Economic Impact of Heat StressN. R. St-PierreThe Ohio State University
Copyright 2013, N. St-Pierre, The Ohio State University
Objectives• To present a simple model for quantifyingfinancial losses due to heat stress across allmajor commercial livest...
Model Overview• Used historical weather data to quantify themultivariate distribution of temperature andrelative humidity ...
Weather• Number of reporting stations: 257• Earliest reports start between 1871 and 1932• Data include daily:Minimum and ...
Weather• Data were summarized by State and by month:Mean, variance and covariances of:o Minimum temperature (Tl)o Maximum...
Weather• Within day changes in T and H modeled as sinefunctions with simultaneity of Tl and Hu, and ofTuans Hl.• T and H i...
WeatherTwo Integrative VariablesCopyright 2013, N. St-Pierre, The Ohio State University
Livestock ClassesCopyright 2013, N. St-Pierre, The Ohio State University
Economic Losses• For each livestock class:DMI loss (economic gain)Production lossDays open lossReproductive culling lo...
Economic LossesDairy Cows• Threshold at 70o THI (e.g., 75o F, 50% H)• DMI loss = 0.0760 x (THIMax-70)2x D• Milk loss = 0.1...
WeatherTwo Integrative Variables(THIMAX – 70)2Copyright 2013, N. St-Pierre, The Ohio State University
Economic LossesDairy Cows• Threshold at 70o THI (e.g., 75o F, 50% H)• DMI loss = 0.0760 x (THIMax-70)2x D• Milk loss = 0.1...
Unit Costs for Five Loss CategoriesCopyright 2013, N. St-Pierre, The Ohio State University
Description of Cooling SystemsMinimal(Fans)Moderate(Sprinklers)Aggressive(Evaporative)Beef Cows Fans +Sprinklers Evaporati...
Reduction in THI from Fan CoolingCopyright 2013, N. St-Pierre, The Ohio State University
Reduction in THI from Sprinkler CoolingCopyright 2013, N. St-Pierre, The Ohio State University
Reduction in THI from Evaporative CoolingCopyright 2013, N. St-Pierre, The Ohio State University
Cooling Costs• Capital Cost10 year depreciation8% interest2-5%/year for maintenance• Operating Cost$0.09/kWh$0.01/h p...
Average Minimum Temperature - July71.772.168.267.169.853.651.459.060.6Copyright 2013, N. St-Pierre, The Ohio State Univers...
Average Maximum Temperature - July94.8100.177.480.892.592.590.991.2Copyright 2013, N. St-Pierre, The Ohio State University
Average Minimum Relative Humidity - July562214668455406858Copyright 2013, N. St-Pierre, The Ohio State University
Average Maximum Relative Humidity - July94744794818289Copyright 2013, N. St-Pierre, The Ohio State University
Average Minimum THI - July68.965.351.660.772.658.366.265.8Copyright 2013, N. St-Pierre, The Ohio State University
Average Maximum THI - July86.081.576.275.281.173.781.1Copyright 2013, N. St-Pierre, The Ohio State University91.6
Milk Production Losses - Dairy CowsNo Cooling - JULY1235108690251194Loss in lbs/month Copyright 2013, N. St-Pierre, The Oh...
Gain Losses - Poultry BroilersNo Cooling - JULY18.3Loss in lbs/month per 1000 birds7.53.11.312.112.8
Total Cost per Animal - Dairy CowsMinimum Cooling - Annual Basis13562131121401310Copyright 2013, N. St-Pierre, The Ohio St...
Total Cost - Dairy CowsMinimum Cooling- Annual Basis, in million $199Cost in million $Cost in million $13747205369Copyrigh...
Total Cost - Dairy CowsSprinklers - Annual Basis, in million $34471991043512Copyright 2013, N. St-Pierre, The Ohio State U...
Optimal System - Dairy CalvesNo Cooling Fans Sprinklers Evaporative CoolingCopyright 2013, N. St-Pierre, The Ohio State Un...
Optimal System - Dairy CowsNo Cooling Fans Sprinklers Evaporative CoolingCopyright 2013, N. St-Pierre, The Ohio State Univ...
Optimal System - Poultry LayersNo Cooling Fans Tunnel Evaporative CoolingCopyright 2013, N. St-Pierre, The Ohio State Univ...
