Passive and Discrete Sampling of Neonicotinoid Pesticides in Saginaw, Michigan (United States) and Implications for the Protection of Aquatic Life

Passive and Discrete Sampling of Neonicotinoid Pesticides in Saginaw, Michigan (United States) and Implications for the Protection of Aquatic Life | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Passive and Discrete Sampling of Neonicotinoid Pesticides in Saginaw, Michigan (United States) and Implications for the Protection of Aquatic Life Sara Nedrich, Sarah Bowman, Elizabeth Stieber, Geoff Rhodes, Brandon Armstrong This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4682502/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Neonicotinoid pesticides are widely applied in urban and agricultural settings despite their toxicity to aquatic organisms at low concentrations. Monitoring for six neonicotinoids (acetamiprid, clothianidin, dinotefuran, imidacloprid, thiacloprid, thiamethoxam) in the Saginaw River watershed of Michigan shows detections of imidacloprid exceeding final chronic values (FCVs) developed to protect aquatic life. The study design implemented both discrete and passive surface water sampling to capture the episodic nature of pesticide release. Fourteen sites were sampled monthly from August-October 2021 and April-July 2022. One or more neonicotinoids were detected in 86% of discrete and 100% of passive samples. Imidacloprid was detected at the highest maximum concentration (220 ng L -1 ), followed by clothianidin (98 ng L -1 ), and thiamethoxam (32 ng L -1 ). Development of aquatic life values for imidacloprid, clothianidin, and thiamethoxam, pursuant to Michigan statute and Rule 57 (Water Quality Standards), resulted in FCVs of 29 ng L -1 , 81 ng L -1 , and 280 ng L -1 , respectively. Seven out of 14 sample locations exceeded the FCV for imidacloprid. The most sensitive species included in derivation of neonicotinoid aquatic life values included mayflies ( Neocloeon triangulifer, Cloeon sp., and McCaffertium sp. ) and a midge ( Chironomus dilutus ). This study provides new insight on monitoring for neonicotinoid pesticides and weighs the costs and benefits of passive and discrete sampling methodologies. neonicotinoids POCIS pesticides toxicity passive sampling imidacloprid Figures Figure 1 Figure 2 Figure 3 Highlights Neonicotinoids were detected in surface waters by passive and discrete sampling Neonicotinoid concentrations varied seasonally and spatially Acute and chronic water quality standards for three neonicotinoids were derived Imidacloprid concentrations exceeded chronic water quality standards Introduction Pesticide usage, while critical for food security, can have detrimental effects on non-target organisms, including aquatic life and wildlife (Gibbons et al., 2015 ; Sánchez-Bayo et al., 2016 ). Neonicotinoids are a class of pesticides used in soil and seed treatment, and foliar spray in the United States, and have been traced to bee and songbird mortality (Lu et al., 2014 ; Rogers et al., 2019 ). Mechanisms of neonicotinoid toxicity include oxidative stress and neurological impairment to an insect's nervous system (Wang et al., 2018 ; Yamamoto et al., 1995 ). While three neonicotinoids were banned for use in the European Union (imidacloprid, clothianidin, and thiamethoxam), their use is prolific in the United States (European Commission, 2018 ). With reports of large-scale declines in insect populations and detections of imidacloprid at concentrations concerning to aquatic life (Barmentlo et al., 2021 ; DiBartolomeis et al., 2019 ; Hladik et al., 2018 ; Morrissey et al., 2015 ; Wolfram et al., 2018 ), water resource managers have become increasingly concerned about potential impacts to non-target aquatic insects. Recent monitoring studies in the United States identified environmentally significant concentrations of neonicotinoids in Saginaw, Michigan, adjacent cities, and Midwest states (Hladik et al., 2018 ). Runoff from both agricultural and urban applications of neonicotinoids are common, with use for yard treatments and pet flea applications in urban settings (Berens et al., 2021 ). Pesticides can show significant variability both temporally and spatially, which makes predicting occurrence and monitoring difficult for water resource managers (Herrmann et al., 2023 ). Environmentally relevant concentrations can be missed using discrete (grab) samples from fixed-interval and composite monitoring (Criquet et al., 2017 ; Norman et al., 2020 ; Stehle and Schulz, 2015 ). While discrete samples are generally more cost effective for budget limited monitoring programs, the benefits of simultaneous passive sampling were assessed in this study to help weigh future monitoring costs against data quality objectives. Passive sampling has been utilized as a monitoring tool for current use pesticides (Metcalfe et al., 2019 ; Van Metre et al., 2017 ) and can detect chemicals occurring at low concentrations in the environment that may show up as non-detect in traditional grab samples (Alvarez, 2010 ; Bernard et al., 2019 ). A passive sampler called Polar Organic Chemical Integrative Sampler (POCIS) had a higher detection frequency of pesticides (median 62 compounds) than grab samples (median 46 compounds) in small streams throughout the Midwest United States (Van Metre et al., 2017 ). The United States Geological Survey (USGS) published guidelines (Alvarez 2010 ) for the use of POCIS devices. POCIS are designed to sample more water-soluble organic chemicals with log Kow < 3 (i.e. pharmaceuticals, polar pesticides, phosphate flame retardants, and surfactants) and have been used successfully in previous neonicotinoid monitoring projects (Aisha et al., 2017 ; Bernard et al., 2019 ; Criquet et al., 2017 ; Hageman et al., 2019 ; Metcalfe et al., 2016 ; Noro et al., 2020 ; Sánchez-Bayo and Hyne, 2014 ; Satiroff et al., 2020 ; Sultana et al., 2018 ; Van Metre et al., 2017 ; Xie et al., 2022 ; Xiong et al., 2021 , 2019 ). Current United States Environmental Protection Agency (US EPA) water quality guidelines for neonicotinoids are derived as aquatic life benchmark screening levels by the Office of Pesticide Programs (OPP) as outlined in the USEPA 1985 document, “Guidelines for Deriving Numerical National Water Quality Criteria for the Protection of Aquatic Organisms and Their Uses”(US EPA, 1985 ). The benchmarks are used in an ecological risk assessment to determine pesticide label restrictions and dosing (US EPA, 2004 , 2023a ). Recent research has indicated that neonicotinoids may have synergistic toxicity, wherein greater than additive effects on insect emergence were observed in neonicotinoid mixtures (Maloney et al., 2018 ; Schmidt et al., 2022 ). The current United States regulatory framework; however, evaluates effects of single compounds (Barata et al., 2006 ) or presumes mechanistic additivity (ex. Polychlorinated biphenyls [PCBs]) even when synergistic effects are well known (Burd et al., 2016 ). One objective of this study is to provide water quality standards consistent with state and federal statute, evaluate all data available, and assess protectiveness to aquatic life. By applying a watershed scale approach to assess impacts of neonicotinoids on aquatic life, several objectives were met. The objectives were to (1) monitor for neonicotinoids in the Saginaw River watershed; (2) investigate the relative effectiveness of passive and discrete samplers at identifying neonicotinoids; (3) assess if there are significant spatial and temporal patterns affecting occurrence; (4) develop water quality standards consistent with State law and protective of aquatic life; and (5) use water quality standards to assess risk to aquatic species. Monitoring data are vitally important for protecting environmental health, and especially so for a pesticide class that is highly toxic to insects. Materials & Methods Site Selection & Characteristics Fourteen locations were selected in the Saginaw River watershed for neonicotinoid passive and discrete sampling. Sample sites were chosen representing both urban and agriculture as dominant land use types (Fig. 1 ). The dominant crop cover in the area is corn and soybeans. Land use estimates were calculated for each sample site’s upstream drainage area. The dataset was derived from the European Space Agency (ESA) Sentinel-2 imagery at 10-meter resolution (from ESRI’s ArcGIS platform) using a 30-meter digital elevation model retrieved from the State of Michigan’s LiDAR GeoData Explorer application. One sampling location (Dutch Creek, DC-0010) was moved 1.2 miles downstream for the 2022 sampling due to sampler theft at the original location. Locations included one mid-order (7) river (Bad River), and several high order rivers (≥ 9), including the Tittabawassee, Saginaw, Cass, Shiawassee, and Flint Rivers. Sampling locations were located proximate to four wastewater treatment plants directly upgradient of sites SG-0030, SG-0070, TW-0010, and CR-0010 (Table 1 , Fig. 1 ). Surface water quality in the area is of moderate hardness, with measured pH ranging from 7-8.5, and specific conductivity of 270–1000 µS/cm throughout the course of the study. Table 1 Land use cover estimates as a percent (%) for sample locations are presented. Geometric mean concentrations (n = 2, highest consecutive months; or n = 7, if no two consecutive months with detections) of imidacloprid, clothianidin, and thiamethoxam for discrete surface water samples are provided. Single time-point discrete concentrations are provided in the Supporting Information (Table S2 ). Site Code Waterbody Name Crops Built Area Trees Other a Imidacloprid (ng/L) Clothianidin (ng/L) Thiamethoxam (ng/L) SG-0030 Saginaw River (S Rail.) 41.11 13.61 38.74 6.55 31.5 b 28.1 23.0 c SG-0040 Saginaw River (Ind.) 41.12 13.59 38.75 6.55 46.8 b 26.3 25.0 c SG-0052a Saginaw River (MGI) 41.25 13.42 38.76 6.56 31.7 b 26.4 11.9 SG-0059 Saginaw River (Dutch) 41.26 13.41 38.77 6.56 29.7 b 26.6 23.0 c SG-0070 Saginaw River (Zilwaukee) 39.88 13.60 39.92 1.74 29.5 b 20.6 16.0 c SG-0110 Saginaw River (W Center) 40.07 13.20 40.14 1.73 24.0 20.1 7.2 DC-0010 Dutch Creek 83.12 9.91 5.64 1.33 75.6 b 55.1 15.1 BD-0110 Bad River 60.88 3.46 34.31 1.35 ND 63.6 9.9 CR-0010 Cass River 55.46 7.00 34.33 3.21 ND 36.0 c 14.9 PR-0010 Pine River 52.70 6.93 35.37 5.00 ND 26.5 14.9 SW-0010 Shiawassee River 41.12 21.65 29.05 8.18 ND 15.0 c ND CP-0020 Chippewa River 33.29 8.73 48.34 2.47 ND 15.1 ND TW-0010 Tittabawassee River 30.69 8.68 52.90 1.59 14.0 c 34.0 c 9.6 c FR-0015 Flint River 29.38 27.26 34.89 2.29 58.8 b 16.0 c 9.7 c a Other land cover accounts for rangeland and flooded/water. b Imidacloprid concentration exceeds the final chronic value (FCV). c Geomean was based on one detection (six other samples were non-detects). Discrete Sampling Discrete surface water grab samples were collected for neonicotinoid analysis using certified cleaned glass amber bottles at each site during deployment and retrieval of the POCIS. Replicate and duplicate samples were collected on every trip. Replicates were 1 L samples collected from the same site within a 5-minute period. Duplicates were collected in a 2 L sample bottle (certified glass amber). Trip blanks with deionized water were included at each sampling event to test bottles for any cross contamination. Water temperature, pH, and conductivity were simultaneously collected using a YSI EXO multiparameter sonde. Water level data were determined using the USGS National Water Information System utilizing the closest proximate stream gauge station, where available. Passive Sampling with POCIS Deployment and retrieval procedures for POCIS were designed in accordance with Alvarez ( 2010 ). To account for in-stream variability, three POCIS (220 mg OASIS-HLB sorbent) were pre-installed onto support holders by Environmental Sampling Technologies (EST) and shipped in sealed metal cans. The cans were stored at -20°C until deployment and then transported to the field on ice. At each site, a can was opened and the support holder containing the three POCIS was placed in perforated stainless-steel canisters. The canisters were suspended off the bottom of the stream using a stainless-steel cage with stainless-steel legs to prevent movement within the stream and sediments from clogging the POCIS. In non-wadable streams, the canisters were secured to a permanent object in the stream (i.e. an overhanging tree, permanent structure). Oasis-HLB POCIS are equilibrium-type samplers providing estimates of mean contaminant load over the deployment time (Ahrens et al. 2015 ). POCIS were deployed for a target of 28 days, with actual deployments ranging from 23–49 days. Deployments exceeding 28-days were either due to scheduling conflicts and/or unsafe field conditions preventing collection (high water). The deployments occurred over two years, from July-October 2021 and April-July 2022. Extended POCIS deployment (49 days) in the Sept-Oct 2021 and (42 days) April-May 2022 sample events added uncertainty in this dataset due to the potential uptake rate declining after 28-days. As these samplers are already designed to capture equilibrium concentrations and the sampling rate is not consistent after 28-days, time-weighted averages could not be reliably calculated. The targeted sampling regime included all growing season months for the region. Upon retrieval, photos were taken of the location and notes on POCIS condition were recorded. Field (open to air at sample site) and trip (taken in car but not opened on-site) blanks were included, as well as an additional POCIS replicate for approximately 10% of the total samples. Following deployment, POCIS were removed from their steel canisters and placed back in their original metal can and kept on ice. They were then frozen at -20°C and stored for ≤ 4 months. POCIS were shipped on ice overnight to the EST laboratory in St. Joseph, Missouri (United States) for extraction. The extraction method followed an updated (2017) USGS gravity flow method (unpublished). The Oasis-HLB was transferred to an extraction column with 100 µL of surrogate LIV-54 and each was extracted separately using 25 mL of methanol. Lab blanks were prepared similarly. The extraction was concentrated by ultra-high purity nitrogen blow-down and transferred to 5 mL ampules using acetonitrile. The pesticide extracts were cooled, flame sealed, and shipped to the Michigan Department of Agriculture and Rural Development (MDARD) laboratory for pesticide analysis. Neonicotinoid Analysis All samples were analyzed via liquid chromatography and tandem mass spectrometry (LC/MS/MS) at the MDARD Geagley Laboratory in East Lansing, Michigan utilizing an Agilent Model G6410 Triple Quadrupole mass spectrometer coupled to an Agilent 1240 LC system. Six neonicotinoids were analyzed including acetamiprid, clothianidin, dinotefuran, imidacloprid, thiamethoxam, and thiacloprid. POCIS extracts were received from EST and run directly on the LC/MS/MS with a method detection limit of 0.0056 ug/POCIS. High volume (1L) discrete sample residues were collected on Biotage C18/ENV solid phase extraction (SPE) cartridges. The cartridges were activated and equilibrated with methanol and reagent water prior to sample addition. The cartridges were vacuum dried and eluted with acidified methanol for neonicotinoid extraction. The eluant was evaporated to < 0.3 mL and solvent exchanged into acetonitrile for analysis. The method detection limit for grab samples was 6.3 ng/L; however, results below detection were occasionally observed and reported as estimated values. Imidacloprid-pyridine-4-d-methylene-d2, 13C from Bayer CropScience was used as an internal standard. The MDARD used a factor of 0.333 POCIS/mL to back-calculate mass accumulation (ug/POCIS) based on dilution to 25.1 mL and a final extract volume of 3 mL. Quality control included reagent blanks, matrix blanks, and matrix spike recoveries with control limits of 50–150%. The LIMS reporting method for this project was derived from SOP-PEST-0048 Quechers and drafted as SOP number PEMTM01 ‘Water Grab Samples for Pesticides’. Data Analysis Neonicotinoid site masses were calculated for each deployment by averaging the canister’s three replicate POCIS disks. Any site where a POCIS disk with observed biofouling (i.e. sediment or algae accumulation) upon collection that resulted in a > 20% difference from the other two replicates was dropped from the mean as a quality control measure. Mean contaminant masses were not transformed to surface water concentrations (using sampling rate conversion, in liters per day, i.e. Rs values) due to exposure periods exceeding 28-days during some of the deployments. Three POCIS samplers were lost or stolen during the sampling period and removed from the dataset. One POCIS sampler was no longer submerged upon retrieval and was removed from the discrete vs. passive sampling