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TECHNICAL REPORTS

Surface Water Quality

Farm Factors Associated with Reducing Cryptosporidium Loading in Storm Runoff from Dairies

^a Dep. of Pathology, Microbiology, and Immunology, School of Veterinary Medicine, Univ. of California, Davis, CA 95616
^b Univ. of California Cooperative Ext., Santa Rosa, CA
^c Veterinary Medicine Ext. & Dep. of Population Health and Reproduction, School of Veterinary Medicine, Univ. of California, Davis, CA
^d Dep. of Plant Sciences, Univ. of California, Davis, CA

^* Corresponding author (wamiller{at}ucdavis.edu).

Received for publication August 3, 2007.

	ABSTRACT

TOP NOTES ABSTRACT INTRODUCTION Materials and Methods Results Discussion Conclusions REFERENCES

 
A systems approach was used to evaluate environmental loading of Cryptosporidium oocysts on five coastal dairies in California. One aspect of the study was to determine Cryptosporidium oocyst concentrations and loads for 350 storm runoff samples from dairy high use areas collected over two storm seasons. Selected farm factors and beneficial management practices (BMPs) associated with reducing the Cryptosporidium load in storm runoff were assessed. Using immunomagnetic separation (IMS) with direct fluorescent antibody (DFA) analysis, Cryptosporidium oocysts were detected on four of the five farms and in 21% of storm runoff samples overall. Oocysts were detected in 59% of runoff samples collected near cattle less than 2 mo old, while 10% of runoff samples collected near cattle over 6 mo old were positive. Factors associated with environmental loading of Cryptosporidium oocysts included cattle age class, 24 h precipitation, and cumulative seasonal precipitation, but not percent slope, lot acreage, cattle stocking number, or cattle density. Vegetated buffer strips and straw mulch application significantly reduced the protozoal concentrations and loads in storm runoff, while cattle exclusion and removal of manure did not. The study findings suggest that BMPs such as vegetated buffer strips and straw mulch application, especially when placed near calf areas, will reduce environmental loading of fecal protozoa and improve stormwater quality. These findings are assisting working dairies in their efforts to improve farm and ecosystem health along the California coast.

	INTRODUCTION

TOP NOTES ABSTRACT INTRODUCTION Materials and Methods Results Discussion Conclusions REFERENCES

 
WATER quality has become a complex and important issue as human demands on coastal ecosystems continue to increase (Daszak et al., 2001). Humans and their animals produce significant amounts of fecal byproducts that must be managed to maximize water quality and minimize public health risks in these coastal ecosystems (Fayer et al., 2004). The Tomales Bay watershed, along the northern California coast, supports livestock, aquaculture, and recreation industries that are currently working together to improve water quality and ecosystem health. Because exposure to even low doses of Cryptosporidium oocysts from contaminated water and food sources is a public health concern (Okhuysen et al., 1999), a better understanding of the environmental ecology and control of these parasites in coastal watersheds is key to designing preventive measures.

A systems approach by Lewis et al. (2005) evaluated stormwater quality on various dairy farm loading units near Tomales Bay, and the study findings suggest that the high concentrations of fecal microbes mobilized in overland runoff during storm events may be more cost-effectively controlled by implementing beneficial management practices (BMPs) targeting point sources such as dairy dry lots and other high use areas, as compared to nonpoint source areas such as pastures. Vegetated buffers are BMPs that can be used on farms to mitigate contaminants in storm runoff, and in recent controlled studies evaluating their capacity to reduce the load of Cryptosporidium oocysts in overland runoff, a 1 to 3 log₁₀ reduction/m buffer was found (Atwill et al., 2002, 2006; Davies et al., 2004; Tate et al., 2004; Trask et al., 2004). This suggests that buffers, when matched appropriately to local environmental conditions, can significantly improve stormwater microbial quality when placed between fecal sources and downstream waterways.

The current study extends our previous evaluations (Atwill et al., 2002, 2006; Tate et al., 2004) of vegetated buffers for reduction of protozoal loading in storm runoff to a working farm setting. Five dairy farms near Tomales Bay, California, participated in the 2-yr study. The goals were to (i) evaluate factors associated with detection of Cryptosporidium oocysts in runoff from dairy high use areas, and (ii) evaluate the efficacy of BMPs to reduce the Cryptosporidium load in storm runoff from treated dry lots compared to adjacent control dry lot sites. In addition to vegetated buffers, BMPs evaluated included straw mulch application, cattle exclusion, and scraping of lots to remove manure. We hypothesized that Cryptosporidium would be detected most often in storm runoff collected near calf areas, and that BMPs such as vegetated buffer strips would significantly decrease the protozoal load in storm runoff from dairy high use areas.

