Spatio-Temporal Analyses of Pesticide Use on Walnuts and Potential

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Chapter 9

Spatio-Temporal Analyses of Pesticide Use on Walnuts and Potential Risks to Surface Water in California Huajin Chen,1 Yu Zhan,2 Michael L. Grieneisen,1 and Minghua Zhang1,* 1Department

of Land, Air and Water Resources, University of California, Davis, 1 Shields Avenue, California 95616, United States 2Department of Environmental Science and Engineering, Sichuan University, Chengdu, Sichuan 610000, China *E-mail address: [email protected]

Large-scale analyses of pesticide use and risk patterns are essential for the development of sustainable pest management strategies and regional ecosystem conservation plans. This study investigated the spatio-temporal patterns of pesticide use on walnuts and associated risks to surface water in California. Pesticide use data from 1996 to 2015 were obtained from the Pesticide Use Report (PUR) database, and pesticide risks to surface water were evaluated using the Pesticide Use Risk Evaluation (PURE) indicator. Results show that insecticides posed the highest risks to surface water. The spatial distributions of temperature and humidity partially contributed to the spatial patterns of insecticide and fungicide use. Spatial differences in drainage density, precipitation, and soil permeability determined the spatial patterns of pesticide risk. The significant decreases (p < 0.01) in risks associated with toxic chemicals over time suggested the effectiveness of regulations and awareness of farmers on limiting the use of high-risk pesticides such as chlorpyrifos and maneb. Increasing herbicide use could be attributed to a combination of herbicide resistance, the surge in walnut prices, and the increase in walnut acreage. Increasing use was observed in pyrethroids including bifenthrin as well as herbicide paraquat dichloride, possibly due to their roles as

© 2018 American Chemical Society

ang et al.; Managing and Analyzing Pesticide Use Data for Pest Management, Environmental Monitoring, Public Health, and Public Pol ACS Symposium Series; American Chemical Society: Washington, DC, 2018.

organophosphate and glyphosate alternatives. The results from this study demonstrate the potential of spatially distributed risk indicators in large-scale risk assessments, and provide valuable information for the development of efficient pest management and surface water protection plans in California.

Introduction California walnuts dominate the world’s market, accounting for 99 percent of the US supply and three-quarters of world walnut sales (1). Increasing demand has elevated walnuts to the fourth leading export from California, generating over $1 billion in annual revenue (2). The high economic value of walnuts has led to a surge in walnut-tree planting (Figure 1), with the planted area of walnuts in California doubling over two decades from about 74,000 hectare in 1996 to 152,000 hectare in 2015. As walnut production grows, large amounts of pesticides are being applied to minimize crop damage caused by pests. In 2015 alone, 3.1 million kilograms of pesticide active ingredients (AIs) were applied on walnut orchards in California for pest control (3). The most important walnut arthropod pests include codling moth, walnut husk fly, navel orangeworm and aphids (1), which can cause a loss of nut yield and quality. Weeds are also a major pest group especially when water availability is of concern (1). In addition, fungal diseases have the potential to destroy the walnut crop, and thus often are managed via preventative, periodic treatments (4). The current control of these pests often relies on applications of conventional, broad-spectrum pesticides, which result in unintended environmental impacts, including contamination of surface water (5, 6). In California, pesticide residues are often detected in surface water bodies at concentrations toxic to aquatic species (7, 8). Surface water contamination is most prominent in California’s agriculturally dominated Central Valley (9), where most of the walnut orchards reside (Figure 1). The growing concerns for pesticide pollution have led to consistent regulatory efforts to reduce or eliminate the use of agricultural pesticides that has risk of contaminating surface water at levels toxic to aquatic species. As required by the Federal Insecticide, Fungicide, and Rodenticide Act (FIFRA), the US Environmental Protection Agency (EPA) has been restricting and re-registering many pesticides by considering all available environmental toxicology data and adjusting allowable uses accordingly (10). USEPA also regulates pesticide use under the Federal Clean Water Act (CWA). Waters that fail to attain quality standards after the technology-based limits are listed in 303(d) list, and the state is required to develop total maximum daily loads (TMDLs) plans by establishing allocations of pollutant loads from all sources and implementation measures (11). In addition, the California Department of Pesticide Regulation (DPR), regulates pesticide use in California under more stringent criteria. Outreach programs, such as the University of California Integrated Pest Management (UC IPM) program, also help growers to reduce unintended environmental impacts by providing ecologically based, integrated pest management options. 172