analysis; however, was still included in monthly mass accumulation analyses. Non-detects were assigned a value of zero to prevent data artifacts from impacting regression analyses of observed detections. Quantitative datasets, including discrete and passive sampling results, water levels, water quality data, and land use coverage, were tested for normality (Shapiro Test) in R version 1.4.1106. For normally distributed data, averages were reported; otherwise, median was reported. For non-normal datasets with insufficient sample size, geometric means were applied. If the geometric mean of imidacloprid concentration of two consecutive months exceeded the final chronic value, then an exceedance was assumed. This assumption is supported by passive sampling results showing a strong correlation with discrete sampling. An independent linear regression between water levels and discrete neonicotinoid concentrations (sum of imidacloprid, clothianidin, and thiamethoxam) was conducted in Microsoft Excel’s Data Analysis Toolkit version 2308 Build 16.0.16731.20310. Multiple linear regressions were likewise used to compare POCIS masses to discrete sample concentrations for all samples with detections. For the analysis, discrete sample geomeans were calculated from water collected at POCIS deployment and collection. Aquatic Life Values Derivation Water quality standards protective of aquatic life were derived pursuant to Rule 57 of the Part 4 Water Quality Standards, promulgated as pursuant to Part 31, Water Resources Protection, of the Natural Resources Protection Act, 1994 PA 451, as amended (NREPA). Final acute values (FAV), ambient maximum values (AMV), and final chronic values (FCV) were derived for imidacloprid, clothianidin, and thiamethoxam. The FAV is the maximum concentration that can be emitted from a discharge pipe (effluent) and the AMV is the maximum average concentration permitted in ambient surface waters over 24-hours. The FAV and AMV are both acute endpoints derived from 48–96-hour LC or EC50 values. The FCV is the maximum monthly average permitted in ambient surface water and is derived from chronic toxicological datasets utilizing the maximum acceptable toxicant concentration (MATC). Literature review to identify appropriate toxicity studies included use of the US EPA Ecotox database, SciFinder database, and a google scholar search. Search terms were limited to CAS or chemical name, and search terms ‘aquatic’ and one or more of the following: ‘LC50’, ‘EC50’, ‘chronic’, or ‘acute’. All three neonicotinoids were derived as ‘Tier II’ values, which indicates toxicological data was missing for one or more pertinent organism class. In the absence of relevant organism data, uncertainty factors (UFs) were used for tier II acute values derivation for imidacloprid (missing warmwater fish in class Osteichthyes, UF = 4.3), clothianidin (missing salmonid, UF = 4.3), and thiamethoxam (missing salmonid and third chordate family, UF = 5.2). FCVs were derived utilizing acute to chronic ratios from available paired acute and chronic studies. Additional information, including the calculations and literature review documents, are provided in the Supplemental Material. Results Neonicotinoids in Water Samples Imidacloprid, clothianidin, and thiamethoxam were observed seasonally in water samples collected in the Saginaw River watershed. Acetamiprid, dinotefuran, and thiacloprid were not detected in any of the discrete water samples. One or more neonicotinoid was observed at 86% of sites sampled. Imidacloprid was detected at 64% of sites with a maximum concentration of 220 ng/L and median concentration of 27 ± 11 ng/L. Clothianidin was detected at 86% of sites with a maximum concentration of 98 ng/L and median detected concentration of 31 ± 5 ng/L. Thiamethoxam was detected at 71% of sites with a maximum concentration of 32 ng/L and median concentration of 7.9 ± 2 ng/L. The maximum concentrations were observed at Dutch Creek (DC-0010) for all three analytes. Geometric means of neonicotinoid concentrations per site are presented in Table 1 . Imidacloprid was observed in discrete samples in four of seven months sampled, from July-October, with highest detections in July (Fig. 2 A). Clothianidin was observed in discrete samples in all months sampled, with maximum concentrations detected in October (Fig. 2 B). Thiamethoxam was only observed in June, July, and October sampling events, with the peak in July (Fig. 2 C). Only three sampling locations had adequate USGS water level datasets and sufficient (≥ 2) detections of neonicotinoids during the sampling period. A strong positive relationship between water levels and neonicotinoid concentrations was observed (r 2 > 0.75, p ≤ 0.05) for two of these sites (Pine River and Saginaw River at West Center Road); however, data suggests snowmelt in early April may have resulted in a diluting effect wherein this trend was not observed. The third site, Saginaw River at Independence, where water levels were not correlated with neonicotinoid concentration, is located close to Saginaw Bay where river water levels are more strongly influenced by Great Lakes water levels than by upgradient runoff. Neonicotinoids in Passive Samplers Imidacloprid, thiamethoxam, and clothianidin were detected at 100% of sites sampled with POCIS. Acetamiprid and dinotefuran were absent in > 95% of samples, with the highest concentrations estimated below the level of detection at 1.7 and 4.6 ng/POCIS, respectively. No detections of thiacloprid were observed. Median mass loading for all sites and deployment times was highest for clothianidin at 20.7 ± 5.2 ng/POCIS, with a range of 3.8-253.3 ng/POCIS. Imidacloprid median mass loading was 20.3 ± 3.0 ng/POCIS, with a range of 2.4–180.0 ng/POCIS. Thiamethoxam detections were lower with a median of 4.7 ± 0.9 ng/POCIS, with a range of 0.9–28.3 ng/POCIS. POCIS results differed from discrete samples in that detections were found during all sampling periods; although, seasonal trends were similar between both sampling methods (Fig. 2 ). Peak imidacloprid concentrations were observed from July-August with lower detections in the spring. Clothianidin and thiamethoxam were again observed to be highest in the late summer (September-October) sampling period, and present in low-moderate concentrations for all other sample months. Linear regressions were used to compare results of passive and discrete sampling methods. Imidacloprid mass accumulation had a strong positive correlation with discrete sample mean concentrations (r 2 = 0.86, p < 0.0001) (Fig. 3 A). The relationship for July-August was stronger (r 2 = 0.95, p < 0.0001) before including the September-October POCIS dataset, possibly due to the extended 49-day October deployment exceeding the recommended 28-day timeframe. A strong positive correlation between clothianidin mass accumulation and discrete sample mean concentrations was also observed (r 2 = 0.74, p < 0.001) (Fig. 3 B). Spatial Variability & Assessment The predominant land cover was cropland, representing 29–83% of land cover at the sample locations. Built (developed) landscapes represented 3.5–27% of land cover types and tree cover (forested) accounted for 5.6–52% of land use coverage. The Dutch Creek drainage area is almost entirely cropland (83%), whereas the Flint River site had nearly equivalent percentages of crop, forested, and urban land coverage. The six Saginaw River sites had nearly identical land coverage estimates. The site with the lowest crop and built area was in the Chippewa River. A summary of site land use coverage is provided in Table 1 . Maximum and geomean mass accumulations (ng/POCIS) were calculated for each sample site and compared to land cover percentages. Crop cover was the best predictor for clothianidin and thiamethoxam concentrations and demonstrated a moderate positive correlation for maximum and mean concentrations (r 2 > 0.45, p 0.42, p 3.5x all sites geomean) and clothianidin (2-4.8x all sites geomean) in both discrete and POCIS during the July 2021 sampling event. In addition to having the highest crop coverage (83%), it also had the lowest percentage of undeveloped area (forested, 5.6%). Another significant source of imidacloprid was the Flint River in July 2021 (1.5-3.5x all sites geomean). In addition to draining a large amount of cropland, the Flint River also drains a large urban landscape. The Bad River was determined to be a source of clothianidin to the watershed (2-4.5x all sites geomean) for most of the growing season. Interestingly, no detections of imidacloprid were observed in the Bad River. Additionally, the clothianidin concentrations found in the Bad River did not have the same seasonal dynamics as the other sample sites and remained elevated in all months except April, suggesting a unique source or fate/transport scenario as compared to the other sample locations. The low detected concentrations of thiamethoxam were not variable enough to distinguish sources but is likely tied to clothianidin as one of its breakdown products. No significant differences in neonicotinoid concentrations were observed in sites upstream and downstream of wastewater treatment plants, although no samples were taken directly from the outfalls. Aquatic life values comparison The literature search captured > 100 pertinent articles that were selected for full article review. Articles meeting the stringent data quality requirements outlined in Rule 57 are presented in the Supplemental Material. Several otherwise acceptable studies were rejected due to the use of a formulation or pesticide product with active ingredient as opposed to reagent grade imidacloprid. Water quality standards for imidacloprid, clothianidin, and thiamethoxam are presented (Table 2 ). From the currently available literature, the most toxic of the neonicotinoids to aquatic life was imidacloprid > clothianidin > > thiamethoxam. The most sensitive organism classes to all three neonicotinoids included mayfly taxa and midges (de Perre et al., 2015 ; Finnegan et al., 2017 ; Maloney et al., 2017 ; Raby et al., 2018a , 2019 ; Stoughton et al., 2008 ). Other sensitive organisms to one or more of the neonicotinoids included caddisfly taxa, a species of amphipod ( Hyalella azteca) , beetles in the genus Gyrinus , and a species of oligochaete * Lumbriculus variegatus) (Lanteigne et al., 2015 ; Raby et al., 2018a , 2019 ). All three water quality standards resulted in a tier II derivation which is presented in the Supplemental Material. Table 2 Water quality standards (ng/L) protective of aquatic life calculated for Michigan, United States, as compared to USEPA aquatic life benchmarks. Standards include final acute values (end of discharge pipe limit), ambient maximum values (24-hour mean limit), and final chronic values (monthly mean limit). Parameter Name Final Acute Value (FAV) Aquatic Maximum Value (AMV) Final Chronic Value (FCV) USEPA acute benchmark USEPA chronic benchmark Clothianidin 580 290 81 11000 50 Imidacloprid 720 360 29 380 10 Thiamethoxam 1100 530 280 17500 740 Imidacloprid concentrations fell below the AMV but occasionally exceeded the FCV. Single discrete samples are not sufficient comparisons to an FCV, since it is based on a 30-day average; therefore, evaluation of geometric means for the two highest consecutive sample months were considered (Table 1 ). In the absence of two consecutive months of detections, geomeans for all sample months were used. This calculation method assumes neonicotinoid concentrations decreased or increased linearly over the month and is supported by passive sampling results showing a strong correlation with discrete sampling. Using discrete geometric means only, a total of seven sites were identified as exceeding the FCV for imidacloprid. No sites exceeded the FCV for clothianidin and thiamethoxam. No sites exceeded the AMV for imidacloprid, clothianidin, or thiamethoxam. Using the two regressions presented in Fig. 3 A, the mass of imidacloprid corresponding with an FCV exceedance is greater than 65–75 ng/POCIS. The sites that exceed both the 29 ng/L discrete FCV and the POCIS mass equivalent of the FCV are the Saginaw River at multiple locations (SG-0030, SG-0040, SG-0059, SG-0052a), Dutch Creek, and the Flint River. One paired sample (for Flint River, September-October) exceeded the POCIS mass equivalent to the FCV (78 ng), but not the discrete concentration (22 ng/L), which indicates the grab sample was likely an underestimate for monthly concentrations. Conversely, one paired discrete sample (Saginaw River, SG-0070) exceeded the FCV in the discrete sample (29.5 ng/L), but not the POCIS mass equivalent to the FCV (63 ng/POCIS). The FCV was not exceeded for any mean clothianidin concentrations (Fig. 3 B). Discussion & Conclusions Monitoring shows the Saginaw River watershed is impacted by neonicotinoids, with potentially concerning concentrations of imidacloprid in several tributaries. Imidacloprid was detected in the highest concentrations using discrete sampling and exceeded the FCV at seven out of 14 sites for ≥ 30-days during the 2021–2022 field season. Discrete imidacloprid concentrations observed in Dutch Creek were high enough where adverse effects to emergence of Chironomus dilutus have been reported in lab-based studies (14-d EC10 130 ng/L) (Raby et al., 2018b ). Future work should be initiated to address imidacloprid inputs to both Dutch Creek and the Flint River as both were source tributaries to the Saginaw River. Previous neonicotinoid monitoring in Michigan collected monthly discrete water samples (composites) over a one-year period (October 2015-September 2016) and reported lower maximum concentrations (13.8 ng/L imidacloprid, 11.7 ng/L clothianidin, 9.6 ng/L thiamethoxam) but similar detection frequencies (Hladik et al., 2018 ). Comparing data from the same location (Saginaw River, adjacent to SG-0070 and SG-0110), maximum detected imidacloprid concentrations have increased 2-4x from 2015 to 2021. Maximum clothianidin concentrations have increased 2.5-5x during the same time frame. Increasing concentrations are not surprising given the likelihood of neonicotinoid use increases (limited reporting data to verify) and half-lives in soils having been reported to exceed 1,000 days (Bonmatin et al., 2015 ). Additional sample locations with neonicotinoid detections in Michigan were identified in the study (Hladik et al., 2018 ), including the Grand River, River Rouge, and St. Joseph River. Further sampling is needed to determine the prevalence and distribution of neonicotinoids and to identify impacted watersheds and track sources. The strong correlation between passive and discrete sampling methodologies indicates that both can be effective methods at determining neonicotinoid occurrence. Similar findings showing agreement between POCIS and discrete sampling methodologies have been reported (Criquet et al., 2017 ; Metcalfe et al., 2019 ; Van Metre et al., 2017 ). Previous studies also found higher detection frequencies for neonicotinoids with POCIS as compared to grab samples (Berens et al., 2021 ; Bernard et al., 2019 ). The benefits of combining sampling strategies could outweigh the costs if (1) pulsing of neonicotinoids into the system is unpredictable (highly variable hydrology), (2) macroinvertebrate impairment has been observed and a suspected neonicotinoid source has not been confirmed by discrete sampling, or (3) additional temporal resolution is needed to assess stream condition. If passive samplers are used in the future to assess neonicotinoid concentrations, use of a spiked Performance Reference Compound (PRC) and adherence to a 14-28-day deployment time is recommended so mass accumulation can be transformed into concentration and compared to the FCV (Ahrens et al., 2015 ; Noro et al., 2019 ; Sultana et al., 2018 ). The usage of neonicotinoids throughout the United States is prolific and resource-limited state water management programs must discriminately prioritize monitoring to stay within budget (Norman et al., 2020 ). Monthly grab samples have been shown to provide adequate resolution if conducted within the correct spatial and temporal landscape. This study shows runoff resulting in high water level conditions during growing season months should be targeted. Similar studies have shown a strong positive correlation with flow (Berens et al., 2021 ; Hladik et al., 2014 ; Struger et al., 2017 ). While this study did not identify wastewater treatment plants as a significant source, previous studies where direct sampling of outfalls was conducted identified wastewater effluent as a point-source of imidacloprid and clothianidin (Berens et al., 2021 ; Webb et al., 2021 ). Previous studies have also observed neonicotinoids are more often detected in agriculturally dominated landscapes (clothianidin, thiamethoxam) and mixed urban and agricultural landscapes (imidacloprid) (Berens et al., 2021 ; Hladik et al., 2018 ; Nowell et al., 2021 ). For efficient use of monitoring funds, sample locations should be targeted toward urban and agricultural land uses. The aquatic life values derived in this study for imidacloprid and chronic clothianidin exposures are comparable to the work of previous authors and the US EPA Benchmarks for Aquatic Life (Table 2 ) (Nowell et al., 2017 ; US EPA, 2023b ). Acute values derived for clothianidin and thiamethoxam were significantly lower than the US EPA benchmark values (> 35x difference). The derived FCV for thiamethoxam is also lower than EPA benchmarks (> 2.5x difference). Lower state derived values are likely due to the inclusion of new toxicity data for sensitive species (Raby et al., 2018a ) which were not previously available when USEPA benchmarks were derived in 2017. The exclusion of synergistic effects and whole product toxicity in water quality standard derivation was further evaluated. The aquatic toxicity of two imidacloprid pesticide formulations found altered toxicity compared to reagent grade imidacloprid; although, differences were species and product dependent (Stoughton et al., 2008 ; Tišler et al., 2009 ). Several acute studies report mayfly LC50 value’s below 2 µg L − 1 (as low as 0.65 µg L − 1 ), all of which used pesticide formulations as opposed to reagent grade imidacloprid and could not be used in derivation of the aquatic life values pursuant to State and Federal rules (Alexander et al., 2007 ; Merga and Van den Brink, 2021; Roessink et al., 2013 ). As a formulation, imidacloprid was ~ 10x more toxic to the mayfly, Cleon dipterum , as compared to reagent grade only tests (LC50 = 1.5 vs. 18 ug/L) (Merga and Van den Brink, 2021; Roessink et al., 2013 ; Van den Brink et al., 2016 ). If the LC50 for the most sensitive organism to imidacloprid ( Neocloeon triangulifer ) was lowered 10x (from 3.1 to 0.31 ug/L), it is plausible that the derived AMV of 0.36 ug/L may not be protective for mayflies downstream of imidacloprid product use (Raby et al., 2018b ). Additional research is needed to assess imidacloprid formulation effects on chronic endpoints, as no comparison studies are currently available for review. Evaluation of current regulatory frameworks are needed to determine if mixture synergies may be more adequately addressed in the future. Decreasing the concentration of neonicotinoids entering the watershed will require multi-agency efforts. Any changes to pesticide label application rates are evaluated through the US EPA Office of Pesticides Program (Yen et al., 2012 ). Once a new pesticide is registered, it is reevaluated at least every 15-years, but not necessarily immediately when new toxicological data becomes available (US EPA, 2023c ). For agricultural pesticide uses, the United States Department of Agriculture or state equivalent oversees pesticide applicator training and can restrict the use of individual pesticides, but do not have any regulatory authority to require modification of pesticide labels pursuant to the Federal Insecticide, Fungicide, and Rodenticide Act of 1996 (Title 7 of the United States Code (U.S.C) Section 136 et seq.). Water quality monitoring for pesticides can be difficult to fund and is generally conducted by resource limited departments in state or federal agencies. The current process can contribute to a slow response to environmental degradation, especially if communication between agencies is not streamlined. Priorities between various agencies within the state and the federal government can be different, leading to challenges in pesticide management and adoption of new regulatory measures. All agencies will need to work collaboratively to address problematic neonicotinoid exposures. While this study provides significant insight into monitoring for neonicotinoids, a few caveats in the research should be known. This study focused mostly on large order rivers, and so findings comparing POCIS to discrete sampling may not be applicable to first order streams. Also, the seasonal trends observed in this study are reflective of the weather for the 2021–2022 timeframe but are subject to change in following years as a result of inconsistencies in weather patterns (particularly precipitation) or the timing of pesticide application. This work does not consider organism exposures to neonicotinoids in sediments as the FCVs are derived from water-only exposure data; however, sediment toxicity has been observed at clothianidin concentrations as low as 30 ug/kg ( C. dilutus 63-day lowest observed effect concentration for emergence) (Picard, 2016 ). Finally, sample locations were placed without knowledge of local farming practices or land application rates which may lead to missing important sources. For that reason, in states with more knowledge of pesticide application practices, hotspots could be more easily identified. Water resource managers would likely benefit from the creation of a public-facing database where farmers may (voluntarily) input data on pesticide use. California employs this type of tool (CalPIP) and a Michigan equivalent would have been helpful to focus and prioritize monitoring work (CDPR 2024). Declarations Funding: This work was supported by the Michigan Department of Environment, Great Lakes, and Energy Renew Michigan Fund. No competing interests are applicable to this research article. Acknowledgements: Special recognition is awarded to State of Michigan staff who assisted in the field, including: Mike McCauley, Kelly Turek, Aaron Parker, and Amanda Chambers. Special thanks to Jon Hoppe from EST Environmental and to Michigan’s MDARD Geagley laboratory staff. References Ahrens L, Daneshvar A, Lau AE, Kreuger J (2015) Characterization of five passive sampling devices for monitoring of pesticides in water. J Chromatogr A 1405:1–11. 10.1016/j.chroma.2015.05.044 Aisha AA, Hneine W, Mokh S, Devier MH, Budzinski H, Jaber F (2017) Monitoring of 45 pesticides in Lebanese surface water using Polar Organic Chemical Integrative Sampler (POCIS). Ocean Sci J 52:455–466. 10.1007/s12601-017-0041-4 Alexander AC, Culp JM, Liber K, Cessna AJ (2007) Effects of insecticide exposure on feeding inhibition in mayflies and oligochaetes. Environ Toxicol Chem 26:1726–1732. 10.1897/07-015R.1 Alvarez Da (2010) Guidelines for the use of the semi permeable membrane device (SPMD) and the polar organic chemical integrative sampler (POCIS) in environmental monitoring. Tech Methods 1–D4:28 Barata C, Baird DJ, Nogueira AJA, Soares AMVM, Riva MC (2006) Toxicity of binary mixtures of metals and pyrethroid insecticides to Daphnia magna Straus. Implications for multi-substance risks assessment. Aquat Toxicol 78:1–14. 10.1016/j.aquatox.2006.01.013 Barmentlo SH, Schrama M, De Snoo GR, Van Bodegom PM, Van Nieuwenhuijzen AE, Vijver MG (2021) Experimental evidence for neonicotinoid driven decline in aquatic emerging insects. Proc. Natl. Acad. Sci. 118. 10.1073/pnas.2105692118/-/DCSupplemental Berens MJ, Capel PD, Arnold WA (2021) Neonicotinoid Insecticides in Surface Water, Groundwater, and Wastewater Across Land-Use Gradients and Potential Effects. Environ Toxicol Chem 40:1017–1033. 10.1002/etc.4959 Bernard M, Boutry S, Lissalde S, Guibaud G, Saüt M, Rebillard JP, Mazzella N (2019) Combination of passive and grab sampling strategies improves the assessment of pesticide occurrence and contamination levels in a large-scale watershed. Sci Total Environ 651:684–695. 10.1016/j.scitotenv.2018.09.202 Bonmatin JM, Giorio C, Girolami V, Goulson D, Kreutzweiser DP, Krupke C, Liess M, Long E, Marzaro M, Mitchell EA, Noome DA, Simon-Delso N, Tapparo A (2015) Environmental fate and exposure; neonicotinoids and fipronil. Environ Sci Pollut Res 22:35–67. 10.1007/s11356-014-3332-7 Burd LA, Hartl B, Parent S (2016) Petition for Rulemaking to Evaluate Synergistic Effects of Pesticides During Registration and Registration Review. Portland, Oregon, USA Criquet J, Dumoulin D, Howsam M, Mondamert L, Goossens JF, Prygiel J, Billon G (2017) Comparison of POCIS passive samplers vs. composite water sampling: A case study. Sci Total Environ 609:982–991. 10.1016/j.scitotenv.2017.07.227 de Perre C, Murphy TM, Lydy MJ (2015) Fate and effects of clothianidin in fields using conservation practices. Environ Toxicol Chem 34:258–265. 10.1002/etc.2800 DiBartolomeis M, Kegley S, Mineau P, Radford R, Klein K (2019) An assessment of acute insecticide toxicity loading (AITL) of chemical pesticides used on agricultural land in the United States. PLoS ONE 14. 10.1371/journal.pone.0220029 European Commission (2018) Neonicotinoids Finnegan MC, Baxter LR, Maul JD, Hanson ML, Hoekstra PF (2017) Comprehensive characterization of the acute and chronic toxicity of the neonicotinoid insecticide thiamethoxam to a suite of aquatic primary producers, invertebrates, and fish. Environ Toxicol Chem 36:2838–2848. 10.1002/etc.3846 Gibbons D, Morrissey C, Mineau P (2015) A review of the direct and indirect effects of neonicotinoids and fipronil on vertebrate wildlife. Environ Sci Pollut Res 22:103–118. 10.1007/s11356-014-3180-5 Hageman KJ, Aebig CHF, Luong KH, Kaserzon SL, Wong CS, Reeks T, Greenwood M, Macaulay S, Matthaei CD (2019) Current-Use Pesticides in New Zealand Streams: Comparing Results from Grab Samples and Three Types of Passive Samplers. Environ Pollut 254 Herrmann LZ, Bub S, Wolfram J, Stehle S, Petschick LL, Schulz R (2023) Large monitoring datasets reveal high probabilities for intermittent occurrences of pesticides in European running waters. Environ Sci Eur 35. 10.1186/s12302-023-00795-4 Hladik ML, Corsi SR, Kolpin DW, Baldwin AK, Blackwell BR, Cavallin JE (2018) Year-round presence of neonicotinoid insecticides in tributaries to the Great Lakes. USA Environ Pollut 235:1022–1029. 10.1016/j.envpol.2018.01.013 Hladik ML, Kolpin DW, Kuivila KM (2014) Widespread occurrence of neonicotinoid insecticides in streams in a high corn and soybean producing region. USA Environ Pollut 193:189–196. 10.1016/j.envpol.2014.06.033 Lanteigne M, Whiting SA, Lydy MJ (2015) Mixture Toxicity of Imidacloprid and Cyfluthrin to Two Non-target Species, the Fathead Minnow Pimephales promelas and the Amphipod Hyalella azteca. Arch Environ Contam Toxicol 68:354–361. 10.1007/s00244-014-0086-7 Lu C, Warchol KM, Callahan RA (2014) Sub-lethal exposure to neonicotinoids impaired honey bees winterization before proceeding to colony collapse disorder. Bull. Insectology 67, 125–130 Maloney EM, Liber K, Headley JV, Peru KM, Morrissey CA (2018) Neonicotinoid insecticide mixtures: Evaluation of laboratory-based toxicity predictions under semi-controlled field conditions. Environ Pollut 243:1727–1739. 10.1016/j.envpol.2018.09.008 Maloney EM, Morrissey CA, Headley JV, Peru KM, Liber K (2017) Cumulative toxicity of neonicotinoid insecticide mixtures to Chironomus dilutus under acute exposure scenarios. Environ Toxicol Chem 36:3091–3101. 10.1002/etc.3878 Van den Merga LB (2021) Ecological effects of imidacloprid on a tropical freshwater ecosystem and subsequent recovery dynamics. Sci Total Environ 784:147167. 10.1016/j.scitotenv.2021.147167 Metcalfe CD, Helm P, Paterson G, Kaltenecker G, Murray C, Nowierski M, Sultana T (2019) Pesticides related to land use in watersheds of the Great Lakes basin. Sci Total Environ 648:681–692. 10.1016/j.scitotenv.2018.08.169 Metcalfe CD, Sultana T, Li H, Helm PA (2016) Current-use pesticides in urban watersheds and receiving waters of western Lake Ontario measured using polar organic chemical integrative samplers (POCIS). J Great Lakes Res 42:1432–1442. 10.1016/j.jglr.2016.08.004 Morrissey CA, Mineau P, Devries JH, Sanchez-Bayo F, Liess M, Cavallaro MC, Liber K (2015) Neonicotinoid contamination of global surface waters and associated risk to aquatic invertebrates: A review. Environ Int 74:291–303. 10.1016/j.envint.2014.10.024 Norman JE, Mahler BJ, Nowell LH, Van Metre PC, Sandstrom MW, Corbin MA, Qian Y, Pankow JF, Luo W, Fitzgerald NB, Asher WE, McWhirter KJ (2020) Daily stream samples reveal highly complex pesticide occurrence and potential toxicity to aquatic life. Sci Total Environ 715:136795. 10.1016/j.scitotenv.2020.136795 Noro K, Endo S, Shikano Y, Banno A, Yabuki Y (2020) Development and Calibration of the Polar Organic Chemical Integrative Sampler (POCIS) for Neonicotinoid Pesticides. Environ Toxicol Chem 39:1325–1333. 10.1002/etc.4729 Noro K, Yabuki Y, Banno A, Tawa Y, Nakamura S (2019) Validation of the Application of a Polar Organic Chemical Integrative Sampler (POCIS) in Non-steady-state. Conditions Aquat Environ 17:432–447. 10.2965/jwet.19-057 Nowell LH, Moran PW, Bexfield LM, Mahler BJ, Van Metre PC, Bradley PM, Schmidt TS, Button DT, Qi SL (2021) Is there an urban pesticide signature? Urban streams in five U.S. regions share common dissolved-phase pesticides but differ in predicted aquatic toxicity. Sci Total Environ 793. 10.1016/j.scitotenv.2021.148453 Nowell LH, Moran PW, Travis S, Norman, Julia E, Shoda N, Megan E (2017) Complex mixtures of dissolved pesticides show potential aquatic toxicity in a synoptic. study of Midwestern U.S. streams Picard CR (2016) Life-Cycle Toxicity Test Exposing Midges (Chironomus dilutus) to Clothianidin Applied to Sediment Under. Static-Renewal Conditions Following EPA Test Methods Raby M, Maloney E, Poirier DG, Sibley PK (2019) Acute effects of binary mixtures of imidacloprid and tebuconazole on 4 freshwater invertebrates. Environ Toxicol Chem 38:1093–1103. 10.1002/etc.4386 Raby M, Nowierski M, Perlov D, Zhao X, Hao C, Poirier DG, Sibley PK (2018a) Acute toxicity of 6 neonicotinoid insecticides to freshwater invertebrates. Environ Toxicol Chem 37:1430–1445. 10.1002/etc.4088 Raby M, Zhao X, Hao C, Poirier DG, Sibley PK (2018b) Chronic toxicity of 6 neonicotinoid insecticides to Chironomus dilutus and Neocloeon triangulifer. Environ Toxicol Chem 37:2727–2739. 10.1002/etc.4234 Roessink I, Merga LB, Van den Zweers HJ (2013) The neonicotinoid imidacloprid shows high chronic toxicity to mayfly nymphs. Environ Toxicol Chem 32:1096–1100. 10.1002/etc.2201 Rogers KH, McMillin S, Olstad KJ, Poppenga RH (2019) Imidacloprid Poisoning of Songbirds Following a Drench Application of Trees in a Residential Neighborhood in California, USA. Environ Toxicol Chem 38:1724–1727. 10.1002/etc.4473 Sánchez-Bayo F, Goka K, Hayasaka D (2016) Contamination of the aquatic environment with neonicotinoids and its implication for ecosystems. Front Environ Sci 4. 10.3389/fenvs.2016.00071 Sánchez-Bayo F, Hyne RV (2014) Detection and analysis of neonicotinoids in river waters - Development of a passive sampler for three commonly used insecticides. Chemosphere 99:143–151. 10.1016/j.chemosphere.2013.10.051 Satiroff JA, Messer TL, Mittelstet AR, Snow DD (2020) Pesticide Occurrence and Persistence Entering Recreational Lakes in Watersheds of Varying Land Uses Schmidt TS, Miller JL, Mahler BJ, Metre PC, Van, Nowell LH, Sandstrom MW, Carlisle DM, Moran PW, Bradley PM (2022) Ecological consequences of neonicotinoid mixtures in streams. Ecology 8:1–13 Stehle S, Schulz R (2015) Pesticide authorization in the EU—environment unprotected? Environ. Sci Pollut Res 22:19632–19647. 10.1007/s11356-015-5148-5 Stoughton SJ, Liber K, Culp J, Cessna A (2008) Acute and chronic toxicity of imidacloprid to the aquatic invertebrates Chironomus tentans and Hyalella azteca under constant- and pulse-exposure conditions. Arch Environ Contam Toxicol 54:662–673. 10.1007/s00244-007-9073-6 Struger J, Grabuski J, Cagampan S, Sverko E, McGoldrick D, Marvin CH (2017) Factors influencing the occurrence and distribution of neonicotinoid insecticides in surface waters of southern Ontario. Can Chemosphere 169:516–523. 10.1016/j.chemosphere.2016.11.036 Sultana T, Murray C, Kleywegt S, Metcalfe CD (2018) Neonicotinoid pesticides in drinking water in agricultural regions of southern Ontario. Can Chemosphere 202:506–513. 10.1016/j.chemosphere.2018.02.108 Tišler T, Jemec A, Mozetič B, Trebše P (2009) Hazard identification of imidacloprid to aquatic environment. Chemosphere 76:907–914. 10.1016/j.chemosphere.2009.05.002 US EPA (2023a) Aquatic Life Benchmarks and Ecological Risk Assessments for Registered Pesticides [WWW Document]. URL https://www.epa.gov/pesticide-science-and-assessing-pesticide-risks/aquatic-life-benchmarks-and-ecological-risk US EPA (2023b) Aquatic Life Benchmarks and Ecological. Risk Assessments for Registered Pesticides [WWW Document] US EPA (2023c) Explanation of Registration Review Schedule [WWW Document]. URL https://www.epa.gov/pesticide-reevaluation/explanation-registration-review-schedule#contact (accessed 12.28.23) US EPA (2004) Overview of the Ecological Risk Assessment Process in the Office of Pesticide Programs. Washington, D.C US EPA (1985) Guidelines for deriving numerical national water quality criteria for the protection of aquatic organisms and their uses. Environ Prot 105 n den Brink PJ, Van Smeden JM, Bekele RS, Dierick W, De Gelder DM, Noteboom M, Roessink I (2016) Acute and chronic toxicity of neonicotinoids to nymphs of a mayfly species and some notes on seasonal differences. Environ Toxicol Chem 35:128–133. 