Climate Impacts: Mountain pine beetle in Eastern Washington

1. Climate Impacts: Mountain pine beetle in Eastern Washington Elaine Oneil PhD. Rural Technology Initiative College of Forest Resources Climate Impacts Group Seminar January 24, 2008

2. The Study • Context

3. Tree Mortality Mountain Pine Beetle caused by Washington Department of Natural Resources Forest Health Program USDA Forest Service PNW Region Forest Health Protection = Host Type Pinus spp. Note: Shaded areas show locations where trees were killed. Intensity of damage is variable and not all trees in shaded areas are dead. Sources: Annual aerial insect and disease surveys flown by USDA Forest Service, Oregon Department of Forestry, and Washington Department of Natural Resources; 250m forest type map developed by USDA Forest Service - Remote Sensing Application Center.

4. Mountain Pine Beetle • Year: Acres • 2005: 554,000 • 2006: 267,000 • Acres not surveyed in 2006 (fires): ~ 200,000 Source: http://www.dnr.wa.gov/htdocs/rp/forhealth/

5. Photo credit: Don Hanley Photo credit: Don Hanley

8. 2000+ Mortality Rate 8.4 TPA 1979-1999 Mortality Rate = 2.2 TPA

9. 2005 aerial survey results • Mountain pine beetle ranks as the number 1 causal agent of tree mortality in Washington State accounting for an estimated 75% of the observed mortality in Eastern Washington 2005 and 56% of the mortality state wide.

10. Western WA 15.9 million acres total 11.9 million acres forestland Eastern WA 26.6 million acres total 9 million acres forestland

12. Approximately 80% of state and private acres have a pine component Over 1 million acres of Douglas-fir types potentially affected

13. The Study • Context • Climate Characteristics of interest

18. Western regional Climate Data www.wrcc.dri.edu

19. Western regional Climate Data www.wrcc.dri.edu

20. Maximum Summer Temperature Maximum precipitation 1980’s outbreak in PP starts Current MPB outbreak in LP starts 2000 Minimum Summer temperature Minimum Precipitation Western regional Climate Data www.wrcc.dri.edu

21. The Study • Context • Literature review and definitions • Conceptual model and research questions

22. MPB risk and susceptibility • Risk • Linked to the likelihood of MPB attack as a function of MPB population dynamics and proximity to host trees • Climate change enhancing insect survival and reproduction • Susceptibility • Linked to the likelihood of a tree, or stand, being attacked as a function of poor vigor. • Warmer and drier summers leading to increased moisture stress and reduced vigor within pine forests • Warmer and/or drier winters reducing snowpack and effective moisture retention into late spring/early summer

23. MPB susceptibility rating systems • Differ for MPB in lodgepole pine (LP) and ponderosa pine (PP) • Various combinations of stand density, vigor, basal area, age, diameter, crown competition, and/or growth rates are used to rate stand susceptibility • Stand susceptibility as measured by these metrics is widely variable across the geographic ranges of host species and differs by species. (Shore et al 1989, Amman & Anhold 1989) • Rating systems need to account for beetle population dynamics and climate (Shore et al 1989, 2001)

24. 15.5 º C Braun and Gara, 1990

25. When the flying population ‘switches’ from attacking stressed focus trees to attacking adjacent healthy trees, the switching mechanism has occurred and an epidemic outbreak has begun Braun and Gara, 1990

26. Topography Weather FireRisk Fuels

27. Stand carrying capacity Weather/Climate Topography Weather FireRisk Mountain Pine Beetle Susceptibility Fuels Stand parameters

28. Research Questions • What role does the relationship between stand and site variables play in host susceptibility to MPB attack? • What role do climate and weather play in host susceptibility to MPB attack?

29. The Study • Context • Literature review and definitions • Conceptual model and research questions • Methods

30. Continuous Vegetation Survey Plots

31. DAYMET data Courtesy of the Numerical Terradynamic Simulation Group University of Montana at http://www.daymet.org/default.jsp 18 year monthly average temperature, precipitation at 1 km resolution Daily weather data for 1980 to 2003 on a square km grid

32. Where is MPB attack located? # Unique plots – some attacked more than once

33. Okanogan National Forest Colville National Forest

34. MPB attack on the Okanogan NF

35. MPB attack on the Colville NF

36. Integrating the Data • GIS analysis • Exploratory Data Analysis • Calculating carrying capacity • Calculating stand variables • Accounting for prior mortality

37. How much MPB attack has there been? Count by year – 1981-2003 Count over time

38. Where is MPB attack located? Elevation range

39. Carrying capacity metrics • Site Index • A species specific measure of actual or potential forest productivity and site quality • Tells us something about stand growth independent of stand density.

41. Carrying capacity metrics • Site Index • A species specific measure of actual or potential forest productivity and site quality • Tells us something about stand growth independent of stand density. • Growth Basal Area • A measure of stocking that relates the site carrying capacity to a stand of 100 years of age that maintains a diameter increment of 1 inch/decade (20 rings/inch) • Poor sites have lower inherent carrying capacity and therefore a lower GBA (Cochran et al 1994) • GBA has been correlated to bark beetle susceptibility (Sartwell 1971, Sartwell & Stevens 1975) • Multiple GBA values in a single site index or site class • GBA varies by species for a given site

42. I V IV III II

43. Analyses • Binary response variable MPB [0,1] • Generalized linear model with a link function • Binomial if it is [0,1] • Poisson if it is [0, number of attacks/plot] • Zero-inflation • Zero-inflated negative binomial • Zero-inflated Poisson

44. The Study • Context • Literature review and definitions • Conceptual model and research questions • Methods • Results • Implications

45. Assessing stocking rates using GBA

46. Carrying Capacity and MPB attack

47. Does Carrying Capacity Matter?

48. For trees over 10” this stand has: SDI =83; DBHq =13.7 ; 72 =TPA; BA =60

49. 1980-1999 Yearly tests (10% PDE) Temperature (S/W), precipitation, VPD, DBH, BA Cumulative tests (36% PDE) Precipitation, first warm day, temperature (S/W) 2000-2003 Yearly tests (17% PDE) VPD, Temperature (W), site variables Cumulative tests (42% PDE) VPD, length of drying period Significant Predictors

50. 1981-1999