	Materials and Methods

TOP NOTES ABSTRACT INTRODUCTION Materials and Methods Results Discussion Conclusions REFERENCES

 
Study Sites
Five dairy farms were selected based on voluntary participation and location within the Tomales Bay watershed. The Mediterranean climate has cool wet winters and dry hot summers, with annual cumulative precipitation ranging from 600 to 1300 mm (Fischer et al., 1996). The farms were situated on hilly pasture terrain above the bay, with an average slope of 9° (range 1–26°) and an average of 104 animals per hectare (range 5–309). A variety of farm sites were evaluated but sampling efforts focused mainly on locations that received extensive cattle use (e.g., corrals, lots) because of the high rate of fecal coliforms discharged from these areas during the 1999 to 2001 water years (Lewis et al., 2005).

Thirty five cattle lots on the five dairies were enrolled in the study. Typically positioned next to barns, these units ranged from several hectares to less than a hectare in size (Table 1 ). The lots are used to provide daily exercise to milking cows, who do not move far from the barn or milking facilities. In general, these areas hold high densities of dairy cattle during the summer, are scraped of manure in the fall, and are not used in the winter. All lots were characterized by area, slope, animal density, and ground cover factors. Real-time precipitation data for the 24 h and 5 d preceding sample collection, and for cumulative seasonal precipitation estimates was collected from Point Reyes and Tomasini Point, CA (http://cdec.water.ca.gov/snow_rain.html [verified 19 May 2008]).

Building on these preexisting practices, vegetative surface treatments were implemented in October before the onset of winter rains on 13 of the dairy lots. Vegetative surface treatments involved seeding the lot with 112 kg/hectare of annual barley (Hordeum vulgare) and 28 kg/hectare rye grasses (Lolium multiflorum) that would provide cover and soil stabilization during later winter storms. On the same day, 5.4 metric tons/hectare straw were applied to the lots to provide soil surface cover during early winter storms (Lennox et al., 2007). Percent straw cover was expected to decrease from over 60 to 20% within 2 mo of application, with corresponding increases in cover by the seeded grasses.

Lastly, existing or newly implemented practices below 17 lots were evaluated to improve the quality of storm runoff after it left the lot. In this case runoff was channeled from the lot through one of three BMPs: vegetative buffer strips (14 lots); grassed waterways (2 lots); or impoundment (1 lot), as a means to reduce the load of waterborne fecal protozoa.

Stormwater Collection and Analysis
Throughout the 2002 to 2003 and 2003 to 2004 water years, surface runoff grab samples were collected during each storm to represent both early and late flushing events at each study site. Samples were collected from small channels which collect and drain stormwater runoff from each lot. Instantaneous runoff rate at the time of each sample collection was determined at each sample site by the area velocity method (Mosley and McKercher, 1993). Water samples were collected and transported chilled in 500 mL plastic bottles within 72 h of collection from the farm study sites to the University of California, Davis for laboratory analysis. Turbidity in nephelometric turbidity units (ntu) was determined using a turbidimeter (Orbeco Analytical Systems, Farmingdale, NY). To each 500 mL water sample, 125 µL 0.2% Tween 80 and 25 mL 50 mmol L^–1 morphilinopropane sulfonic acid (MOPS) sodium extraction solution (Fisher Scientific, Pittsburg, PA) were added. Samples were hand mixed and decanted to two 250 mL spin bottles. Bottles were agitated for 5 min on a hand-wrist shaker at speed 7 and then centrifuged at 1100 x g for 10 min. Supernatant was aspirated down to a 1:1 pellet/liquid ratio.

For Cryptosporidium quantitation, pellets less than 50 µL were analyzed by direct fluorescent antibody (DFA) assay without immunomagnetic separation (IMS) concentration, by drying 10 µL loop aliquots onto three-well Merifluor (Meridian Bioscience Inc., Cincinnati, OH) slides for direct DFA analysis. For larger pellets, up to 0.5 mL of the pellet was processed by Cryptosporidium IMS (Dynal Biotech, Oslo, Norway) and then DFA (Meridian Bioscience) analysis according to the manufacturer's instructions. All slides were read by the same microscopist.