Optimal System - Poultry TurkeysNo Cooling Fans Tunnel Evaporative CoolingCopyright 2013, N. St-Pierre, The Ohio State Uni...
Optimal System - Swine SowsNo Cooling Fans Sprinklers Evaporative CoolingCopyright 2013, N. St-Pierre, The Ohio State Univ...
Optimal System - Swine Feeder PigsNo Cooling Fans Sprinklers Evaporative CoolingCopyright 2013, N. St-Pierre, The Ohio Sta...
Economic Efficiency of Heat Abatement SystemsCost of Optimal System Cost of No Cooling0.460.710.750.620.610.730.870.870.90...
TX MO NE OK SDOptimal System None None None None NoneDMI Loss 0 0 0 0 0Gain Loss 0 0 0 0 0DO Loss 15.5 2.2 1.5 3.6 1.0Repr...
TX KS NE CO OKOptimal System None None None None NoneDMI Loss (34.8) (12.2) (10.8) (1.9) (3.8)Gain Loss 162.0 57.1 50.5 8....
CA WI NY PA MNOptimal System Sprinkler Sprinkler Sprinkler Sprinkler SprinklerDMI Loss (31.6) (10.8) (3.6) (10.0) (6.2)Gai...
NC IA MN IL MOOptimal System Sprinkler Sprinkler None Sprinkler SprinklerDMI Loss 0 0 0 0 0Gain Loss 0 0 0 0 0DO Loss 10.2...
NC IA MN IL MOOptimal System None None None None NoneDMI Loss (12.0) (7.5) (2.2) (3.9) (4.9)Gain Loss 54.0 33.8 10.0 17.4 ...
Total Cost of Heat Stressto U.S. Livestock IndustriesW/o Heat Abatement Systems: 2.7 billion $/yrW Optimal Systems: 1.9 bi...
Impact of Climate Change on Future CostsAn honest discussion on the difficultiesof forecasting weather and temperaturesCop...
Temperature Forecasting Issues• IPCC forecasts failed to abide by seventy-two ofeighty-nine forecasting principles1:Agree...
Temperature Forecasting Issues“You cannot assume that a model with millionsand millions lines of code, literally millionso...
Predictions and ForecastsData driven predictions can succeed – and theycan fail. It is when we deny our role in theprocess...
Predictions and ForecastsWe have a prediction problem. We love topredict things – and we aren’t very good at it.Nate Silve...
I am a DENIER!Copyright 2013, N. St-Pierre, The Ohio State University
I am a DENIER!I can live with doubt and uncertainty and notknowing. I think it is much more interesting tolive not knowing...
The Essence of ScienceWhen a scientist doesn’t know the answer to aproblem, he is ignorant. When he has a hunch asto what ...
A responsibilityIf we suppress all discussion, all criticism,saying, “This is it boys!”… and thus we doomman for a long ti...
A Principled ScientistIt’s a kind of scientific integrity, a principle ofscientific thought that corresponds to a kind ofu...
U.S. Temperature DataCopyright 2013, N. St-Pierre, The Ohio State University
U.S. Temperature DataCopyright 2013, N. St-Pierre, The Ohio State University
Copyright 2013, N. St-Pierre, The Ohio State University
Copyright 2013, N. St-Pierre, The Ohio State University
Trends in Hurricane IntensityCopyright 2013, N. St-Pierre, The Ohio State University
Trends in Hurricane IntensityCopyright 2013, N. St-Pierre, The Ohio State University
Copyright 2013, N. St-Pierre, The Ohio State University
Great Lakes Ice CoverageCopyright 2013, N. St-Pierre, The Ohio State University
Great Lakes Ice CoverageCopyright 2013, N. St-Pierre, The Ohio State University
Arctic Ice Extent in September
Arctic Ice Extent in September
Arctic Ice Extent in September
Oceans AcidificationCopyright 2013, N. St-Pierre, The Ohio State University
PteropodsSeawater with pH and carbonate projected for the year 2100Copyright 2013, N. St-Pierre, The Ohio State University
Oceans AcidificationCopyright 2013, N. St-Pierre, The Ohio State University
PteropodsSeawater with pH and carbonate projected for the year 2100Copyright 2013, N. St-Pierre, The Ohio State University
Predictions and ForecastsThe conditions of the universe are knowable onlywith some degree of certainty.Copyright 2013, N. ...
