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Kevin Wagner, Terry Gentry, Larry
Redmon, Daren Harmel, Jamie Foster, Robert
Knight, Allan Jones

 More than 50% of impairments in Texas are due to
excess bacteria levels.
Background

Avian
Wildlife
7%
Sewage
11%
Avian
Livestock
1%
Cattle
22%
Non-Avian
Livestock
12%
Non-Avian
Wildlife
29%
Unknown
10%
Pets
8%
Major sources of bacteria
Leon River Peach Creek
Leon River
0
10
20
30
40
50
60
70
Domestic Sewage Pet Cattle Other Livestock Wildlife Unidentified
SourceContributions(%of200isolates)

Exclusionary Fencing
Fecal Coliform
Reduction
Reference
30% Brenner et al. 1994
41% Brenner 1996
66% Line 2003
 Eliminates cattle access to streams
 Expensive to construct & maintain
 Often not feasible to fence-off
entire stream, i.e. rangeland
 Fencing of streams not accepted by
many landowners

Management of Creek
Pastures is Critical
Reduce cattle’s time in &
near stream
Maintain ground cover with
proper grazing management
 5 yr study on:
 Proper grazing management
 Alternative water supplies
 Alternative shade
 Conducted by:
 Texas AgriLife Extension Service
 Texas AgriLife Research
 Texas Water Resources Institute
 USDA-ARS
 Funded by:
 Texas State Soil and Water Conservation Board
 USDA Natural Resources Conservation Service
 US Environmental Protection Agency
Grazingland Research
Grazing Management Evaluation
 Seven 1 ha sites assessed across 3 locations
 3 – ungrazed
 3 – properly stocked
 1 – stocked @ 2 X recommended rate
 Grazed sites were rotationally grazed
 Flow measured w/
bubble flow meter
 V-notch weir
 H-flumes
 Sample Collection
 Automated samplers

Grazing management effects
on E. coli runoff
Grazing Management Stocking Rate
Unstocked Properly stocked Heavy stocked
E.coliConcentration(cfu/100mL)
1e+1
1e+2
1e+3
1e+4
1e+5
1e+6
1e+7
1.E+01
1.E+02
1.E+03
1.E+04
1.E+05
1.E+06
1 10 100 1000
E.coliConc.(cfu/100mL)
12 Month Stocking Rate (ac/AUY)
Ungrazed
Cultivated Cultivated with
grazed pasture
Grazed
pasture
E.coli(cfuper100mL)
1
10
100
1000
10000
100000
Outlier
90th
75th
Median
Mean
25th
10th

Comparison of E. coli Levels
While Sites Stocked & Destocked
Cultivated Cultivated with
grazed pasture
Grazed
pasture
E.coli(cfuper100mL)
1
10
100
1000
10000
100000
Outlier
90th
75th
Median
Mean
25th
10th

Why no correlation btwn E. coli
& grazing management?
Rapid decline following rotation Significant background levels

Why no correlation btwn E. coli
& grazing management?
80-99% of loading from wildlife
at 3 sites in 2009
Date BB1 BB2 BB3
3/13/09 140
3/25/09 1,200
3/26/09 1,000 7,200
3/27/09 2,000
4/17/09 1,155 980 450
4/18/09 4,400 2,225 2,100
4/28/09 7,600 12,200 24,000
10/4/09 57,000 5,114 3,065
10/9/09 36,000 24,043 15,000
10/13/09 42,851 23,826 5,591
10/22/09 172,500
10/26/09 261,000 181,000 45,000

 Rotationally graze creek pastures
 Target grazing of creek pastures to dry periods
 Rotate cattle to upland pastures during wet periods
 88-99% reductions in edge-of-field runoff of bacteria
from creek pastures potentially achievable
Management Implications

Alternative Water Evaluation
Bi-monthly water sampling & quarterly GPS tracking

Alternative water effectiveness
Reduction in
Time Spent
in Stream
Reference
43% Wagner et al. 2012
85-94%
Miner et al. 1992
Clawson 1993
Sheffield et al. 1997
E. coli Load (cfu/AU/day)
-57%
43%
Reduction

