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Analysis of Western Root Disease Model's Predictions on Stand Structure and Density Changes

This study assesses the capability of the Western Root Disease Model (WRDM) to predict changes in stand structure, density, and fuel loads caused by Armillaria root disease. The projections of the WRDM are compared to actual measured changes in the field over a 10-year period.

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Analysis of Western Root Disease Model's Predictions on Stand Structure and Density Changes

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  1. SIMULATION AND PLOT REMEASUREMENT ANALYSIS10 YEAR CHANGES IN STAND STRUCTURE AND DENSITYVS PREDICTIONS OF THE WESTERN ROOT DISEASE MODEL HELEN MAFFEI GREG FILIP LANCE DAVID KRISTEN FIELDS OPUS

  2. OBJECTIVES • ASSESS THE CAPABILITY OF THE WESTERN ROOT DISEASE MODEL TO PREDICT CHANGES IN STRUCTURE , DENSITY AND FUEL LOADS CAUSED BY ARMILLARIA ROOT DISEASE BY COMPARING THESE PROJECTIONS TO ACTUAL MEASURED CHANGES IN THE FIELD

  3. BASE MODEL ONLY 40 YEAR PROJECTIONARMILLARIA ROOT DISEASE WESTERN ROOT DISEASE (WRDM) OVERVIEW USING WRDM

  4. DIAGRAM OF ROOT DISEASE CENTER RR CENTER STAND INFECTED ROOTS

  5. Western Root Disease Impact Model (WRDIM) Overview • Infects new host trees through root contact with the root system of an infected tree. • (The probability of contact is based on assumptions re the shape and geometry of roots and root growth).

  6. Western Root Disease Impact Model (WRDIM) Overview • Kills tree when a threshold amount of root the root system is colonized by root disease . • Bark beetles can also kill root disease infected trees.

  7. Western Root Disease Impact Model (WRDIM) • Root disease inoculum dies out when root decays. Other factors being equal the larger the root the longer it persists

  8. OPUS ADMINISTRATIVE STUDY STUDY DESIGN R6 FHP AND PNW PLOT ESTABLISHENT FUNDED BY WINEAMA NF REMEASUREMENTS FUNDED BY PTIPS – STDP DESIGNED, MEASURED AND MAINTAINED BY R6 FHP AND WINEMA NF

  9. Established by: Helen Maffei and Gregorio Armillarius Leo Torba and Phil Jahns in 1991

  10. Study Area Characteristics • 166 acres • White fir/Shasta red fir • Occasional ponderosa pine and DF in the overstory • Little evidence of harvest • Armillaria root disease very active • Elevation approx 5,000 feet • East Aspect • 13 stands—full range of ARD severity • 147 plots—full range of ARD severity

  11. Methods: RR severity rating and plot density Significant (p=000) negative linear relationship between RR Severity Rating and plot density (N=145)

  12. Methods: The effect of Armillaria Root Disease on Density Root disease causes an overall decrease in density as represented by % canopy cover Red =1991 Blue=2002

  13. Study Area Characteristics • Late Successional Reserve

  14. Study Location Cascade Canal FR 200 Opus Study Area, No Treatment FR 3633

  15. SCALE OF COMPARSONS • INDIVIDUAL PLOT LEVEL (147) Started with plots because: -IMAP calibration uses inventory plots, not SE. plot data & pest models are currently being used to calibrate VDDT state transition models for IMAP project for the effects of I & Disease -Scale more consistent with IMAP-- 1/6 acre (30 m pixel) -Short time frame---Expect to see more decadal change • STAND LEVEL (13)

  16. WHAT CONSITUTES SUCCESS? 11 YR PREDICTIONS: • ARE BETTER CORRELATED WITH WHAT REALLY HAPPENED USING THE WRDM THAN THE BASE MODEL ALONE • THE TRAJECTORY OF THE CHANGE IS SIMILAR TO WHAT WE KNOW ACTUALLY HAPPENS