Predictions and ForecastsTwo strikes in weather forecasting:• The systems are dynamicThe behavior of the system at one po...
Climate Forecasts• How much uncertainty is in the forecast?• How right or wrong have the predictions been sofar?• How much...
How Cows Dissipate Heat• Conduction• Convection• Radiation• Evaporative coolingCopyright 2013, N. St-Pierre, The Ohio Stat...
Flow of Energy (Mcal/day)40 lbs 120 lbsGross Energy 73.4 135.7Feces 25.7 40.7Digestible Energy 47.7 95.0Urine 5.6 11.0Gas ...
A Simplified Cow...Ta TeEg>EdThe cow The environmentkdkdαΔ TΔ TCopyright 2013, N. St-Pierre, The Ohio State University
Increased Productivity vs. Global Warming• The current IPCC forecasts predict that thetemperatures might increase by 1.2 °...
Increased Productivity vs. Global Warming• Current animal productivity averages ~ 70lbs/cow per day nationally.Results in...
Increased Productivity vs. Global Warming• The current IPCC forecasts predict that thetemperatures might increase by 1.2 °...
The Real Issue• Current cooling systems are not very energyefficient and they all rely on significant amountsof water bein...
The Real Issue• Current cooling systems are not very energyefficient and they all rely on significant amountsof water.Wil...
Closing CommentsCopyright 2013, N. St-Pierre, The Ohio State University
The End
Economic Impact of Heat Stress
Economic Impact of Heat Stress
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Farm animals have well known zones of thermal comfort (ZTC). The range of ZTC is primarily dependent on the species, the physiological status of the animals, the relative humidity and velocity of ambient air, and the degree of solar radiation. Economic losses are incurred by the U.S. livestock industries because farm animals are raised in locations and/or seasons where temperature conditions venture outside the ZTC. The objective of this presentation is to provide current estimates of the economic losses sustained by major U.S. livestock industries from thermal stress and to outline future challenges as animal productivity is improved. Species (production) considered are: chicken (meat), chicken (eggs), turkey (meat), cattle (meat), cattle (milk), and pig (meat).

http://www.extension.org/pages/67799/current-and-future-economic-impact-of-heat-stress-in-the-us-livestock-and-poultry-sectors

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Economic Impact of Heat Stress

  1. 1. Economic Impact of Heat StressN. R. St-PierreThe Ohio State University
  2. 2. Copyright 2013, N. St-Pierre, The Ohio State University
  3. 3. Objectives• To present a simple model for quantifyingfinancial losses due to heat stress across allmajor commercial livestock industries in theU.S.,• To peek into the future:Global warmingIncrease in animal productivityCopyright 2013, N. St-Pierre, The Ohio State University
  4. 4. Model Overview• Used historical weather data to quantify themultivariate distribution of temperature andrelative humidity for each of the 48 lower States.• Summarized research data to quantify therelationships between magnitude of heat stress,duration of heat stress, and expectedperformance across 10 livestock classes.Copyright 2013, N. St-Pierre, The Ohio State University
  5. 5. Weather• Number of reporting stations: 257• Earliest reports start between 1871 and 1932• Data include daily:Minimum and maximum temperature (T)Minimum and maximum relative humidity (H)Rain and snow precipitationSnow coverCopyright 2013, N. St-Pierre, The Ohio State University
  6. 6. Weather• Data were summarized by State and by month:Mean, variance and covariances of:o Minimum temperature (Tl)o Maximum temperature Tu)o Minimum relative humidity (Hl)o Maximum relative humidity (Hu)Copyright 2013, N. St-Pierre, The Ohio State University
