Mark Petersen, Jen Muscha & Travis Mulliniks USDA-ARS Fort Keogh Livestock & Range Research Laboratory

OUTLINE  Background Water quality questions Fort Keogh Customer Focus Group inquired about: Variability in water quality? Predictability of changes ? How much does water quality change? Objective: To determine the effect of year, location, season and source on nitrate concentration and other water quality characteristics.

 55,000+ acre near Miles City, MT,  96 % of the land has been maintained as native range  2,000 acres cultivated corn silage, barley grain & hay  2 feedlot s with 999 head capacity

Water Quality Studies

 Samples were collected from 4 sources: Springs reservoirs ground water flowing surface water  Sites classified into 3 geographical locations: north (N), southeast (SE) and southwest (SW).

WATER QUALITY RESEARCH– Ft Keogh LARRL 2009, 2010, 2011, 2012 and 2013

 Other variables accounted for :  Season Wetter – May Drier – September  Year to 2013

OUTLINE  Yearly Variability August 16, 2012 – Lower Coal Pasture August 18, 2011 – Lower Coal Pasture

 45 sample site  450 possible samples could be collected  Only 393 were collected All May samples were collected with exception of 1 In September, 56 samples could not be collected (25% of sites dried up)

CURRENT WATER QUALITY RESEARCH–Ft Keogh LARRL CURRENT WATER QUALITY RESEARCH–Ft Keogh LARRL Analysis included; Analysis included; Nitrates, sulfates Sodium, chloride, calcium, magnesium Manganese, iron, fluoride pH/ alkalinity Conductivity, total dissolved solids Temperature Midwest laboratories, Omaha

 Location, source, year, sampling date, and their interactions were analyzed : As 3 × 4 x 5 x 2 factorial arrangement of treatments.  Sampling date was not a significant (P>0.05) factor influencing nitrate concentrations.

 Average nitrate concentration for all samples collected; ppm  Range N.D. to 26.7 ppm

 May vs September, non significant P = 0.56  September mean = Range =nd  May mean = Range =nd – 26.7

Results – Effect of sample year  2009, 2010, 2011, 2012 & non significant P = 0.49 Item Mean Range0 – 6.40 – 5.90 – 26.7

 A location by source interaction (P<0.05) was found for nitrates. The highest concentration of nitrates was found in spring water in the north (1.38 ± 0.27 ppm) and flowing water in the southwest (0.93 ± 0.26 ppm).

LocationAverageRange N SE SW

Nitrate N *100 SE SW creek ground reservoir spring dry wet

Sodium Item Flowing GroundReservoirSpringSE +mean upper limit N *300 SE SW X wet dry N SE SW X Flowing Ground Reservoir Spring

Item Number of samples Analyzed Average Concentration ppm Range of Concentration % of Samples Exceeding Max Upper Level for Livestock Maxiumum upper limit Calcium ppm, Chloride Fluoride *2 Iron *0.4 Magnesium *100 Manganese *0.5 Nitrate *100 pH *8.5 Sodium *300 Sulfate *300 TDS *3000 Temperature 39360° F42-81° F Summary Results for all Minerals 2009 to 2013

Sodium Item Flowing GroundReservoirSpringSE +mean upper limit N *300 SE SW X wet dry N SE SW X Flowing Ground Reservoir Spring

Sodium Item Flowing GroundReservoirSpringSE +mean upper limit N *300 SE SW X wet dry N SE SW X Flowing Ground Reservoir Spring

Sodium Item Flowing GroundReservoirSpringSE +mean upper limit N *300 SE SW X wet dry N SE SW X Flowing Ground Reservoir Spring

Sodium Item Flowing GroundReservoirSpringSE +mean upper limit N *300 SE SW X wet dry N SE SW X Flowing Ground Reservoir Spring

Sulfate Item FlowingGroundReservoirSpringSE +mean upper limit N *300 SE SW X N SE SW X Flowing Ground Reservoir Spring

Sulfate Item FlowingGroundReservoirSpringSE +mean upper limit N *300 SE SW X N SE SW X Flowing Ground Reservoir Spring

Sulfate Item FlowingGroundReservoirSpringSE +mean upper limit N *300 SE SW X N SE SW X Flowing Ground Reservoir Spring

Sulfate Item FlowingGroundReservoirSpringSE +mean upper limit N *300 SE SW X N SE SW X Flowing Ground Reservoir Spring

Iron Item FlowingGroundReservoirSpringSE +mean upper limit N *0.4 SE SW X Flowing Ground Reservoir Spring X

Iron Item FlowingGroundReservoirSpringSE +mean upper limit N *0.4 SE SW X Flowing Ground Reservoir Spring X

Iron Item FlowingGroundReservoirSpringSE +mean upper limit N300198*0.4 SE SW X Flowing Ground Reservoir Spring X

Iron Item FlowingGroundReservoirSpringSE +mean upper limit N300198*0.4 SE SW X Flowing Ground Reservoir Spring X

Iron Item FlowingGroundReservoirSpringSE +mean upper limit N300198*0.4 SE SW X Flowing Ground Reservoir Spring X

Iron Item FlowingGroundReservoirSpringSE +mean upper limit N *0.4 SE SW X Flowing Ground Reservoir Spring X