Figure 1. Planted areas for California walnuts from 1996 to 2015: (a) spatial patterns of the median annual planted areas, and (b) temporal trends of the planted areas. (see color insert) In recent decades, risk indicators have become valuable tools for government agencies and researchers to use in assessing environmental impacts of agricultural pesticide use. Numerous pesticide risk indicators have been developed and they have become valuable alternatives to direct risk measurement, as they are cost-effective means to evaluate potential environmental hazards (12). The progress in Geographic Information System (GIS) further enhances our ability to 173


assess spatial patterns of pesticide risks (13, 14), which is essential in regionally coordinated water quality management. The selection of indicators is critical in risk assessments as each indicator is constrained by its own realms of use and validity (12). The Pesticide Use Risk Evaluation (PURE) is a deterministic pesticide risk indicator developed specifically for California agricultural lands (15). It calculates risk values based on pesticide toxicity and exposure levels under the worst-case scenarios. For example, the PURE indicator assumes that water input (sum of irrigation and rainfall amount) occurs three days after a pesticide application. During validation, the predictions of PURE were generally consistent with the surface water monitoring data in the Central Valley (r = 0.82, p < 0.001) (15). PURE also served as a good predictor for the net environmental impact of the multidimensional responses of growers to crop-disease forecasts (16). Large-scale analyses of pesticide use and risk patterns are essential for informing region-wide policies on pest management and environmental conservation. Characterizing such patterns, however, remains challenging due to the lack of pesticide use data and the complexities of environmental fate, including the diffusive nature of pesticide pollutant sources, the diversity of their chemical properties, as well as spatially variable environmental conditions (8, 14, 17, 18). The Pesticide Use Report (PUR) database is the world’s most comprehensive source of pesticide use data that records every application of pesticides on California agricultural lands (19). The PURE indicator is able to integrate complex, interacting processes in order to evaluate the risks of agricultural pesticide use in California. Empowered by the unique features of the PUR database and the PURE indicator, the goal of this study is to analyze the spatial patterns and temporal trends of pesticide use on California walnuts and potential risks to surface water. Walnut was chosen as a study case because of dramatic increase in walnut tree acreage, associated increasing demand for pest controls, and major shifts in walnut growers’ pest management practices over the last decades. Specifically, our objectives include: (1) identification of the spatial patterns of pesticide use and risks, (2) investigation of the temporal trends of pesticide use and risks, and (3) exploration of the variety of factors that contributed to these observed spatio-temporal patterns. The results not only provide recommendations to better inform pest management decisions and surface water protection planning in California, but also demonstrate the potential of a GIS-integrated risk indicator in large-scale risk assessments.

Materials and Methods Study Area and Temporal Scale The state of California was selected as the study area, focusing on the Central Valley where the majority of walnut production occurs (Figure 1). The Central Valley consists of three sub-regions from north to south: the Sacramento Valley, the San Joaquin Valley, and the Tulare Lake Basin. California has a Mediterranean climate with warm, dry summers and cool, wet winters. Across the Central Valley, 174


annual precipitation is highly variable spatially, ranging from more than 50 cm a year in the north to roughly 10 cm a year in the far south (20). To provide a thorough spatial investigation, pesticide use and risk patterns were analyzed at the township level (~9.7 × 9.7 km2), the basin level (i.e., the Sacramento Valley, the San Joaquin Valley, and the Tulare Lake Basin) and the state level (California). The three basins correspond to the three Central Valley sections of the California Regional Water Quality Control Boards (21). Spatial aggregation was performed using the area-weighted-mean approach, i.e., for a particular attribute, the average value of the entire patch mosaic equals the sum of patch value multiplied by the areal proportion of the patch:

where and xi stand for the attribute values of the entire patch mosaic and the ith patch, respectively, and Ai represents the area of the ith patch. The time period under investigation was from 1996 to 2015, which witnessed a prolonged boom in the walnut industry and changes in both grower pest management practices and government regulations (22). The temporal analysis was performed at the annual level. Input Data Pesticide use data were retrieved from the PUR database, which is maintained by the California DPR (19). The PUR database is a globally unique repository, which records agricultural pesticide use at a spatial resolution of ~1.6 × 1.6 km2 and temporal resolution of the specific date and time of each individual application. The database contains 32 data fields that capture key pesticide application attributes including chemical code of AI, amount of chemical used, crop type that received the application, the location identifier and the applicator identifier. All pesticide applications between 1996 and 2015 on California walnuts (> 1.4 million records) were retrieved from the PUR database which had been imported into an open source database, PostgreSQL (23), for data query and analysis. Because pesticide application rates vary considerably by AI, both pesticide use intensity (UI) and treated area intensity (TAI) were used to quantify the intensity of pesticide application:

Data on walnut planted area were also collected from the PUR database (19). TAI may be greater than 100% of planted area if more than one application covering the entire planted area are made per year. Data on pesticides’ physico-chemical and toxcicological properties were collected from several sources. The product-level properties, including the emission potential and percentage of AI, were retrieved from the DPR’s pesticide product/label database (24). The ChemPest database (25), the Pesticide Properties 175


