Understanding the Tools Used for Codling Moth Management: Models

Transcription

1 Understanding the Tools Used for Codling Moth Management: Models Vince Jones and Mike Doerr Tree Fruit Research and Extension Center Washington State University Wenatchee, WA

2 Overview Why bother? How and why models work How models are developed How accurate are models? Factors that effect the CM model CM Response to pheromone Biofix, flight temperatures, other factors What they can tell us

3 Why Bother with Phenology Models? Models allow you to predict an event which is difficult to observe directly, but that is important to the IPM program from an easy to observe event Predict egg hatch from trap capture Models allow you to optimize control programs in systems where many pests are found How does the phenology of the different pests overlap Can a single spray take out LR and CM? They give advanced warning of problems

4 How They Work Enzymatic reactions (rx) are the basis for many physiological processes These reactions have an optimal temperature Above the optimal temperature, the rx rate quickly decreases to zero Further increases results in deactivation of the enzymes and death of the organism Below optimal temperature, rx rate drops somewhat slowly to zero, further drops generally not fatal unless ice crystals form. Developmental Rate (1/time *100) Temperature ( C)

5 Warm Blooded Animals Core body temperatures are relatively stable Optimal rx rate generally occurs at body temperatures (98.6 F in humans) Ë Physiological processes occur at a relatively constant rate Ë Developmental rate is closely related to calendar time

6 Cold Blooded Animals No physiological mechanisms to regulate body temperatures precisely Some behavioral mechanisms, but limited duration/efficiency Ë Reaction rates vary with temperature experienced by the insect Ë Temperature (heat units) is a better predictor of developmental rate than calendar days.

7 Law of Constant Thermal Summation The amount of heat required to complete a physiological process (= stage) is constant and does not depend on the rate of temperature accumulation (within reason) Example Does the rate of filling a one gallon bucket change its capacity?

8 Definitions Upper Threshold Temperature at which no development occurs because of heat deactivation Lower Threshold Temperature where no development occurs because of cold deactivation Degree-Day (= heat unit) The amount of heat accumulated when the temperature is 1 above the lower threshold for a period of 1 day. Biofix Some easily observed event which can be used to synchronize the model to field populations

9 Determining Thresholds, etc. Laboratory studies run at 4 or more constant temperatures Determine the average time to complete each stage Plot developmental rate (1/average length of stage) vs. temperature Developmental Rate (1/time *100) Temperature ( C)

10 Modeling Emergence Need some mathematical function to approximate the insect s emergence Desirable features: Should be adaptable to a wide-range of different insects and emergence patterns Should tend to be skewed to the emerge sooner than a normal frequency distribution ( bellshaped curve )

11 Erlang Distribution Shape parameter (K) specifies the shape of the curve Average duration (in D) of the stage in question CUMULATIVE % EMERGENCE K=2 K = 10 K = 25 Probability of emerging at any particular time (in D) DEGREE DAYS

12 CM Phenology 100 % Adult Emergence % Oviposition % Hatch Cumulative Percentage Degree-Days

13 CM Phenology 100 % Adult Emergence % Oviposition % Hatch Cumulative Percentage Degree-Days

14 Also Numbers No. Adults No. Eggs Number Present Degree-Days from Biofix

15 Next Step! Field validation (Mike Doerr s Data) Use field data to determine the accuracy Cumulative % % Egg Hatch Model % Egg Hatch % Injury Degree-Days Since Biofix ( F)

16 Model Accuracy II (Beers and Brunner) How does the model compare to spraying 21 days after full bloom of reds? No. Days Between Observed and Predicted Larval Entry into the Fruit Model Calendar Year

17 Stage Specific Development (Naches) % Stage Completed in 1 wk Stage DD Required May 1-7 June 1-7 July 1-7 Aug 1-7 Naches DD/wk Egg Larval Pupal Protandary Adult Egg-Adult

18 Stage Specific Development (20 yr. Average TFREC) % Stage Completed in 1 Week Stage DD Required May 1-7 June 1-7 July 1-7 Aug 1-7 Wenatchee DD/wk 30 yr. Aver Egg Larval Pupal Protandary Adult Total

19 Stage Specific Development (Wenatchee 2002) % Stage Completed in 1 week Stage DD Required May 1-7 June 1-7 July 1-7 Aug 1-7 Wenatchee DD/wk Egg Larval Pupal Protandary Adult Total

20 Phenology of Codling Moth Biofix to: Summer Gen Hatch Summer Gen Oviposition Summer Gen Moths Hatch period Oviposition period Moth Emergence Period Degree Days ( F) From Biofix

21 Factors Important for Model Predictions Daily Flight Patterns Temperature Effects Developmental Threshold = 50 F Flight Temperature Other Environmental Effects Bin Piles

22 Flight Times of CM (Riedl 1986) Dusk Virgin Females Pheromone Trap % Daily Catch Time

23 Temperature Effects (Riedl 1986) Minimal flight temp is not constant for all moths Population response! Lots of variability in literature on minimal flight temp F Different response in morning and evening Optimal response between F Level of Activity } Lab studies

24 Temperature Effects (Riedl 1986) Minimal flight temp is not constant for all moths Population response! Lots of variability in literature on minimal flight temp F Different response in Morning and Evening Optimal response between F Level of Activity 50% activity } Lab studies

25 Temperature Effects (Riedl 1986) Minimal flight temp is not constant for all moths Population response! Lots of variability in literature on minimal flight temp F Different response in Morning and Evening Optimal response between F Too high and drops off Level of Activity } Lab studies

26 Setting Biofix Biofix is used to synch the model with field populations Biofix really is the first moth caught Model resets to 0 DD so all DD accumulations from this point forward are actually 220 less than from start of the season. Biofix requires the traps be checked frequently and enough traps be placed to ensure you catch moths if they are present If your orchard biofix is more than 10 d after a nearby comparable orchard, you re probably wrong

27 Spring Time & Biofix Weather patterns are extremely variable - wind, rain, temperature 9 mph wind stops flight all together 0.08 rain/hr stops flight Need the dusk temperatures to be over 60 F to get biofix Don t try and set biofix if you have low density orchard or one with MD, use a comparable site nearby

28 Why do moth catches jump up so fast? The lower threshold for development is below than flight threshold, so development continues even when flight is not observed Especially noticeable in the spring when it gets warm and then cools off for a few days When Temps are above 50 during the day but not over flight temp at dusk or dawn, moths emerge but don t fly Result is no moth catch When temp go over the flight threshold, it appears like a large number of moths emerge all at once

29 Bin Pile Effects (Higbee et al. 2001) Codling moth were commonly found in wooden bins, rarely in plastic bins Larvae colonize the bins if placed in the field before harvest (don t need fruit in the bins) If placed in the field early next year, moths emerge into the field at off model times There is a temperature gradient in bin piles, so that moths emerge over a long period of time As close to harvest as possible is best!

30 Higbee et al Effect of Bin Piles 30 Field Bin Pile 25 Mean No. Moths/Trap /3/97 4/17/97 5/1/97 5/15/97 5/29/97 6/12/97 6/26/97 7/10/97 7/24/97 Date

31 Summary: What factors affect the model? ^ or appear to affect Poor weather data Spring weather and poor biofix Pesticide applications or mating disruption Different quality of food in the spring and summer generation Summer generation has shorter development time Overhead irrigation? Differences in diapause? Warmer areas tend to have a broader, more variable emergence curve Bin Piles!!!!!!