  7. 7. Weather• Within day changes in T and H modeled as sinefunctions with simultaneity of Tl and Hu, and ofTuans Hl.• T and H integrated into a Temperature-HumidityIndex (65% dry-bulb temperature, 35% wet-bulbtemperature).Copyright 2013, N. St-Pierre, The Ohio State University
  8. 8. WeatherTwo Integrative VariablesCopyright 2013, N. St-Pierre, The Ohio State University
  9. 9. Livestock ClassesCopyright 2013, N. St-Pierre, The Ohio State University
  10. 10. Economic Losses• For each livestock class:DMI loss (economic gain)Production lossDays open lossReproductive culling lossMortality lossCopyright 2013, N. St-Pierre, The Ohio State University
  11. 11. Economic LossesDairy Cows• Threshold at 70o THI (e.g., 75o F, 50% H)• DMI loss = 0.0760 x (THIMax-70)2x D• Milk loss = 0.1532 x (THIMax-70)2x Dwhere D = Proportion of a day above threshold• PR = 0.20 - 0.0009 xHeatload• DO loss = 164.5 - 184.5 PR + 29.38 PR2 - 128.75• RCullRate = 100 - 102.7(1-1.10109 EXP(10.1874 x PR)• Pmonthlydeath = 0.000855 EXP(0.00981 xHeatload)Copyright 2013, N. St-Pierre, The Ohio State University
  12. 12. WeatherTwo Integrative Variables(THIMAX – 70)2Copyright 2013, N. St-Pierre, The Ohio State University
  13. 13. Economic LossesDairy Cows• Threshold at 70o THI (e.g., 75o F, 50% H)• DMI loss = 0.0760 x (THIMax-70)2x D• Milk loss = 0.1532 x (THIMax-70)2x Dwhere D = Proportion of a day above threshold• PR = 0.20 - 0.0009 xHeatload• DO loss = 164.5 - 184.5 PR + 29.38 PR2 - 128.75• RCullRate = 100 - 102.7(1-1.10109 EXP(10.1874 x PR)• Pmonthlydeath = 0.000855 EXP(0.00981 xHeatload)Copyright 2013, N. St-Pierre, The Ohio State University
  14. 14. Unit Costs for Five Loss CategoriesCopyright 2013, N. St-Pierre, The Ohio State University
  15. 15. Description of Cooling SystemsMinimal(Fans)Moderate(Sprinklers)Aggressive(Evaporative)Beef Cows Fans +Sprinklers EvaporativeBeef Finish Fans +Sprinklers EvaporativeDairy Calves Fans +Sprinklers EvaporativeDairy Cows Fans +Sprinklers EvaporativeDairy Yearlings Fans +Sprinklers EvaporativePoultry Broilers Fans Tunnel EvaporativePoultry Layers Fans Tunnel EvaporativePoultry Turkey Fans Tunnel EvaporativeSwine Feeders Fans +Sprinklers Cool CellsSwine Sows Fans +Sprinklers Cool CellsCopyright 2013, N. St-Pierre, The Ohio State University
  16. 16. Reduction in THI from Fan CoolingCopyright 2013, N. St-Pierre, The Ohio State University
  17. 17. Reduction in THI from Sprinkler CoolingCopyright 2013, N. St-Pierre, The Ohio State University
  18. 18. Reduction in THI from Evaporative CoolingCopyright 2013, N. St-Pierre, The Ohio State University
  19. 19. Cooling Costs• Capital Cost10 year depreciation8% interest2-5%/year for maintenance• Operating Cost$0.09/kWh$0.01/h per unit for water0.65 kW/h for fans (92 cm), 2.55 kW/h forevaporative coolingCopyright 2013, N. St-Pierre, The Ohio State University
  20. 20. Average Minimum Temperature - July71.772.168.267.169.853.651.459.060.6Copyright 2013, N. St-Pierre, The Ohio State University
  21. 21. Average Maximum Temperature - July94.8100.177.480.892.592.590.991.2Copyright 2013, N. St-Pierre, The Ohio State University
  22. 22. Average Minimum Relative Humidity - July562214668455406858Copyright 2013, N. St-Pierre, The Ohio State University
  23. 23. Average Maximum Relative Humidity - July94744794818289Copyright 2013, N. St-Pierre, The Ohio State University
  24. 24. Average Minimum THI - July68.965.351.660.772.658.366.265.8Copyright 2013, N. St-Pierre, The Ohio State University
  25. 25. Average Maximum THI - July86.081.576.275.281.173.781.1Copyright 2013, N. St-Pierre, The Ohio State University91.6
  26. 26. Milk Production Losses - Dairy CowsNo Cooling - JULY1235108690251194Loss in lbs/month Copyright 2013, N. St-Pierre, The Ohio State University