Database (PPDB) (26), and the Pesticide Action Network (PAN) (27) were queried for AI-level chemical, physical, and toxicity properties, including the sorption coefficient (KOC), Henry’s law constant (KH), the aerobic (DTSO) and anaerobic (DTSA) half-lives in the soil, the half-life in water (DTW), and the minimum acute (LECA) and chronic (NOECA) concentrations toxic to representative aquatic organisms (i.e., fish, algae and Daphnia). In some cases, the data sources only provided “persistent” as half-lives for some pesticides (i.e., no numerical half-life values were available). In the calculations, the half-lives of persistent pesticides were replaced with 3650 days (10 years), which was the smallest integer year longer than the maximum of the reported numerical half-lives. Environmental parameters were extracted from public databases maintained by various government agencies. Meteorological data including precipitation, temperature and reference evapotranspiration (ET) were retrieved from the California Irrigation Management Information System (CIMIS) (28). Reference ET was then used to calculate irrigation amount by the Basic Irrigation Scheduling program (29). The Geospatial Data Gateway (30) was queried for the Digital Elevation Model (DEM) dataset. Soil attributes such as bulk density, sand, silt and clay content, organic matter content, and hydrological group were extracted from the Soil Survey Geographic database (SSURGO) and the State Soil Geographic database (STATSGO) (30). Land use and crop type information was extracted from the PUR database at the section level (~1.6 × 1.6 km2). The nearest distance from the section centroid of a pesticide application to the polylines of the stream network (31) was calculated by using the ArcMap software. Pesticide Risk Assessments The PURE indicator (15) evaluates potential risks of pesticide application to surface water bodies based on two factors: (1) pesticide toxicity to aquatic organisms (LECA and NOECA), and (2) the duration and magnitude of exposure. The latter is determined by UI, pesticide properties such as persistence and partitioning in the environment, and on-site environmental conditions, such as proximity to surface water bodies, monthly maximum daily water input (sum of rainfall and estimated irrigation amount), temperature, ground slope, soil field capacity which is calculated using soil texture (32), soil hydrological group, and land use type. The risk value (RVW, Eq. 4) equals the maximum of the short-term (RVWS) and long-term risks (RVWL), calculated as the ratio of the predicted short-term or long-term environmental concentration (PECWS or PECWL) to the minimum acute or chronic concentration (LECA or NOECA) that is toxic to aquatic organisms, respectively (Eq. 5 and 6). PECWS is determined by the quantity of AI that reaches surface water through drift and water runoff. PECWL is determined as the average concentration in surface water after an exposure interval since the pesticide application. Similar to pesticide use, pesticide risks to surface water were characterized by risk intensity (RI, Eq. 7).

176


Pesticide use records were summarized at three levels: (1) major pesticide use types of surface water pollution concerns (insecticide, fungicide, and herbicide); (2) chemical groups (e.g. organophosphate and pyrethroid); and (3) individual AIs (e.g. chlorpyrifos and copper hydroxide). Data for the three use types, the two chemical groups, and the five AIs with the highest statewide median annual RI were extracted for subsequent analysis.

Statistical Analysis and Mapping Kendall-Theil robust line was applied to detect the existence and magnitude of monotonic dependence of UI, TAI and RI on time. This nonparametric rank-based method does not rely on the normality of residuals for validity of significance tests and is not sensitive to outliers. It is therefore particularly useful in analyzing environmental time-series data (33). Temporal trends were considered as significant at the 0.1 level. Spatial mapping and trend analysis were performed in R, a free programming environment for statistical computing and graphics (34). Spatial mapping was performed at the township level using the software packages sp (35) and rgdal (36), and trend analyses were implemented in the packages Kendall (37) and zyp (38).

Results Summary Statistics of Statewide Pesticide Use and Risks Table 1 shows the summary statistics of the median annual UI, TAI and RI of pesticides by use types. Fungicides were applied at the highest UI (7.2 kg/ha), followed by insecticides (4.5 kg/ha) and herbicides (2.0 kg/ha). Organophosphates and pyrethroids were the two chemical groups with the highest RI (Table 2). Organophosphate UI was 1.8 kg/ha, contributing about 40% of the overall insecticide use. Pyrethroids were applied at much lower intensity (0.04 kg/ha). The five AIs with the highest RI were bifenthrin, chlorpyrifos, copper hydroxide, maneb, and paraquat dichloride. Table 3 shows the physical and chemical properties of these high-risk AIs. Chlorpyrifos was applied at 0.85 kg/ha, accounting for 48% of the organophosphate use and 19% of the overall insecticide use (Tables 1, 2 and 4). The UI of copper hydroxide and maneb were 3.9 and 1.0 kg/ha, contributing 54% and 14% of the total fungicide use, respectively. 177


Table 1. Temporal trends of annual pesticide use and associated surface water risks by pesticide use types for California walnuts (1996-2015)a Use Type