10.1002/etc.3152 Van Metre PC, Alvarez DA, Mahler BJ, Nowell L, Sandstrom M, Moran P (2017) Complex mixtures of Pesticides in Midwest U.S. streams indicated by POCIS time-integrating samplers. Environ Pollut 220:431–440. 10.1016/j.envpol.2016.09.085 Wang X, Anadón, Arturo Anadón, Anad´, Wu Q, Qiao F, Ares I, Martínez-Larrã Naga M-R, Yuan Z, Martínez M-A (2018) Mechanism of Neonicotinoid Toxicity: Impact on Oxidative Stress and Metabolism. Annu Rev Pharmacol Toxicol Annu Rev Pharmacol Toxicol 58:471–507. 10.1146/annurev-pharmtox Webb DT, Zhi H, Kolpin DW, Klaper RD, Iwanowicz LR, Lefevre GH (2021) Emerging investigator series: Municipal wastewater as a year-round point source of neonicotinoid insecticides that persist in an effluent-dominated stream. Environ Sci Process Impacts 23:678–688. 10.1039/d1em00065a Wolfram J, Stehle S, Bub S, Petschick LL, Schulz R (2018) Meta-Analysis of Insecticides in United States Surface Waters: Status and Future Implications. Environ Sci Technol 52:14452–14460. 10.1021/acs.est.8b04651 Xie P, Yan Q, Xiong J, Li H, Ma X, You J (2022) Point or non-point source: Toxicity evaluation using m-POCIS and zebrafish embryos in municipal sewage treatment plants and urban waterways. Environ Pollut 292. 10.1016/j.envpol.2021.118307 Xiong J, Tan B, Ma X, Li H, You J (2021) Tracing neonicotinoid insecticides and their transformation products from paddy field to receiving waters using polar organic chemical integrative samplers. J Hazard Mater 413. 10.1016/j.jhazmat.2021.125421 Xiong J, Wang Z, Ma X, Li H, You J (2019) Occurrence and risk of neonicotinoid insecticides in surface water in a rapidly developing region: Application of polar organic chemical integrative samplers. Sci Total Environ 648:1305–1312. 10.1016/j.scitotenv.2018.08.256 Yamamoto I, Yabuta G, Tomizawa M, Saito T, Miyamoto T, Kagabu S (1995) Molecular Mechanism for Selective Toxicity of Nicotinoids and Neonicotinoids, J. Pesticide Sci Yen JH, Esworth R, Schierow L-J (2012) Pesticide law: A summary of the statutes, RL 31921 Version 19 Supplementary Files SupportingInformation.docx SupportingInformationWaterQualityStandardCalculations.xls Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4682502","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":322745844,"identity":"3c06e7b5-ea21-447d-9b37-7175d37be0f1","order_by":0,"name":"Sara Nedrich","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxElEQVRIiWNgGAWjYJACCQYDhgR+IOMAYwOIJFaLZANpWhgYEgxAKonSIj+7+eDtigK7POMb2YkHfu5gkOO7kYBfi8GdY8mWZwySi81u5G442HuGwViSoBaJHDPJBoMDiduAWg4ztjEkbiCkRX5G/jewls0zIFrqCWphuJHDBtayQQKiJcGAoMNupBlbNhgkJ8448xbolzYJw5lnHhByWPLDmw1/7BL723M3f/jZZiPPd5yQw9CABGnKR8EoGAWjYBRgBwA0GE4Pp73pkgAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0001-8879-2847","institution":"Michigan Department of Environment, Great Lakes, and Energy","correspondingAuthor":true,"prefix":"","firstName":"Sara","middleName":"","lastName":"Nedrich","suffix":""},{"id":322745845,"identity":"caeae69f-689d-4d6b-92dc-502701d5dcf3","order_by":1,"name":"Sarah Bowman","email":"","orcid":"","institution":"Michigan Department of Environment, Great Lakes, and Energy","correspondingAuthor":false,"prefix":"","firstName":"Sarah","middleName":"","lastName":"Bowman","suffix":""},{"id":322745846,"identity":"2c382b69-4dc8-4879-be36-03a7425358ad","order_by":2,"name":"Elizabeth Stieber","email":"","orcid":"","institution":"Michigan Department of Environment, Great Lakes, and Energy","correspondingAuthor":false,"prefix":"","firstName":"Elizabeth","middleName":"","lastName":"Stieber","suffix":""},{"id":322745847,"identity":"b3fd666d-7b42-44ac-9931-9404a3e55984","order_by":3,"name":"Geoff Rhodes","email":"","orcid":"","institution":"Michigan Department of Environment, Great Lakes, and Energy","correspondingAuthor":false,"prefix":"","firstName":"Geoff","middleName":"","lastName":"Rhodes","suffix":""},{"id":322745848,"identity":"0abb700e-a08c-4825-84ab-1974d40e4d64","order_by":4,"name":"Brandon Armstrong","email":"","orcid":"","institution":"Michigan Department of Environment, Great Lakes, and Energy","correspondingAuthor":false,"prefix":"","firstName":"Brandon","middleName":"","lastName":"Armstrong","suffix":""}],"badges":[],"createdAt":"2024-07-03 20:05:35","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4682502/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4682502/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":61342662,"identity":"13eb49c3-616d-44d5-818d-bc9003535647","added_by":"auto","created_at":"2024-07-29 17:11:20","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1210717,"visible":true,"origin":"","legend":"\u003cp\u003eFourteen sampling sites were located in the Saginaw River watershed near Saginaw, Michigan. Land cover types are depicted, and sites are labelled with unique identifiers.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4682502/v1/cabbcb577e21f228aacd790a.jpeg"},{"id":61343130,"identity":"43620039-2289-4791-92dd-487cbcfdb823","added_by":"auto","created_at":"2024-07-29 17:19:20","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":531565,"visible":true,"origin":"","legend":"\u003cp\u003ePercentage of sites (n=14) with discrete surface water detections and final chronic value (FCV) exceedances of (2A) imidacloprid, (2B) clothianidin, or (2C) thiamethoxam as a function of sample date. Figures 2D-F are median POCIS mass accumulation (ng per POCIS ± standard error) for all sites (n=14) and sample periods.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4682502/v1/8aca88bb40272d03c38857a3.jpeg"},{"id":61342663,"identity":"1fb9d91b-a824-47cf-878f-bbe187ca992f","added_by":"auto","created_at":"2024-07-29 17:11:20","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":304100,"visible":true,"origin":"","legend":"\u003cp\u003eMean monthly concentrations of neonicotinoids in discrete surface water samples were strongly correlated with POCIS monthly mass accumulation (p\u0026lt;0.001). Figure 3A shows linear regressions derived for imidacloprid using all datapoints (black solid line) and July-August POCIS results only (blue dotted line). The pink line is the final chronic value (FCV) and calculated POCIS mass equivalent to the FCV for both regressions (solid vs. dotted). The final chronic value (FCV) for imidacloprid was exceeded for 7 of the timepoints sampled when applying one or both sampling methodologies (3A). The FCV of 81 ng/L clothianidin was not exceeded in any of the time averaged samples (3B).\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4682502/v1/aa8a5d1f0f9e545a7b8cbd54.jpeg"},{"id":61442908,"identity":"20d15e1f-e804-420f-ad79-fec5f4dfba3e","added_by":"auto","created_at":"2024-07-30 21:04:33","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2588941,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4682502/v1/3542c746-5c79-4267-89c7-cef7c973366c.pdf"},{"id":61342667,"identity":"ccf4e11a-530a-4d16-97e7-e338ce1d0dd9","added_by":"auto","created_at":"2024-07-29 17:11:21","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":270944,"visible":true,"origin":"","legend":"","description":"","filename":"SupportingInformation.docx","url":"https://assets-eu.researchsquare.com/files/rs-4682502/v1/3a4dfa120ea3ea049f6b821f.docx"},{"id":61342664,"identity":"1d107782-35bf-41d3-86e4-90ea9cd41780","added_by":"auto","created_at":"2024-07-29 17:11:20","extension":"xls","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":77312,"visible":true,"origin":"","legend":"","description":"","filename":"SupportingInformationWaterQualityStandardCalculations.xls","url":"https://assets-eu.researchsquare.com/files/rs-4682502/v1/82bfc45a3a84004777c56221.xls"}],"financialInterests":"","formattedTitle":"Passive and Discrete Sampling of Neonicotinoid Pesticides in Saginaw, Michigan (United States) and Implications for the Protection of Aquatic Life","fulltext":[{"header":"Highlights","content":"\u003cul\u003e\n \u003cli\u003eNeonicotinoids were detected in surface waters by passive and discrete sampling\u003c/li\u003e\n \u003cli\u003eNeonicotinoid concentrations varied seasonally and spatially\u003c/li\u003e\n \u003cli\u003eAcute and chronic water quality standards for three neonicotinoids were derived\u003c/li\u003e\n \u003cli\u003eImidacloprid concentrations exceeded chronic water quality standards\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Introduction","content":"\u003cp\u003ePesticide usage, while critical for food security, can have detrimental effects on non-target organisms, including aquatic life and wildlife (Gibbons et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; S\u0026aacute;nchez-Bayo et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Neonicotinoids are a class of pesticides used in soil and seed treatment, and foliar spray in the United States, and have been traced to bee and songbird mortality (Lu et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Rogers et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Mechanisms of neonicotinoid toxicity include oxidative stress and neurological impairment to an insect's nervous system (Wang et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Yamamoto et al., \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e1995\u003c/span\u003e). While three neonicotinoids were banned for use in the European Union (imidacloprid, clothianidin, and thiamethoxam), their use is prolific in the United States (European Commission, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). With reports of large-scale declines in insect populations and detections of imidacloprid at concentrations concerning to aquatic life (Barmentlo et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; DiBartolomeis et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Hladik et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Morrissey et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Wolfram et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), water resource managers have become increasingly concerned about potential impacts to non-target aquatic insects.\u003c/p\u003e \u003cp\u003eRecent monitoring studies in the United States identified environmentally significant concentrations of neonicotinoids in Saginaw, Michigan, adjacent cities, and Midwest states (Hladik et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Runoff from both agricultural and urban applications of neonicotinoids are common, with use for yard treatments and pet flea applications in urban settings (Berens et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Pesticides can show significant variability both temporally and spatially, which makes predicting occurrence and monitoring difficult for water resource managers (Herrmann et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Environmentally relevant concentrations can be missed using discrete (grab) samples from fixed-interval and composite monitoring (Criquet et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Norman et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Stehle and Schulz, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). While discrete samples are generally more cost effective for budget limited monitoring programs, the benefits of simultaneous passive sampling were assessed in this study to help weigh future monitoring costs against data quality objectives.\u003c/p\u003e \u003cp\u003ePassive sampling has been utilized as a monitoring tool for current use pesticides (Metcalfe et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Van Metre et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and can detect chemicals occurring at low concentrations in the environment that may show up as non-detect in traditional grab samples (Alvarez, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Bernard et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). A passive sampler called Polar Organic Chemical Integrative Sampler (POCIS) had a higher detection frequency of pesticides (median 62 compounds) than grab samples (median 46 compounds) in small streams throughout the Midwest United States (Van Metre et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The United States Geological Survey (USGS) published guidelines (Alvarez \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) for the use of POCIS devices. POCIS are designed to sample more water-soluble organic chemicals with log Kow\u0026thinsp;\u0026lt;\u0026thinsp;3 (i.e. pharmaceuticals, polar pesticides, phosphate flame retardants, and surfactants) and have been used successfully in previous neonicotinoid monitoring projects (Aisha et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Bernard et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Criquet et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Hageman et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Metcalfe et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Noro et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; S\u0026aacute;nchez-Bayo and Hyne, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Satiroff et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Sultana et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Van Metre et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Xie et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Xiong et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCurrent United States Environmental Protection Agency (US EPA) water quality guidelines for neonicotinoids are derived as aquatic life benchmark screening levels by the Office of Pesticide Programs (OPP) as outlined in the USEPA 1985 document, \u0026ldquo;Guidelines for Deriving Numerical National Water Quality Criteria for the Protection of Aquatic Organisms and Their Uses\u0026rdquo;(US EPA, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e1985\u003c/span\u003e). The benchmarks are used in an ecological risk assessment to determine pesticide label restrictions and dosing (US EPA, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2004\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2023a\u003c/span\u003e). Recent research has indicated that neonicotinoids may have synergistic toxicity, wherein greater than additive effects on insect emergence were observed in neonicotinoid mixtures (Maloney et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Schmidt et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The current United States regulatory framework; however, evaluates effects of single compounds (Barata et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) or presumes mechanistic additivity (ex. Polychlorinated biphenyls [PCBs]) even when synergistic effects are well known (Burd et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). One objective of this study is to provide water quality standards consistent with state and federal statute, evaluate all data available, and assess protectiveness to aquatic life.\u003c/p\u003e \u003cp\u003eBy applying a watershed scale approach to assess impacts of neonicotinoids on aquatic life, several objectives were met. The objectives were to (1) monitor for neonicotinoids in the Saginaw River watershed; (2) investigate the relative effectiveness of passive and discrete samplers at identifying neonicotinoids; (3) assess if there are significant spatial and temporal patterns affecting occurrence; (4) develop water quality standards consistent with State law and protective of aquatic life; and (5) use water quality standards to assess risk to aquatic species. Monitoring data are vitally important for protecting environmental health, and especially so for a pesticide class that is highly toxic to insects.\u003c/p\u003e"},{"header":"Materials \u0026 Methods","content":"\u003cp\u003eSite Selection \u0026amp; Characteristics\u003c/p\u003e \u003cp\u003eFourteen locations were selected in the Saginaw River watershed for neonicotinoid passive and discrete sampling. Sample sites were chosen representing both urban and agriculture as dominant land use types (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The dominant crop cover in the area is corn and soybeans. Land use estimates were calculated for each sample site\u0026rsquo;s upstream drainage area. The dataset was derived from the European Space Agency (ESA) Sentinel-2 imagery at 10-meter resolution (from ESRI\u0026rsquo;s ArcGIS platform) using a 30-meter digital elevation model retrieved from the State of Michigan\u0026rsquo;s LiDAR GeoData Explorer application. One sampling location (Dutch Creek, DC-0010) was moved 1.2 miles downstream for the 2022 sampling due to sampler theft at the original location. Locations included one mid-order (7) river (Bad River), and several high order rivers (\u0026ge;\u0026thinsp;9), including the Tittabawassee, Saginaw, Cass, Shiawassee, and Flint Rivers. Sampling locations were located proximate to four wastewater treatment plants directly upgradient of sites SG-0030, SG-0070, TW-0010, and CR-0010 (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Surface water quality in the area is of moderate hardness, with measured pH ranging from 7-8.5, and specific conductivity of 270\u0026ndash;1000 \u0026micro;S/cm throughout the course of the study.