After parasite quantification, selected slides were scraped with a razor blade and washed with sterile phosphate buffered saline (PBS) into a microcentrifuge tube for subsequent DNA extraction, polymerase chain reaction (PCR) amplification, and DNA sequence analysis (Miller et al., 2005). For each dairy, five oocyst-positive runoff samples were processed for molecular determination of Cryptosporidium genotypes. Cryptosporidium andersoni oocysts were readily distinguished by their typical 5- x 7-µm morphology compared to the smaller 5-µm diameter spherical C. parvum-like oocysts, and were thereby excluded from all C. parvum calculations in this cohort of dairy farms.

Two conventional 18S small subunit ribosomal DNA PCR protocols (Morgan et al., 1997, Xiao et al., 1999) were used to genotype Cryptosporidium spp. detected in stormwater samples. For DNA extraction, a 50-µL pellet was mixed with 180 µL QIAGEN ATL buffer and suspended in liquid nitrogen for 4 min, then boiling water for 4 min. Using the QIAGEN DNA Mini Kit tissue protocol (QIAGEN Inc., Valencia, CA), each sample was digested, bound to a QIAamp column, washed, and the DNA eluted with 50 µL of 95°C PCR water. The PCR and DNA sequence analysis methods targeted 300 and 850 bp 18S regions.

Stormwater Spiking Trials
The stormwater spiking experiments were designed to simulate a range of field conditions and contained a known number of oocysts so that recovery efficiency of the water processing protocols could be evaluated. Cryptosporidium parvum oocysts were obtained from calf fecal samples submitted to the Veterinary Medical Teaching Hospital in Davis, California. Calf feces were sieved through #40, 100, and 200 mesh strainers with 1X PBS and purified by sucrose flotation methods (Arrowood and Sterling, 1987). Oocyst concentrations were determined from the mean of eight hemacytometer counts and confirmed with DFA enumeration. Oocyst suspensions were kept at 4°C and used within 1 mo of collection.

Soil and cattle manure from the participating farms were pre-tested and then used to adjust stormwater turbidity to 1, 100, or 500 ntu. Oocyst doses of 0, 10, 50, or 500 oocysts per 500 mL water sample were mixed with each water sample and refrigerated overnight before processing. Four replicates were created for each oocyst dose and turbidity combination, and were processed identically to the field samples.

Statistical Analyses
Percent recovery values for oocyst DFA and IMS-DFA procedures were estimated by fitting a negative binomial regression model to the observed oocyst count data over the range of turbidity values, with the number of spiked oocysts as the offset variable (Hardin and Hilbe, 2001; Atwill et al., 2003). In addition to the percent recovery estimates, the assay sensitivity S(c), defined as the probability of detecting at least one oocyst per sample, was calculated as shown in Eq. [1], where e^βxi is the percent recovery of the assay, is an ancillary parameter for modeling dispersion, c_i is the number of oocysts spiked per 500 mL stormwater sample, and W_i is the proportion of sample tested in the assay (Atwill et al., 2003).

[1]

In the field study, water samples were first classified as Cryptosporidium positive or negative for use in prevalence calculations. The percent recovery estimates were used to adjust the oocyst count data from water samples to estimate the true concentration of parasites. Adjusted parasite concentrations were then used to calculate instantaneous parasite load by multiplying the stormwater concentration by the instantaneous flow for each sample, as seen in Eq. [2]:

[2]

Negative binomial regression was used to identify farm factors and BMPs associated with detection of Cryptosporidium oocysts in storm runoff. The stormwater outcome variables were oocyst concentration and instantaneous parasite load, with study site functioning as a group effect to adjust for repeated sampling at the same sites over time. Categorical predictor variables included month of sampling (November-March), cattle age class (dry and milking adults, calving adults, 3–6 mo old calves, 1–2 mo old calves), and dry lot BMP status (control site, vegetated buffer, mulch straw application, cattle exclusion, scraping of manure). Continuous predictor variables included instantaneous flow, 24 h precipitation, cumulative annual precipitation, percent slope, acreage, cattle stocking number, and cattle density. Forward stepping multivariate regression models were created and used to estimate the effect of changing predictor variables on protozoal stormwater concentration and load. Statistical significance was defined as P < 0.10. The McFadden likelihood-ratio index was used to estimate the percent variance explained by the model, calculated as R² = 1-{(log likelihood of the full model/log likelihood of the intercept-only model)} (Hardin and Hilbe, 2001).

