Baude, M, Goddard, MA, Kunin, WE (2016) Food for pollinators: quantifying the nectar and pollen resources of urban flower meadows. PLoS ONE 11:e0158117 CrossRefGoogle ScholarPubMed
Johnson, SD, Andersson, S (2002) A simple field method for manipulating ultraviolet reflectance of flowers. Can J Bot 80:13251328 CrossRefGoogle Scholar
Kearns, CA, Inouye, DW, Waser, NM (1998) Endangered mutualisms: the conservation of plant–pollinator interactions. Annu Rev Ecol Syst 29:83112 CrossRefGoogle Scholar
King, CC (1964) Effects of herbicides on nectar secretion. J Apic Res 3:59 CrossRefGoogle Scholar
Klomberg, Y, Dywou Kouede, R, Bartos, M, Mertens, JE, Tropek, R, Fokam, EB, Janecek, S (2019) The role of ultraviolet reflectance and pattern in the pollination system of Hypoxis camerooniana (Hypoxidaceae). AoB Plants 11:lz057CrossRefGoogle ScholarPubMed
Koh, I, Lonsdorf, EV, Williams, NM, Brittain, C, Isaacs, R, Gibbs, J, Ricketts, TH (2015) Modeling the status, trends, and impacts of wild bee abundance in the United States. Proc Natl Acad Sci USA 113:140145 CrossRefGoogle ScholarPubMed
Kőrösi, Á, Szentirmai, I, Batáry, P, Kövér, S, Örvössy, N, Peregovits, L (2014) Effects of timing and frequency of mowing on the threatened scarce large blue butterfly—a fine-scale experiment. Agric Ecosyst Environ 196:2433 CrossRefGoogle Scholar
Koski, MH, Ashman, TL (2014) Dissecting pollinator responses to ubiquitous ultraviolet floral pattern in the wild. Func Ecol 28:868877 CrossRefGoogle Scholar
Larson, JL, Dale, A, Held, D, McGraw, B, Richmond, DS, Wickings, K, Williamson, RC (2017) Optimizing pest management practices to conserve pollinators in turf landscapes: current practices and future research needs. J Integr Pest Manag 8:110 CrossRefGoogle Scholar
Larson, JL, Kesheimer, AJ, Potter, DA (2014) Pollinator assemblages on dandelions and white clover in urban and suburban lawns. J Insect Conserv 18:863873 CrossRefGoogle Scholar
Larson, JL, Redmond, CT, Potter, DA (2013) Assessing insecticide hazard to bumble bees foraging on flowering weeds in treated lawns. PLoS ONE 8:e66375 CrossRefGoogle ScholarPubMed
Larson, JL, Redmond, CT, Potter, DA (2015) Mowing mitigates bioactivity of neonicotinoid insecticides in nectar of flowering lawn weeds and turfgrass guttation. Environ Toxicol Chem 34:127132 CrossRefGoogle ScholarPubMed
Lerman, SB, Contosta, AR, Milam, J, Bang, C (2018) To mow or to mow less: lawn mowing frequency affects bee abundance and diversity in suburban yards. Biol Conserv 221:160174 CrossRefGoogle Scholar
MacRae, AW, Culpepper, AS, Batts, RB, Lewis, KL (2008) Seeded watermelon and weed response to halosulfuron applied preemergence and postemergence. Weed Technol 22:8690 CrossRefGoogle Scholar
MacRae, AW, Mitchem, WE, Monks, DW, Parker, ML (2005) White clover (Trifolium repens) control and flower head suppression in apple orchards. Weed Technol 19:219233 CrossRefGoogle Scholar
McCurdy, JD, McElroy, JS, Flessner, ML, Hoyle, JA, Parker, ET (2016) Tolerance of three clovers (Trifolium spp.) to common herbicides. Weed Technol 30:478485 CrossRefGoogle Scholar
McDougall, R, DiPaola, A, Blaauw, B, Nielsen, AL (2021) Managing orchard groundcover to reduce pollinator foraging post-bloom. Pest Manag Sci 77:35543560 CrossRefGoogle ScholarPubMed
[NCIPMC] North Central Integrated Pest Management Center (2019) Best Management Practices for Turf Care and Pollinator Conservation. https://www.ncipmc.org/2019-pollinators-bmp-booklet. Accessed: January 30, 2024Google Scholar
Papiorek, S, Junker, RR, Alves-Dos-Santos, I, Melo, GA, Amaral-Neto, LP, Sazime, M, Wolowski, M, Freitas, L, Lunau, K (2016) Bees, birds and yellow flowers: pollinator-dependent convergent evolution of UV patterns. Plant Biol 18:4655 CrossRefGoogle ScholarPubMed
Parachnowitsch, AL, Kessler, A (2010) Pollinators exert natural selection on flower size and floral display in Penstemon digitalis . New Phytol 188:393402 CrossRefGoogle ScholarPubMed
Peitsch, D, Fietz, A, Hertel, H, de Souza, J, Ventura, DF, Menzel, R (1992) The spectral input systems of hymenopteran insects and their receptor-based colour vision. J Comp Physiol A 170:2340 CrossRefGoogle ScholarPubMed
[PMRA] Pest Management Regulatory Agency (2014) Registration Decision For Halosulfuron, Present as Methyl Ester. Ontario, Canada: PMRA. 7 p. https://www.canada.ca/content/dam/hc-sc/migration/hc-sc/cps-spc/alt_formats/pdf/pubs/pest/_decisions/rd2014-20/rd2014-20-eng.pdf. Accessed: December 12, 2023Google Scholar
Rae, JM, Vamosi, JC (2012) Ultraviolet reflectance mediates pollinator visitation in Mimulus guttatus. Plant Species Biol 28:177184 CrossRefGoogle Scholar
Ramos, SE, Bakhtiari, M, Castañeda-Zárate, M, Iriart, V, Ashman, TL (2023) Herbicides and their potential to disrupt plant-insect chemical communication. J Syst Evol 61:550560 CrossRefGoogle Scholar
Sarukhan, J (1974) Studies on plant demography: Ranunculus repens L., R. bulbosus L. and R. acris L. II. Reproductive strategies and seed population dynamics. J Ecol 62:151177 CrossRefGoogle Scholar
Schmitz, J, Schafer, K, Bruhl, CA (2013) Agrochemicals in field margins-assessing the impacts of herbicides, insecticides, and fertilizer on the common buttercup (Ranunculus acris). Environ Toxicol Chem 32:11241131 CrossRefGoogle ScholarPubMed
Shaner, DL, ed (2014) Herbicide Handbook. 10th ed. Lawrence, KS: Weed Science Society of America Google Scholar
Strandberg, B, Boutin, C, Mathiassen, SK, Damgaard, C, Dupont, YL, Carpenter, DJ, Kudsk, P (2017) Effects of herbicides on non-target terrestrial plants. Pages 149–166 in Duke SO, Kudsk P, Solomon K, eds. Pesticide Dose: Effects on the Environment and Target and Non-target Organisms. Washington, DC: American Chemical SocietyCrossRefGoogle Scholar
[SAREP] Sustainable Agriculture Research & Education Program (2024) White Clover. Davis: University of California Agriculture & Natural Resources. https://sarep.ucdavis.edu/covercrop/whiteclover. Accessed: June 30, 2024Google Scholar
Tunes, P, Camargo, MGG, Guimaraes, E (2021) Floral UV features of plant species from a neotropical savanna. Front Plant Sci 12:618028 CrossRefGoogle ScholarPubMed
[USDA] U.S. Department of Agriculture (2016) Reversing Pollinator Decline Is Key to Feeding the Future. https://www.usda.gov/media/blog/2016/06/24/reversing-pollinator-decline-key-feeding-future. Accessed: January 28, 2024Google Scholar
[USEPA] U.S. Environmental Protection Agency (2012) Environmental Fate and Ecological Risk Assessment for First Residential Uses of Topramezone. Washington, DC: USEPA. 26 p. https://www.regulations.gov/document/EPA-HQ-OPP-2012-0310-0006. Accessed: November 14, 2023Google Scholar
[USEPA] U.S. Environmental Protection Agency (2014) Preliminary Ecological Risk Assessment for the Registration Review of Sulfentrazone and Proposed New Uses on Apples, Sinclair, Barrett. Washington, DC: USEPA. 145 p. https://www.regulations.gov/document/EPA-HQ-OPP-2009-0624-0017. Accessed: December 17, 2023Google Scholar
van der Kooi, CJ, Elzenga, JT, Dijksterhuis, J, Stavenga, DG (2017) Functional optics of glossy buttercup flowers. J R Soc Interface 14:20160933 CrossRefGoogle ScholarPubMed
Westrich, P (1996) Habitat requirements of central European bees and the problems of partial habitats. Pages 116 in Matheson, A, Buchmann, SL, O’Toole, C, Westrich, P, Williams, IH, eds. The Conservation of Bees, London: Academic Press Google Scholar
Wolfin, J, Watkins, E, Lane, I, Portman, ZM, Spivak, M (2023) Floral enhancement of turfgrass lawns benefits wild bees and honey bees (Apis mellifera). Urban Ecosyst 26:361375 CrossRefGoogle Scholar
Zaleski, A (1964) Effect of density of plant population, photoperiod, temperature and light intensity on inflorescence formation in white clover. Grass Forage Sci 19:237247 CrossRefGoogle Scholar
Figure 0