Iron Item FlowingGroundReservoirSpringSE +mean upper limit N *0.4 SE SW X Flowing23332 Ground Reservoir Spring X

Iron Item FlowingGroundReservoirSpringSE +mean upper limit N *0.4 SE SW X Flowing2355 Ground Reservoir Spring X 61

TDS Item FlowingGroundReservoirSpringSE +mean upper limit N *3000 SE SW X wet dry N SE SW X Flowing Ground Reservoir Spring

TDS Item FlowingGroundReservoirSpringSE +mean upper limit N *3000 SE SW X wet dry N SE SW X Flowing Ground Reservoir Spring

TDS Item FlowingGroundReservoirSpringSE +mean upper limit N *3000 SE SW X wet dry N SE SW X Flowing Ground Reservoir Spring

TDS Item FlowingGroundReservoirSpringSE +mean upper limit N *3000 SE SW X wet dry N SE SW X Flowing Ground Reservoir Spring

$285 20,000 ppm TDS

Especially surface flowing water and in the south

PREDICTING MINERAL INTAKE FROM WATER PREDICTING MINERAL INTAKE FROM WATER ItemWater analysisAmt supplied in water Calcium1.04 ppm0.045 g/d Chloride14 ppm0.604 g/d Fluoride3.3 ppm142.4 mg/d Iron0.04 ppm1.726 mg/d Magnesium0.29 ppm0.013 g/d Sodium365.0 ppm15.75 g/d Sulfur45.29 ppm1.95 g/d 28 g = 1 oz

PREDICTING MINERAL INTAKE FROM WATER & DIET PREDICTING MINERAL INTAKE FROM WATER & DIET Item Minerals Diet water & diet Required intake calcium0.48 %0.484 %0.36 % Chloride14 ppm 0.06 %? Fluoride142 ppm (hi) ? (hi) Iron1,378 ppm 1,379 ppm 50 ppm (hi) Magnesium0.17 %0.171 %0.20 % (lo) Sodium0.032 % 1.61 % 0.1 % (hi) Sulfur0.17 % % 0.15 % (hi) Copper3.0 ppm 10 ppm (lo) Manganese83.0 ppm 40 ppm Phosphorus0.18% 0.23 % (lo) Potassium1.30 %1.31 %0.70 % Selenium0.13 ppm 0.1 ppm Zinc21.O ppm21.0 ppm30 ppm (lo)

PREDICTING MINERAL INTAKE FROM WATER & DIET PREDICTING MINERAL INTAKE FROM WATER & DIET Item Minerals Diet water & diet Required calcium0.48 %0.484 %0.36 % Chloride14 ppm 0.06 %? Fluoride142 ppm? Iron1,378 ppm1,379 ppm50 ppm (hi) Magnesium0.17 % % 0.20 % (lo) Sodium0.032 %1.61 %0.1 % (hi) Sulfur0.17 %0.365 %0.15 % (hi) Copper3.0 ppm 10 ppm (lo) Manganese83.0 ppm 40 ppm Phosphorus0.18%0.18% 0.23 % (lo) Potassium1.30 %1.31 %0.70 % Selenium0.13 ppm 0.1 ppm Zinc21.O ppm 21.0 ppm 30 ppm (lo)

 Excess Sodium Sulfate Iron Fluoride  Deficient Magnesium Phosphorus Copper Zinc

 Need to know water quality  Multiple water sites pasture  During drought forced to drink poorer water At Ft Keogh use North in summer drought At Ft Keogh use North in summer drought  Use known poor water pasture in winter Use southeast in winter Use southeast in winter  Early spring may dilute poor water

 May result in reduced mineral intake  Water quality is highly variable Source Source Location Location Season Season Year Year  Especially in a dry year check TDS before cattle are moved to a fresh pasture.

 Factors influencing voluntary loose mineral consumption – speculated season of the year season of the year water salinity water salinity daily temperature daily temperature salt bush frequency salt bush frequency forage maturity forage maturity vegetation dry matter content vegetation dry matter content

 To evaluate variation in herd mineral intake, individual cow mineral tub use due season and daily high temperature 80 mixed-age native English cross-bred cows, access to open range mineral tub (containing 34% salt, 57% minerals and 9% distillers grain) Cows rotationally grazed native range. Data not collected in Feb & Mar. Bushnell Trophy Cam XLT motion activated trail cameras recorded daily appearance.

 Magnitude of variability in mineral consumption  Productivity influences due to mineral consumption

Percent of cows at mineral tub daily throughout study from August 2010-June 2011

Percent of cows at mineral tub Average mineral daily consumption daily by growing season (P<0.01). by growing season (P<0.01). % of cows at mineral tub grams consumed head/day

 Supply mineral to “fix” known deficiencies  Intake is not predictable  Our next step add titanium

 Why titanium?  Not in environment  Marker for intake  Collected 1,400 fecal samples

 Rank cows by Ti concentration  Assumption ; Higher Ti consume more  Evaluate Ti on calving interval in days Weaning weight Cow wt change weaning to weaning

 Leading conclusion Need to test Portable TDS meter  Need to develop methods to improve stock water quality

 Water sample collection  Plucked forage samples  Mineral analysis  Calculated diet composition

 Mineral research program Water quality Forages Self fed mineral