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLand use cover estimates as a percent (%) for sample locations are presented. Geometric mean concentrations (n\u0026thinsp;=\u0026thinsp;2, highest consecutive months; or n\u0026thinsp;=\u0026thinsp;7, if no two consecutive months with detections) of imidacloprid, clothianidin, and thiamethoxam for discrete surface water samples are provided. Single time-point discrete concentrations are provided in the Supporting Information (Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSite Code\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWaterbody Name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCrops\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBuilt Area\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTrees\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOther\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eImidacloprid (ng/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eClothianidin (ng/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eThiamethoxam (ng/L)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSG-0030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSaginaw River (S Rail.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e38.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e31.5\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e28.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e23.0\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSG-0040\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSaginaw River (Ind.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e38.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e46.8\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e26.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e25.0\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSG-0052a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSaginaw River (MGI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e38.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e31.7\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e26.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e11.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSG-0059\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSaginaw River (Dutch)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e38.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e29.7\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e26.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e23.0\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSG-0070\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSaginaw River (Zilwaukee)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e39.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e29.5\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e20.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e16.0\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSG-0110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSaginaw River (W Center)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e40.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e24.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e20.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e7.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDC-0010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDutch Creek\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e83.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e75.6\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e55.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e15.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBD-0110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBad River\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e34.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e63.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e9.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCR-0010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCass River\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e55.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e34.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e36.0\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e14.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePR-0010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePine River\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e52.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e35.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e26.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e14.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSW-0010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eShiawassee River\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e29.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e15.0\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCP-0020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChippewa River\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e48.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e15.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTW-0010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTittabawassee River\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e52.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e14.0\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e34.0\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e9.6\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFR-0015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFlint River\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e34.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e58.8\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e16.0\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e9.7\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003ea\u003c/sup\u003eOther land cover accounts for rangeland and flooded/water.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003eb\u003c/sup\u003eImidacloprid concentration exceeds the final chronic value (FCV).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003ec\u003c/sup\u003eGeomean was based on one detection (six other samples were non-detects).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eDiscrete Sampling\u003c/p\u003e \u003cp\u003eDiscrete surface water grab samples were collected for neonicotinoid analysis using certified cleaned glass amber bottles at each site during deployment and retrieval of the POCIS. Replicate and duplicate samples were collected on every trip. Replicates were 1 L samples collected from the same site within a 5-minute period. Duplicates were collected in a 2 L sample bottle (certified glass amber). Trip blanks with deionized water were included at each sampling event to test bottles for any cross contamination. Water temperature, pH, and conductivity were simultaneously collected using a YSI EXO multiparameter sonde. Water level data were determined using the USGS National Water Information System utilizing the closest proximate stream gauge station, where available.\u003c/p\u003e \u003cp\u003ePassive Sampling with POCIS\u003c/p\u003e \u003cp\u003eDeployment and retrieval procedures for POCIS were designed in accordance with Alvarez (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). To account for in-stream variability, three POCIS (220 mg OASIS-HLB sorbent) were pre-installed onto support holders by Environmental Sampling Technologies (EST) and shipped in sealed metal cans. The cans were stored at -20\u0026deg;C until deployment and then transported to the field on ice. At each site, a can was opened and the support holder containing the three POCIS was placed in perforated stainless-steel canisters. The canisters were suspended off the bottom of the stream using a stainless-steel cage with stainless-steel legs to prevent movement within the stream and sediments from clogging the POCIS. In non-wadable streams, the canisters were secured to a permanent object in the stream (i.e. an overhanging tree, permanent structure). Oasis-HLB POCIS are equilibrium-type samplers providing estimates of mean contaminant load over the deployment time (Ahrens et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePOCIS were deployed for a target of 28 days, with actual deployments ranging from 23\u0026ndash;49 days. Deployments exceeding 28-days were either due to scheduling conflicts and/or unsafe field conditions preventing collection (high water). The deployments occurred over two years, from July-October 2021 and April-July 2022. Extended POCIS deployment (49 days) in the Sept-Oct 2021 and (42 days) April-May 2022 sample events added uncertainty in this dataset due to the potential uptake rate declining after 28-days. As these samplers are already designed to capture equilibrium concentrations and the sampling rate is not consistent after 28-days, time-weighted averages could not be reliably calculated. The targeted sampling regime included all growing season months for the region. Upon retrieval, photos were taken of the location and notes on POCIS condition were recorded. Field (open to air at sample site) and trip (taken in car but not opened on-site) blanks were included, as well as an additional POCIS replicate for approximately 10% of the total samples.\u003c/p\u003e \u003cp\u003eFollowing deployment, POCIS were removed from their steel canisters and placed back in their original metal can and kept on ice. They were then frozen at -20\u0026deg;C and stored for \u0026le;\u0026thinsp;4 months. POCIS were shipped on ice overnight to the EST laboratory in St. Joseph, Missouri (United States) for extraction. The extraction method followed an updated (2017) USGS gravity flow method (unpublished). The Oasis-HLB was transferred to an extraction column with 100 \u0026micro;L of surrogate LIV-54 and each was extracted separately using 25 mL of methanol. Lab blanks were prepared similarly. The extraction was concentrated by ultra-high purity nitrogen blow-down and transferred to 5 mL ampules using acetonitrile. The pesticide extracts were cooled, flame sealed, and shipped to the Michigan Department of Agriculture and Rural Development (MDARD) laboratory for pesticide analysis.\u003c/p\u003e \u003cp\u003eNeonicotinoid Analysis\u003c/p\u003e \u003cp\u003eAll samples were analyzed via liquid chromatography and tandem mass spectrometry (LC/MS/MS) at the MDARD Geagley Laboratory in East Lansing, Michigan utilizing an Agilent Model G6410 Triple Quadrupole mass spectrometer coupled to an Agilent 1240 LC system. Six neonicotinoids were analyzed including acetamiprid, clothianidin, dinotefuran, imidacloprid, thiamethoxam, and thiacloprid. POCIS extracts were received from EST and run directly on the LC/MS/MS with a method detection limit of 0.0056 ug/POCIS. High volume (1L) discrete sample residues were collected on Biotage C18/ENV solid phase extraction (SPE) cartridges. The cartridges were activated and equilibrated with methanol and reagent water prior to sample addition. The cartridges were vacuum dried and eluted with acidified methanol for neonicotinoid extraction. The eluant was evaporated to \u0026lt;\u0026thinsp;0.3 mL and solvent exchanged into acetonitrile for analysis. The method detection limit for grab samples was 6.3 ng/L; however, results below detection were occasionally observed and reported as estimated values. Imidacloprid-pyridine-4-d-methylene-d2, 13C from Bayer CropScience was used as an internal standard. The MDARD used a factor of 0.333 POCIS/mL to back-calculate mass accumulation (ug/POCIS) based on dilution to 25.1 mL and a final extract volume of 3 mL. Quality control included reagent blanks, matrix blanks, and matrix spike recoveries with control limits of 50\u0026ndash;150%. The LIMS reporting method for this project was derived from SOP-PEST-0048 Quechers and drafted as SOP number PEMTM01 \u0026lsquo;Water Grab Samples for Pesticides\u0026rsquo;.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis\u003c/h2\u003e \u003cp\u003eNeonicotinoid site masses were calculated for each deployment by averaging the canister\u0026rsquo;s three replicate POCIS disks. Any site where a POCIS disk with observed biofouling (i.e. sediment or algae accumulation) upon collection that resulted in a\u0026thinsp;\u0026gt;\u0026thinsp;20% difference from the other two replicates was dropped from the mean as a quality control measure. Mean contaminant masses were not transformed to surface water concentrations (using sampling rate conversion, in liters per day, i.e. Rs values) due to exposure periods exceeding 28-days during some of the deployments. Three POCIS samplers were lost or stolen during the sampling period and removed from the dataset. One POCIS sampler was no longer submerged upon retrieval and was removed from the discrete vs. passive sampling analysis; however, was still included in monthly mass accumulation analyses. Non-detects were assigned a value of zero to prevent data artifacts from impacting regression analyses of observed detections.\u003c/p\u003e \u003cp\u003eQuantitative datasets, including discrete and passive sampling results, water levels, water quality data, and land use coverage, were tested for normality (Shapiro Test) in R version 1.4.1106. For normally distributed data, averages were reported; otherwise, median was reported. For non-normal datasets with insufficient sample size, geometric means were applied. If the geometric mean of imidacloprid concentration of two consecutive months exceeded the final chronic value, then an exceedance was assumed. This assumption is supported by passive sampling results showing a strong correlation with discrete sampling. An independent linear regression between water levels and discrete neonicotinoid concentrations (sum of imidacloprid, clothianidin, and thiamethoxam) was conducted in Microsoft Excel\u0026rsquo;s Data Analysis Toolkit version 2308 Build 16.0.16731.20310. Multiple linear regressions were likewise used to compare POCIS masses to discrete sample concentrations for all samples with detections. For the analysis, discrete sample geomeans were calculated from water collected at POCIS deployment and collection.\u003c/p\u003e \u003cp\u003eAquatic Life Values Derivation\u003c/p\u003e \u003cp\u003eWater quality standards protective of aquatic life were derived pursuant to Rule 57 of the Part 4 Water Quality Standards, promulgated as pursuant to Part 31, Water Resources Protection, of the Natural Resources Protection Act, 1994 PA 451, as amended (NREPA). Final acute values (FAV), ambient maximum values (AMV), and final chronic values (FCV) were derived for imidacloprid, clothianidin, and thiamethoxam. The FAV is the maximum concentration that can be emitted from a discharge pipe (effluent) and the AMV is the maximum average concentration permitted in ambient surface waters over 24-hours. The FAV and AMV are both acute endpoints derived from 48\u0026ndash;96-hour LC or EC50 values. The FCV is the maximum monthly average permitted in ambient surface water and is derived from chronic toxicological datasets utilizing the maximum acceptable toxicant concentration (MATC).\u003c/p\u003e \u003cp\u003eLiterature review to identify appropriate toxicity studies included use of the US EPA Ecotox database, SciFinder database, and a google scholar search. Search terms were limited to CAS or chemical name, and search terms \u0026lsquo;aquatic\u0026rsquo; and one or more of the following: \u0026lsquo;LC50\u0026rsquo;, \u0026lsquo;EC50\u0026rsquo;, \u0026lsquo;chronic\u0026rsquo;, or \u0026lsquo;acute\u0026rsquo;. All three neonicotinoids were derived as \u0026lsquo;Tier II\u0026rsquo; values, which indicates toxicological data was missing for one or more pertinent organism class. In the absence of relevant organism data, uncertainty factors (UFs) were used for tier II acute values derivation for imidacloprid (missing warmwater fish in class Osteichthyes, UF\u0026thinsp;=\u0026thinsp;4.3), clothianidin (missing salmonid, UF\u0026thinsp;=\u0026thinsp;4.3), and thiamethoxam (missing salmonid and third chordate family, UF\u0026thinsp;=\u0026thinsp;5.2). FCVs were derived utilizing acute to chronic ratios from available paired acute and chronic studies. Additional information, including the calculations and literature review documents, are provided in the Supplemental Material.