Water quality conditions associated with cattle grazing and recreation on national forest lands
Contact Person: Dr. Kenneth W. Tate
Participants: Leslie Roche, Rob Atwill, Randy Dahlgren, Lea Kromschroeder, Thomas Lushinsky, Kristin Oles, USDA Forest Service – Region 5, Stanislaus National Forest, Plumas National Forest, Tahoe National Forest, Shasta-Trinity National Forest, Klamath National Forest.Comment or Questions?
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We conducted a cross sectional survey of water quality conditions associated with cattle grazing and recreation on 12 U.S. Forest Service (USFS) public lands grazing allotments in northern California as part of a larger public lands grazing and water quality project. Our specific objectives were to:
|Abbreviations key: AUM = animal unit month; FC = fecal coliform; FIB = fecal indicator bacteria; TP = total phosphorus; TN = total nitrogen; USFS = U.S. Forest Service; USEPA = U.S. Environmental Protection Agency|
|Supplemental information about methods and background studies related to this study can be found >>here.|
In collaboration with multiple stakeholder groups, we conducted a cross sectional survey of water quality conditions associated with cattle grazing and recreation on 12 USFS public lands grazing allotments in northern California during 2011. These allotments were located across 5 national forests (Klamath, Plumas, Shasta-Trinity, Stanislaus, and Tahoe National Forests) and four mountain ranges (Klamath, Coast, Cascade, and Sierra Nevada Mountain Ranges). The total study area was approximately 1,300 km2 (320,000 acres) and elevation ranged from 207 m to 3,016 m (679 feet to 9,895 feet) (Table 1). Allotments were chosen to represent the diversity of climate, soil, vegetation, water quality regulatory agencies, and resource use activities found on this landscape.
Study allotments were grazed with commercial beef cow-calf pairs during the June to November grazing-recreation season, following allotment-specific management plans designed to achieve annual herbaceous forage use standards. Timing of grazing, duration of grazing season, and number of cattle were determined by allotment-specific permits issued by the USFS (Table 1). Stocking densities ranged from 1 animal unit per 18 ha (1 animal unit per 44 acres) to 1 animal unit per 447 ha (1 animal unit per 1,105 acres) (Table 1).
Sample Site Selection
Key grazing areas and concentrated recreation areas within 200 m (660 ft) of streams in each allotment were identified and enrolled in the study in collaboration with local USFS managers and forest stakeholders. Key grazing areas were meadows and riparian areas that cattle were known to graze and occupy frequently and/or for extended periods throughout the grazing season. Recreational activities included developed and undeveloped campgrounds, swimming-bathing areas, and trailheads used by hikers and recreational horse riders. Additional sites were established at perennial flow tributary confluences with no concentrated use activities, enabling us to objectively include comparison sites across allotments with no concentrated grazing and/or recreation.
Sample Collection and Analysis
We collected a total of 743 water samples from 155 stream collection sites. We sampled each stream collection site monthly during the study period (Jun 1 - Nov 9, 2011). All sites in an allotment were sampled on the same day. Total sample numbers per allotment ranged from 40 to 88. (Table 1). Stream conditions were noted at the time of sampling, specifically whether any of the following conditions were present: 1) stagnant-low stream flow (< 0.5 gallons per minute); 2) turbid stream water; 3) recreation (i.e. swimming-bathing, camping, hiking, fishing, horse riding); and 4) cattle.
Water quality indicators measured were fecal coliform (FC), E. coli, total nitrogen (TN), nitrate (NO3-N), ammonium (NH4-N), total phosphorus (TP), and soluble-reactive phosphorus (PO4-P) concentrations. See supplemental materials for more information about laboratory methods.
|Table 1. Geographic characteristics, study year precipitation, cattle grazing management, and water quality sample collection sites and sample number for 12 U.S. Forest Service grazing allotments in northern California enrolled in this cross-sectional longitudinal study of stream water quality between June and November 2011.|
|a Dominant soil suborder identified with soil survey data .
b Precipitation realized during the October 1, 2010 through September 30, 2011 water year. Percentage values are the percent of 30-year mean annual precipitation realized during the 2010-11 water year .
c Animal Unit Month. The dry weight mass of forage required to feed a 1000 lb. cow for a 30 day period. It is the standard unit by which grazing pressure is permitted on U.S. Forest Service grazing allotments.
d Total cow-calf pairs per allotment.
e Date that cattle were released onto the grazing allotment.
f Date that cattle were removed from the grazing allotment.
g Maximum permissible removal of annual herbaceous vegetation production in meadows and riparian areas on the grazing allotment.
