Chapter 9
Pesticides in Surface Water: Monitoring, Modeling, Risk Assessment, and Management Downloaded from pubs.acs.org by BETHEL UNIV on 04/02/19. For personal use only.
Pesticide Monitoring of Surface Water in the Complex Agronomic and Ecological Landscape of California’s Central Coast Sarah G. Lopez* Central Coast Water Quality Preservation, Inc., Watsonville, California 95076, United States *E-mail:
[email protected].
Produce is grown on the Central Coast agricultural lands of California with unprecedented efficiency; however, the very climatic conditions that are so conducive to efficient production can also exacerbate the discharge of farming inputs into surface and groundwaters. Natural features and cropping systems of the Central Coast also result in a logistically complicated arena for pest management by growers. As a cost-effective means of complying with the Conditional Waiver of Waste Discharge Requirements for Discharges from Irrigated Lands (Order No. R3-2004-0117) water quality regulation, the Central Coast irrigated agriculture industry formed a nonprofit entity to implement a cooperative surface water quality monitoring program (CMP). Early monitoring by the CMP showed frequent aquatic toxicity and concurrent detections of organophosphate (OP) pesticides in agricultural watersheds. Over the following decade, subsequent studies showed a reduction in detections for chlorpyrifos and diazinon, with continued malathion detections as well as the neonicotinoid, imidacloprid. In 2017, concurrently measured concentrations of imidacloprid and OP pesticides in water were generally not sufficient to explain the observed toxicity to Ceriodaphnia dubia, suggesting the presence of one or more additional, unmeasured toxicants in the water column. By comparison, the relationship between toxicity to Hyalella azteca and the presence of pyrethroids or chlorpyrifos, or both, in sediment was robust across three CMP
© 2019 American Chemical Society
study periods. A strong spatial pattern also emerged in which pesticide detection rates and concentrations, as well as both water and sediment toxicity, were consistently higher in the Lower Salinas and Santa Maria valleys than in another group of CMP sites located in other impaired agricultural watersheds of the Central Coast.
Introduction Natural Features Stretching over 450 km from Pescadero to south of Santa Barbara and spreading from the Pacific Ocean roughly 65 km inland, California’s Central Coast region (29,000 km2) is ecologically and agronomically complex. The region features several mountain ranges and inland valleys, coastal terraces, sea cliffs, and beaches. This geographic diversity gives rise to climatic diversity and consequent biological diversity, where coastal cypress groves and redwood forests contrast with a dry interior landscape dominated by chaparral and grasses, and shoreline wildlife and marine aquatic organisms contrast with upland terrestrial fauna and freshwater species. The region is also home to the federally designated Monterey Bay National Marine Sanctuary, and to the last remaining population of California sea otter, three subspecies of threatened or endangered steelhead, and one subspecies of endangered coho salmon (1). Perhaps the most important natural feature of the Central Coast with respect to agriculture and water quality is its hydrology. The region is considered semiarid with an average annual precipitation of 46 cm, but with microclimates ranging in annual precipitation of 23 cm on the dry Carrizo Plain to over 125 cm in the Santa Cruz mountains. Limited rainfall combined with natural surface and groundwater hydrological characteristics, consumptive water usage, and other hydromodifications give rise to intermittent streamflow in many water bodies, particularly small tributaries to the lower Salinas River and in the Estero Bay and South Coast areas. The Salinas River was famously described by John Steinbeck as “only a part-time river,” where in wet winters “the river tore the edges of the farm lands and washed whole acres down,” but “in the summer the river didn’t run at all above ground” (2). The ephemeral or low-flow characteristics of many Central Coast water bodies result in streamflows that at times consist of undiluted agricultural and urban discharges, without the relatively unpolluted base flows that act in wetter climates to dilute concentrations of entrained pollutants. Agronomic Features and Pest Control The Central Coast’s mild, Mediterranean climate gives rise to long growing seasons conducive to year-round agricultural activity, and the many microclimates and varied topography yield conditions to support a wide variety of crops and agricultural production systems. The region is the nation’s leading supplier of fresh vegetables and several fruits (3), and the middle section of the region (i.e., the Salinas Valley) is often referred to as the “Salad Bowl of the World.” Proximity 144
to the ocean has a moderating effect on summer temperatures, allowing “cool season vegetable” production throughout most of the year near the coast. The cool ocean mists and rich clay soils of Castroville support artichoke production that has earned the area the nickname “Artichoke Capital of the World.” Wine grape production in the Central Coast’s Monterey County rivals that of the better known Napa and Sonoma Valleys (4), and within a single vineyard in Paso Robles there is sufficient topographical and microclimatic diversity for one block of vines to yield grapes suitable for both mass-market grocery store wines and limited edition bottles available only at the vineyard’s own tasting room. Between strawberry fields in the Santa Maria and Watsonville areas, the Central Coast produces nearly 90% of all strawberries grown in the United States and more organic strawberries than the other 49 states combined (5). The natural resource value of farmland supportive of this level of productivity is recognized by the state of California, which classifies a large majority of the agricultural land on the Central Coast as “Prime Farmland,” “Farmland of Statewide Importance,” or “Unique Farmland” (6). Natural features and cropping systems of the Central Coast also result in a complicated arena for pest management. The mild climate and intensity of Central Coast crop cycles (i.e., 2 to 3 crops per acre of land per year, in rapid succession) are particularly conducive to the growth and persistence of pest populations. Every crop grown on the Central Coast is considered a “specialty crop” (or minor crop) by industry standards, which means that manufacturers of pest control products (i.e., insecticides, fungicides, and herbicides) have little incentive to invest resources in the management of their products as used by Central Coast growers. Research dollars, including environmental fate and transport studies, tend to be invested in larger-market crops such as the cereal grains and soybeans that dominate U.S. agriculture on a national scale. Fresh produce crops also require more direct manual harvesting by fieldworkers as opposed to the mechanized techniques available to grain commodities, and fresh produce is eaten by consumers much sooner after harvest than foods with longer shelf lives. Both of these factors elevate human health concerns and make Central Coast crops more sensitive to pesticide residues, and hence subject to more stringent regulatory oversight. Human health considerations also limit the suite of allowable pest control materials that produce growers can legally use. These regulatory and natural complications are juxtaposed with the sheer entomological and pathological complexity of pest control in general. Contemporary examples include viral diseases that are vectored by insect pests, weed species that act as reservoirs for insect pests in between crops, and pests that do not affect crop yields but cause cosmetic damage sufficient to render a crop unmarketable. Despite a high percentage of Central Coast growers reporting the use of integrated pest management as a best management practice, many growers and pest control advisors report feeling constrained to a small handful or even single insecticide(s) to effectively bring their crops to market. These insecticides tend to have reduced environmental residence times compared to older classes like the organochlorines [e.g., 1,1,1-trichloro-2,2-bis(p-chlorophenyl)ethane, also 145
known as DDT] but have demonstrated impacts to sensitive terrestrial and aquatic invertebrates at off-farm sites. Changes in application techniques and landscape-scale use patterns for individual pesticides may also bear on instream pesticide detections and aquatic toxicity. The industry-oriented details of pesticide application practices are poorly studied in the context of impacts to Central Coast aquatic environments. However, this information may be pertinent to the regulatory process and has been named by the industry as a critical information gap in its ability to comply with numeric water quality objectives (7). Environmental Impacts Produce is grown on Central Coast agricultural lands with unprecedented efficiency, as many growers can produce two to three crops per year in rapid succession on the same acreage. High costs of production and low profit margins create incentives to maximize yield and minimize unharvested product. Multiple crop cycles entail frequent cultivation and low nutrient uptake efficiencies, which make these systems especially prone to nutrient runoff (1, 8). In addition, the very climatic conditions that are so conducive to efficient production can also exacerbate the discharge of nutrients into surface and groundwaters due to the timing of annual rainfall in relation to the high production season (1). A similar phenomenon occurs with other agricultural inputs such as pest control products, which can move off-site via spray drift, storm runoff, and discharges of irrigation tailwater. Finally, the hydrologic features of many Central Coast water bodies and their underlying aquifers result in streamflows (particularly in small tributaries) consisting of undiluted agricultural and urban discharges, which result in varied rates of loading to downstream water bodies but, due to the lack of dilution, carry high concentrations of entrained pollutants. Over the past decade, impacts from Central Coast agriculture on surface and groundwater have been repeatedly monitored and documented (9, 10). In addition to intensive agricultural activity and resultant environmental impacts, the Central Coast and nearby areas host a consortium of environmental research institutions and watchdog organizations, two prominent agricultural research universities, and a number of conservation-oriented field service agencies, both public and private. Numerous Central Coast farms also have their own in-house research teams and have created high-level positions to co-manage environmental and other regulatory concerns (e.g., food safety). The level of attention given by a variety of stakeholders to studying and mitigating agricultural impacts to the Central Coast environment provides important context for the regulatory process, which is constantly evolving to address this topic. Agricultural Water Quality Regulation Nonpoint source pollution is less straightforward to regulate than point sources, in particular because efforts to allocate pollutant loading to any specific source could result in costs that far exceed the budgets of local regulatory agencies or the revenues of the regulated dischargers, and do not necessarily yield 146
