1. Variance in Growth and
Susceptibility to Beetle Attack in
Engelmann Spruce and
Lodgepole Pine
(these trees were doomed from the
start…)
Rachel Strawn
Graduate Seminar

2. Outline
Introduction
Motivations for study
Methodology
Major questions asked
Local conclusions
Larger implications

3. Introduction
Image credit: USFS Rocky Mountain Research Station

4. Image credit: U.S. Fish and Wildlife Service
“Developing appropriate management responses
to bark beetle outbreaks requires understanding
the complexities of interactions between the
beetles and host trees.” –USDA Forest Service

5. Outline
Introduction
Motivations for study
Methodology
Major questions asked
Local conclusions
Larger implications

6. Motivation For Study
Andrew King Unpublished
(data collected 2012)
Mitchell et al. 1983

7. Motivation For Study

8. Motivation For Study
0
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1400 1500 1600 1700 1800 1900 2000
Year
Tree Ring Width by Year ESL LIVE
ESL DEAD
FC LIVE
FC DEAD
DH LIVE
DH DEAD
LC LIVE
LC DEAD
Figure 1: Tree ring data from Frasier, CO at four different sites
(East St. Louis (ESL), Fool Creek (FC), Dead Horse (DH), Lexen
Creek (LC)). Tree rings from trees that have been attacked by
beetles are in red, healthy trees are in green.
Data obtained from USFS RMRS, R. Hubbard and C. Rhoades
RingWidth(μm)

9. Outline
Introduction
Motivations for study
Methodology
Major questions asked
Local conclusions
Larger implications

10. Methodology
 Two sites:
Chimney Park
GLEES
 Two species:
i. Pinus contorta var.
latifolia
(lodgepole pine)
ii. Picea engelmannii
(Engelmann spruce)

11. Methodology: Competition Index (CI)
Competition Index (CI) is a way to
quantify amount of shade a tree is
receiving--above-ground only!
Several models, model used here
below:
ai = angle Contributor tree is from Main tree
di = distance Contributor tree is from Main tree
hi = height of Contributor tree
hs = height of Main tree
(Loranty et al. 2010)

12. Methodology: Data Collection
16 circular plots
Radii of 5m and 10m
One main tree in the
center – randomly
selected
Trees between 315° and
45° in “Exclusion Zone”

14. Methodology: Data Collection (cont.)
From every tree in
each site:
DBH
Height
Distance from Main
Angle from Main
Beetle Status
Canopy Status
Tree Core
Over 600 trees
cored and
analyzed!

16. Methodology: CI back in Time
 To calculate CI in the past, require height
 Using current data, found relationship between
height and DBH:
Height = 1.3 + β0 (1-e -β1*DBH) β2
 Used function and DBH
(calculated via ring widths) to
estimate the height over a tree’s
life time.
 These heights were then used
to calculate CI across each Main
tree’s life span

18. Outline
Introduction
Motivations for study
Methodology
Major questions asked
Local conclusions
Larger implications

19. Major Questions
1) What is the predictive power of
using CI back in time?
2) Was there a difference in growth
between beetle-attacked trees and
healthy trees?
3) What caused this difference?

20. Variance of C.I. Through Time
N=16

21. Question 1: Summary
1) What is the predictive power of using CI
back in time?
Variance in CI increases the further
back in time you go
The data that we have in the present
cannot explain every variable in the
past

22. Q2) Growth in Lodgepole
 All trees approximately same age
 Beetle-attacked trees were both taller and
thicker than healthy trees in 2014  indicating
difference in growth
Attribute Status Mean F P-Value
Age Beetle
(n=230)
94.08 ± 1.473 2.344 0.127
Healthy
(n=93)
91.83 ± 1.243
DBH (cm) Beetle
(n=230)
16.85 ± 0.437 100.5 2e-16 ***
Healthy
(n=93)
12.48 ± 0.369
Height (m) Beetle
(n=230)
15.23 ± 0.642 17.95 2.97e-5 **
Healthy
(n=93)
12.51 ± 0.542

23. n = 230
n = 93
* * *
0.708 + 2.747 e (-0.248 * AGE )
0.521 + 2.339 e (-0.303 * AGE )

24. Q2) Growth in Engelmann
Beetle-attacked trees were much older,
therefore larger and taller as well.
Attribute Status Mean F P-Value
Age Beetle
(n=211)
130.4 ± 6.771 46.99 4.89e-11 ***
Healthy
(n=64)
83.95 ± 5.957
DBH (cm) Beetle
(n=211)
22.39 ± 1.355 56.99 6.89e-13 ***
Healthy
(n=64)
12.16 ± 1.193
Height (m) Beetle
(n=211)
13.49 ± 0.818 56.6 8.11e-13 ***
Healthy
(n=64)
7.331 ± 0.720

25. n = 211
n = 64

26. *
0.400 + 1.434 e (-0.032 * AGE )
0.412 + 1.378 e (-0.065 * AGE )

27. Question 2: Summary
2) Was there a difference in growth between
beetle-attacked trees and healthy trees?
Lodgepole: Yes, occurred at the same
time
Engelmann: Yes, but occurred at two
different times

28. Q3) Climate?
 Climate was not different for the two groups within each
species
 All trees sampled within same environment, relatively same
altitude
 GLEES sampled across ~ 80,000 m2 (19.3 acres)

29. Q3) Climate?
 All trees sampled
within same
environment
 Chimney Park sampled
across ~ 14,000 m2
(3.2 acres)

30. Q3) Competition? Lodgepole (n=8)

31. n = 230
n = 93
n = 8
n = 8

32. Q3) Competition? Engelmann (n=7)

33. Q3) Competition? Engelmann (n=7)

34. Question 3: Summary
3) What caused this difference in
growth?
Climate? No
Competition? No
Period of establishment? Yes in
Engelmann, No in lodgepole
Genetic Variation? NOT ADDRESSED
Microsite Variation? NOT ADDRESSED

35. Outline
Introduction
Motivations for study
Methodology
Major questions asked
Local conclusions
Larger implications

36. Local Conclusions
Cause of growth and
susceptibility in lodgepole not
due to climate, competition, or
period of establishment
Cause of susceptibility in
Engelmann due to period of
establishment

37. Local Conclusions (cont.)
Older trees and faster growing
trees are more susceptible to
attack; reasons?
Overall larger (more food)
Easier to find
Chemical signals (Raffa et al. 2008)

38. Outline
Introduction
Motivations for study
Methodology
Major questions asked
Local conclusions
Larger implications

39. Larger Implications
Current management practices
aimed at thinning  promotes
growth
Past literature suggests that
larger trees are more resilient to
beetle attack (Christiansen et al.
1987), this data says otherwise
Continue to maintain diversity
of age classes

40. Acknowledgments
Committee members:
Brent Ewers
Dan Tinker
Urszula Norton
Technicians:
Brady Hickerson
Kaleb Kenneaster
Funding and Data:
WYCEHG, NSF, EPSCoR
Ron Hubbard
Chuck Rhoades
Lab Members:
Daniel Beverly
Heather Speckman
John Frank
Other Help!:
Paige Copenhaver
Kellen Nelson
Daniel Strawn