Results and Discussion
Nutrient Concentrations and Water Quality Benchmarks
Nutrient concentrations were generally low: over 32% of samples were below the detection limit (<10 µg N/L and <5 µg P/L) for all nutrients except TN. Additionally, nutrient concentrations observed across this grazed landscape were well below eutrophication benchmarks (NO3-N, TP, and PO4-P) and background estimates (TN, NO3-N, and TP) (Table 2). These results do not support concerns that excessive nutrient pollution is degrading surface waters on these USFS grazing allotments .
|Table 2. Concentrations of total nitrogen (TN), nitrate (NO3-N), ammonium (NH4-N), total phosphorus (TP), and phosphate (PO4-P). Published estimates of concentrations of general concern for eutrophication of stream water and estimates of background concentrations for the study area are provided for context.|
|a The ‘±’ indicates 1 standard error of the mean.
b Percentage of samples below minimum analytical detection limit. Limits were 10 µg/L for nitrogen and 5 µg/L for phosphorous. Observations below detection limit were set to one half detection limit (5 µg/L for nitrogen and 2.5 µg/L for phosphorus) for calculation of mean and median concentrations.
c Concentrations if exceeded indicate potential for eutrophication of streams [4-8].
d Estimated range of background concentrations for the three U.S. Environmental Protection Agency Level III sub-ecoregions (5, 9, 78) included in the study.
Fecal Indicator Bacteria (FIB) Concentrations and Water Quality Benchmarks
The percentage of all sites that exceeded water quality benchmarks for FIB concentrations varied by benchmark. The overall percentage of sites that exceeded a benchmark at least once ranged from 83% (benchmark FC > 20 cfu/100 ml) to 6% (benchmark E. coli > 410 cfu/100 ml) (Table 3). Overall mean and median E. coli were 40 cfu/100 ml and 8 cfu/100 ml, and mean and median FC were 82 cfu/100 ml and 21 cfu/100 ml – indicating that the nationally recommended E. coli FIB-based benchmarks would be broadly met, and that the more restrictive, FC FIB-based regional water quality benchmarks would be commonly exceeded across the study region.
USEPA recommends adoption of an indicator E. coli water quality objective as an improvement over FC . This guidance is because, in part, E. coli is better correlated to human pathogens such as Salmonella spp. [11-14], E. coli is less likely to establish and reproduce as environmental strains in stream habitats  than FC, and there is also evidence that E. coli is a better predictor of gastro-intestinal illness than FC . Therefore, comparing our results to the most relevant and scientifically defensible E. coli FIB-based recommendations, 17% of all sites exceeded the 190 cfu/100 ml benchmark, and 14% of all sites exceeded the 235 cfu/100 ml benchmark . This analysis, based on the best available science and USEPA guidance, clearly contrasts with the FC FIB-based interpretations currently in use by several regional regulatory programs, which suggest that as many as 83% of all sites in our study present potential human health risks.
|Table 3. Percentage of 155 stream water sample sites which had at least one exceedance of water quality benchmarks relevant to the study area, specifically, and the nation, broadly. Results are reported for all sample sites (overall) as well as for sample sites monitored to characterize specific resource use activities across the allotments. *Indicates the most relevant and contemporary standards for this study.|
|a Fecal coliform (FC) benchmark designated by Lahontan Regional Water Quality Control Board (LRWQCB) (based on geometric mean (GM) of samples collected over a 30-day interval) .
b FC benchmark designated by North Coast Regional Water Quality Control Board (NCRWQCB) (based on a median of samples collected over a 30-day interval) .
c FC benchmark designated by Central Valley Regional Water Quality Control Board (CVRWQCB) (based on geometric mean of samples collected over a 30-day interval) .
dFC benchmark designated by CVRWQCB and NCRWQCB (maximum threshold value not to be exceeded by more than 10% of samples over a 30-day interval).
e E. coli benchmark designated by U.S. Environmental Protection Agency (USEPA)  for an estimated illness rate of 32 per 1,000 primary contact recreators (based on geometric mean of samples collected over a 30-day interval).
f E. coli benchmark designated by USEPA  for an estimated illness rate of 36 per 1,000 primary contact recreators (based on geometric mean of samples collected over a 30-day interval).
g E. coli benchmark designated by USEPA  for an estimated illness rate of 32 per 1,000 primary contact recreators (for a single grab sample, approximates the 75th percentile of a water quality distribution based on desired geometric mean).
h E. coli benchmark designated by USEPA  for an estimated illness rate of 36 per 1,000 primary contact recreators (for a single grab sample, approximates the 75th percentile of a water quality distribution based on desired geometric mean).
i E. coli benchmark designated by USEPA  for an estimated illness rate of 32 per 1,000 primary contact recreators (approximates the 90th percentile of a water quality distribution based on desired geometric mean).
j E. coli benchmark designated by USEPA  for an estimated illness rate of 36 per 1,000 primary contact recreators (approximates the 90th percentile of a water quality distribution based on desired geometric mean).
|FIB Concentrations relative to grazing, recreation, and environmental conditions
Mean FC and E. coli concentrations at key grazing and non-concentrated use areas were higher than recreation sites, but did not exceed USEPA E. coli FIB-based benchmarks (Table 4). Mean FIB concentrations for all resource use activity categories exceeded the most restrictive regional FC FIB-based benchmarks of 20 and 50 cfu/100 ml (Table 4).