conclusive results (1). Farmers in the United States are exempted as nonpoint source dischargers from common regulatory mechanisms in the Federal Clean Water Act, and until 2004 California farmers were also exempted in the state’s water code (Porter Cologne Act) by a broad waiver of regulatory requirements applied to other waste dischargers. As amended in 1999 for implementation in 2004, the California Water Code allowed waivers for specific types of discharges if the waiver met five conditions and did not exceed five years in length. In July of 2004 the agency charged with implementing the California Water Code for the Central Coast region—the Central Coast Regional Water Quality Control Board (CCRWQCB)—adopted a waiver for irrigated agriculture requiring irrigated agricultural operations to enroll under the Conditional Waiver of Waste Discharge Requirements for Discharges from Irrigated Lands (Order No. R3-2004-0117) (hereafter referred to as the Ag Order) or be excluded from the Ag Order and regulated under other, more onerous CCRWQCB discharge requirements. The 2004 Ag Order required irrigated commercial farm operators to meet the following requirements: (1) enroll with the CCRWQCB, (2) attend a minimum of 15 hours of approved related education, (3) complete a farm water quality management plan, (4) implement management practices to improve water quality in tailwater, stormwater runoff, and discharges to groundwater, and (5) perform individual water quality monitoring or participate in a cooperative water quality monitoring program. As a cost-effective and practical means of complying with the fifth requirement (above) of the Ag Order, the Central Coast irrigated agriculture industry formed a nonprofit entity to implement a cooperative surface water quality monitoring program (Cooperative Monitoring Program, hereafter referred to as the CMP). The CMP initiated monthly water quality monitoring in January of 2005 at 25 sites within two hydrologic units: the Santa Maria River (including Oso Flaco Creek) in Santa Barbara and San Luis Obispo counties, and the Lower Salinas River in Monterey County. This was expanded with an additional 25 sites one year later to include four additional Central Coast hydrologic units. In March 2012, the CCRWQCB adopted a new Ag Order, which resulted in the addition of several more sites within the existing study areas. The overall goals of CMP monitoring are to characterize the water quality conditions in Central Coast agricultural watersheds, to understand long-term water quality trends in these areas, and to meet the reporting requirements specified in the Ag Order. The CMP monitoring sites were selected to reflect a population of impaired, agricultural water bodies throughout the Central Coast region. This is a unique feature of the CMP design, particularly among programs that monitor pesticides, as it supports inferences regarding the scope of agricultural water quality impairment across the entire region. Results from the initial year of CMP monitoring showed repeated toxicity to aquatic invertebrates in laboratory bioassays, and by that time several studies had been published linking toxicity observed on the Central Coast to the organophosphate (OP) pesticides chlorpyrifos and diazinon (11–16). Both chemicals have been commonly applied in recent decades to crops grown in CMP monitoring areas. Subsequent studies by the CMP and others have shown continued detections of OP and other major pesticide 147
classes in the surface waters and sediments of the Central Coast streams, with some changes over time (17–19). This chapter examines changes over time in detection rates and concentrations for several major pesticide classes, and concurrent toxicity to sensitive aquatic invertebrates in both the water column and stream-bottom sediments. The approach taken is a re-examination of several discrete studies conducted by the CMP over an 11-year period during which major changes in pesticide regulation and use patterns occurred, as well as changes to major cropping patterns and significant advances in irrigation management by growers. A 5-year drought also occurred during this time period. Trends identified in pesticide detections and aquatic toxicity likely reflect influences from a mix of these factors.
Methods Monitoring Sites and Study Design This chapter synthesizes the results of four studies that characterize the presence of several major pesticide classes as well as aquatic toxicity in the water column and bed sediments of CMP water bodies over an 11-year period. Selection of water bodies for CMP monitoring was conducted in 2004 for compliance with the Ag Order (described above) and was based primarily on current placement, or proposed future placement, on the Clean Water Act 303(d) list of impaired water bodies for pollutants associated with irrigated agriculture. Water bodies were also selected to have expected instream flows during much or all of the year, as many Central Coast streams are ephemeral or dry except in major storms. Within these water bodies, monitoring sites were selected for public access and to best characterize agricultural inputs. The sites were generally placed along mainstem rivers and at the lower ends of tributaries in areas associated with agricultural activity. In a few cases, sites were also located to aid in distinguishing agricultural inputs from urban or industrial sources. Most sites were selected from the suite of existing monitoring sites for the CCRWQCB’s Central Coast Ambient Monitoring Program, for which at least one year of monitoring data were already available. The CMP monitoring sites are located within the following Central Coast hydrologic units (listed from north to south and shown in Figure 1): Pajaro Valley, Lower Salinas Valley, Estero Bay (i.e., San Luis Obispo area), Santa Maria Valley, San Antonio Creek, Santa Ynez River, and South Coast (i.e., Santa Barbara area). Areas of the Central Coast region not covered by CMP sites generally have fewer water bodies with consistent streamflow or do not represent impaired agricultural watersheds, or both. In addition to the monitoring results discussed here, the CMP has conducted monthly water quality monitoring for a suite of physical and chemical water quality parameters (i.e., temperature, pH, conductivity, dissolved oxygen, turbidity, discharge [streamflow], nitrate, and other nutrient-related parameters) every year since 2005. Routine CMP monitoring also incorporates sample collection for water column and bed sediment bioassays of toxicity to sensitive aquatic invertebrates and algae. Results of routine CMP monitoring are submitted 148
electronically to the CCRWQCB on a quarterly basis in a raw format, and are summarized and discussed in detail in annual narrative reports (9, 20). Samples for water column toxicity analysis are collected from CMP sites four times per year as follows: Once during the first quarter of the year (ideally timed with a rain event generating significant runoff, but no later than March 31 if significant rain does not occur); once during the second quarter of the year concurrent with sediment toxicity monitoring (typically in April or May); once in either August or September to indicate fully “dry season” conditions; and once in the fourth quarter of the year (ideally timed with the first significant rain event of the season, but no later than December 31 if significant rain does not occur). Samples for sediment toxicity analysis are collected from CMP sites during the spring of each year, most commonly in April. Logistics (e.g., access to sites) and environmental conditions affect the actual number of toxicity analyses performed during the year. Sample collection was planned for each study period discussed here, as described in Table 1. The CMP is required for regulatory compliance purposes to achieve 90% completeness for all program components, and sites were preselected to have a high likelihood of both access and flowing water relative to other potential sites in the region. Not all sites had flowing water or sufficient access to be sampled during every monitoring event; however, sample counts are generally balanced across subregions and all portions of the period of record for all parameters, as reflected in Table 1. To address Ag Order requirements for follow-up monitoring (21) and further explore the link between OP pesticides and toxicity to the sensitive aquatic invertebrate Ceriodaphnia dubia (C. dubia, a cladoceran), OP pesticides were measured in the CMP’s most highly impacted watersheds (i.e., Lower Salinas and Santa Maria valleys, which contain about half of the CMP’s total sites) concurrent with regularly scheduled CMP water toxicity sampling in August and September 2006, and again in February and March 2007. This initial study was completed in 2009 by repeating the same monitoring design at the other half of CMP sites, which are located in watersheds outside of the Lower Salinas and Santa Maria valleys, as depicted in Figure 1. A second study was conducted in 2013–2014 with four monitoring events for all CMP sites (Table 1), and a third study conducted in 2017 (two sampling events per site, with an additional two events planned for 2018). Beginning in 2017, the study was expanded to evaluate the presence of pesticides from the neonicotinoid class, as well as toxicity to an additional aquatic invertebrate—Chironomus dilutus (C. dilutus, a midge fly larva). The full list of compounds analyzed from each pesticide class is given in Table 2. Sampling events were distributed in each study between summer months (April through October) and winter months (November through March). Winter events were scheduled to target storm runoff, but due to limited precipitation this was not always possible. Winter samples may be better considered as cold season or off-peak relative to Central Coast crop cycles.
149
Figure 1. Cooperative Monitoring Program (CMP) Project Area and Monitoring Site Locations.