State Mdn

UI: kg/ha

TAI: % ha/ha

178

RI: R/ha

Sacramento Slope

Mdn

Slope

San Joaquin Mdn

Slope

Tulare Lake Mdn

Slope

Fungicide

7.2

0.01

9.6

-0.18·

6.5

0.12·

3.1

0.08

Herbicide

2.0

0.07**

1.9

0.08**

2.0

0.05**

2.5

0.06**

Insecticide

4.5

0.12*

3.4

0.09*

5.2

0.17**

5.7

0.14**

Fungicide

173

0.97

255

-1.52

129

3.1·

41

-0.33

Herbicide

215

2.75**

194

3**

244

2.69*

234

1.96·

Insecticide

201

4.03*

163

3.07·

246

6.39*

242

4.4**

Fungicide

119

-8.59**

132

-11.71**

103

-6.8**

36

-4.52**

Herbicide

26

-0.84·

19

0.34·

30

-1.04

50

-4.36**

Insecticide

229

4.3*

192

9.75**

277

5.09·

229

-8.83*

a

UI: use intensity. TAI: treated area intensity. RI: risk intensity. Mdn: median. Slope: the Theil-Sen slope. Significance of the Mann-Kendall trend test: **p < 0.01, *0.01 ≤ p < 0.05, ·0.05 ≤ p < 0.1.

Zhang et al.; Managing and Analyzing Pesticide Use Data for Pest Management, Environmental Monitoring, Public Health, and Public Policy ACS Symposium Series; American Chemical Society: Washington, DC, 2018.

Table 2. Temporal trends of annual pesticide use and associated surface water risks of the top-two pesticide chemical groups with the highest statewide median annual RI used on California walnuts (1996-2015)a Chem

State Mdn

UI: kg/ha

TAI: % ha/ha

RI: R/ha

Sacramento Slope

Mdn

Slope

San Joaquin Mdn

Tulare Lake

Slope

Mdn

Slope

OP

1.78

-0.1**

1.62

-0.07**

1.99

-0.13**

1.82

-0.14**

PY

0.04

0.002*

0.06

0.002

0.03

0.002*

0.0008

0.0005**

OP

87

-3.64**

74

-2.08**

99

-5.28**

85

-5.12**

PY

34

1.82**

41

1.48*

47

2.55*

0.86

0.54**

OP

162

-6.63**

146

-3.65**

176

-8.96**

196

-11.65**

PY

30

9.64**

20

10.04**

40

11.98**

0.004

0.005**

179

a UI: use intensity. TAI: treated area intensity. RI: risk intensity. Chem: chemical group. Mdn: median. Slope: the Theil-Sen slope. Significance of the Mann-Kendall trend test: **p < 0.01, *0.01 ≤ p < 0.05. OP: organophosphate insecticides. PY: pyrethroid insecticides.


Table 3. Physical and chemcial properties of the top-five AIs with the highest statewide median annual RI used on California walnuts (1996-2015) AI

Use Type

Chem

KOC (ml/g)

KH (Pa·m3/mol)

DTSO (day)

DTSA (day)

DTw (day)

LECA (mg/l)

NOECA (mg/l)

BF

INS

PY

2.6E+05

730

114

180

115

0.0001

1.3E-06

CL

INS

OP

9400

0.67

79

136

72

0.0001

5.0E-05

CH

FUN

CP

12000

2.0E-07

2600

2600

Pa

0.009

0.0005

MB

FUN

DC

870

2.1E-05

7

7

P

0.002

0.001

PD

HEB

BP

1.0E+06

4.0E-12

1720

644

30

0.0002

5.8E-05

a

180

P represents persistent. The half-life of persistent pesticide was replaced with 3650 days in calculation. Chem: chemical group. BF: bifenthrin. CL: chlorpyrifos. CH: copper hydroxide. MB: maneb. PD: paraquat dichloride. INS: insecticide. FUN: fungicide. HEB: herbicide. PY: pyrethroid. OP: organophosphate. CP: copper. DC: dithiocarbamate. BP: bipyridylium.


Table 4. Temporal trends of annual pesticide use and associated surface water risks of the top-five pesticide AIs with the highest statewide median annual RI used on California walnuts (1996-2015) AI

State Mdn

UI: kg/ha

TAI: %ha/ha

181 RI: R/ha

Sacramento Slope

Mdn

San Joaquin

Slope

Mdn

Tulare Lake

Slope

Mdn

Slope

BF

0.002

0.002**

0.001

0.002**

0.004

0.002**

0

0.0002**

CL

0.85

-0.02**

0.82

-0.01·

0.92

-0.03**

0.66

-0.03**

CH

3.88

-0.21**

4.62

-0.36**

3.79

-0.09·

1.10

-0.14**

MB

0.99

-0.09**

1.74

-0.16**

0.57

-0.04**

0.03

0

PD

0.13

0.005**

0.09

0.01**

0.18

0.01**

0.16

-0.003

BF

2

1.32**

1

1.36**

3

1.86**

0

0.18**

CL

42

-1.02**

40

-0.66*

45

-1.46**

31

-1.25**

CH

86

-1.18

115

-2.98*

70

0.27

22

-1.49**

MB

52

-4.46**

91

-8.05**

31

-2.25**

1

0

PD

18

0.14

9

0.56**

26

-0.29.