|Table 4. Mean concentrations for fecal coliform (FC) and E. coli for each resource use category. The ‘±’ indicates 1 standard error of the mean. Different lower case letters indicate significant (P < 0.05 with Bonferroni-correction for multiple comparisons) differences between resource use activity categories.|
|Relative to conditions at time of sample collection, FC and E. coli concentrations were significantly higher when stream flow was low or stagnant, stream water was turbid, and when cattle were actively observed (Table 5). FC and E. coli concentrations were also lower when recreation activities were observed at time of sampling, compared to sample events when recreation was not occurring (Table 5).|
|Table 5. Mean concentrations for fecal coliform (FC) and E. coli by category of field observation of resource use activities and environmental conditions observed at the time of sample collection. The ‘±’ indicates 1 standard error of the mean; * indicates a difference at P < 0.05 (Bonferroni-adjusted), and ** indicates a difference at P < 0.01 (Bonferroni-adjusted) between Yes and No within each category.|
|a Stagnant or low stream flow (<2 liters per second).
b Stream water turbid.
c Cattle observed.
d Recreational activities observed.
eAny activities (low stream flow, turbid water, precipitation, cattle, or recreation) observed that potentially impact water quality.
Mean allotment FIB concentrations showed apparent increasing trends with greater cattle densities (Figure 1); however, this relationship was not statistically significant (P > 0.2). Decreasing cattle density has been shown to reduce fecal-microbial pollutant loading  and subsequent increases in FIB concentrations in runoff , as well as reduce in-stream disturbance and re-suspension of FIB-sediment complexes [21-26].
Mean allotment FIB concentrations tended to decrease with increasing precipitation during the 2010-2011 water-year (October 1 to September 30), although this relationship was not statistically significant (P > 0.2) (Figure 1). It is likely that the precipitation during the 2010-2011 water-year is primarily reflecting snowpack, which supported higher than historical stream flow volume during the study period. A similar relationship was observed on California coastal dairy pastures , and possibly reflects the capacity of higher base flow volumes to dilute FIB concentrations.
|Figure 1. Relationship between overall mean E. coli concentration across sample sites during the June through November 2011 sample period and (A) allotment cattle stocking density and (B) 2010-2011 water year precipitation on 12 U.S. Forest Service grazing allotments in northern California enrolled in this cross-sectional longitudinal study. There were no significant relationships between allotment cattle stocking density and mean allotment concentrations of (A) E. coli (P > 0.9). During the study period, there were also no significant relationships between 2010-2011 water year precipitation and mean allotment concentrations of (B) E. coli (P > 0.6).|
Our results do not support previous concerns of widespread microbial water quality pollution across these grazed landscapes, as concluded in other surveys [3, 28, 29]. Although we did find apparent trends between cattle density and FIB concentrations (Figures 1A and 1B) and significantly greater FIB concentrations when cattle were actively present, only 16% and 13% (Table 3) of key grazing areas (n = 97) exceeded the E. coli FIB-based benchmarks of 190 cfu/100 ml and 235 cfu/100 ml, respectively. Only 5% and 3% of total samples collected exceeded the E. coli FIB-based benchmarks of 190 cfu/100 ml and 235 cfu/100 ml, respectively. In contrast, Derlet et al.  reported 60% and 53% of cattle grazing sites (n = 15) exceeded the 190 cfu/100 ml and 235 cfu/100 ml benchmarks, respectively. We also found no significant differences in FIB concentrations among key grazing areas and areas of no concentrated use activities (Table 4), which contrasts with previous work in the Sierra Nevada [3, 28]. Finally, in this landscape of mixed livestock grazing and recreational uses, we found FIB concentrations to be lowest at recreation sites, indicating that water
|recreation objectives can be broadly attained within these grazing allotments. There are three important distinctions that separate our study from previous work: 1) in reaching our conclusions, we compared our study results to regulatory and background water quality benchmarks, which are based on current and best available science and policy; 2) these co-occurring land-use activities were directly compared on the same land units managed by a single agency (USFS), as opposed to previous comparisons between these land-uses occurring on different management units administered by different agencies with very different land-use histories and policies (e.g., USFS and U.S. National Park Service); and 3) to date, this study is the most comprehensive water quality survey in existence for National Forest public grazing lands, including an assessment of seven water quality indicators at 155 sites across five National Forests.|
We thank Anne Yost, Barry Hill, staff from the Klamath, Shasta-Trinity, Plumas, Tahoe, and Stanislaus National Forests, Tom Lushinsky, Mark Noyes, Natalie Wegner, Donna Dutra, D.J. Eastburn, Xien Wang, and Kristin Oles for project support; and UC Cooperative Extension and USFS District Rangers and Forest Supervisors who provided lab space.
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