150
Table 1. Monitoring Design and Sample Counts for Each Study Period Monitoring Events Targeted Per Sitea
Yearsa
Study Period
Monitoring Subregions
2006–2007
4
Lower Salinas & Santa Maria valleys
93
2009b
4
Other subregions
77
1b (sediment only)
2010
1
All subregions
51
2 (water & sediment)
2013–2014
4 water
All subregions
173 water
1a (water only)
1 sediment
151
3 (water & sediment)
2017c
2 water 1 sediment
a
Sample Count
51 sediment All subregions
88 water 51 sediment
“Year(s)” indicates calendar year(s) over which each study period occurred. “Monitoring Events” indicates the total number of events spread over the years in each study period, NOT that this number of events was repeated in each year. b The initial study was originally planned only for the Lower Salinas and Santa Maria valleys. Based on the results, it was then determined within the Ag Order regulatory framework that the study should be repeated at all sites outside these areas. Despite a time lag of a few years, the second portion of this study was sufficiently near the inception of the CMP, and sufficiently in advance of the second study period (2013–2014) that factors influencing instream pesticide concentrations should have been similar to the earlier portion of this initial study period. c The third study period was planned to take place from 2017 through 2018. As 2018 monitoring was in progress at the time of this writing, only the 2017 results could be incorporated. Two additional water monitoring events and one additional sediment event are planned for 2018 at each site.
Table 2. List of Target Analytes, Analytical Methods, and Reporting Limits Parameter
Method
Laboratory Reporting Limit
Organophosphate Insecticides in Water
152
Azinphos-methyl
EPA 625M
0.01 µg/L
Chlorpyrifos
EPA 625M
0.001 µg/L
Diazinon
EPA 625M
0.001 µg/L
Dichlorvos
EPA 625M
0.006 µg/L
Dimethoate
EPA 625M
0.01 µg/L
Demeton-S
EPA 625M
0.002 µg/L
Disulfoton
EPA 625M
0.002 µg/L
Malathion
EPA 625M
0.005 µg/L
Methamidophos
EPA 625M
0.01 µg/L
Methidathion
EPA 625M
0.01 µg/L
Parathion-methyl
EPA 625M
0.002 µg/L
Phorate
EPA 625M
0.01 µg/L
Phosmet
EPA 625M
0.01 µg/L
Neonicotinoid Insecticides in Water Acetamiprid
EPA 625M
0.02 µg/L
Dinotefuran
EPA 625M
0.012 µg/L
Clothianidin
EPA 625M
0.02 µg/L
Parameter
Method
Laboratory Reporting Limit
Imidacloprid
EPA 625M
0.004 µg/L
Thiacloprid
EPA 625M
0.004 µg/L
Thiamethoxam
EPA 625M
0.004 µg/L
Bioassays for Toxicity in Water Ceriodapnia dubia, 7-day chronic
1002.0 in EPA/821/R-02/013
NA
Chironomus dilutus, 96-h acute
Alternate test species in EPA/821/R-02/012
NA
Pyrethroid Insecticides in Sediment
153
Gamma-cyhalothrin
EPA 8720M NCI
1.25 ng/g
Lambda-cyhalothrin
EPA 8720M NCI
0.74 ng/g
Bifenthrin
EPA 8720M NCI
0.71 ng/g
Beta-cyfluthrin
EPA 8720M NCI
1.25 ng/g
Cyfluthrin
EPA 8720M NCI
0.8 ng/g
Esfenvalerate
EPA 8720M NCI
0.9 ng/g
Permethrin, cis-
EPA 8720M NCI
0.55 ng/g
Permethrin, trans-
EPA 8720M NCI
0.7 ng/g
Cypermethrin
EPA 8720M NCI
0.9 ng/g
Fenpropathrin
EPA 8720M NCI
0.66 ng/g
Fenvalerate
EPA 8720M NCI
0.8 ng/g Continued on next page.
Table 2. (Continued). List of Target Analytes, Analytical Methods, and Reporting Limits Parameter Fluvinate
Method EPA 8720M NCI
Laboratory Reporting Limit 0.74 ng/g
Organophosphate Insecticides in Sediment Chlorpyrifos
EPA 8270C
2 ng/g
Interpretive Parameters for Sediment Particle size distribution
SM 2560D v20,21
0.05%
Percent solids
SM 2540B
0.10%
Total organic carbon
SM 5310B
0.10%
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Bioassay for Toxicity in Sediment Hyalella azteca, 10-day NA, Not applicable.
EPA, 2000
NA
In May 2010, the CMP undertook its first study of pesticides in stream-bottom sediments, with a single sampling event at all sites for pyrethroid pesticides and the OP chlorpyrifos in sediment (Table 2), concurrent with regularly scheduled CMP monitoring for toxicity to Hyalella azteca (H. azteca, an amphipod) in sediment (Table 1). A second study was conducted in either April or May 2013–2014, with a third study in April 2017. Sample Collection, Chemistry, and Toxicity Testing Methods A full description of sampling protocols for surface water and sediments, as well as detailed descriptions of laboratory analytical methods, are contained in the CMP Quality Assurance Project Plan, or QAPP (22). The following is a brief description of these methods. Water samples were collected by hand from below the surface (typically 1 to 6 in., depending on overall water column depth) into a stainless steel bucket. The “bucket grab” was then proportionally split into polyethylene or glass containers as specified by the QAPP for each analyte. This process was repeated until each sample container was adequately filled. Samples were not filtered in the field. Samples were immediately placed on ice to begin chilling without freezing at 0–6 °C. Sample container materials, volumes, and storage and holding time specifications are given in Table B-1 of the QAPP (22). Aliquots were then designated for either bioassay or chemical analysis (Table 2). For sediment samples, depositional fine-grain sediments were collected from the upper 2 cm of the streambed using a precleaned stainless steel scoop and placed into a precleaned stainless steel bowl. Once approximately 4 L of sediment had been collected and placed in the bowl, the sediment was thoroughly homogenized by manual stirring with a large stainless steel spoon, after which the homogenized sediment was partitioned into containers as described in Table B-1 of the QAPP (22). Aliquots were then designated for either bioassay or chemical analysis (Table 2). Sample transportation and handling followed QAPP guidelines, including maintenance of cold and dark storage conditions, observance of holding time limits, maintenance of chain-of-custody records, and so forth. Water and sediment toxicity bioassays were performed by Pacific EcoRisk Laboratory (Cordelia, CA). Pesticide analyses were performed by Physis Environmental Laboratories, Inc. (Anaheim, CA). The U.S. Environmental Protection Agency (USEPA) method 625M-NCI (gas chromatography/negative chemical ionization mass spectrometry) was used to quantify OP and neonicotinoid insecticides in water. The USEPA method 8270M-NCI was used to quantify pyrethroid insecticides and the OP chlorpyrifos in sediment. The auxiliary parameter, total organic carbon, was also analyzed in sediment (SM 5310B) to aid in quantifying bioavailability of sediment insecticides. Reporting limits for each analyte were selected to be substantially lower than the toxic effect thresholds of interest, on the order of “parts per trillion” as specified in Table 2. Laboratory standard operating procedures for each analytical method are provided in Attachments 8 through 21 of Appendix B of the CMP QAPP for chemistries, and in Appendix C of the QAPP for toxicity bioassays (22). 155
Survival rates for toxicity test organisms were analyzed relative to control organism performance to evaluate any statistically significant toxic effects due to the sample water or sediments. The USEPA standard 6- to 8-day water test method for C. dubia was performed for invertebrates in water, and the USEPA standard 10-day sediment test method for H. azteca was performed for invertebrates in sediment. In the third study period (2017), an additional water test for C. dilutus (96-hour) was introduced. Though not described in the USEPA manual as a primary test species, C. dilutus is listed as a supplemental species for the described C. dubia method (23). All statistical analyses of bioassay results were performed using the Comprehensive Environmental Toxicity Information System (CETIS®) software package (24). In concept, survival rates for test organisms were compared to survival rates for organisms in control samples, and samples showing a significant negative difference between test and control performance were deemed toxic. In addition to the determination of “significant toxic effect,” results were also expressed in terms of the test samples’ performance as a “percent (%) of control” samples’ performance, where “% of control” is conceptually equal to:
with some additional calculations relative to replicate samples. In samples with elevated conductivity, USEPA protocols were followed for use of the alternative test species H. azteca or Americamysis bahia (A. bahia) in water, or Eohaustorius estuarius in sediment. The USEPA standard 6- to 8-day water test method for C. dubia includes both survival and reproduction endpoints. Samples may show a significant effect (i.e., toxicity) to reproduction, even when there is little or no impact on survival. Reproductive effects are reported by the CMP and considered by the CCRWQCB in designating impaired water bodies (25), and have been evaluated in annual CMP reports (9, 26). Due to scope limitations and also because survival-based results have supported a robust discussion of toxicity patterns in this and other studies (18), the results presented here are generally limited to the survival endpoint. Toxic Unit Analysis Toxic unit (TU) analysis provides a means to compare the relative toxicities of different measured pesticides with one another and to express pesticide concentrations in terms of their expected toxic effects to aquatic organisms. Toxic units for each pesticide class measured in water or sediment were calculated by dividing the pesticide concentration by the LC50 (median lethal concentration) value, as determined by a current review of scientific literature and the USEPA’s ECOTOX database (Table 3; (36)). A TU is the pesticide concentration in water or sediment, divided by the LC50, and is specific to both the test organism and test duration. A TU of 1 represents an expected survival rate of 50% of the test organism over the test duration, or may also be interpreted to signify the concentration at which significant mortality to test organisms would be expected to occur with 50% frequency over multiple tests. 156
Table 3. LC50’s Used to Calculate TUs for Selected Pesticides in Water and Sediment Parameter
C. dubia LC50 (µg/L)a
Pesticide Class
H. azteca LC50 ( µg/g)b
C. dilutus LC50 (µg/L)
Reference for Lowest LC50
LC50’s for Water Column Parameters Chlorpyrifos
Organophosphate
0.023
0.29
--
(27)
Diazinon
Organophosphate
0.164
10.7
--
(27)
Dimethoate
Organophosphate
NA
1.29
--
(28)
Malathion
Organophosphate
1.9979
613.8
--
(29)
Acetamiprid
Neonicotinoid
33,500
2.8
--
(30)
11.6
--
(30)
23.5
--
(30) (28)
Clothianidin
157
Dinotefuran
Neonicotinoid Neonicotinoid
100,000 87,000
Imidacloprid
Neonicotinoid
72,124.9
2.65
--
Thiacloprid
Neonicotinoid
3390
1.6
--
(30)
Thiamethoxam
Neonicotinoid
80,000
61.9
--
(30)
LC50’s for Sediment Parameters Chlorpyrifos
Organophosphate
--
--
1.77
(31, 32)
Bifenthrin
Pyrethroid
--
--
0.52
(33)
Cyfluthrin, Total
Pyrethroid
--
--
1.08
(33)
Cyhalothrin, gamma-
Pyrethroid
--
--
0.45
(33) Continued on next page.