Table 1. List of treatments with trade names, manufacturer details, herbicide modes of action, and rates evaluated in experiments assessing ultraviolet (UV)-absorbing inflorescence, UV-reflecting at petal apex with bullseye-pattern, and UV-reflecting petals with contrasting reproductive part weedy flowers.

Figure 1

Table 2. Nonlinear and polynomial regression equations with parameters utilized for pollinator visitation and floral quality of ultraviolet (UV)-absorbing inflorescence and UV-reflecting at petal apex with bullseye-pattern flowers.

Figure 2

Figure 1. Effect of herbicides 2,4-D + dicamba + MCPP (A); halosulfuron (B); sulfentrazone (C); and topramezone (D) on floral quality of ultraviolet (UV)-absorbing inflorescence and pollinator visitation.

Figure 3

Table 3. Effect of herbicides on area under progress curve (AUPC) for pollinator visitation and flower quality of ultraviolet (UV)-absorbing inflorescence and UV-reflecting at petal apex with bullseye-pattern flowers.a

Figure 4

Table 4. Effect of herbicides on weedy floral density at 7 and 14 d after treatment (DAT).a

Figure 5

Figure 2. Effect of herbicides 2,4-D + dicamba + MCPP (A); halosulfuron (B); sulfentrazone (C); and topramezone (D) on floral quality of ultraviolet (UV)-reflecting at petal apex with bullseye-pattern flower and pollinator visitation.

Figure 6

Table 5. Effect of herbicides on ultraviolet (UV) reflectance from petal apex of weedy flowers assessed via radiometry at 4 h after treatment.a

Figure 7

Table 6. Effect of herbicides on digitally assessed ultraviolet (UV)-reflecting area of weedy flowers at 4 hours after treatment.a