21

-0.67**

BF

25

9.97**

13

10.13**

30

12.67**

0

0**

CL

146

-4.57**

129

-1.05

160

-7.27**

182

-9.4*

CH

110

-7.94**

121

-9.67**

100

-6.61**

35

-4.55**

MB

11

-0.81**

20

-1.73**

4

-0.34**

0

0

PD

19

-0.13

12

0.71**

25

-0.73

15

-1.22

UI: use intensity. TAI: treated area intensity. RI: risk intensity. Mdn: median. Slope: the Theil-Sen slope. Significance of the Mann-Kendall trend test: **p < 0.01, *0.01 ≤ p < 0.05, ·0.05 ≤ p < 0.1. BF: bifenthrin. CL: chlorpyrifos. CH: copper hydroxide. MB: maneb. PD: paraquat dichloride.


When measured by TAI, herbicides had the highest value (TAI = 215%) among the three use types, followed by insecticides (TAI = 201%) and fungicides (TAI = 173%; Table 1). At the chemical group level, the cumulative hectares treated by organophosphates and pyrethroids were about 87% and 34% of the area planted, respectively (Table 2). At the AI level, the TAI for copper hydroxide and maneb were 86% and 52%, respectively, followed by chlorpyrifos (TAI = 42%) and paraquat dichloride (TAI = 18%; Table 4). Rankings of RI did not necessarily follow those of UI (Tables 1, 2 and 4). Although ranked second in UI, insecticides had the highest RI (229) among the three use types, followed by fungicides (RI = 119) and herbicides (RI = 26). Organophosphates was the leading chemical group in terms of surface water risks (RI = 162), followed by pyrethroids (RI = 30). At the AI level, chlorpyrifos was the major contributor to surface water risks (RI = 146), followed by copper hydroxide (RI = 110). Spatial Patterns of Pesticide Use and Risks At the regional level, the median annual UI and TAI of both insecticides and herbicides increased from north to south, while the UI and TAI of fungicides decreased from north to south (Table 1). Similar latitudinal patterns were observed at the township level (Figures 2 and 3). At the chemical group level, organophosphate use was higher in the San Joaquin Valley and the Tulare Lake basins, as measured by both UI and TAI (Table 2). In contrast, pyrethroids were applied with higher UI and TAI in the Sacramento and San Joaquin Valley basins. At the AI level, the Sacramento Valley used copper hydroxide and maneb most intensively, while the San Joaquin Valley had the highest use of bifenthrin, chlorpyrifos and paraquat dichloride (Table 4). For surface water risks, we found that the spatial patterns of RI for fungicides and herbicides were similar to those observed in UI and TAI (Table 1). For insecticides, the highest RI was observed in the San Joaquin Valley. The township-level maps show that RI was higher in the northern and middle regions, and this pattern holds true for insecticides, fungicides and herbicides (Figure 4). At the chemical group and AI levels, regional RI patterns generally followed the patterns of corresponding UI and TAI (Tables 2 and 4). Temporal Trends of Statewide Pesticide Use and Risks The statewide UI and TAI of insecticides and herbicides increased significantly from 1996 to 2015 (p < 0.05; Table 1). In contrast, no significant trends were detected for fungicides’ UI and TAI. A closer inspection of the time series plots indicated that insecticide UI doubled from 2002 (3.1 kg/ha) to 2008 (6.5 kg/ha; Figure 5). After 2008, the UI of insecticides decreased dramatically through 2011, before increasing to 5.5 kg/ha in 2015. Similar trends were observed in insecticide TAI, which doubled from 150% in 2002 to 300% in 2015. Herbicide UI steadily increased by 87% from 1996 (1.5 kg/ha) to 2015 (2.8 kg/ha). Herbicide TAI also increased from 187% to 246% over the study period. 182


Figure 2. Spatial patterns of the median annual use intensity (UI; kg/ha) of (a) insecticides, (b) fungicides, and (c) herbicides applied on California walnuts from 1996 to 2015. (see color insert)

183


Figure 3. Spatial patterns of the median annual treated area intensity (TAI; %ha/ha) of (a) insecticides, (b) fungicides, and (c) herbicides applied on California walnuts from 1996 to 2015. (see color insert)

184


Figure 4. Spatial patterns of the median annual risk intensity (RI; R/ha) of (a) insecticides, (b) fungicides, and (c) herbicides applied on California walnuts from 1996 to 2015. (see color insert)

185


Figure 5. Time series plots of use intensity (UI; kg/ha), treated area intensity (TAI; %ha/ha) and surface water risk intensity (RI; R/ha) of pesticide use on California walnuts from 1996 to 2015 by pesticide use types.