Table 3. (Continued). LC50’s Used to Calculate TUs for Selected Pesticides in Water and Sediment Parameter
C. dilutus LC50 (µg/L)
C. dubia LC50 (µg/L)a
Pesticide Class
H. azteca LC50 ( µg/g)b
Reference for Lowest LC50
Cyhalothrin, lambda-
Pyrethroid
--
--
0.45
(33)
Cypermethrin, Total
Pyrethroid
--
--
0.38
(34)
Esfenvalerate
Pyrethroid
--
--
1.54
(33)
Fenpropathrin
Pyrethroid
--
--
1.1
(35)
Fenvalerate
Pyrethroid
--
--
1.54
(33)
Permethrin (cis + trans)
Pyrethroid
--
--
10.8
(33)
T-Fluvalinate
pyrethroid
--
--
NA
NA
158
NA, Not available. a LC50 (median lethal concentration) values are reported for C. dubia and C. dilutus in water. In several cases the metric listed is an “effects concentration” that is either sublethal, based on a shorter test duration, or involved a different invertebrate species than the CMP standard, or combination of all three. In these cases, the alternative threshold is typically expected to be lower than a 96-h C. dubia lethal effect. b LC50 values for H. azteca reported for sediment are TOC-corrected, or “ng/g-TOC.”
Toxicants with a strong affinity for organic carbon (OC) tend to adhere to OC particles and are less bioavailable, making them generally less toxic to aquatic organisms when sediments have high total organic carbon (TOC) content (37); therefore, TU calculations for sediment parameters were normalized by the measured TOC at each site. Toxic units of pesticides in sediments were based on the identified LC50 values and calculated using the following equation:
where TU is dimensionless, C is the concentration of parameter in sediment (ng/ g), S is the concentration of TOC in sediment (ng/g), and LC50 is the median lethal concentration (ng/g). The equation used for calculation of sediment TUs was also used for water column TUs, except that water column parameters and LC50 concentrations were expressed as ng/L, and water column LC50’s were not normalized for TOC for the purposes of this study.
Statistical Analysis of Spatial and Temporal Patterns The incidence of “nondetects,” or samples with results below laboratory detection limits, was determined to be very high for concentration-based results in the CMP dataset, exceeding 90% for some parameter groupings. As with other California surface water monitoring programs, the high proportion of samples with nondetected results undermines confidence testing on the CMP data due to uncertainties around the actual values for these results (38). In light of this complicating factor, the “Nondetects And Data Analysis for environmental data” package (39) for R statistical software was used to account for nondetects. Complications from high proportions of nondetect samples affect only the concentration-based pesticide dataset and do not affect the corresponding toxicity tests as these do not result in nondetected values. A visual inspection of the data and comparison of arithmetic versus geometric mean values determined that the CMP data are approximately log–normally distributed. The regression on order statistics imputation method was used to calculate summary statistics for the entire dataset. The geometric mean and median were determined to be the most appropriate measures of central tendency for the skewed datasets. For pesticide monitoring results, statistical models relating concentrations for each pesticide of interest and study period were developed for each of two site groupings (i.e., sites within the Lower Salinas and Santa Maria valleys, and sites outside those areas). The maximum likelihood estimation imputation method was used to account for nondetected results. Model terms included each pesticide parameter of interest, space (i.e., site grouping as inside or outside of the Lower Salinas and Santa Maria valleys), and study period (as a categorical term). For toxicity monitoring results (i.e., bioassays), a multiple linear regression model was developed for each toxicity dataset. The response (percent survival) was modeled using space (i.e., site grouping as described above), time (with dates converted to a continuous time variable, or “fractional year”), and their interaction (i.e., Fractional Year:Site Grouping). 159
Prior CMP data analysis included seasonal Mann–Kendall analysis using R for all parameters in the larger CMP dataset, which includes one to four toxicity tests for each site during each year from 2005 through 2017. The method for this analysis was originally described in ref 20, and the most current results are described in ref 9. For the purpose of this chapter, however, the number of time points reflected by the relatively few study periods are more limited, due to the limited number of CMP sampling efforts for specific pesticides. For this reason, prior Mann–Kendall trend analysis is included in the discussion where applicable, but full results and p values are presented here only for the more limited temporal testing described above, which is constrained to the targeted study periods. Quality Assurance Water and sediment quality data collected for this study are compatible with state of California Surface Water Ambient Monitoring Program data quality objectives. The CMP also generally follows guidance provided by the USEPA regarding data verification and validation (40, 41). Quality assurance protocols are described in detail in the CMP QAPP (22). Briefly, field blank and duplicate samples were collected regularly to identify any contamination and to demonstrate the precision of sampling procedures. Laboratory control samples, method blanks, duplicates, and matrix spikes were also analyzed to identify contamination and to demonstrate precision and accuracy of analytical procedures. The number and frequency of quality control samples required for the CMP, as well as measurement quality objectives, are given in Tables A-8 through A-12 of the CMP QAPP. Additional details regarding quality control for toxicity bioassays are given in QAPP Appendix B (22). Both field and laboratory instruments were calibrated according to a regular schedule and user manuals where applicable. Data generated by analytical laboratories were flagged as necessary by laboratory personnel and validated by the CMP quality assurance officer.
Results In addition to the study periods discussed here, the CMP performs monthly water quality monitoring for routine physical and chemical parameters, as well as quarterly and annual testing for water and sediment toxicity, respectively. Monitoring results are public record and can be accessed via the California Environmental Data Exchange Network at http://www.ceden.org. Results are also summarized and discussed in annual reports (e.g., (9, 20)), which are available to the public via the CCRWQCB’s Irrigated Lands Regulatory Program website (www.waterboards.ca.gov/centralcoast/water_issues/programs/ ag_waivers/#wqmondata). The results discussed here reflect special studies performed by the CMP for the purpose of evaluating contributions of agricultural pesticides in current use to toxicity observed in routine CMP toxicity tests, and by extrapolation, effects on sensitive aquatic invertebrates in Central Coast water bodies. While it is outside the scope of this chapter to summarize the CMP’s entire history of toxicity monitoring, the general patterns and trends discussed are 160
reflective of the CMP dataset as a whole and have been documented in detail in the CMP’s annual monitoring reports (e.g., (9, 20)). This chapter presents the entirety of the CMP’s pesticide-specific monitoring efforts to date. Results of Water Column Studies Organophosphate Pesticides in Water Summary statistics for OP pesticides are given in Table 4. Of the 13 OPs analyzed, the following seven were detected at least once: chlorpyrifos, diazinon, dichlorvos, dimethoate, ethoprop, fenchlorphos, and malathion. Of these, only chlorpyrifos and diazinon were detected at concentrations likely to cause mortality to the toxicity test organism (C. dubia), though malathion was also detected frequently and in some cases near the LC50 value (Tables 3 and 4). Therefore, only results for these three parameters are presented. Though the scope of this chapter is limited to analysis of broader regional and annual patterns, prior analysis by the CMP has examined seasonal and subregional patterns. The following selected results from the CMP’s initial OP study report (42) are reiterated here, as they illustrate the widespread presence of OP pesticides in the early years of the Ag Order regulatory process. During the initial study period for the Lower Salinas and Santa Maria valleys (2006–2007), OP pesticides were detected at every site during at least one of four site visits. Sixteen of the sites had detections during all four sampling events; only three sites had detections limited to a single event. Seasonally, the OP detections in the 2006–2007 study were relatively evenly distributed among sampling events, which took place in February, March, August, and September (i.e., over the course of a year and spanning several different crop cycle components). On a subregional basis, detection patterns for specific OPs differed slightly between the Salinas and Santa Maria study areas. In the Santa Maria valley, diazinon detections were most frequent in winter events, with chlorpyrifos detections more evenly distributed across months and more numerous overall. Conversely, in the Lower Salinas valley, chlorpyrifos detections were more frequent in winter events, and diazinon detections more evenly distributed and more numerous overall. Malathion was more frequently detected around Santa Maria. Dimethoate detections were also of note, particularly in the Lower Salinas area. During the initial study for sites outside of the Lower Salinas and Santa Maria valleys, OP pesticides were detected less frequently, at fewer sites, and at lower concentrations relative to LC50’s (43). The results of subsequent monitoring efforts showed a reduction in detection rates over time for chlorpyrifos and diazinon individually, as well as for the total number of samples per event showing a detection of any (i.e., at least one) of the OPs analyzed (Table 4, Figure 2). This pattern of declining detection rates occurred both in the subset of sites located in the Lower Salinas and Santa Maria valleys, as well as in the subset of sites located outside these areas. In 2017, chlorpyrifos was not detected at any CMP site outside of the Lower Salinas and Santa Maria valleys, and diazinon was detected at only three sites (one in the Lower Salinas valley and two in the upper Pajaro valley). In addition to the declining pattern in detection frequencies, significant reductions in concentration (geometric 161
mean) were observed for both chlorpyrifos (p < 0.0001) and diazinon (p < 0.0001) within the Lower Salinas and Santa Maria valley areas, and for diazinon (p < 0.0001) for sites outside those areas (Figure 3). Reductions in chlorpyrifos for sites outside these areas were not statistically significant (p = 0.06), however, the incidence of nondetects for this group of data was extremely high, which leaves some question as to the power of the test.