	Results

TOP NOTES ABSTRACT INTRODUCTION Materials and Methods Results Discussion Conclusions REFERENCES

 
Between November 2002 and March 2004, a total of 350 stormwater samples were processed from high use areas on the five dairy farms. Overall, Cryptosporidium oocysts were detected in 21% of storm runoff samples. The highest prevalence was in runoff collected near calves 0 to 2 mo of age, with 59% of stormwater samples testing positive for Cryptosporidium oocysts. In comparison, Cryptosporidium oocysts were detected in 38% of runoff discharging from sites housing 3- to 6-mo-old calves and in 10% of runoff discharging from locations with dry, milking, or calving adult cattle.

Cryptosporidium parvum-like and C. andersoni-like oocysts were detected in runoff from four of the five dairy farms. Amplification and sequence analysis of up to five randomly selected DFA-positive samples per farm confirmed that both C. parvum and C. andersoni were present but not other genotypes reported in cattle such as C. bovis or cervine genotypes. Results herein focus on 5 µm oocysts resembling C. parvum, with C. andersoni excluded from the loading calculations and analysis.

In the percent recovery experiments, no negative controls tested positive as part of the 48 stormwater samples spiked with 0, 10, 50, or 500 oocysts that were used to estimate the recovery efficiencies of the Cryptosporidium detection methods over a range of turbidities. Detection by DFA alone resulted in 21% recovery of spiked oocysts, whereas IMS concentration before DFA detection improved recovery to 47% overall, as determined by negative binomial regression modeling of the experimental data. The percent recovery values were used to adjust the raw oocyst count data from field samples so that the true parasite concentrations in the storm runoff samples could be estimated for the statistical analyses.

Figure 1 illustrates the assay sensitivity curves for Cryptosporidium oocysts detected in stormwater samples by DFA and IMS-DFA. The IMS-DFA analytic sensitivity improved by 1 to 2 log₁₀ units, shown by the IMS-DFA curve left shifted from the DFA curve. When IMS concentration was performed before DFA detection, the 50% probability detection threshold (DT₅₀) improved from approximately 100 to 2 oocysts per 500 mL stormwater sample, and the DT₉₀ improved from 400 to 10 oocysts.

View larger version (18K): [in this window] [in a new window]   Fig. 1. Sensitivity of direct fluorescent antibody (DFA) testing and immunomagnetic separation (IMS) with DFA testing for detection of Cryptosporidium oocysts spiked into stormwater samples.

View larger version (24K): [in this window] [in a new window]   Fig. 2. Monthly concentration and load distributions for Cryptosporidium-positive samples collected from dairy lots during runoff conditions, 2002–2004, Tomales Bay, California.

View larger version (23K): [in this window] [in a new window]   Fig. 3. Concentration and load distributions for Cryptosporidium-positive samples collected from dairy lots during runoff conditions stratified by cattle age class, 2002–2004, Tomales Bay, California.

View larger version (25K): [in this window] [in a new window]   Fig. 4. Predicted Cryptosporidium oocyst concentrations (oocysts/L) in storm runoff from dairy lots for cattle of various age classes as a function of (a) percentage of each lot covered in straw, (b) length of vegetated buffer, and (c) 24 h precipitation, and (d) cumulative precipitation.

View larger version (29K): [in this window] [in a new window]   Fig. 5. Predicted Cryptosporidium oocyst loads (oocysts/sec) in storm runoff from dairy lots for cattle of various age classes as a function of (a) percentage of each lot covered in straw, (b) length of vegetated buffer, and (c) 24 h precipitation.

	Discussion

TOP NOTES ABSTRACT INTRODUCTION Materials and Methods Results Discussion Conclusions REFERENCES

Vegetated buffers and straw mulch BMPs demonstrated their potential to significantly reduce the load of Cryptosporidium oocysts in storm runoff on working dairy farms. Both BMPs function in part as barriers to impede overland flow and provide surfaces to trap oocysts, thereby removing them from runoff, as well as slowing down the runoff to allow more time for infiltration and sedimentation of microorganisms (Atwill et al., 2002; Tyrrel and Quinton 2003; Blanco-Canqui et al., 2006). Moreover, application of straw mulch is a proven method for reducing soil erosion created by rain drop impact and soil particle entrainment on bare soil (USDA-NRCS 2004). Given the very slow settling velocity of oocysts, it is thought that one mechanism of removal is by sedimentation when attached to particulate matter (Medema et al., 1998; Searcy et al., 2006), though the Kaucner et al. (2005) study suggests that oocysts may often remain as single entities in overland runoff instead of attaching and settling out. Consistent with our findings, the Davies et al. (2004) and Trask et al. (2004) studies found reduced oocyst concentrations in runoff from vegetated soil plots compared with paired devegetated plots. Additional management approaches such as applying anionic polyacrylamide (PAM) to increase flocculation and soil infiltration were not evaluated in our study but may also prove useful for improving stormwater quality (Sojka et al., 2005).

