1. IPPC Degree-Day Models including Douglas-Fir Needle Midge (Contarinia spp.) Len Coop, IPPC, OSU Corvallis Feb 22, 2013

2. Phenology and degree-day concepts Some features of the IPPC "Online weather data and degree-days" website at http://uspest.org/weahttp://uspest.org/wea Development and use of the Douglas-fir needle midge model Topics for today's session:

3. "Who?" and "What?" Identification keys, diagnostic guides, management guides "When?" Phenology models (crops, insects, weeds), Risk models (plant diseases) "If?" Economic thresholds, crop loss models, sampling calculators, other decision tools "Where?" GIS, precision agriculture Typical IPM questions/decision tools:

4. Insects have complex life cycles e.g. Douglas-fir needle midge (Contarinia spp.) Eggs Larvae Pupae (most) Adults -Timing of stages *is often* predictable using degree-days, which are a two dimensional “heat unit“ of development for cold blooded organisms

5. Degree-day calculations – method varies: Simplest: (daily max + min)/2 – low threshold Single triangle compared with typical daily fluctuation How fast are they going?

6. Weather and Degree-day Concepts 1)Degree-day models: accumulate a daily "heat unit index" (DD total) until some event is expected (e. g. egg hatch) 38 20 18 32 14 22 20 26 daily: cumulative: 20 70 84 106 126 152 Eggs hatch: 152 cumulative DDs Eggs start developing: 0 DDs 70 o(avg) - 50 o(threshold) =20 DD

7. Degree-day model development: A bit more detail

8. Developing degree-day models from lab studies

9.  Degree-day models: x-intercept method (Arnold 1959) x-intercept ~ Tlow = 37 F 1/slope = 1/0.0011 = 920 ~ DD requirement

10. Pest Management: Monitoring plays a major role especially since populations are cyclical (due to natural enemies or to swarming conditions perhaps?) 2012: 22 traps in 22 fields, 44 flies total 2011: 23 traps in 22 fields, 206 flies total 2010: 21 traps in 20 fields, 2 flies total 2009: 47 traps in 47 fields, >500 flies total; swarming noted Box trap Sticky trap

11. Need at least 3-4 years data from a variety of locations Doug fir needle midge – mostly from 1 trap/field, more than 20-47 fields 2009-2011 (provided by D. Silen) Plus data from OSU Extension 1990 Method is to vary the lower threshold and start date and use the value that provides lowest error Phenology Models – developed by field data using lowest error methods

12. Here is how version 1 of the model looks: Phenology Models – developed by field data using lowest error methods

13. Here is how version 1 of the model looks w/2012 data: Phenology Models – developed by field data using lowest error methods

14. http.uspest.org/wea

15. DFNM linked from PNW Insect Management Handbook – ID photos and DD model

16. New interface to DD Models – Douglas-fir needle midge http://uspest.org/cgi-bin/ddmodel.us?spp=dnm Google maps for location selection Nothing else to do but click “Calc”

17. DD model example output – Corvallis 2013

18. DD model output (cont.)

19. DD model output (cont.)

20. Watch for missing data/bad QA (quality assurance) reports e.g. Albany Weather Underground Flag for missing/interpolated data QA report not bad in this case

21. What the model is telling us: timing can vary by 5 weeks or more for cool vs. warm years

22. Pest Management: Spray or let natural enemies do their job? (avoid late sprays to protect later-emerging parasitoids) Genus Platygaster Genus Gastrancistrus Parasitoid wasp - family Pteromalidae Parasitoid wasp - family Platygastridae

23. - Control critical in years just before and during harvest - Export issues: Mexico has zero tolerance - Biological control likely to be very important but needs further study! -Work on larval exit timing in the fall (range reported to be mid-Oct-Dec) to see if any remain in needles after harvest Pest Management: Other considerations

24. - Economic thresholds are lacking for christmas tree pests in general, would be especially helpful for DFNM - More work should be conducted to distinguish the ID, biology, phenology, and parasitism of the three or more Contarinia species Pest Management: Other considerations (cont.)

25. Summary Points: IPPC uspest.org/wea has evolved as a hybrid for support of State, Regional, and National needs (>100 models, 17,000 weather stations) New model interface uses Google maps for easier weather station selection The new Douglas-fir needle midge DD model appears to succeed in taking on much of the 4-5 week year-to- year variability caused by weather. Further work on biology of this pest complex is recommended!