186


Organophosphate UI and TAI significantly decreased while pyrethroid UI and TAI significantly increased (p < 0.05; Table 2). The time series plots indicate that organophosphate UI and TAI decreased dramatically by 78% and 65% over the study period, respectively (Figure 6). In contrast, pyrethroid UI and TAI have more than tripled since 2002. All of the top five AIs showed significant UI trends (p < 0.01; Table 4). The UI of chlorpyrifos, copper hydroxide, and maneb significantly decreased, while the UI of bifenthrin and paraquat dichloride significantly increased. Similar patterns were observed for TAI, except for the TAI of copper hydroxide and paraquat dichloride, which showed no significant trends at the state level. According to the time series plots, the UI of chlorpyrifos dropped dramatically from 1.0 to 0.3 kg/ha over the study period (Figure 7). Similarly, the TAI of chlorpyrifos decreased from 50% in 1996 to 17% in 2015. The UI of copper hydroxide decreased from about 7.3 kg/ha in the late 1990s to 3.0 kg/ha in 2015. The use of maneb on California walnuts was discontinued in 2010. The use of bifenthrin on California walnuts, on the contrary, began in 2005 and increased annually thereafter. Recent increases were observed in the UI and TAI trends of paraquat dichloride, which increased from 0.1 kg/ha and 12% in 2010 to 0.3 kg/ha and 24% in 2015, respectively.

Figure 6. Time series plots of use intensity (UI; kg/ha), treated area intensity (TAI; %ha/ha) and surface water risk intensity (RI; R/ha) of pesticide use on California walnuts from 1996 to 2015 by pesticide chemical groups. 187


188


Figure 7. Time series plots of use intensity (UI; kg/ha), treated area intensity (TAI; %ha/ha) and surface water risk intensity (RI; R/ha) of pesticide use on California walnuts from 1996 to 2015 by pesticide AIs. The statewide RI of insecticides showed significant trends similar to those observed in the corresponding use (Figure 5 and Table 1). The RI of fungicides significantly decreased (p < 0.01) despite the fact that fungicide UI and TAI showed no significant trends. The RI of herbicides, on the other hand, showed the opposite trends as those observed in the UI and TAI. Temporal trends of RI were consistent with the corresponding UI and TAI trends at the chemical group and AI levels (Figures 6 and 7, and Tables 2 and 4). Three out of the top five AIs showed significant decreasing trends in RI (Figure 7 and Table 4). Spatial Patterns of Pesticide Use and Risk Trends In general, the regional UI and TAI trends were consistent with the statewide trends (Tables 1, 2 and 4). Exceptions to this include copper hydroxide and paraquat dichloride. The TAI of copper hydroxide significantly decreased in the Sacramento Valley and the Tulare Lake Basin while showing no trends at the state level (Table 4). The TAI of paraquat dichloride significantly increased in the Sacramento Valley while decreased in the San Joaquin Valley and the Tulare Lake 189


Basin. At the township level, increases in insecticide UI were clustered in the middle region while scattered across the north and south (Figure 8a). Increases and decreases of fungicide UI and TAI were scattered over various parts of the Central Valley (Figures 8b and 9b). In contrast, insecticide TAI and herbicide UI and TAI increased throughout the Central Valley, especially in the northern and middle regions.

Figure 8. Temporal trends of the annual use intensities (UI; kg/ha) of (a) insecticides, (b) fungicides, and (c) herbicides applied on California walnuts from 1996 to 2015. (see color insert) 190


Figure 9. Temporal trends of the annual treated area intensities (TAI; %ha/ha) of (a) insecticides, (b) fungicides, and (c) herbicides applied on California walnuts from 1996 to 2015. (see color insert) The regional RI trends were consistent with the statewide RI trends, except for the decreased trends of insecticide RI in the Tulare Lake Basin and the increased trends of paraquat dichloride RI in the Sacramento Valley (Tables 1, 2 and 4). At the township level, the spatial patterns of RI trends were similar to those observed in the UI trends but with more areas showing decreasing trends and fewer areas showing increasing trends (Figure 10). 191


Figure 10. Temporal trends of the annual risk intensity (RI; R/ha) of (a) insecticides, (b) fungicides, and (c) herbicides applied on California walnuts from 1996 to 2015. (see color insert)

Discussion Summary Statistics of Statewide Pesticide Use and Risks Pesticide use and risk values vary considerably by use type, chemical group, and AI, and these variations are most likely attributed to the different demands, 192