Figure 2. Detection rates for key OP pesticides over three CMP study periods, for sites within and outside of the Lower Salinas and Santa Maria valleys. ns = not sampled.
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Table 4. Summary Statistics for CMP Pesticide and Toxicity in Water Monitoring Results 2006 – 2007 & 2009
2013-2014
2017
GeoMeana Concentration or Survival Rate Chlorpyrifos (ng/L)
3 (164, 1494)
1 (13, 112)
0.8 (8, 48)
Diazinon (ng/L)
12 (1934, 24465)
1 (512, 6650)
0.6 (165, 2170)
Malathion (ng/L)
6 (146, 1293)
5 (217, 2796)
6 (284, 1500)
Imidacloprid (ng/L)
--
--
12 (538, 3020)
Toxicity to C. dubia survival (% of control)
73%
88%
88%
Toxicity to C. dilutus survival (% of control)
--
--
77%
163
Detection Frequency Chlorpyrifos
73%
23%
7%
Diazinon
49%
17%
3%
Malathion
77%
17%
19%
Imidacloprid
--
--
42%
Toxicity to C. dubia survival
31%
11%
19%
Toxicity to C. dilutus survival
--
--
29%
0.21
0.05
Mean Toxic Units Chlorpyrifos
2.17
Continued on next page.
Table 4. (Continued). Summary Statistics for CMP Pesticide and Toxicity in Water Monitoring Results 2006 – 2007 & 2009
a
2013-2014
2017
Diazinon
1.67
0.33
0.16
Malathion
0.02
0.02
0.04
Imidacloprid
--
--
0.00
The geometric mean concentration (GeoMean) is given in ng/L for each parameter and study period, followed by the standard deviation (SD) and maximum (max) value in parentheses.
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Figure 3. Concentrations of key pesticides over three CMP study periods, measured at sites within and outside of the Lower Salinas and Santa Maria valleys. Bars representing study year results that are significantly different (p < 0.01) within each parameter grouping are marked with an asterisk. ns = not sampled.
165
Monitoring results for malathion followed a different pattern in most cases, with detections decreasing in frequency between the initial and 2013–2014 studies, but then increasing in 2017 for sites within the Lower Salinas and Santa Maria valleys (Figure 2). The detection rate for malathion at CMP sites outside of these areas decreased across all study periods, but the geometric mean concentration for malathion was significantly higher (p = 0.007) in 2017 than in the initial study (Figure 3). Sites within the Lower Salinas and Santa Maria valleys followed the same pattern in terms of concentration, but differences between years were not statistically significant. It is also of note that the more frequent malathion detections in 2017 were distributed over fewer sites (9 sites in 2017 versus 19 in 2013–2014). This may be due to the fact that the two 2017 sampling events were limited to the months of September and December, whereas previous studies included four events, including months in the first and second quarters of the year. Alternatively, this could indicate a reduced geographic extent for malathion loading to surface waters. Forthcoming results from the 2018 study should at least partially address this question. Also on a broad spatial basis and over the course of the three studies discussed herein, concentrations of chlorpyrifos, diazinon, and malathion were significantly higher in the subset of sites located in the Lower Salinas and Santa Maria valleys, than in the subset of sites located outside those areas (p < 0.01 for each compound; Figure 4).
Figure 4. Concentrations of key pesticides in water over three CMP study periods differ for sites within and outside of the Lower Salinas and Santa Maria valleys. Geometric mean concentrations were significantly lower for CMP sites outside of the Salinas and Santa Maria valleys for chlorpyrifos, diazinon, malathion (p < 0.0001 for each), and imidacloprid (p = 0.006). 166
Neonicotinoid Pesticides in Water In 2017, the neonicotinoid pesticide class was added to the analyte list for CMP pesticide and toxicity studies. Neonicotinoids are relatively persistent in soil and also break down slowly via hydrolysis; however, breakdown via photolysis is rapid at around 3 h (44). Summary results for neonicotinoid samples are given in Table 4. Neonicotinoids as a class were detected about twice as frequently in 2017 as the OP pesticides, and the neonicotinoid of greatest interest (imidacloprid) was detected more frequently than each of the OPs of greatest concern (chlorpyrifos, diazinon, and malathion; Figure 2). The neonicotinoid thiamethoxam was detected even more frequently than imidacloprid, which is not surprising given its order-ofmagnitude higher solubility. Thiamethoxam is less toxic to aquatic invertebrates than imidacloprid, however (Table 3). Imidacloprid concentrations in 2017 ranged from not detected (58% of samples, laboratory minimum detection limit = 2 ng/L) to a maximum of 3020 ng/L (Table 4). Detections on this order of magnitude occurred at only two sites, both located in the lower Santa Maria valley. These two sites are hydrologically connected via upstream/downstream location relative to one another within the Orcutt-Solomon stream network. Concentrations of imidacloprid were significantly higher than 2017 concentrations for chlorpyrifos and diazinon (p < 0.0001 for each), but significantly lower than for malathion (p = 0.008; Figure 3). Imidacloprid concentrations were significantly higher for sites within the Lower Salinas and Santa Maria valley areas than for the subset of CMP sites located outside those areas (p = 0.006; Figure 4). Water Column Toxicity Bioassays Concurrent with OP analysis in each study period, sample splits were also sent for toxicity testing (i.e., bioassays) with C. dubia in the water. The frequency with which toxicity was observed was higher in the subset of sites from the Lower Salinas and Santa Maria valleys across all study periods, as compared to the subset of CMP sites outside those areas (Figure 5). A reduction in the frequency of toxicity was observed between the initial study and the second study period (2013–2014), but this pattern reversed with slight increases in toxicity observed between the second and third (2017) study periods (Figure 5). Despite the small increase in frequency of toxicity observed between the 2013–2014 and 2017 study periods, there was an overall improvement in C. dubia survival rates over the course of the three studies (p < 0.01; Figure 6). There was also a significant difference in survival rates between the group of sites located within the Lower Salinas and Santa Maria valleys, and the group located outside those areas (p < 0.01), with the former group apparently driving the temporal trend (Figure 6). Beginning in 2017, the bioassay study was expanded to evaluate toxicity to C. dilutus, which is commonly used as a sensitive indicator species for neonicotinoid class insecticides. Toxicity to C. dilutus was observed in 37% of Lower Salinas and Santa Maria samples and in 20% of samples from sites outside those areas 167
(Figure 5). About half of the samples that were toxic to C. dilutus did not show concurrent toxicity to C. dubia based on the survival endpoint, however, several of these did show toxicity to the reproductive endpoint for C. dubia (26). In fact, there were more samples that showed toxicity to C. dubia reproduction without a concurrent survival effect on either species, than there were samples showing toxicity to C. dilutus (26). Also, all 2017 samples that were toxic to C. dubia (or high-salinity alternate species) survival were either toxic to C. dilutus (survival) as well, or did not have a corresponding C. dilutus test performed due to high specific conductance in the sample water.
