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

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 - 5 2009 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; 0.3+ 0.27 ppm  Range N.D. to 26.7 ppm

 May vs September, non significant P = 0.56  September mean = 0.2+ 0.2 Range =nd - 6.4  May mean = 0.4+ 0.2 Range =nd – 26.7

Results – Effect of sample year  2009, 2010, 2011, 2012 & 2013 - non significant P = 0.49 Item20092010201120122013 Mean0.21 0.54 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 N0.380-6.4 SE0.130-2.5 SW0.420-26.7

Nitrate N840.380-6.40*100 SE780.130-2.50 SW860.420-26.70 creek520.590-26.70 ground720.10-1.10 reservoir680.120-20 spring560.590-6.40 dry1130.20-6.40 wet1350.420-26.70 2009810.210-6.40 2010830.210-5.90 2011840.540-26.70

Sodium Item Flowing GroundReservoirSpringSE +mean upper limit N2574441252650213*300 SE23944318143863325 SW58641022011849333 X360432175194 20092010201120122013 wet21125724429522338246 dry22423045339328648318 N17825222220516847205 SE23326234143832253319 SW24121648238927346320 X217243348344254 Flowing16125559340520566332 Ground47143240442352349 Reservoir9711220128210155158 Spring14217419626218856193

Item Number of samples Analyzed Average Concentration ppm Range of Concentration % of Samples Exceeding Max Upper Level for Livestock Maxiumum upper limit Calcium39347.50.51-9122.5200 ppm, Chloride39314.90-2550300 Fluoride3931.10-818*2 Iron39315.90-119266*0.4 Magnesium39325.50.14-5293*100 Manganese3930.30-19.811*0.5 Nitrate3930.290-26.70*100 pH3938.36.95-10.636*8.5 Sodium3932815.72-375742*300 Sulfate3933660-959137*300 TDS39393983-94901.5*3000 Temperature 39360° F42-81° F Summary Results for all Minerals 2009 to 2013

Sulfate Item FlowingGroundReservoirSpringSE +mean upper limit N40745415345117264*300 SE179517287701147421 SW126082398157115474 X582351279301 20092010201120122013 N168303335262203109254 SE281273554588497122415 SW1581621005555308107468 X206246631468336 Flowing1443261397608337153562 Ground392319322370518113384 Reservoir81126431468119128245 Spring192213377427371130316

Sulfate Item FlowingGroundReservoirSpringSE +mean upper limit N40745415345117264*300 SE179517287701147421 SW126082398157115474 X582351279301 20092010201120122013 N168303335262203109 SE281273554497122415 SW158162308107468 X206246 631468 336 Flowing1443261397608337153562 Ground392319322370518113384 Reservoir81126431468119128245 Spring192213377427371130316

Iron Item FlowingGroundReservoirSpringSE +mean upper limit N29300198*0.4 SE4515172317 SW1463110.21840 X73256 20092010201120122013 Flowing302615235023332 Ground0.41.05.03.05.017 Reservoir8131002819158 Spring131261120193 X 1011106111

TDS Item FlowingGroundReservoirSpringSE +mean upper limit N8791362450331129756*3000 SE800138566214491621074 SW176611267596541271076 X11481291623811 20092010201120122013 wet696809884795102837 dry7747539951241060 N635811815776669124741 SE8118441125144010841391060 SW758689160312459321211045 X73478111811153895 Flowing579780186712867891741061 Ground137012361256130115551291346 Reservoir344392746998357145567 Spring6477178541030879148825

$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 % 0.365 % 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 % 0.171 % 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

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

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