potencies, costs, and availabilities of these chemicals. Fungicides are often applied repeatedly to prevent severe damage from fungal diseases (4). Therefore, the use of fungicides was more intense than that of insecticides (Table 1), which are typically applied more sporadically to control pest outbreaks. Pyrethroids were applied at a much lower intensity than organophosphates (Table 2: 0.04 vs. 1.8 kg/ha), as they typically have higher toxic potency and are used at lower rates per hectare (39). Among AIs, copper hydroxide was the dominant fungicide from 1996 to 2015 (Table 4). It has been used in agriculture since the late 1800s and is relatively inexpensive (40). Chlorpyrifos was traditionally used as a cost-effective tool to control important walnut arthropod pests including codling moth, walnut husk fly, navel orangeworm and aphids (41). However, the heavy restrictions on chlorpyrifos use (42) have led to the gradual replacement of this chemical by reduced-risk alternatives. As a result, chlorpyrifos accounted for a relatively low percentage of insecticide use in the last two decades. The high RI of insecticides was mainly the combined result of the high UI and toxicity of insecticidal compounds (Tables 1 and 3). For herbicides, their moderate toxicity to aquatic species and relatively high leaching potential resulted in more modest surface water risks. Organophosphates and pyrethroids were the major contributors to the high risks of insecticide use (Table 2). These two chemical groups vary in their mobility and persistence in the environment. There are two important pathways for pesticide exposure in aquatic systems: binding to soil particles, moving with sediment-laden runoff and persisting in aquatic sediments (such as pyrethroids), and (2) having high runoff potential and persisting in the water column (such as maneb). Organophosphates are more water-soluble with aqueous half-life on the order of days to weeks, while pyrethroids are strongly adsorbed to soil particles and might persist in aquatic sediments on the order of 8 to 17 months (8). PURE is likely to underestimate the risks posed by strongly adsorbed pesticides, such as pyrethroids which are transported via suspended particles during runoff events, as the indicator only accounts for pesticide transport to surface water through drift and runoff water. At the AI level, all of the high-risk chemicals are moderately to highly toxic to aquatic organisms and persist in the soil and aquatic environment (Table 3 and 4). It should be noted that maneb was predicted as a high-risk AI despite its relatively short soil half-life. This could be attributed to the worst-case scenario configuration of PURE, where water input (sum of irrigation and rainfall amount) occurs three days after a pesticide application. Such conservative assumptions are typically adopted in most deterministic risk analyses to present the maximum of the expected risk range. Spatial Patterns of Pesticide Use and Risks For a particular crop, the spatial patterns of pesticide use is largely a function of the site-specific pest pressure and climatic conditions (1). The spatial UI and TAI patterns of insecticides and fungicides are mainly driven by spatial patterns in pest pressure under various climatic conditions (Figures 2 and 3). Insect pests are more likely to survive and achieve higher reproduction rates in warmer temperatures whereas fungi prefer cool and moist environments. As a result, insecticide UI and 193


TAI and temperature increased from north to south, while fungicide UI and TAI and humidity decreased from north to south. Higher temperatures and water supply via irrigation are also expected to favor the growth of weeds in the south, necessitating higher herbicide use. The combined effects of spatial differences in drainage density (i.e., the ratio of total channel length in a watershed to watershed area), precipitation, and soil permeability partially explained the higher surface water risks in the Sacramento Valley and the San Joaquin Valley (Figure 4). Proximity to surface water is a key factor that determines the length of the transport pathway and days of degradation before pesticide drift and runoff reach the waterways. The expansive river systems formed by the Sacramento River and the San Joaquin River dramatically increased the risk of exposure in the Sacramento Valley and the San Joaquin Valley, respectively. Precipitation is another important factor that affects the level of pesticide runoff. The amount, intensity and frequency of rainfall are essential in producing runoff, releasing dislodgeable pesticide residues, and transporting them to nearby surface water. Therefore, the more abundant rainfall in the north (20) is likely to contribute to higher surface water risk levels. In addition, runoff potential is significantly associated with soil permeability (43). Part of the western San Joaquin Valley is characterized by dense clay layers that prevent infiltration of rainfall and irrigation water (44), thus increasing the surface water risks from pesticide applications in those areas. A previous sensitivity analysis of PURE indicated that input water amount and soil permeability were the two most sensitive factors in determining surface water risks (45), which is consistent with prior knowledge on the transport of nonpoint source pollutants to surface water (43, 46). Temporal Trends of Pesticide Use and Risks, and Associated Spatial Patterns The yearly fluctuations and trends in pesticide use are partially driven by changes in regulations and outreach programs (14, 47). As required by FIFRA, USEPA has been restricting the use of pesticides that pose high risks to aquatic organisms including chlorpyrifos, bifenthrin, and paraquat dichloride, as well as re-registering AIs such as maneb (48). The TMDLs plan also regulates pesticides such as chlorpyrifos that contributed to the 303(d) listing of surface water bodies in the Central Valley region (49). In addition, government agencies, research institutes and other organizations have been encouraging alternative methods to reduce pesticide risk during dormant-season storm events (47). Increasingly stringent regulation is partially responsible for the significant decrease in the statewide and regional use of chlorpyrifos and maneb (Figure 7 and Table 4). The UI of chlorpyrifos is expected to further decrease in the near future as it has been recently labeled as a restricted material for use in agricultural production in California (50, 51) and added to California’s Proposition 65 list for causing developmental toxicity (52). The continuing evolution of resistance to pesticides also influences pesticide use patterns. The decreases in copper hydroxide UI and TAI (Figure 7 and Table 4) might result from the resistance of some bacterial strains to copper that has been observed in many Sacramento Valley orchards and a few San Joaquin Valley 194