Figure 5. Frequency of water toxicity observed in CMP samples from sites within and outside of the Lower Salinas and Santa Maria valleys during each study period. For the 2017 study period, results for both invertebrate test species are shown. Note: “%” units shown in this figure reflect frequency of significantly toxic results for each group of samples (and not the “% survival” endpoint for any toxicity test).
168
Figure 6. Results of statistical analysis for C. dubia survival rates in CMP samples from sites within and outside of the Lower Salinas and Santa Maria valleys.
169
Results of Sediment Studies Pyrethroid Pesticides and Chlorpyrifos in Sediment Sample collection for the measurement of 10 pyrethroid pesticides and chlorpyrifos in sediment was planned for all sites in each study year as described in Table 1, however, not all sites met criteria for access or sample collection, or both, during every event. During the initial study (May 2010) at least one of the measured pesticides was detected in 89% of samples (Table 5). Chlorpyrifos was detected in 46% of samples. At least one pyrethroid was detected in 67% of samples, and nine individual pyrethroid compounds were each detected in two or more samples. Allethrin was only detected once, at a low concentration (0.6 ng/g) below the laboratory reporting limit. Detection frequencies for compounds detected at least twice are depicted in Figure 7 for each of the three study periods.
Table 5. Summary Statistics for CMP Pesticide and Toxicity in Sediment Monitoring Results 2010 GeoMean
a
2013 - 2014
2017
Concentration (ng/g dw)
Chlorpyrifos
2.02 (14, 63)
0.45 (97, 646)
0.28 (0.70, 3.4)
Bifenthrin
1.13(31, 216)
0.85 (21, 127)
0.44 (62, 442)
Lambda-cyhalothrin
0.71 (6.8, 22)
0.21 (33,217)
0.20 (2.7, 16)
Cypermethrin
0.45(2.7, 15)
0.15 (1.2, 4.9)
0.12 (0.58, 4)
Fenpropathrin
0.17 (31, 195)
0.02 (0.57, 3.2)
0.04 (2.2, 13)
Esfenvalerate
0.14 (5.4, 21)
0.01 (0.19, 1.0)
0.01 (2.0, 15)
Cyfluthrin
0.09 (3.3, 16)
0.04 (3.3, 22)
0.02 (0.20, 1.1)
Permethrin
2.04 (55, 286)
0.65 (39, 247)
0.39 (1.4, 6.2)
Fenvalerate
0.08 (1.9, 8.2)
0.02 (0.28, 1.6)
0.02 (2.4, 17)
Fluvalinate
0.00 (3.7, 25)
0.00 (1.8, 9.7)
0.00 (0.1, 0.7)
Toxicity to H. azteca survival (% of control)b
63%
44%
66%
Detection Frequency Overall (i.e., any compound)
89%
66%
66%
Chlorpyrifos
46%
34%
31%
Bifenthrin
54%
56%
44%
Lambda-cyhalothrin
50%
27%
29%
Cypermethrin
46%
15%
9% Continued on next page.
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Table 5. (Continued). Summary Statistics for CMP Pesticide and Toxicity in Sediment Monitoring Results 2010
2013 - 2014
2017
Fenpropathrin
39%
5%
24%
Esfenvalerate
39%
7%
4%
Cyfluthrin
37%
15%
7%
Permethrin
37%
12%
7%
Fenvalerate
35%
10%
2%
Fluvalinate
9%
10%
4%
Toxicity to H. azteca survival (% of control)
57%
69%
49%
Mean Toxic Units Chlorpyrifos
0.51
0.75
0.13
Bifenthrin
2.25
0.56
0.94
Lambda-cyhalothrin
0.45
0.30
0.33
Cypermethrin
0.16
0.09
0.02
Fenpropathrin
NA
0.00
0.09
Esfenvalerate
0.07
0.00
0.01
Cyfluthrin
0.09
0.04
0.00
Permethrin
0.24
0.04
0.10
Fenvalerate
0.01
0.01
0.01
Fluvalinate
NA
0.01
0.00
a
The geometric mean (GeoMean) concentration is given in ng/g dw for each concentration parameter and study period, followed by the standard deviation (SD) and maximum (max) value in parentheses. b Summary data for toxicity to H. azteca survival are given as arithmetic mean survival rates (% of control). NA, Not assessed.
Detection frequencies for most compounds declined over the course of the three study periods (Figure 7), with the most frequently detected compounds (bifenthrin, lambda-cyhalothrin, cypermethrin, and chlorpyrifos) generally remaining as such across all three study periods despite declines in the detection rates for each. Though every compound showed an overall decline in detection rate between the initial (2010) and final (2017) study periods, detection rates for two of these (lambda-cyhalothrin andfenpropathrinfenpropathrin increased somewhat between the 2013–2014 and the 2017 study.
171
Temporal patterns in sediment concentrations of pyrethroids and chlorpyrifos were similar to patterns in detection frequencies, with a few important exceptions. Eight of the measured compounds exhibited significant decreases in concentration between the initial and final study periods (p > 0.01 for each compound; Figure 8). Bifenthrin did not show a significant decrease in concentration, and despite an apparent decline between 2010 and 2013–2014, the 2017 average rebounded to very near the 2010 level. There was a visually apparent decline in fluvalinate from 2010 to 2013–2014, and again in 2017; however, the sample count for nondetect results was very high for this compound (92%) and may have undermined the analysis as a high percentage of nondetected results both increases statistical uncertainty, and on a more basic level, simply leaves little room for further reductions in concentration.
Figure 7. Detection rates for pyrethroid pesticides and chlorpyrifos in CMP sediment samples over three study periods.
To address the possibility that the overall declining trends in sediment chlorpyrifos and pyrethroids were an artifact of changes in analytical laboratory recoveries, laboratory quality assurance reports were reviewed for each study year to rule out systematic over- or under-recovery in laboratory control samples (LCS). In particular, LCS results from 2010 were reviewed for over-recovery and results from 2013–2014 and 2017 were reviewed for under-recovery. Three split samples were also sent in early 2018 to an independent laboratory (AXYS Analytical of British Columbia, Canada) for comparison of results. Though it is impossible to affirmatively rule out an incident of over-recovery in 2010, the LCS results from that year do not support this idea, nor do the LCS or split sample analysis results from later years support the idea of under-recovery. 172
Figure 8. Geometric mean concentrations for pyrethroid pesticides and chlorpyrifos in CMP sediment samples over three study periods. The 2017 concentrations were significantly lower than initial study (2010) concentrations for every compound (p < 0.01) except bifenthrin and fluvalinate.
Spatial Patterns for Pesticides in Sediment On a broad spatial basis and over the course of the three CMP studies, concentrations of chlorpyrifos and all but one measured pyrethroid were significantly higher in the subset of sites located in the Lower Salinas and Santa Maria valleys than in the subset located outside those areas (p < 0.05 for each compound except fluvalinate). Prior exploratory analyses of these datasets by the CMP have also examined subregional patterns in sediment pesticide concentrations (17, 26, 45). In the initial study (2010), average pyrethroid concentrations were considerably higher in the Santa Maria area than in other subregions, though these averages are biased by the high concentrations above 195 ng/g for each of these three pesticides (bifenthrin, permethrin, and fenpropathrin) found at just one or two sites (45). The area with the second highest averages for pyrethroid concentrations in 2010 included tributaries to the lower Salinas River and Reclamation Canal with relatively high concentrations of permethrin, lambda-cyhalothrin, and bifenthrin. In the 2013–2014 study, sediment concentrations of some insecticides were again higher in the Santa Maria area than for other watersheds, however, several pyrethroids were detected at concentrations in South Coast water bodies that were much higher than levels typical of other regions in the 2013–2014 study, or of any region in the initial (2010) study (17). In 2017, detection rates were again highest in the Santa Maria and Lower Salinas watersheds, however, concentrations in the Salinas area were more noticeably elevated relative to other regions in the 2017 study and also relative to other regions in prior years (26). 173
Sediment Toxicity Bioassays Concurrent with sediment insecticide analysis in 2010 and again in subsequent studies (2013–2014 and 2017), sample splits were also sent for toxicity testing with H. azteca in sediment. In the initial study (2010), 57% of samples were toxic to H. azteca (Table 5, Figure 9). The highest frequency of toxicity was observed in the lower Santa Maria and Salinas valleys, where 100% and 75% of samples were toxic to H. azteca, respectively. In the 2013–2014 study, 60% of samples were toxic to H. azteca, with 100% of samples from both the Lower Salinas and Santa Maria valleys showing toxicity. In 2017, the frequency of toxicity in sediment was slightly reduced, with 49% of samples overall showing toxicity to H. azteca. The highest frequency of toxicity was again observed in the lower Santa Maria and Salinas valleys, however, the frequency of toxicity in each of these areas was reduced to roughly 2/3 (66%) of samples in 2017. There was no significant difference in H. azteca survival over the course of the three studies, however, on a spatial basis survival rates were significantly higher (and thus, toxicity lower) for the group of sites located outside the Lower Salinas and Santa Maria valleys (p < 0.01; Figure 10).