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eNeonicotinoids in Water Samples\u003c/p\u003e \u003cp\u003eImidacloprid, clothianidin, and thiamethoxam were observed seasonally in water samples collected in the Saginaw River watershed. Acetamiprid, dinotefuran, and thiacloprid were not detected in any of the discrete water samples. One or more neonicotinoid was observed at 86% of sites sampled. Imidacloprid was detected at 64% of sites with a maximum concentration of 220 ng/L and median concentration of 27\u0026thinsp;\u0026plusmn;\u0026thinsp;11 ng/L. Clothianidin was detected at 86% of sites with a maximum concentration of 98 ng/L and median detected concentration of 31\u0026thinsp;\u0026plusmn;\u0026thinsp;5 ng/L. Thiamethoxam was detected at 71% of sites with a maximum concentration of 32 ng/L and median concentration of 7.9\u0026thinsp;\u0026plusmn;\u0026thinsp;2 ng/L. The maximum concentrations were observed at Dutch Creek (DC-0010) for all three analytes. Geometric means of neonicotinoid concentrations per site are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eImidacloprid was observed in discrete samples in four of seven months sampled, from July-October, with highest detections in July (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Clothianidin was observed in discrete samples in all months sampled, with maximum concentrations detected in October (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). Thiamethoxam was only observed in June, July, and October sampling events, with the peak in July (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eOnly three sampling locations had adequate USGS water level datasets and sufficient (\u0026ge;\u0026thinsp;2) detections of neonicotinoids during the sampling period. A strong positive relationship between water levels and neonicotinoid concentrations was observed (r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.75, p\u0026thinsp;\u0026le;\u0026thinsp;0.05) for two of these sites (Pine River and Saginaw River at West Center Road); however, data suggests snowmelt in early April may have resulted in a diluting effect wherein this trend was not observed. The third site, Saginaw River at Independence, where water levels were not correlated with neonicotinoid concentration, is located close to Saginaw Bay where river water levels are more strongly influenced by Great Lakes water levels than by upgradient runoff.\u003c/p\u003e \u003cp\u003eNeonicotinoids in Passive Samplers\u003c/p\u003e \u003cp\u003eImidacloprid, thiamethoxam, and clothianidin were detected at 100% of sites sampled with POCIS. Acetamiprid and dinotefuran were absent in \u0026gt;\u0026thinsp;95% of samples, with the highest concentrations estimated below the level of detection at 1.7 and 4.6 ng/POCIS, respectively. No detections of thiacloprid were observed. Median mass loading for all sites and deployment times was highest for clothianidin at 20.7\u0026thinsp;\u0026plusmn;\u0026thinsp;5.2 ng/POCIS, with a range of 3.8-253.3 ng/POCIS. Imidacloprid median mass loading was 20.3\u0026thinsp;\u0026plusmn;\u0026thinsp;3.0 ng/POCIS, with a range of 2.4\u0026ndash;180.0 ng/POCIS. Thiamethoxam detections were lower with a median of 4.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9 ng/POCIS, with a range of 0.9\u0026ndash;28.3 ng/POCIS.\u003c/p\u003e \u003cp\u003ePOCIS results differed from discrete samples in that detections were found during all sampling periods; although, seasonal trends were similar between both sampling methods (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Peak imidacloprid concentrations were observed from July-August with lower detections in the spring. Clothianidin and thiamethoxam were again observed to be highest in the late summer (September-October) sampling period, and present in low-moderate concentrations for all other sample months.\u003c/p\u003e \u003cp\u003eLinear regressions were used to compare results of passive and discrete sampling methods. Imidacloprid mass accumulation had a strong positive correlation with discrete sample mean concentrations (r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.86, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). The relationship for July-August was stronger (r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.95, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) before including the September-October POCIS dataset, possibly due to the extended 49-day October deployment exceeding the recommended 28-day timeframe. A strong positive correlation between clothianidin mass accumulation and discrete sample mean concentrations was also observed (r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.74, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eSpatial Variability \u0026amp; Assessment\u003c/p\u003e \u003cp\u003eThe predominant land cover was cropland, representing 29\u0026ndash;83% of land cover at the sample locations. Built (developed) landscapes represented 3.5\u0026ndash;27% of land cover types and tree cover (forested) accounted for 5.6\u0026ndash;52% of land use coverage. The Dutch Creek drainage area is almost entirely cropland (83%), whereas the Flint River site had nearly equivalent percentages of crop, forested, and urban land coverage. The six Saginaw River sites had nearly identical land coverage estimates. The site with the lowest crop and built area was in the Chippewa River. A summary of site land use coverage is provided in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eMaximum and geomean mass accumulations (ng/POCIS) were calculated for each sample site and compared to land cover percentages. Crop cover was the best predictor for clothianidin and thiamethoxam concentrations and demonstrated a moderate positive correlation for maximum and mean concentrations (r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.45, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Total percentage crop and built land covers had a moderate positive correlation with imidacloprid maximum concentrations (r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.42, p\u0026thinsp;\u0026lt;\u0026thinsp;0.02). These relationships were observed for both POCIS and discrete datasets.\u003c/p\u003e \u003cp\u003eOf the tributaries sampled, Dutch Creek had significantly higher concentrations of imidacloprid (\u0026gt;\u0026thinsp;3.5x all sites geomean) and clothianidin (2-4.8x all sites geomean) in both discrete and POCIS during the July 2021 sampling event. In addition to having the highest crop coverage (83%), it also had the lowest percentage of undeveloped area (forested, 5.6%). Another significant source of imidacloprid was the Flint River in July 2021 (1.5-3.5x all sites geomean). In addition to draining a large amount of cropland, the Flint River also drains a large urban landscape. The Bad River was determined to be a source of clothianidin to the watershed (2-4.5x all sites geomean) for most of the growing season. Interestingly, no detections of imidacloprid were observed in the Bad River. Additionally, the clothianidin concentrations found in the Bad River did not have the same seasonal dynamics as the other sample sites and remained elevated in all months except April, suggesting a unique source or fate/transport scenario as compared to the other sample locations. The low detected concentrations of thiamethoxam were not variable enough to distinguish sources but is likely tied to clothianidin as one of its breakdown products. No significant differences in neonicotinoid concentrations were observed in sites upstream and downstream of wastewater treatment plants, although no samples were taken directly from the outfalls.\u003c/p\u003e \u003cp\u003eAquatic life values comparison\u003c/p\u003e \u003cp\u003eThe literature search captured\u0026thinsp;\u0026gt;\u0026thinsp;100 pertinent articles that were selected for full article review. Articles meeting the stringent data quality requirements outlined in Rule 57 are presented in the Supplemental Material. Several otherwise acceptable studies were rejected due to the use of a formulation or pesticide product with active ingredient as opposed to reagent grade imidacloprid. Water quality standards for imidacloprid, clothianidin, and thiamethoxam are presented (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). From the currently available literature, the most toxic of the neonicotinoids to aquatic life was imidacloprid\u0026thinsp;\u0026gt;\u0026thinsp;clothianidin\u0026thinsp;\u0026gt;\u0026thinsp;\u0026gt;\u0026thinsp;thiamethoxam. The most sensitive organism classes to all three neonicotinoids included mayfly taxa and midges (de Perre et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Finnegan et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Maloney et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Raby et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2018a\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Stoughton et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Other sensitive organisms to one or more of the neonicotinoids included caddisfly taxa, a species of amphipod (\u003cem\u003eHyalella azteca)\u003c/em\u003e, beetles in the genus \u003cem\u003eGyrinus\u003c/em\u003e, and a species of oligochaete *\u003cem\u003eLumbriculus variegatus)\u003c/em\u003e (Lanteigne et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Raby et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2018a\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). All three water quality standards resulted in a tier II derivation which is presented in the Supplemental Material.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eWater quality standards (ng/L) protective of aquatic life calculated for Michigan, United States, as compared to USEPA aquatic life benchmarks. Standards include final acute values (end of discharge pipe limit), ambient maximum values (24-hour mean limit), and final chronic values (monthly mean limit).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameter Name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFinal Acute Value (FAV)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAquatic Maximum Value (AMV)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFinal Chronic Value (FCV)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eUSEPA acute benchmark\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUSEPA chronic benchmark\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClothianidin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e580\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e290\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e11000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImidacloprid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e720\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e360\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e380\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThiamethoxam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e530\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e280\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e17500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e740\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eImidacloprid concentrations fell below the AMV but occasionally exceeded the FCV. Single discrete samples are not sufficient comparisons to an FCV, since it is based on a 30-day average; therefore, evaluation of geometric means for the two highest consecutive sample months were considered (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In the absence of two consecutive months of detections, geomeans for all sample months were used. This calculation method assumes neonicotinoid concentrations decreased or increased linearly over the month and is supported by passive sampling results showing a strong correlation with discrete sampling. Using discrete geometric means only, a total of seven sites were identified as exceeding the FCV for imidacloprid. No sites exceeded the FCV for clothianidin and thiamethoxam. No sites exceeded the AMV for imidacloprid, clothianidin, or thiamethoxam.\u003c/p\u003e \u003cp\u003eUsing the two regressions presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA, the mass of imidacloprid corresponding with an FCV exceedance is greater than 65\u0026ndash;75 ng/POCIS. The sites that exceed both the 29 ng/L discrete FCV and the POCIS mass equivalent of the FCV are the Saginaw River at multiple locations (SG-0030, SG-0040, SG-0059, SG-0052a), Dutch Creek, and the Flint River. One paired sample (for Flint River, September-October) exceeded the POCIS mass equivalent to the FCV (78 ng), but not the discrete concentration (22 ng/L), which indicates the grab sample was likely an underestimate for monthly concentrations. Conversely, one paired discrete sample (Saginaw River, SG-0070) exceeded the FCV in the discrete sample (29.5 ng/L), but not the POCIS mass equivalent to the FCV (63 ng/POCIS). The FCV was not exceeded for any mean clothianidin concentrations (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB).\u003c/p\u003e"},{"header":"Discussion \u0026 Conclusions","content":"\u003cp\u003eMonitoring shows the Saginaw River watershed is impacted by neonicotinoids, with potentially concerning concentrations of imidacloprid in several tributaries. Imidacloprid was detected in the highest concentrations using discrete sampling and exceeded the FCV at seven out of 14 sites for \u0026ge;\u0026thinsp;30-days during the 2021\u0026ndash;2022 field season. Discrete imidacloprid concentrations observed in Dutch Creek were high enough where adverse effects to emergence of \u003cem\u003eChironomus dilutus\u003c/em\u003e have been reported in lab-based studies (14-d EC10 130 ng/L) (Raby et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2018b\u003c/span\u003e). Future work should be initiated to address imidacloprid inputs to both Dutch Creek and the Flint River as both were source tributaries to the Saginaw River.\u003c/p\u003e \u003cp\u003ePrevious neonicotinoid monitoring in Michigan collected monthly discrete water samples (composites) over a one-year period (October 2015-September 2016) and reported lower maximum concentrations (13.8 ng/L imidacloprid, 11.7 ng/L clothianidin, 9.6 ng/L thiamethoxam) but similar detection frequencies (Hladik et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Comparing data from the same location (Saginaw River, adjacent to SG-0070 and SG-0110), maximum detected imidacloprid concentrations have increased 2-4x from 2015 to 2021. Maximum clothianidin concentrations have increased 2.5-5x during the same time frame. Increasing concentrations are not surprising given the likelihood of neonicotinoid use increases (limited reporting data to verify) and half-lives in soils having been reported to exceed 1,000 days (Bonmatin et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Additional sample locations with neonicotinoid detections in Michigan were identified in the study (Hladik et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), including the Grand River, River Rouge, and St. Joseph River. Further sampling is needed to determine the prevalence and distribution of neonicotinoids and to identify impacted watersheds and track sources.\u003c/p\u003e \u003cp\u003eThe strong correlation between passive and discrete sampling methodologies indicates that both can be effective methods at determining neonicotinoid occurrence. Similar findings showing agreement between POCIS and discrete sampling methodologies have been reported (Criquet et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Metcalfe et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Van Metre et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Previous studies also found higher detection frequencies for neonicotinoids with POCIS as compared to grab samples (Berens et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Bernard et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The benefits of combining sampling strategies could outweigh the costs if (1) pulsing of neonicotinoids into the system is unpredictable (highly variable hydrology), (2) macroinvertebrate impairment has been observed and a suspected neonicotinoid source has not been confirmed by discrete sampling, or (3) additional temporal resolution is needed to assess stream condition. If passive samplers are used in the future to assess neonicotinoid concentrations, use of a spiked Performance Reference Compound (PRC) and adherence to a 14-28-day deployment time is recommended so mass accumulation can be transformed into concentration and compared to the FCV (Ahrens et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Noro et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Sultana et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe usage of neonicotinoids throughout the United States is prolific and resource-limited state water management programs must discriminately prioritize monitoring to stay within budget (Norman et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Monthly grab samples have been shown to provide adequate resolution if conducted within the correct spatial and temporal landscape. This study shows runoff resulting in high water level conditions during growing season months should be targeted. Similar studies have shown a strong positive correlation with flow (Berens et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Hladik et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Struger et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). While this study did not identify wastewater treatment plants as a significant source, previous studies where direct sampling of outfalls was conducted identified wastewater effluent as a point-source of imidacloprid and clothianidin (Berens et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Webb et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Previous studies have also observed neonicotinoids are more often detected in agriculturally dominated landscapes (clothianidin, thiamethoxam) and mixed urban and agricultural landscapes (imidacloprid) (Berens et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Hladik et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Nowell et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). For efficient use of monitoring funds, sample locations should be targeted toward urban and agricultural land uses.