 Sheffield (1997) also found:
 77% decrease in sedimentation
 90% decrease in suspended solids
 54% decrease in nitrogen
 81% decrease in phosphorus
Alternative Water Source
Bacteria Reduction Reference
85-95% (EC) Byers et al. 2005
51% (FC) Sheffield 1997

Shade Structure
GPS Collar Evaluation
Time Spent w/in 25’ of Stream Reference
27% Reduction Wagner et al. 2012
 Shade, coupled with
alternative water &
salt/mineral locations,
encourages cattle to
spend less time in
riparian areas.
Conclusions
 Rotate cattle to upland
pastures during wet periods
 Promote loafing, drinking &
grazing away from creeks
 Alternative water supplies
 Additional shade
 Proper grazing management
 Be aware of impacts of
background/wildlife sources

Kevin Wagner, PhD
klwagner@ag.tamu.edu
979-845-2649
http://lshs.tamu.edu/
Questions?
Funding Provided By:
TSSWCB, EPA & USDA-NRCS

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Managing Creek Pastures for Improved Water Quality

  • 1. Kevin Wagner, Terry Gentry, Larry Redmon, Daren Harmel, Jamie Foster, Robert Knight, Allan Jones
  • 2.   More than 50% of impairments in Texas are due to excess bacteria levels. Background
  • 3.  Avian Wildlife 7% Sewage 11% Avian Livestock 1% Cattle 22% Non-Avian Livestock 12% Non-Avian Wildlife 29% Unknown 10% Pets 8% Major sources of bacteria Leon River Peach Creek Leon River 0 10 20 30 40 50 60 70 Domestic Sewage Pet Cattle Other Livestock Wildlife Unidentified SourceContributions(%of200isolates)
  • 4.  Exclusionary Fencing Fecal Coliform Reduction Reference 30% Brenner et al. 1994 41% Brenner 1996 66% Line 2003  Eliminates cattle access to streams  Expensive to construct & maintain  Often not feasible to fence-off entire stream, i.e. rangeland  Fencing of streams not accepted by many landowners
  • 5.  Management of Creek Pastures is Critical Reduce cattle’s time in & near stream Maintain ground cover with proper grazing management
  • 6.  5 yr study on:  Proper grazing management  Alternative water supplies  Alternative shade  Conducted by:  Texas AgriLife Extension Service  Texas AgriLife Research  Texas Water Resources Institute  USDA-ARS  Funded by:  Texas State Soil and Water Conservation Board  USDA Natural Resources Conservation Service  US Environmental Protection Agency Grazingland Research
  • 7. Grazing Management Evaluation  Seven 1 ha sites assessed across 3 locations  3 – ungrazed  3 – properly stocked  1 – stocked @ 2 X recommended rate  Grazed sites were rotationally grazed  Flow measured w/ bubble flow meter  V-notch weir  H-flumes  Sample Collection  Automated samplers
  • 8.  Grazing management effects on E. coli runoff Grazing Management Stocking Rate Unstocked Properly stocked Heavy stocked E.coliConcentration(cfu/100mL) 1e+1 1e+2 1e+3 1e+4 1e+5 1e+6 1e+7 1.E+01 1.E+02 1.E+03 1.E+04 1.E+05 1.E+06 1 10 100 1000 E.coliConc.(cfu/100mL) 12 Month Stocking Rate (ac/AUY) Ungrazed Cultivated Cultivated with grazed pasture Grazed pasture E.coli(cfuper100mL) 1 10 100 1000 10000 100000 Outlier 90th 75th Median Mean 25th 10th
  • 9.  Comparison of E. coli Levels While Sites Stocked & Destocked Cultivated Cultivated with grazed pasture Grazed pasture E.coli(cfuper100mL) 1 10 100 1000 10000 100000 Outlier 90th 75th Median Mean 25th 10th
  • 10.  Why no correlation btwn E. coli & grazing management? Rapid decline following rotation Significant background levels
  • 11.  Why no correlation btwn E. coli & grazing management? 80-99% of loading from wildlife at 3 sites in 2009 Date BB1 BB2 BB3 3/13/09 140 3/25/09 1,200 3/26/09 1,000 7,200 3/27/09 2,000 4/17/09 1,155 980 450 4/18/09 4,400 2,225 2,100 4/28/09 7,600 12,200 24,000 10/4/09 57,000 5,114 3,065 10/9/09 36,000 24,043 15,000 10/13/09 42,851 23,826 5,591 10/22/09 172,500 10/26/09 261,000 181,000 45,000
  • 12.   Rotationally graze creek pastures  Target grazing of creek pastures to dry periods  Rotate cattle to upland pastures during wet periods  88-99% reductions in edge-of-field runoff of bacteria from creek pastures potentially achievable Management Implications
  • 13.  Alternative Water Evaluation Bi-monthly water sampling & quarterly GPS tracking
  • 14.  Alternative water effectiveness Reduction in Time Spent in Stream Reference 43% Wagner et al. 2012 85-94% Miner et al. 1992 Clawson 1993 Sheffield et al. 1997
  • 15. E. coli Load (cfu/AU/day) -57% 43% Reduction
  • 16.   Sheffield (1997) also found:  77% decrease in sedimentation  90% decrease in suspended solids  54% decrease in nitrogen  81% decrease in phosphorus Alternative Water Source Bacteria Reduction Reference 85-95% (EC) Byers et al. 2005 51% (FC) Sheffield 1997
  • 17.  Shade Structure GPS Collar Evaluation Time Spent w/in 25’ of Stream Reference 27% Reduction Wagner et al. 2012  Shade, coupled with alternative water & salt/mineral locations, encourages cattle to spend less time in riparian areas.
  • 18. Conclusions  Rotate cattle to upland pastures during wet periods  Promote loafing, drinking & grazing away from creeks  Alternative water supplies  Additional shade  Proper grazing management  Be aware of impacts of background/wildlife sources