The Atwill et al. (2002, 2006) and Tate et al. (2004) Cryptosporidium studies found a 1 to 3 log₁₀ reduction per meter in controlled soil box experiments or field-plot studies, whereas in the current study oocyst concentrations and instantaneous loads were reduced by a factor of 0.97 and 0.98 respectively, which corresponds to a 0.01 log₁₀ reduction per meter. The decreased magnitude of protozoal retention per meter of buffer length in the current study is likely due to a combination of factors. For example, in the present study only a single point in the pathogen breakthrough curve was measured, preventing a calculation of the total number oocysts retained during the storm event due to the presence of a vegetated buffer strip. If total runoff or runoff duration was shortened by the presence of a buffer, our calculation of oocyst retention via calculating concentration or instantaneous load would not reflect this reduction in total storm load reductions. In the work reported by Atwill et al. (2002), the entire runoff event was captured so that a complete mass balance could be calculated (entire pathogen load above and below the buffer was measured in surface runoff). In Atwill et al. (2006), the efficacy of a meter of vegetated buffer to retain C. parvum was based on capturing the entire surface runoff generated by each storm event for the entire storm season for two separate years, thereby allowing the calculation of buffer retention on an annualized basis. The calculations reported by Tate et al. (2004) were based on repeated subsampling across the duration of a set of runoff events, somewhat similar to the work reported in Atwill et al. (2002).

Furthermore, differences between these studies with respect to soil type, buffer composition and its morphology, hydrologic behavior of runoff, and storm dynamics likely influence buffer efficacy calculations. The vegetated buffers in this study were typically grassy channels that resulted in channelized flow, in contrast to the hill-slope conditions (Atwill et al., 2006) or soil-box buffers (Atwill et al., 2002; Tate et al., 2004) that created more sheet-like flow conditions. This reduction in buffer retention due to channelized flow would be consistent with the finding of Tate et al. (2004) and Atwill et al. (2006) where they found that as rate of precipitation or runoff volume increased, the efficacy of buffer strips to retain C. parvum oocysts decreased. Careful site selection for installation of buffers and ensuring that percent cover is maintained may increase buffer efficacy on dairy farms to a greater extent than our models currently predict.

Cattle age class was significantly associated with Cryptosporidium loading in storm runoff. Consistent with other dairy fecal studies (Olson et al., 1997; Huetink et al., 2001), we found the highest prevalence and oocyst concentrations in runoff collected from sites housing calves less than 2 mo of age. Given that oocyst concentrations and loads in storm runoff collected from sites housing young calves were 2100 and 728 times greater than runoff collected from sites housing adult cows, respectively, designing BMPs to filter or reduce runoff from calf areas may be one of the best strategies for improving on-farm water quality. The BMPs could involve installing vegetative buffers to reduce runoff from calf areas, or removing calf feces before it can become entrained in runoff events, either with sanitation measures or indoor calf housing. It is also possible that confounding factors are causing us to underestimate the potential for oocyst loading from adult cattle, such as covered calving pens with straw bedding leading to decreased runoff flow and oocyst loading even though the calving adults could be shedding significant numbers of oocysts.

Seasonal precipitation factors were also significantly associated with Cryptosporidium discharging in storm runoff from high use areas. Increasing volumes of rain in the watershed during the 24 h preceding sample collection (e.g., late in storm events), and increasing cumulative precipitation (e.g., late in the storm season) were associated with decreased storm runoff concentrations (Fig. 4c, 4d). These findings represent general trends in oocyst loading as related to precipitation events, and are useful when considering seasonal patterns and the associated farm management practices. They are consistent with the idea that early in a storm event and early in the storm season is when accumulated fecal matter will be mobilized in overland runoff, and are consistent with the Sischo et al. (2000) study that found a decreased probability of detecting oocysts in farm-associated streams as 5-d cumulative precipitation increased. Our results are also consistent with the Bodley-Tickell et al. (2002) study in which samples taken early in the storm season were more likely to contain oocysts than samples taken during other times.