\u003c/p\u003e \u003cp\u003eThe aquatic life values derived in this study for imidacloprid and chronic clothianidin exposures are comparable to the work of previous authors and the US EPA Benchmarks for Aquatic Life (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) (Nowell et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; US EPA, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2023b\u003c/span\u003e). Acute values derived for clothianidin and thiamethoxam were significantly lower than the US EPA benchmark values (\u0026gt;\u0026thinsp;35x difference). The derived FCV for thiamethoxam is also lower than EPA benchmarks (\u0026gt;\u0026thinsp;2.5x difference). Lower state derived values are likely due to the inclusion of new toxicity data for sensitive species (Raby et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2018a\u003c/span\u003e) which were not previously available when USEPA benchmarks were derived in 2017.\u003c/p\u003e \u003cp\u003eThe exclusion of synergistic effects and whole product toxicity in water quality standard derivation was further evaluated. The aquatic toxicity of two imidacloprid pesticide formulations found altered toxicity compared to reagent grade imidacloprid; although, differences were species and product dependent (Stoughton et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Tišler et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Several acute studies report mayfly LC50 value\u0026rsquo;s below 2 \u0026micro;g L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (as low as 0.65 \u0026micro;g L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), all of which used pesticide formulations as opposed to reagent grade imidacloprid and could not be used in derivation of the aquatic life values pursuant to State and Federal rules (Alexander et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Merga and Van den Brink, 2021; Roessink et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). As a formulation, imidacloprid was ~\u0026thinsp;10x more toxic to the mayfly, \u003cem\u003eCleon dipterum\u003c/em\u003e, as compared to reagent grade only tests (LC50\u0026thinsp;=\u0026thinsp;1.5 vs. 18 ug/L) (Merga and Van den Brink, 2021; Roessink et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Van den Brink et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). If the LC50 for the most sensitive organism to imidacloprid (\u003cem\u003eNeocloeon triangulifer\u003c/em\u003e) was lowered 10x (from 3.1 to 0.31 ug/L), it is plausible that the derived AMV of 0.36 ug/L may not be protective for mayflies downstream of imidacloprid product use (Raby et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2018b\u003c/span\u003e). Additional research is needed to assess imidacloprid formulation effects on chronic endpoints, as no comparison studies are currently available for review. Evaluation of current regulatory frameworks are needed to determine if mixture synergies may be more adequately addressed in the future.\u003c/p\u003e \u003cp\u003eDecreasing the concentration of neonicotinoids entering the watershed will require multi-agency efforts. Any changes to pesticide label application rates are evaluated through the US EPA Office of Pesticides Program (Yen et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Once a new pesticide is registered, it is reevaluated at least every 15-years, but not necessarily immediately when new toxicological data becomes available (US EPA, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2023c\u003c/span\u003e). For agricultural pesticide uses, the United States Department of Agriculture or state equivalent oversees pesticide applicator training and can restrict the use of individual pesticides, but do not have any regulatory authority to require modification of pesticide labels pursuant to the Federal Insecticide, Fungicide, and Rodenticide Act of 1996 (Title 7 of the United States Code (U.S.C) Section 136 et seq.). Water quality monitoring for pesticides can be difficult to fund and is generally conducted by resource limited departments in state or federal agencies. The current process can contribute to a slow response to environmental degradation, especially if communication between agencies is not streamlined. Priorities between various agencies within the state and the federal government can be different, leading to challenges in pesticide management and adoption of new regulatory measures. All agencies will need to work collaboratively to address problematic neonicotinoid exposures.\u003c/p\u003e \u003cp\u003eWhile this study provides significant insight into monitoring for neonicotinoids, a few caveats in the research should be known. This study focused mostly on large order rivers, and so findings comparing POCIS to discrete sampling may not be applicable to first order streams. Also, the seasonal trends observed in this study are reflective of the weather for the 2021\u0026ndash;2022 timeframe but are subject to change in following years as a result of inconsistencies in weather patterns (particularly precipitation) or the timing of pesticide application. This work does not consider organism exposures to neonicotinoids in sediments as the FCVs are derived from water-only exposure data; however, sediment toxicity has been observed at clothianidin concentrations as low as 30 ug/kg (\u003cem\u003eC. dilutus\u003c/em\u003e 63-day lowest observed effect concentration for emergence) (Picard, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Finally, sample locations were placed without knowledge of local farming practices or land application rates which may lead to missing important sources. For that reason, in states with more knowledge of pesticide application practices, hotspots could be more easily identified. Water resource managers would likely benefit from the creation of a public-facing database where farmers may (voluntarily) input data on pesticide use. California employs this type of tool (CalPIP) and a Michigan equivalent would have been helpful to focus and prioritize monitoring work (CDPR 2024).\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding:\u003c/h2\u003e \u003cp\u003eThis work was supported by the Michigan Department of Environment, Great Lakes, and Energy Renew Michigan Fund. No competing interests are applicable to this research article.\u003c/p\u003e\u003ch2\u003eAcknowledgements:\u003c/h2\u003e \u003cp\u003eSpecial recognition is awarded to State of Michigan staff who assisted in the field, including: Mike McCauley, Kelly Turek, Aaron Parker, and Amanda Chambers. Special thanks to Jon Hoppe from EST Environmental and to Michigan\u0026rsquo;s MDARD Geagley laboratory staff.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAhrens L, Daneshvar A, Lau AE, Kreuger J (2015) Characterization of five passive sampling devices for monitoring of pesticides in water. J Chromatogr A 1405:1\u0026ndash;11. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.chroma.2015.05.044\u003c/span\u003e\u003cspan address=\"10.1016/j.chroma.2015.05.044\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAisha AA, Hneine W, Mokh S, Devier MH, Budzinski H, Jaber F (2017) Monitoring of 45 pesticides in Lebanese surface water using Polar Organic Chemical Integrative Sampler (POCIS). Ocean Sci J 52:455\u0026ndash;466. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s12601-017-0041-4\u003c/span\u003e\u003cspan address=\"10.1007/s12601-017-0041-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlexander AC, Culp JM, Liber K, Cessna AJ (2007) Effects of insecticide exposure on feeding inhibition in mayflies and oligochaetes. Environ Toxicol Chem 26:1726\u0026ndash;1732. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1897/07-015R.1\u003c/span\u003e\u003cspan address=\"10.1897/07-015R.1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlvarez Da (2010) Guidelines for the use of the semi permeable membrane device (SPMD) and the polar organic chemical integrative sampler (POCIS) in environmental monitoring. Tech Methods 1\u0026ndash;D4:28\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarata C, Baird DJ, Nogueira AJA, Soares AMVM, Riva MC (2006) Toxicity of binary mixtures of metals and pyrethroid insecticides to Daphnia magna Straus. Implications for multi-substance risks assessment. Aquat Toxicol 78:1\u0026ndash;14. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.aquatox.2006.01.013\u003c/span\u003e\u003cspan address=\"10.1016/j.aquatox.2006.01.013\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarmentlo SH, Schrama M, De Snoo GR, Van Bodegom PM, Van Nieuwenhuijzen AE, Vijver MG (2021) Experimental evidence for neonicotinoid driven decline in aquatic emerging insects. Proc. Natl. Acad. Sci. 118. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1073/pnas.2105692118/-/DCSupplemental\u003c/span\u003e\u003cspan address=\"10.1073/pnas.2105692118/-/DCSupplemental\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBerens MJ, Capel PD, Arnold WA (2021) Neonicotinoid Insecticides in Surface Water, Groundwater, and Wastewater Across Land-Use Gradients and Potential Effects. Environ Toxicol Chem 40:1017\u0026ndash;1033. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/etc.4959\u003c/span\u003e\u003cspan address=\"10.1002/etc.4959\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBernard M, Boutry S, Lissalde S, Guibaud G, Sa\u0026uuml;t M, Rebillard JP, Mazzella N (2019) Combination of passive and grab sampling strategies improves the assessment of pesticide occurrence and contamination levels in a large-scale watershed. Sci Total Environ 651:684\u0026ndash;695. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.scitotenv.2018.09.202\u003c/span\u003e\u003cspan address=\"10.1016/j.scitotenv.2018.09.202\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBonmatin JM, Giorio C, Girolami V, Goulson D, Kreutzweiser DP, Krupke C, Liess M, Long E, Marzaro M, Mitchell EA, Noome DA, Simon-Delso N, Tapparo A (2015) Environmental fate and exposure; neonicotinoids and fipronil. Environ Sci Pollut Res 22:35\u0026ndash;67. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11356-014-3332-7\u003c/span\u003e\u003cspan address=\"10.1007/s11356-014-3332-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBurd LA, Hartl B, Parent S (2016) Petition for Rulemaking to Evaluate Synergistic Effects of Pesticides During Registration and Registration Review. Portland, Oregon, USA\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCriquet J, Dumoulin D, Howsam M, Mondamert L, Goossens JF, Prygiel J, Billon G (2017) Comparison of POCIS passive samplers vs. composite water sampling: A case study. Sci Total Environ 609:982\u0026ndash;991. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.scitotenv.2017.07.227\u003c/span\u003e\u003cspan address=\"10.1016/j.scitotenv.2017.07.227\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ede Perre C, Murphy TM, Lydy MJ (2015) Fate and effects of clothianidin in fields using conservation practices. Environ Toxicol Chem 34:258\u0026ndash;265. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/etc.2800\u003c/span\u003e\u003cspan address=\"10.1002/etc.2800\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDiBartolomeis M, Kegley S, Mineau P, Radford R, Klein K (2019) An assessment of acute insecticide toxicity loading (AITL) of chemical pesticides used on agricultural land in the United States. PLoS ONE 14. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1371/journal.pone.0220029\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0220029\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEuropean Commission (2018) Neonicotinoids\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFinnegan MC, Baxter LR, Maul JD, Hanson ML, Hoekstra PF (2017) Comprehensive characterization of the acute and chronic toxicity of the neonicotinoid insecticide thiamethoxam to a suite of aquatic primary producers, invertebrates, and fish. Environ Toxicol Chem 36:2838\u0026ndash;2848. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/etc.3846\u003c/span\u003e\u003cspan address=\"10.1002/etc.3846\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGibbons D, Morrissey C, Mineau P (2015) A review of the direct and indirect effects of neonicotinoids and fipronil on vertebrate wildlife. Environ Sci Pollut Res 22:103\u0026ndash;118. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11356-014-3180-5\u003c/span\u003e\u003cspan address=\"10.1007/s11356-014-3180-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHageman KJ, Aebig CHF, Luong KH, Kaserzon SL, Wong CS, Reeks T, Greenwood M, Macaulay S, Matthaei CD (2019) Current-Use Pesticides in New Zealand Streams: Comparing Results from Grab Samples and Three Types of Passive Samplers. Environ Pollut 254\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHerrmann LZ, Bub S, Wolfram J, Stehle S, Petschick LL, Schulz R (2023) Large monitoring datasets reveal high probabilities for intermittent occurrences of pesticides in European running waters. Environ Sci Eur 35. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12302-023-00795-4\u003c/span\u003e\u003cspan address=\"10.1186/s12302-023-00795-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHladik ML, Corsi SR, Kolpin DW, Baldwin AK, Blackwell BR, Cavallin JE (2018) Year-round presence of neonicotinoid insecticides in tributaries to the Great Lakes. USA Environ Pollut 235:1022\u0026ndash;1029. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.envpol.2018.01.013\u003c/span\u003e\u003cspan address=\"10.1016/j.envpol.2018.01.013\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHladik ML, Kolpin DW, Kuivila KM (2014) Widespread occurrence of neonicotinoid insecticides in streams in a high corn and soybean producing region. USA Environ Pollut 193:189\u0026ndash;196. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.envpol.2014.06.033\u003c/span\u003e\u003cspan address=\"10.1016/j.envpol.2014.06.033\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLanteigne M, Whiting SA, Lydy MJ (2015) Mixture Toxicity of Imidacloprid and Cyfluthrin to Two Non-target Species, the Fathead Minnow Pimephales promelas and the Amphipod Hyalella azteca. Arch Environ Contam Toxicol 68:354\u0026ndash;361. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00244-014-0086-7\u003c/span\u003e\u003cspan address=\"10.1007/s00244-014-0086-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLu C, Warchol KM, Callahan RA (2014) Sub-lethal exposure to neonicotinoids impaired honey bees winterization before proceeding to colony collapse disorder. Bull. Insectology 67, 125\u0026ndash;130\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMaloney EM, Liber K, Headley JV, Peru KM, Morrissey CA (2018) Neonicotinoid insecticide mixtures: Evaluation of laboratory-based toxicity predictions under semi-controlled field conditions. Environ Pollut 243:1727\u0026ndash;1739. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.envpol.2018.09.008\u003c/span\u003e\u003cspan address=\"10.1016/j.envpol.2018.09.008\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMaloney EM, Morrissey CA, Headley JV, Peru KM, Liber K (2017) Cumulative toxicity of neonicotinoid insecticide mixtures to Chironomus dilutus under acute exposure scenarios. Environ Toxicol Chem 36:3091\u0026ndash;3101. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/etc.3878\u003c/span\u003e\u003cspan address=\"10.1002/etc.3878\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVan den Merga LB (2021) Ecological effects of imidacloprid on a tropical freshwater ecosystem and subsequent recovery dynamics. Sci Total Environ 784:147167. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.scitotenv.2021.147167\u003c/span\u003e\u003cspan address=\"10.1016/j.scitotenv.2021.147167\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMetcalfe CD, Helm P, Paterson G, Kaltenecker G, Murray C, Nowierski M, Sultana T (2019) Pesticides related to land use in watersheds of the Great Lakes basin. Sci Total Environ 648:681\u0026ndash;692. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.scitotenv.2018.08.169\u003c/span\u003e\u003cspan address=\"10.1016/j.scitotenv.2018.08.169\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMetcalfe CD, Sultana T, Li H, Helm PA (2016) Current-use pesticides in urban watersheds and receiving waters of western Lake Ontario measured using polar organic chemical integrative samplers (POCIS). J Great Lakes Res 42:1432\u0026ndash;1442. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jglr.2016.08.004\u003c/span\u003e\u003cspan address=\"10.1016/j.jglr.2016.08.004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMorrissey CA, Mineau P, Devries JH, Sanchez-Bayo F, Liess M, Cavallaro MC, Liber K (2015) Neonicotinoid contamination of global surface waters and associated risk to aquatic invertebrates: A review. Environ Int 74:291\u0026ndash;303. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.envint.2014.10.024\u003c/span\u003e\u003cspan address=\"10.1016/j.envint.2014.10.024\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNorman JE, Mahler BJ, Nowell LH, Van Metre PC, Sandstrom MW, Corbin MA, Qian Y, Pankow JF, Luo W, Fitzgerald NB, Asher WE, McWhirter KJ (2020) Daily stream samples reveal highly complex pesticide occurrence and potential toxicity to aquatic life. Sci Total Environ 715:136795. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.scitotenv.2020.136795\u003c/span\u003e\u003cspan address=\"10.1016/j.scitotenv.2020.136795\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNoro K, Endo S, Shikano Y, Banno A, Yabuki Y (2020) Development and Calibration of the Polar Organic Chemical Integrative Sampler (POCIS) for Neonicotinoid Pesticides. Environ Toxicol Chem 39:1325\u0026ndash;1333. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/etc.4729\u003c/span\u003e\u003cspan address=\"10.1002/etc.4729\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNoro K, Yabuki Y, Banno A, Tawa Y, Nakamura S (2019) Validation of the Application of a Polar Organic Chemical Integrative Sampler (POCIS) in Non-steady-state. Conditions Aquat Environ 17:432\u0026ndash;447. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2965/jwet.19-057\u003c/span\u003e\u003cspan address=\"10.2965/jwet.19-057\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNowell LH, Moran PW, Bexfield LM, Mahler BJ, Van Metre PC, Bradley PM, Schmidt TS, Button DT, Qi SL (2021) Is there an urban pesticide signature? Urban streams in five U.S. regions share common dissolved-phase pesticides but differ in predicted aquatic toxicity. Sci Total Environ 793. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.scitotenv.2021.148453\u003c/span\u003e\u003cspan address=\"10.1016/j.scitotenv.2021.148453\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNowell LH, Moran PW, Travis S, Norman, Julia E, Shoda N, Megan E (2017) Complex mixtures of dissolved pesticides show potential aquatic toxicity in a synoptic. study of Midwestern U.S. streams\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePicard CR (2016) Life-Cycle Toxicity Test Exposing Midges (Chironomus dilutus) to Clothianidin Applied to Sediment Under. Static-Renewal Conditions Following EPA Test Methods\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRaby M, Maloney E, Poirier DG, Sibley PK (2019) Acute effects of binary mixtures of imidacloprid and tebuconazole on 4 freshwater invertebrates. Environ Toxicol Chem 38:1093\u0026ndash;1103. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/etc.4386\u003c/span\u003e\u003cspan address=\"10.1002/etc.4386\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRaby M, Nowierski M, Perlov D, Zhao X, Hao C, Poirier DG, Sibley PK (2018a) Acute toxicity of 6 neonicotinoid insecticides to freshwater invertebrates. Environ Toxicol Chem 37:1430\u0026ndash;1445. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/etc.4088\u003c/span\u003e\u003cspan address=\"10.1002/etc.4088\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRaby M, Zhao X, Hao C, Poirier DG, Sibley PK (2018b) Chronic toxicity of 6 neonicotinoid insecticides to Chironomus dilutus and Neocloeon triangulifer. Environ Toxicol Chem 37:2727\u0026ndash;2739. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/etc.4234\u003c/span\u003e\u003cspan address=\"10.1002/etc.4234\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRoessink I, Merga LB, Van den Zweers HJ (2013) The neonicotinoid imidacloprid shows high chronic toxicity to mayfly nymphs. Environ Toxicol Chem 32:1096\u0026ndash;1100. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/etc.2201\u003c/span\u003e\u003cspan address=\"10.1002/etc.2201\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRogers KH, McMillin S, Olstad KJ, Poppenga RH (2019) Imidacloprid Poisoning of Songbirds Following a Drench Application of Trees in a Residential Neighborhood in California, USA. Environ Toxicol Chem 38:1724\u0026ndash;1727. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/etc.4473\u003c/span\u003e\u003cspan address=\"10.1002/etc.4473\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eS\u0026aacute;nchez-Bayo F, Goka K, Hayasaka D (2016) Contamination of the aquatic environment with neonicotinoids and its implication for ecosystems. Front Environ Sci 4. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fenvs.2016.00071\u003c/span\u003e\u003cspan address=\"10.3389/fenvs.2016.00071\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eS\u0026aacute;nchez-Bayo F, Hyne RV (2014) Detection and analysis of neonicotinoids in river waters - Development of a passive sampler for three commonly used insecticides. Chemosphere 99:143\u0026ndash;151. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.chemosphere.2013.10.051\u003c/span\u003e\u003cspan address=\"10.1016/j.chemosphere.2013.10.051\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSatiroff JA, Messer TL, Mittelstet AR, Snow DD (2020) Pesticide Occurrence and Persistence Entering Recreational Lakes in Watersheds of Varying Land Uses\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchmidt TS, Miller JL, Mahler BJ, Metre PC, Van, Nowell LH, Sandstrom MW, Carlisle DM, Moran PW, Bradley PM (2022) Ecological consequences of neonicotinoid mixtures in streams. Ecology 8:1\u0026ndash;13\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStehle S, Schulz R (2015) Pesticide authorization in the EU\u0026mdash;environment unprotected? Environ. Sci Pollut Res 22:19632\u0026ndash;19647. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11356-015-5148-5\u003c/span\u003e\u003cspan address=\"10.1007/s11356-015-5148-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStoughton SJ, Liber K, Culp J, Cessna A (2008) Acute and chronic toxicity of imidacloprid to the aquatic invertebrates Chironomus tentans and Hyalella azteca under constant- and pulse-exposure conditions. Arch Environ Contam Toxicol 54:662\u0026ndash;673. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00244-007-9073-6\u003c/span\u003e\u003cspan address=\"10.1007/s00244-007-9073-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStruger J, Grabuski J, Cagampan S, Sverko E, McGoldrick D, Marvin CH (2017) Factors influencing the occurrence and distribution of neonicotinoid insecticides in surface waters of southern Ontario. Can Chemosphere 169:516\u0026ndash;523. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.chemosphere.2016.11.036\u003c/span\u003e\u003cspan address=\"10.1016/j.chemosphere.2016.11.036\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSultana T, Murray C, Kleywegt S, Metcalfe CD (2018) Neonicotinoid pesticides in drinking water in agricultural regions of southern Ontario. Can Chemosphere 202:506\u0026ndash;513. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.chemosphere.2018.02.108\u003c/span\u003e\u003cspan address=\"10.1016/j.chemosphere.2018.02.108\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTišler T, Jemec A, Mozetič B, Trebše P (2009) Hazard identification of imidacloprid to aquatic environment. Chemosphere 76:907\u0026ndash;914. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.chemosphere.2009.05.002\u003c/span\u003e\u003cspan address=\"10.1016/j.chemosphere.2009.05.002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUS EPA (2023a) Aquatic Life Benchmarks and Ecological Risk Assessments for Registered Pesticides [WWW Document]. URL \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.epa.gov/pesticide-science-and-assessing-pesticide-risks/aquatic-life-benchmarks-and-ecological-risk\u003c/span\u003e\u003cspan address=\"https://www.epa.gov/pesticide-science-and-assessing-pesticide-risks/aquatic-life-benchmarks-and-ecological-risk\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUS EPA (2023b) Aquatic Life Benchmarks and Ecological. Risk Assessments for Registered Pesticides [WWW Document]\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUS EPA (2023c) Explanation of Registration Review Schedule [WWW Document]. URL \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.epa.gov/pesticide-reevaluation/explanation-registration-review-schedule#contact\u003c/span\u003e\u003cspan address=\"https://www.epa.gov/pesticide-reevaluation/explanation-registration-review-schedule#contact\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (accessed 12.28.23)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUS EPA (2004) Overview of the Ecological Risk Assessment Process in the Office of Pesticide Programs. Washington, D.C\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUS EPA (1985) Guidelines for deriving numerical national water quality criteria for the protection of aquatic organisms and their uses. Environ Prot 105\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003en den Brink PJ, Van Smeden JM, Bekele RS, Dierick W, De Gelder DM, Noteboom M, Roessink I (2016) Acute and chronic toxicity of neonicotinoids to nymphs of a mayfly species and some notes on seasonal differences. Environ Toxicol Chem 35:128\u0026ndash;133. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/etc.3152\u003c/span\u003e\u003cspan address=\"10.1002/etc.3152\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVan Metre PC, Alvarez DA, Mahler BJ, Nowell L, Sandstrom M, Moran P (2017) Complex mixtures of Pesticides in Midwest U.S. streams indicated by POCIS time-integrating samplers. Environ Pollut 220:431\u0026ndash;440. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.envpol.2016.09.085\u003c/span\u003e\u003cspan address=\"10.1016/j.envpol.2016.09.085\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang X, Anad\u0026oacute;n, Arturo Anad\u0026oacute;n, Anad\u0026acute;, Wu Q, Qiao F, Ares I, Mart\u0026iacute;nez-Larr\u0026atilde; Naga M-R, Yuan Z, Mart\u0026iacute;nez M-A (2018) Mechanism of Neonicotinoid Toxicity: Impact on Oxidative Stress and Metabolism. Annu Rev Pharmacol Toxicol Annu Rev Pharmacol Toxicol 58:471\u0026ndash;507. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1146/annurev-pharmtox\u003c/span\u003e\u003cspan address=\"10.1146/annurev-pharmtox\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWebb DT, Zhi H, Kolpin DW, Klaper RD, Iwanowicz LR, Lefevre GH (2021) Emerging investigator series: Municipal wastewater as a year-round point source of neonicotinoid insecticides that persist in an effluent-dominated stream. Environ Sci Process Impacts 23:678\u0026ndash;688. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1039/d1em00065a\u003c/span\u003e\u003cspan address=\"10.1039/d1em00065a\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWolfram J, Stehle S, Bub S, Petschick LL, Schulz R (2018) Meta-Analysis of Insecticides in United States Surface Waters: Status and Future Implications. Environ Sci Technol 52:14452\u0026ndash;14460. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1021/acs.est.8b04651\u003c/span\u003e\u003cspan address=\"10.1021/acs.est.8b04651\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXie P, Yan Q, Xiong J, Li H, Ma X, You J (2022) Point or non-point source: Toxicity evaluation using m-POCIS and zebrafish embryos in municipal sewage treatment plants and urban waterways. Environ Pollut 292. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.envpol.2021.118307\u003c/span\u003e\u003cspan address=\"10.1016/j.envpol.2021.118307\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXiong J, Tan B, Ma X, Li H, You J (2021) Tracing neonicotinoid insecticides and their transformation products from paddy field to receiving waters using polar organic chemical integrative samplers. J Hazard Mater 413. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jhazmat.2021.125421\u003c/span\u003e\u003cspan address=\"10.1016/j.jhazmat.2021.125421\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXiong J, Wang Z, Ma X, Li H, You J (2019) Occurrence and risk of neonicotinoid insecticides in surface water in a rapidly developing region: Application of polar organic chemical integrative samplers. Sci Total Environ 648:1305\u0026ndash;1312. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.scitotenv.2018.08.256\u003c/span\u003e\u003cspan address=\"10.1016/j.scitotenv.2018.08.256\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYamamoto I, Yabuta G, Tomizawa M, Saito T, Miyamoto T, Kagabu S (1995) Molecular Mechanism for Selective Toxicity of Nicotinoids and Neonicotinoids, J. Pesticide Sci\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYen JH, Esworth R, Schierow L-J (2012) Pesticide law: A summary of the statutes, RL 31921 Version 19\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"neonicotinoids, POCIS, pesticides, toxicity, passive sampling, imidacloprid","lastPublishedDoi":"10.21203/rs.3.rs-4682502/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4682502/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eNeonicotinoid pesticides are widely applied in urban and agricultural settings despite their toxicity to aquatic organisms at low concentrations. Monitoring for six neonicotinoids (acetamiprid, clothianidin, dinotefuran, imidacloprid, thiacloprid, thiamethoxam) in the Saginaw River watershed of Michigan shows detections of imidacloprid exceeding final chronic values (FCVs) developed to protect aquatic life. The study design implemented both discrete and passive surface water sampling to capture the episodic nature of pesticide release. Fourteen sites were sampled monthly from August-October 2021 and April-July 2022. One or more neonicotinoids were detected in 86% of discrete and 100% of passive samples. Imidacloprid was detected at the highest maximum concentration (220 ng L\u003csup\u003e-1\u003c/sup\u003e), followed by clothianidin (98 ng L\u003csup\u003e-1\u003c/sup\u003e), and thiamethoxam (32 ng L\u003csup\u003e-1\u003c/sup\u003e). Development of aquatic life values for imidacloprid, clothianidin, and thiamethoxam, pursuant to Michigan statute and Rule 57 (Water Quality Standards), resulted in FCVs of 29 ng L\u003csup\u003e-1\u003c/sup\u003e, 81 ng L\u003csup\u003e-1\u003c/sup\u003e, and 280 ng L\u003csup\u003e-1\u003c/sup\u003e, respectively. Seven out of 14 sample locations exceeded the FCV for imidacloprid. The most sensitive species included in derivation of neonicotinoid aquatic life values included mayflies (\u003cem\u003eNeocloeon triangulifer, Cloeon sp., and McCaffertium sp.\u003c/em\u003e) and a midge (\u003cem\u003eChironomus dilutus\u003c/em\u003e). This study provides new insight on monitoring for neonicotinoid pesticides and weighs the costs and benefits of passive and discrete sampling methodologies.\u0026nbsp;\u003c/p\u003e","manuscriptTitle":"Passive and Discrete Sampling of Neonicotinoid Pesticides in Saginaw, Michigan (United States) and Implications for the Protection of Aquatic Life","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-29 17:11:16","doi":"10.21203/rs.3.rs-4682502/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a6d3cdcf-a94d-4e23-8611-c7ec0b1e1881","owner":[],"postedDate":"July 29th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-12-23T01:38:26+00:00","versionOfRecord":[],"versionCreatedAt":"2024-07-29 17:11:16","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4682502","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4682502","identity":"rs-4682502","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}