Editor's Notes

  1. You might not have realized it, but bacteria is the #1 cause of water pollution in Texas. In fact, more than 50% of the impairments in Texas are due to excess bacteria levels. But, you would never know it. While some water pollution is often easy to detect, bacteria pollution is not. A waterbody choked with algae, a muddy river loaded with sediment, or a lake covered with an oily sheen all exhibit clearly noticeable impairments. Bacteria in water, on the other hand, are not at all noticeable to the naked eye.
  2. No difference in E. coli concentrations at ungrazed, proper grazed & heavy grazed pasturesNo correlation between stocking rate & E. coli concentrations
  3. Significant correlation between E. coli concentration & cattle presence during runoff eventAt all grazed sites, I found that the highest E. coli concentrations occurred while the sites were stocked.At BB2, conc 88% lower when destockedThis appears to be the primary factor determining E. coli conc from my sitesAt BB3, conc 98% lower when destockedAt SW17, conc 99% lower when destocked
  4. E. coli levels in runoff declined rapidly after rotationLevels reach background levels within 1 month (typically 2 wks)Background E. coli levels were SIGNIFICANTMedian E. coli levels at ungrazed & destocked sites ranged from 3,500 to 5,500 cfu/10080-99% of loading from 3 sites in 2009 was from wildlife
  5. To summarize my findings from Objective II, my study indicatesthat the timing…
  6. Found 57% reduction in EC load (on animal unit basis) however NSD due to highly variability
  7. Background E. coli levels were considerable and relatively consistent across all sites, with median levels typically ranging from 3,500 to 5,500 cfu/100 mL. Most existing water quality modeling efforts, TMDL projects, and other watershed assessment and planning efforts do not take background E. coli levels into account. However, because background concentrations have been found by this study and others (Guzman et al. 2010) to be a significant component of total E. coli in runoff, especially as time lag between fecal deposition by livestock (i.e. grazing event or manure or litter spreading) and runoff event increases, this source should be considered as a separate source when allocating loads and assessing load reductions