  17. WHAT CONSITUTES SUCCESS continued ANY NEEDED CALIBRATION MUST BE: • LOGICAL STRAIGHTFORWARD THAT: • CAN BE APPLIED ACROSS ALL STANDS WITH CONSISTENT RESULTS • CAN BE MEASURED AND REPEATED IN OTHER SITUATIONS (NOT JUST TINKERING AROUND WITH MODIFIERS UNTIL IT COMES OUT RIGHT)

  18. WHAT CONSITUTES SUCCESS? PREDICTIONS WITH BASE MODEL + WESTERN ROOT DISEASE MODEL SHOULD HAVE: • BETTER CORRELATIONS WITH THE OBSERVED THAN WITH THE BASE MODEL ALONE • AVERAGE PREDICTIONS OF INDICATOR VARIABLES THAT ARE: • Not significantly different from average observed value • Significantly different from projections with base model alone

  19. INDICATOR VARIABLES DENSITY • CHANGES IN % CANOPY COVER STRUCTURE • CHANGES IN % CANOPY COVER FOR 4 SIZE CLASSES

  20. Structure.. % Canopy Cover of 4 size class groups: Size class 1. DBH 0 to 5 inches (SEEDLINGS AND SAPLINGS Size class 2. DBH 5+ to 9 inches (POLES) Size class 3. DBH 9+ to 21 inches (MEDIUM) Size class 4. DBH 21+ inches (LARGE TREES) % CC Calculated using FVS cover model SORNEC Variant

  21. Methods Plots/size classes subdivided into 2 root disease severity groups 1. No apparent root disease 2. Mod-Heavy root disease

  22. BASE MODEL CALIBRATION • SDI MAX SET TO 600 FOR WHITE FIR AND SHASTA RED FIR • OTHER SPECIES USE DEFAULT VALUES

  23. WRDM CALIBRATION • RECODED SH TO WF--DOES NOT SEEM TO RECOGNIZE SHASTA RED FIR IN BARK BEETLE COMMAND FIR ENGRAVER BEETLE ATTACK IS VERY IMPORTANT COMPONENT OF DEATH FROM ROOT DISEASE. • ROOT ROT AREA IS SET TO 1 ACRE FOR INDIVIDUAL PLOTS • 100% OF THE AREA IS IN ROOT DISEASE FOR PLOTS WITH INITIAL ROOT DISEASE SEVERITY RATINGS OF 2 OR GREATER.

  24. RESULTS

  25. Results: Predicted vs actual 11 year change in cc for 9-21 dbh trees in plots no initial root disease on plot..n=118 DBH 9-11 BASE MODEL

  26. CORRELATION WITH ACTUAL CHANGE IN CC (ADJ R2)

  27. SAMPLE DESIGN ISSUES RELATED TO INVENTORY PLOTS

  28. Thoughts • For our landscape the model reflects the general trend in changes in structure and density caused by root disease • However changes occurring within size classes do not appear to be well correlated; although some are better than others • Calibration and trouble shooting of WRDM is difficult because its difficult to isolate and correct individual causes • We need to keep working on this

  29. Methods Key variables and groupings used to evaluate the performance of FVS and the WRDM in predicting 11 year change in vertical fuel loads • Change in vertical dead fuels (tons/acre)

  30. Methods—Predicted vs Measured Fuel Loads by Root Disease Severity Root Disease Intensity/Severity: • Root Disease Severity Rating (Hagle); • Recorded by plot; 1991 Fuel loads: • Predicted and Measured Standing Dead (tons/acre) • Down Dead (not completed) • Calculated by FVS Fire Effects Model

  31. How good are the root disease model predictionsBarriers to assessment Complex structure and calibration needs Great calibration of base model required prior to assessment or impossible to discern

  32. Tentative conclusions re 11 year WRDM projections of density and structural change in unmanaged plots • *Under predicts changes in dead vertical fuels

  33. Methods—Armillaria Root Disease and Fuel Loads Root Disease Intensity/Severity: • Root Disease Severity Rating (Hagle); • Recorded by plot; 1991 Fuel loads: • Standing Dead • Calculated by FVS Fire Effects Model

  34. Methods Evaluation variables denoting changes in density, structure and fuel load over 11 years. • Change in % CC • Change in % CC by size class • Change in vertical dead fuels (tons/acre)

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