  27. 27. Gain Losses - Poultry BroilersNo Cooling - JULY18.3Loss in lbs/month per 1000 birds7.53.11.312.112.8
  28. 28. Total Cost per Animal - Dairy CowsMinimum Cooling - Annual Basis13562131121401310Copyright 2013, N. St-Pierre, The Ohio State University
  29. 29. Total Cost - Dairy CowsMinimum Cooling- Annual Basis, in million $199Cost in million $Cost in million $13747205369Copyright 2013, N. St-Pierre, The Ohio State University
  30. 30. Total Cost - Dairy CowsSprinklers - Annual Basis, in million $34471991043512Copyright 2013, N. St-Pierre, The Ohio State University
  31. 31. Optimal System - Dairy CalvesNo Cooling Fans Sprinklers Evaporative CoolingCopyright 2013, N. St-Pierre, The Ohio State University
  32. 32. Optimal System - Dairy CowsNo Cooling Fans Sprinklers Evaporative CoolingCopyright 2013, N. St-Pierre, The Ohio State University
  33. 33. Optimal System - Poultry LayersNo Cooling Fans Tunnel Evaporative CoolingCopyright 2013, N. St-Pierre, The Ohio State University
  34. 34. Optimal System - Poultry TurkeysNo Cooling Fans Tunnel Evaporative CoolingCopyright 2013, N. St-Pierre, The Ohio State University
  35. 35. Optimal System - Swine SowsNo Cooling Fans Sprinklers Evaporative CoolingCopyright 2013, N. St-Pierre, The Ohio State University
  36. 36. Optimal System - Swine Feeder PigsNo Cooling Fans Sprinklers Evaporative CoolingCopyright 2013, N. St-Pierre, The Ohio State University
  37. 37. Economic Efficiency of Heat Abatement SystemsCost of Optimal System Cost of No Cooling0.460.710.750.620.610.730.870.870.900.790.860.82 0.730.770.690.640.710.910.670.590.790.740.700.610.660.750.620.640.720.650.630.670.650.760.710.790.590.520.75Copyright 2013, N. St-Pierre, The Ohio State University
  38. 38. TX MO NE OK SDOptimal System None None None None NoneDMI Loss 0 0 0 0 0Gain Loss 0 0 0 0 0DO Loss 15.5 2.2 1.5 3.6 1.0Repro Cull Loss 0 0 0 0 0Death Loss 17.7 2.9 2.0 4.4 1.3Capital Cost 0 0 0 0 0Operating Cost 0 0 0 0 0Total Cost 33.2 5.1 3.4 8.0 2.2Beef CowsEconomic Losses (Million $)Five Largest Producing StatesCopyright 2013, N. St-Pierre, The Ohio State University
  39. 39. TX KS NE CO OKOptimal System None None None None NoneDMI Loss (34.8) (12.2) (10.8) (1.9) (3.8)Gain Loss 162.0 57.1 50.5 8.9 17.6DO Loss 0 0 0 0 0Repro Cull Loss 0 0 0 0 0Death Loss 19.0 5.0 4.5 0.6 1.9Capital Cost 0 0 0 0 0Operating Cost 0 0 0 0 0Total Cost 146.6 49.8 44.2 7.6 15.7Beef FinishEconomic Losses (Million $)Five Largest Producing StatesCopyright 2013, N. St-Pierre, The Ohio State University
  40. 40. CA WI NY PA MNOptimal System Sprinkler Sprinkler Sprinkler Sprinkler SprinklerDMI Loss (31.6) (10.8) (3.6) (10.0) (6.2)Gain Loss 103.2 35.3 11.6 32.7 20.4DO Loss 23.3 11.4 4.5 8.9 5.7Repro Cull Loss 7.4 3.2 1.2 2.8 1.7Death Loss 2.3 1.0 0.4 0.9 0.5Capital Cost 13.7 11.6 5.9 5.3 4.6Operating Cost 18.3 11.6 5.4 7.3 4.8Total Cost 136.6 63.3 25.4 47.9 31.5Dairy CowsEconomic Losses (Million $)Five Largest Producing States (2002)Copyright 2013, N. St-Pierre, The Ohio State University
  41. 41. NC IA MN IL MOOptimal System Sprinkler Sprinkler None Sprinkler SprinklerDMI Loss 0 0 0 0 0Gain Loss 0 0 0 0 0DO Loss 10.2 6.8 4.0 3.5 5.3Repro Cull Loss 0 0 0 0 0Death Loss 0.1 0.1 0 0 0.1Capital Cost 3.7 3.2 0 1.4 1.2Operating Cost 5.4 3.3 0 1.7 2.0Total Cost 19.3 13.4 4.1 6.7 8.5Swine SowsEconomic Losses (Million $)Five Largest Producing StatesCopyright 2013, N. St-Pierre, The Ohio State University
  42. 42. NC IA MN IL MOOptimal System None None None None NoneDMI Loss (12.0) (7.5) (2.2) (3.9) (4.9)Gain Loss 54.0 33.8 10.0 17.4 22.1DO Loss 0 0 0 0 0Repro Cull Loss 0 0 0 0 0Death Loss 0.9 0.5 0.1 0.3 0.4Capital Cost 0 0 0 0 0Operating Cost 0 0 0 0 0Total Cost 42.9 26.8 7.9 13.8 17.6Swine FeederEconomic Losses (Million $)Five Largest Producing StatesCopyright 2013, N. St-Pierre, The Ohio State University