Figure 9. Frequency of toxicity to H. azteca in sediment observed in CMP samples from sites within and outside of the Lower Salinas and Santa Maria valleys during each study period. Note: “%” units shown in this figure reflect frequency of significantly toxic results for each group of samples (and not the “% survival” endpoint for any toxicity test).
174
Figure 10. Mean H. azteca survival in sediment observed in CMP samples from sites within and outside of the Lower Salinas and Santa Maria valleys during each study period. Note: “%” units shown in this figure reflect percent survival rates for test organisms relative to a control. Low percent survival rates indicate toxicity.
Discussion Relationship between Pesticides in Sediment and Toxicity A summary of TU calculations over time for each pesticide measured by the CMP in sediment is given in Table 5 and depicted in Figure 11. Results from the initial 2010 study illustrated a relatively clear relationship between H. azteca mortality in bioassays and concurrent measurement of chlorpyrifos and pyrethroids at or above 0.5 TU (Figure 12). This relationship has proven consistent over several years of repeated study. In the 2010 study, pesticide detections above 0.5 TU occurred in 48% of samples collected, and all of these showed significant mortality to H. azteca in concurrent toxicity tests (45). In the 2013–2014 study, 50% of samples had pesticide detections ≥0.5 TU, and all but three of these showed significant mortality to H. azteca in concurrent toxicity tests. One of these three samples showed significant toxic effects to H. azteca growth rates. Of the other two samples, neither showed growth effects, but neither had a very high TU summation (0.5 and 0.7, or less than one full TU each). In the 2017 study, 36% of samples collected from the same sites had pesticide detections that summed to ≥0.5 TU, and as in 2013–2014, all but three of these showed significant mortality to H. azteca in concurrent bioassays. In summary, the 0.5 TU threshold proposed by others (46) is supported by the CMP results, where the overwhelming majority of samples show toxicity to H. azteca when at least 0.5 TU of measured pesticides are present. 175
Figure 11. Mean summed H. azteca TUs at CMP sites during the three study periods.
The inverse of the relationship just described was also apparent, with the large majority of samples that showed toxicity to H. azteca also displaying ≥0.5 TU of concurrently measured pesticides. However, 4 to 28% of samples from each study year showed significant H. azteca mortality without at least 0.5 TU of corresponding pesticides (e.g., Figure 12). Due to many factors, including the generally recognized nonhomogeneity of sediment sample matrices (despite the implementation of sampling protocols to maximize homogenization), some degree of variability is to be expected in any biological study or environmental dataset. Relaxing the threshold for deeming measured TUs to be “explanatory” of observed toxicity to 0.25 TU yields that only 4 to 15% of samples showed toxic effects without sufficient concurrently measured pesticides to explain the toxicity. While it is possible that one or more additional unmeasured toxicants contribute to sediment toxicity in CMP bioassays, the relationship between sediment toxicity and the presence of pyrethroids and chlorpyrifos has been generally robust throughout the three CMP studies.
176
Figure 12. Relationship between H. azteca survival and summed TUs. Results displayed are for the 2010 study period, however, the relationship is illustrative of results from all three studies.
Relationship between Pesticides in Water and Toxicity for C. dubia A summary of TU calculations over time for each pesticide measured by the CMP in water is depicted in Figure 13. Results from the CMP’s initial (2006–2007) study of organophosphate pesticides in water and toxicity to aquatic invertebrates (C. dubia) illustrated a relatively clear relationship between C. dubia mortality in bioassays and concurrent detection of OP pesticides at or above toxic concentrations. In this initial study, OP detections occurred in 89% of samples collected, and detections amounting to at least 1 TU of chlorpyrifos, diazinon, or both comprised 40% of samples collected. Within the subset of samples that had ≥1 TU of measured OPs, 35 of 38 samples (92%) resulted in toxicity to C. dubia in concurrent bioassays, and mortality rates were 100% in all of these cases. Also, 53% of all samples collected for the 2006–2007 study showed toxicity to C. dubia (i.e., statistically significant, though not necessarily complete mortality), and 70% of these had 1 TU or more of concurrently measured OPs. 177
Figure 13. Mean C. dubia TUs for OP pesticides at CMP sites during the three study periods. Seven years later in the 2013–2014 study, this relationship was not nearly as strong. Though 21 samples collected for the study (13%) showed toxicity to C. dubia survival, only one of these contained OPs at concentrations summing to 0.5 TU or more. The rest of the toxic samples contained 1 TU of OPs showed toxicity (0% survival, in fact) in concurrent bioassays, as did all samples containing at least 0.5 TU. However, the majority of toxic samples did not contain sufficient concurrently measured OPs to explain the observed toxicity. Relationship between Pesticides in Water and Toxicity for C. dilutus Neonicotinoids were not monitored in the early years of the CMP; however, in 2017, detections occurred in 85% of samples from sites in the Lower Salinas and Santa Maria valleys, which is similar to the 89% detection rate for OPs at these sites in the initial (2006–2007) study, and about twice the rate of more recent OP detections (41% in 2017). Toxic units from neonicotinoids were generally low or absent, however, two samples collected from the Santa Maria area in 2017 showed 0.7 to 1.1 TU of imidacloprid (other neonicotinoid compounds did not contribute appreciably to any TU sums). Both samples had conductivity levels above the acceptable range for C. dilutus. Concurrent tests with an alternate species (A. bahia) showed toxicity for the sample with 0.7 TU imidacloprid, but no toxicity in the sample with 1.1 TU. This is not entirely surprising, as C. dilutus is the generally accepted most-sensitive test organism for neonicotinoids, so A. bahia would not 178
have the same expected sensitivity. The literature review of LC50’s conducted for this and other CMP studies failed to identify a relevant effect threshold for A. bahia with respect to imidacloprid, however, a 4-day LC50 for thiamethoxam indicates that general neonicotinoid sensitivities for this alternative species are two orders of magnitude higher than for C. dilutus. Also, while 17% of samples in the 2017 study showed toxicity to C. dilutus, only one of these samples had even 0.5 TU of concurrently measured neonicotinoid or OP pesticides. In summary, an important shift occurred between 2006 and 2017 in the frequency and concentrations of OP pesticides detected by the CMP, as well as in concurrent toxicity to C. dubia. Detection frequencies and concentrations for neonicotinoids in 2017 bear some similarities to the frequencies and concentrations with which OP pesticides were detected in 2006–2007, prior to the onset of major regulatory scrutiny. However, neonicotinoids are less toxic to all common bioassay test species on an acute basis, and not surprisingly the frequency of toxicity observed in CMP bioassays is less than in previous years, even when an additional test organism is used. A more risk-based approach to setting concern thresholds for imidacloprid may result in orders-of-magnitude-lower chronic benchmarks for regulatory purposes (47). However, these will not further explain the weak relationship between observed toxicity to C. dubia or C. dilutus and the relatively few concurrently detected OP or neonicotinoid TUs. Importantly, C. dilutus is considerably more sensitive to OPs (e.g., chlorpyrifos, LC50 = 290 ng/L) and pyrethroids (e.g., bifenthrin, LC50 = 690 ng/L) than it is to neonicotinoids (e.g., imidacloprid, LC50 = 2650 ng/L) on an acute basis. C. dilutus is also highly sensitive to the urban-use insecticide, fipronil (LC50 = 33 ng/L). In the CMP’s 2017 study, OPs were monitored in water concurrently with the neonicotinoid and C. dilutus toxicity tests, and organism-specific TUs were calculated for the detected OPs, however, the maximum OP TU calculated was 0.2, and this occurred in only one sample. That sample did show corresponding toxicity to C. dilutus survival. Pyrethroid pesticides and other major current-use classes such as carbamates were not monitored in water for this study. Therefore, the toxicity observed in CMP samples not explained by OP or neonicotinoid insecticides may be due to one or more additional toxicants that were unmeasured in the water column by the CMP. Pyrethroids are commonly found in bed sediments of CMP sites (Figure 7), and other studies have detected pyrethroids in the water column at a subset of CMP sites (18, 48). At least two additional studies have also found toxicity to H. azteca in the water column when toxicity to C. dubia was absent (48, 49), which is another potential indicator of pyrethroid presence as H. azteca is the most sensitive test organism for the pyrethroid pesticide class. A final possible unmeasured toxicant is the urban-use insecticide, fipronil. The CMP sites are all located in watersheds with substantial agricultural land use, however, several CMP sites are located downstream of urban areas and many more include at least some degree of rural–residential development upstream. The CMP dataset is most typically and appropriately used to assess water quality impairments of agricultural origin. However, due to the very low threshold for acute fipronil toxicity to C. dilutus and the ubiquitous nature of fipronil-based pest control products available to both homeowners and to farm operations for structural (i.e., 179