While Cryptosporidium oocysts were detected on most dairies (4/5), they were detected in a minority of the total stormwater samples tested (21%). These findings are similar to the Sischo et al. (2000) study that detected Cryptosporidium on 10 of 11 dairy farms in the northeastern United States, but in only 9% of the farm-associated stream samples. The findings are in contrast to a Japanese study which detected Cryptosporidium spp. in 88% of dairy associated river samples (Tsushima et al., 2001), and a study in the United Kingdom that found Cryptosporidium in 79% of surface water samples collected near a farming site (Bodley-Tickell et al., 2002). Differences in detection methods do not sufficiently explain the broad range of study findings. Taken together, these studies demonstrate that even with widespread endemic cryptosporidiosis in dairy operations, the environmental loading of these parasites may vary across farm units, depending on both biotic animal factors and abiotic environmental factors.

Although the variables in Tables 2 and 3 were significantly associated with the occurrence of Cryptosporidium oocysts in runoff from dairy lots, collectively these variables did not explain the majority of the variance associated with Cryptosporidium oocysts in dairy runoff. The calculated McFadden similarity index for maximum likelihood models emulates the R² values typical of least squares theory (Hardin and Hilbe, 2001). The goal of this study was to develop a model that estimates the association between the various independent variables and the outcome variable of Cryptosporidium oocysts in dairy runoff, not to completely explain the occurrence of oocysts in dairy runoff.

The water spiking trials were critical to accurately assess the water processing recovery efficiency, to adjust the raw oocyst counts in the field samples and estimate the true parasite concentration in each sample. The overall percent recovery of 21% by DFA alone, and 47% when IMS concentration preceded DFA analysis, is similar to what has been found in other studies (Pereira et al., 1999; Atwill et al., 2003). The Pereira et al. (1999) study reported a mean percent recovery of 28 to 34% for DFA when 1000 or more oocysts were spiked into a fecal sample and analyzed by DFA alone. The same study found an improved percent recovery of up to 48% when 100 or more oocysts were spiked into a fecal sample and concentrated with IMS before DFA analysis. Similarly, the Atwill et al. (2003) study reported an IMS-DFA recovery of 32 to 40% when 10 to 500 oocysts were spiked into a fecal sample. The Atwill et al. (2002) study reported higher recovery values, 63 to 81% oocyst recovery by DFA, in runoff samples from vegetated buffer soil box experiments.

	Conclusions

TOP NOTES ABSTRACT INTRODUCTION Materials and Methods Results Discussion Conclusions REFERENCES

 
This study of BMP efficacy and farm factors associated with protozoal loading in storm runoff has taken the next steps toward understanding the environmental ecology and control of Cryptosporidium on coastal California dairies. Factors associated with environmental loading of Cryptosporidium oocysts included cattle age class, 24 h precipitation, and cumulative seasonal precipitation, but not percent slope, lot acreage, cattle stocking number, or cattle density. Vegetated buffer strips and straw mulch application significantly reduced the protozoal concentrations and loads in storm runoff, while cattle exclusion and removal of manure did not. The study findings suggest that BMPs such as vegetated buffer strips and straw mulch application, especially when placed near calf areas, will reduce environmental loading of fecal protozoa and improve stormwater quality. Using a systems approach to evaluate the flow and control of pathogens from specific farm loading units such as dry lots, pastures, roads, and waste management systems will help farmers and regulatory agencies prioritize their management efforts in the future (Lewis et al., 2005; Oborn et al., 2005). The BMPs evaluated in this study represent practical on-farm solutions to improve water quality and decrease pathogen loading in storm runoff.

	ACKNOWLEDGMENTS

 
This research was supported in part by the National Sea Grant College Program under NOAA Grant NA06RG0142, Project R/CZ-180, through the California Sea Grant College Program; and in part by the California State Resources Agency. Additional support was received the University of California-Davis Center for Food Animal Health. The authors thank the Univ. of California Cooperative Extension and the Tomales Bay Agricultural Group for participating in this study.

	NOTES

TOP NOTES ABSTRACT INTRODUCTION Materials and Methods Results Discussion Conclusions REFERENCES

 
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	REFERENCES

TOP NOTES ABSTRACT INTRODUCTION Materials and Methods Results Discussion Conclusions REFERENCES

 

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