orchards (53). The significant increase in herbicide use (Figures 5, 8 and 9, and Table 1) is likely associated with herbicide resistance that has been confirmed in California (1, 53, 54). Another important factor could be the dramatic increase in walnut prices. Since 1990, walnut prices have tripled to over $3,000 per ton. As herbicide is usually the first use type that is affected by drops in crop prices (B. Hanson, personal communication, Aug 2017), the surge in walnut prices in the recent decades is likely to lead to increased herbicide use on walnut orchards. In addition, this increase might be related to the tremendous increase in walnut-tree planting, as weed pressure is generally greater in young orchards because of higher sunlight penetration through the canopy (J. Grant, personal communication, Aug 2017). In some cases, the trends of chemical groups and AIs of the same use type are inter-related. For instance, the significant increases in the UI and TAI of pyrethroids were likely due to the heavy restrictions on organophosphates (55). Pyrethroids were initially proposed as an alternative to organophosphates until their high usage led to sediment contamination issues (56). Another example could be the use trends of glyphosate and paraquat dichloride. Glyphosate is the world’s most widely used herbicide (57). The growing popularity of glyphosate over the last 40 years can be attributed to its effectiveness and low risk, although it was recently listed as a carcinogen under California’s Proposition 65 effective Jul 7, 2017 (58). The increasing reliance on glyphosate in orchard operation might have accelerated the evolution and spread of glyphosate resistance (59). Paraquat dichloride is currently recommended as an alternative to glyphosate (1), which might have driven its increasing use (Figure 7 and Table 4). The sharp increases in the UI and TAI of paraquat dichloride after 2010 might also be related to the short supply of glufosinate in the west as an alternative to glyphosate (1). The statewide RI trends of insecticides were primarily dominated by the corresponding use trends, given the relatively high persistence and toxicity of this use type (Figure 5 and Table 1). The decrease in herbicide RI despite the increasing UI and TAI was mainly caused by the regulatory phase-out of herbicides that have high runoff potential as well as the promotion of post-emergent herbicide use outside the rainy season. The significant increase in the RI of pyrethroids partially contributed to the increasing risks of overall insecticide use (Figure 6 and Table 2). The significant decrease in the RI of high-risk AIs demonstrated the effectiveness of regulatory efforts in phasing out these compounds in agricultural production (Figure 7 and Table 4). It is also likely that growers have voluntarily adopted lower risk pest controls, as encouraged by various outreach and extension programs. The spatial patterns of RI trends were similar to those observed in UI but with fewer areas with increasing trends (Figures 8-10). This was likely the result of a general shift from high-risk pesticides to lower risk products for pest control. Limitations and Recommendations Pesticide use and risk are highly variable spatially and temporally, and are affected by multiple factors. The limitations of our study could be divided into three categories: (1) input uncertainty, (2) uncertainty in the PURE algorithm, and 195


(3) the knowledge gap about the toxicity of pesticide mixtures and metabolites. The magnitude of certain pesticide properties, such as half-life in the soil, tend to vary substantially depending on soil organic carbon content, moisture, temperature, and microbial activity (60). Therefore, values reported in the literature might not be suitable for specific site conditions. Uncertainties also emerge from estimating soil field capacity using soil texture. Uncertainties in PURE include the adoption of the empirical curve number method (61) and the lack of a procedure to simulate pesticide transport in the sediment phase. It is important to also note that chemicals normally exist as mixtures in the waterways, especially in intensively cultivated areas such as the California’s Central Valley. Synergistic responses have been observed in many pesticide mixture experiments (62, 63), though our understanding of the potential impacts caused by pesticide interactions is still quite limited (64). Modeling the risk posed by pesticide metabolites also remains challenging but critical, as degradation is known in some cases to lead to the formation of new chemicals that are more toxic and persistent than the precursors (65). Future research needs to focus on understanding the impacts of pesticide interactions and degradation on the fate and toxicity of pesticides in the environment.

Conclusions In this study, we performed a spatio-temporal analysis of pesticide use on California walnuts and potential risks to surface water by querying the PUR database and analyzing the results with the PURE indicator. Results show that insecticides posed the highest risk to surface water, followed by fungicides and herbicides. Spatial distributions of UI and TAI were associated with variations in temperature and humidity. Spatial patterns of pesticide risks were associated with interactions of spatially different drainage density, precipitation, and soil permeability. The temporal trends in pesticide use are the mixed results of changes in regulations and outreach programs, evolution of pesticide resistance, and fluctuations in crop values. The significant decrease (p < 0.01) in the RI of many high-risk chemical groups and AIs demonstrated the effectiveness of regulatory efforts and growers’ awareness in phasing out high-risk pesticide compounds. However, the increasing use of high-risk alternatives to organophosphates and glyphosate should be noted. Future work and research needs to focus on the increasing risks posed by insecticide use, herbicide resistance issues, and the toxicity introduced by pesticide interactions and degradation. In addition, areas identified as pesticide hotspots and areas with increasing use/risks should be investigated in greater detail and validated with observational data in the future.

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Spatio-Temporal Analyses of Pesticide Use on Walnuts and Potential

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