  43. 43. Total Cost of Heat Stressto U.S. Livestock IndustriesW/o Heat Abatement Systems: 2.7 billion $/yrW Optimal Systems: 1.9 billion $/yrCopyright 2013, N. St-Pierre, The Ohio State University
  44. 44. Impact of Climate Change on Future CostsAn honest discussion on the difficultiesof forecasting weather and temperaturesCopyright 2013, N. St-Pierre, The Ohio State University
  45. 45. Temperature Forecasting Issues• IPCC forecasts failed to abide by seventy-two ofeighty-nine forecasting principles1:Agreement among forecasters is not related toaccuracyThe complexity of the global warming problemmake’s forecasting a fool’s errand – The morecomplex you make the model the worse the forecastgets.The forecasts do not adequately account for theuncertainty intrinsic to the global warming problem.Kester C. Green and J. Scott Armstrong. 2007. Global warming: Forecast by scientists versesscientific forecasts. Energy and the Environment 18:718.Copyright 2013, N. St-Pierre, The Ohio State University
  46. 46. Temperature Forecasting Issues“You cannot assume that a model with millionsand millions lines of code, literally millionsof instructions, that there isn’t a mistake in there”K. Emmanuel, M.I.T.Copyright 2013, N. St-Pierre, The Ohio State University
  47. 47. Predictions and ForecastsData driven predictions can succeed – and theycan fail. It is when we deny our role in theprocess that the odds of failure rises.Copyright 2013, N. St-Pierre, The Ohio State UniversityNate Silver.
  48. 48. Predictions and ForecastsWe have a prediction problem. We love topredict things – and we aren’t very good at it.Nate Silver.Copyright 2013, N. St-Pierre, The Ohio State University
  49. 49. I am a DENIER!Copyright 2013, N. St-Pierre, The Ohio State University
  50. 50. I am a DENIER!I can live with doubt and uncertainty and notknowing. I think it is much more interesting tolive not knowing than to have answers whichmight be wrong.Richard P. FeynmanCopyright 2013, N. St-Pierre, The Ohio State University
  51. 51. The Essence of ScienceWhen a scientist doesn’t know the answer to aproblem, he is ignorant. When he has a hunch asto what the result is, he is uncertain. And whenhe is pretty darn sure of what the result is goingto be, he is in some doubt.Richard P. FeynmanCopyright 2013, N. St-Pierre, The Ohio State University
  52. 52. A responsibilityIf we suppress all discussion, all criticism,saying, “This is it boys!”… and thus we doomman for a long time to the chains of authority,confined to the limits of our present imagination.Richard P. FeynmanCopyright 2013, N. St-Pierre, The Ohio State University
  53. 53. A Principled ScientistIt’s a kind of scientific integrity, a principle ofscientific thought that corresponds to a kind ofutterly honesty – a kind of leaning overbackwards.Richard P. FeynmanCopyright 2013, N. St-Pierre, The Ohio State University
  54. 54. U.S. Temperature DataCopyright 2013, N. St-Pierre, The Ohio State University
  55. 55. U.S. Temperature DataCopyright 2013, N. St-Pierre, The Ohio State University
  56. 56. Copyright 2013, N. St-Pierre, The Ohio State University
  57. 57. Copyright 2013, N. St-Pierre, The Ohio State University
  58. 58. Trends in Hurricane IntensityCopyright 2013, N. St-Pierre, The Ohio State University
  59. 59. Trends in Hurricane IntensityCopyright 2013, N. St-Pierre, The Ohio State University
  60. 60. Copyright 2013, N. St-Pierre, The Ohio State University
  61. 61. Great Lakes Ice CoverageCopyright 2013, N. St-Pierre, The Ohio State University
  62. 62. Great Lakes Ice CoverageCopyright 2013, N. St-Pierre, The Ohio State University