noncrop) applications, this should not be overlooked as a possible explanatory factor for C. dilutus toxicity that is not attributable to imidacloprid in certain watersheds. Spatial Patterns Concentrations of chlorpyrifos, diazinon, malathion, and imidacloprid differed significantly between the group of CMP sites located in the Lower Salinas and Santa Maria valleys, and the group of sites located outside these areas (Figure 4), despite many similarities in cropping patterns and an identical regulatory structure applied throughout the region (i.e., county agricultural commissioners and the CCRWQCB Ag Order). The same spatial pattern is true of pyrethroids in sediment, for eight of nine different compounds. Other factors such as hydrology, topography, and a host of other natural and anthropogenic features may play an important role in influencing instream pesticide concentrations. This is an important finding, as studies comparing various agricultural regions of California tend to treat the Lower Salinas and Santa Maria valleys as representative of Central Coast agricultural watersheds. While monitoring sites within these areas certainly highlight hot spots, the CMP results suggest that these valleys are not representative of all or even most Central Coast agricultural subregions, even when the population of monitoring sites is constrained in all subregions to water bodies with known impairments. Temporal Patterns The temporal trends for OPs in water in this study corroborate key findings of other important bodies of work conducted in the Central Coast region over a similar period of time (18, 19, 50, 51). Similar to CMP results presented here, California Department of Pesticide Regulation (CDPR) surface water monitoring shows reductions over time in detection frequencies for chlorpyrifos and diazinon, with no such trend for malathion. The CDPR work also evaluated agricultural pesticide use for the Central Coast over this same time period, and qualitatively shows a noticeable pattern of decreasing total pounds applied of chlorpyrifos and diazinon, with a weaker pattern of decreasing malathion use (19). While the CMP initiated monitoring for neonicotinoids such as imidacloprid in 2017, the CDPR work includes imidacloprid results from prior years and reflects sustained high detection frequencies for this material at monitoring sites that correspond to CMP sites in the lower Salinas and Santa Maria valleys (19, 50). Another important body of work evaluating pesticides in Central Coast water bodies over approximately the same time period reported that agricultural use (i.e., pounds applied) of imidacloprid was also sustained over this time period for at least one major Central Coast agricultural subregion (i.e., Monterey County) (18). There is a certain common sense to the idea that on a broad scale, the presence of key pesticides measured in the water column at least loosely tracks regional patterns in use of these materials, and for certain materials (i.e., chlorpyrifos and diazinon), these patterns also align with a period of increased regulatory 180
scrutiny. Pesticide use is an indicator of loading to the landscape, and a general principle of “reduced loading to the landscape leads to reduced presence in downstream waters” may indeed be operating in the region for some pesticides. However, a number of assumptions regarding the fate and transport of applied pesticides are implicit in this idea. Additional key variables such as solubility and persistence of the various pesticide classes may act to either augment or reduce the offsite movement of land-applied materials. Also, in the context of the Ag Order regulatory program, one hope is that increased awareness of water quality issues will result in management actions by growers, which in theory should act to reduce the off-site movement of pesticides into the region’s water bodies, independent of the gross pounds applied. Linking ambient water quality improvements to site-specific management changes by growers has proven to be a challenge for the region, however. Instream Flow and Loading In early 2018, the CMP reported significant reductions in streamflow at 62% of monitoring sites over the prior 14-year program history based on a seasonal Mann–Kendall trend analysis (9). This finding expanded on a 2010 CMP trend analysis, which found significant reductions in streamflow at 37% of sites (20). A load-based analysis of pesticide detections across the three study periods discussed in this chapter is beyond the current scope, but could readily be performed with the existing data. Conceptually, loads are the product of concentration (mass/volume) and streamflow (volume/time). Prior load calculations and trend analysis by the CMP have shown significant load reductions for both nitrogen (i.e., fertilizer) and sediment (i.e., eroded soil) at large percentages of CMP sites from 2005 through 2017 (9). Significant reductions in streamflow are a major factor in these load reductions and may have acted to reduce pesticide loading as well. Simple analysis based on existing datasets could confirm the presence of trends in pesticide loading. One important caveat to the above discussion is that the biological relevance of pesticide load reductions is really for downstream receiving waters since toxicity is a concentration-based phenomenon. Load reductions within small water bodies that continue to manifest high pesticide concentrations will not improve the habitat for aquatic life within those water bodies. Another important caveat is that while the declining trends in streamflow and consequent load reductions are dramatic and could, in certain water bodies, be the result of management actions by growers, other factors (e.g., climate) are certainly involved, and care should be taken not to infer a causal relationship where none exists. That said, the direct impact of precipitation and associated runoff on these flow reductions should be minimal because over 85% of all CMP site visits are conducted during nonrainfall events. Furthermore, rainfall on the Central Coast occurs primarily from October through April, and when trend analysis of CMP flow results is restricted to dry season months across all years (i.e., May through September), trend analysis results are strengthened in the direction of significant, declining streamflows (20). A drought of historic proportions, which took place from 2012 through 2015, certainly impacted Central Coast streamflows; however, 181
the fact that a substantial fraction of the observed trends in streamflow predate the drought (20) suggests this is not the only factor. It is also noteworthy that within this subset of sites that showed trends prior to the drought, a majority display the effluent-dominated hydrology described in the Introduction of this chapter, which makes both the volume and quality of instream water highly reflective of discharges from the surrounding landscape. Concurrent with the downward trends in streamflow in the CMP results, regional water management agency data shows striking improvements in irrigation efficiency by growers and a shift away from irrigation methods associated with surface runoff (i.e., furrow and sprinkler) toward newer methods (i.e., drip irrigation and microsprinklers) that tend not to produce runoff (52).
Conclusions More than a decade of CMP monitoring results indicate the continued presence of agricultural pesticides and associated toxicity to sensitive aquatic invertebrates, however, notable spatial and temporal patterns have emerged from the dataset, which should contribute to management and future study design for the CMP and other programs. The CMP study design includes a robust population of water bodies that are biased toward subregions of the Central Coast with both intensive agricultural land use and known water quality impairments. Significant differences in pesticide concentrations and aquatic toxicity shown here between different agricultural subregions of the Central Coast demonstrate the importance of study design to support inferences about the spatial scope and severity of agricultural water quality impacts that are reflective of the region as a whole. An analysis of variables contributing to subregional differences in water quality for Central Coast agricultural watersheds is beyond the scope of this chapter, however, it is worth noting that these differences exist in spite of an identical regulatory structure being applied to all subregions and many similarities in crop types and growing systems among them. As noted in the Introduction of this chapter, the Central Coast features a diversity of climatic, geologic, and hydrologic conditions. In particular, instream flow conditions, which vary by water body, lead to greater or lesser dilution of pollutant loads, which affects both pesticide concentrations and aquatic toxicity (which is concentration-dependent). The relationship between sediment toxicity and the presence of pyrethroids and chlorpyrifos in sediment has been robust throughout the three CMP studies. The 0.5 TU threshold proposed by others (46) is supported by the CMP results, where the overwhelming majority of samples show toxicity to H. azteca in sediment when at least 0.5 TU of measured pesticides are present. The relationship between water column toxicity and the presence of measured pesticides in water has weakened over the course of the three CMP studies. Results from the CMP’s initial (2006–2007) study of OP pesticides in water and toxicity to aquatic invertebrates illustrated a relatively clear relationship between C. dubia mortality in toxicity tests and concurrent detection of OP pesticides at or above the LC50’s for those compounds. However, in the most recent study (2017), the majority of toxic samples contained neither sufficient 182
concurrently measured OPs nor the neonicotinoid imidacloprid to explain the observed toxicity. The addition in 2017 of an additional invertebrate test species, C. dilutus, showed toxicity in several samples for which toxicity to C. dubia was not observed. However, deeper analysis of toxicity test results for C. dubia reproduction, as described in other CMP reports (26), suggests that C. dubia reproduction may be a more sensitive indicator of toxicity than the survival endpoint for either organism. Mean concentrations for several key pesticides in both sediment and water were significantly lower in the most recent study period (2017) than when measured in early years of the program (2006–2007). Results from this study did not show a corresponding significant improvement for H. azteca survival in sediment, however, C. dubia survival in water did increase significantly at the subset of sites within the lower Salinas and Santa Maria valleys. Additional toxicity indicated by C. dilutus testing in 2017, coupled with toxicity detected in other studies using H. azteca tests in water, suggests the presence of additional water column toxicants and toxicity that are not currently tested by the CMP. However, the CMP’s existing sediment monitoring program robustly addresses both pyrethroid pesticides and toxicity to H. azteca, albeit in stream-bottom habitats as opposed to the water column. An evolving regulatory process will continue to rely on the CMP and other surface water monitoring programs to inform management and policy. Results to date from the CMP demonstrate the program’s ability to detect spatial and temporal trends in key indicators of agricultural water quality impacts. The interpretation of pesticide monitoring and aquatic toxicity test results is highly nuanced, however, the study design to date has proven informative and will no doubt evolve to meet changing informational needs.
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