  63. 63. Arctic Ice Extent in September
  64. 64. Arctic Ice Extent in September
  65. 65. Arctic Ice Extent in September
  66. 66. Oceans AcidificationCopyright 2013, N. St-Pierre, The Ohio State University
  67. 67. PteropodsSeawater with pH and carbonate projected for the year 2100Copyright 2013, N. St-Pierre, The Ohio State University
  68. 68. Oceans AcidificationCopyright 2013, N. St-Pierre, The Ohio State University
  69. 69. PteropodsSeawater with pH and carbonate projected for the year 2100Copyright 2013, N. St-Pierre, The Ohio State University
  70. 70. Predictions and ForecastsThe conditions of the universe are knowable onlywith some degree of certainty.Copyright 2013, N. St-Pierre, The Ohio State University
  71. 71. Predictions and ForecastsTwo strikes in weather forecasting:• The systems are dynamicThe behavior of the system at one point in timeinfluences its behavior in the future.• The systems are nonlinearThey abide by exponential rather than additiverelationships.Copyright 2013, N. St-Pierre, The Ohio State University
  72. 72. Climate Forecasts• How much uncertainty is in the forecast?• How right or wrong have the predictions been sofar?• How much have politics and other perverseincentives undermined the search for scientificproof?Healthy skepticism toward climate predictions!Copyright 2013, N. St-Pierre, The Ohio State University
  73. 73. How Cows Dissipate Heat• Conduction• Convection• Radiation• Evaporative coolingCopyright 2013, N. St-Pierre, The Ohio State University
  74. 74. Flow of Energy (Mcal/day)40 lbs 120 lbsGross Energy 73.4 135.7Feces 25.7 40.7Digestible Energy 47.7 95.0Urine 5.6 11.0Gas 3.4 6.1Metabolizable Energy 39.0 77.9Heat 26.2 39.5Milk Energy 12.8 38.4Copyright 2013, N. St-Pierre, The Ohio State University
  75. 75. A Simplified Cow...Ta TeEg>EdThe cow The environmentkdkdαΔ TΔ TCopyright 2013, N. St-Pierre, The Ohio State University
  76. 76. Increased Productivity vs. Global Warming• The current IPCC forecasts predict that thetemperatures might increase by 1.2 °F by 2050.• Dairy productivity has increased at a rate of 318lbs/cow per year since 1980.Copyright 2013, N. St-Pierre, The Ohio State University
  77. 77. Increased Productivity vs. Global Warming• Current animal productivity averages ~ 70lbs/cow per day nationally.Results in 30.1 Mcal/cow per day in heat energy.• Assuming that improvement in productivity willbe maintained at 300 lbs/cow per year, theaverage U.S. dairy will be producing 102lbs/cow per day in 2050Results in 35.7 Mcal/cow per day in heat energy• The projected improvement in potentialproductivity will lower the THI-threshold from70 to 64.Copyright 2013, N. St-Pierre, The Ohio State University
  78. 78. Increased Productivity vs. Global Warming• The current IPCC forecasts predict that thetemperatures might increase by 1.2 °F by 2050.• The increased projected productivity has a net“warming effect” equivalent to 6 °F by 2050.Increased potential productivity will haveabout 5 times more impact on heat stress indairy cattle than global warming.Copyright 2013, N. St-Pierre, The Ohio State University
  79. 79. The Real Issue• Current cooling systems are not very energyefficient and they all rely on significant amountsof water being used.Copyright 2013, N. St-Pierre, The Ohio State University
  80. 80. The Real Issue• Current cooling systems are not very energyefficient and they all rely on significant amountsof water.Will energy costs outpace our ability to coolanimals?Will water availability restrict our ability to coolanimals?Copyright 2013, N. St-Pierre, The Ohio State University
  81. 81. Closing CommentsCopyright 2013, N. St-Pierre, The Ohio State University
  82. 82. The End
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