REGIONAL CLIMATE VARIABILITY AND COMPOSITIONAL CHANGE AT UPPER
TREELINE ALONG A LATITUDINAL GRADIENT IN THE ROCKY MOUNTAINS
Elliott, Grant P. (1), Kipfmueller, Kurt F. (2)
(1) Department of Geography, University of Missouri, Columbia, MO, (2) Center for Dendrochronology and Department of Geography, University of Minnesota, Minneapolis, MN
Introduction
Age Structure & Species Composition
Methods & Analysis
Abrupt increases in tree establishment throughout upper
treeline ecotones during the latter half of the twentieth
century have been attributed to regional climate variability
along a latitudinal gradient in the Rocky Mountains (Fig. 1).
However, little attention has been directed towards
examining the species-specific response of these trees to
changes in climate, particularly with respect to possible
varying trajectories between species positioned in closedcanopy conditions below timberline versus more open
environments above.
Figure 1. Regime-shift
analysis of regional
age-structure data.
(from Elliott 2012)
Field Methods
A
B
D
C
dgl = diameter at
ground level
• Sampled
climatic treelines on
contrasting south- & north-facing
slopes on 11 mountain peaks.
bristlecone pine
Engelmann spruce
• Started nested-belt transects (A) at
outpost tree (B; term after Paulsen et
al., 2000) and ran downslope 40 m into
closed-canopy subalpine forest. X-axis
is transect width and Y-axis is elevation
(m). Circles are trees & size is
proportional to age.
subalpine fir
lodgepole pine
whitebark pine
Conclusions
Ordination
• Seedlings (< 1.2 cm dgl) inventoried throughout transect.
Data Analysis
Dendroecological techniques were used to create hybrid
age-structure data that were grouped into ten-year (pre1900) & five-year age classes (1900–2000; Fig. 1).
Objective:
This research seeks to measure the compositional change
within upper treeline ecotones along a latitudinal gradient in
the Rocky Mountains to determine whether species
establishment patterns vary above and below timberline.
We used a non-metric multidimensional scaling ordination
technique based on the relative density values for each
tree species (n = 5) in treeline (above timberline) and
closed forest environments (below timberline) at each site.
Axis 1 & Axis 2 ordination scores were correlated with the
following environmental variables for each site: 1)
Topographic Relative Moisture Index (TRMI); 2) Elevation;
3) Latitude; 4) Annual Evapotranspiration (AET); 5) Annual
Potential Evapotranspiration (PET); 6) Annual Deficit
(PET- AET).
Study Area
Soil moisture data based on Thornthwaite-type water
balance model (cf., Cowell & Urban 2010).
Our results indicate that species dominance differs
between treeline and closed forest in the Sangre de
Cristos and Front Range, with spruce-dominated forest
moving towards bristlecone pine above timberline. This is
noteworthy given the impact that white pine blister rust
could have on the new species configurations within
upper treeline ecotones (e.g., Tomback & Resler 2007).
In the Bighorns, treeline ecotones switch from a firdominated forest to treeline areas favoring lodgepole pine
establishment. This research highlights the importance of
assessing species-specific responses to changes in
environmental conditions, as future treeline ecotones
comprised of new species assemblages could introduce
novel climate-disturbance interactions.
• Trees & saplings (< 5 cm dbh; < 9 cm
dgl) sampled within narrow belt (C) &
only saplings in outer belt (D). Widths
2x as wide above timberline (ATL).
• Recorded species and X & Y
coordinates of each tree & sapling
along transect
Discussion
Bighorns
Given that observed changes in species composition
above timberline differ from what currently exists
downslope in closed forest, this research highlights the
importance of assessing species-specific responses to
changes in climate. Future treeline ecotones comprised
of new species assemblages could introduce novel
climate-disturbance interactions.
References Cited:
• Cowell, C.M. & Urban, M.A. (2010) The changing geography of the
U.S. water budget: Twentieth-century patterns and twenty firstcentury-projections. Annals of the Association of American
Geographers, 100: 740–754.
Medicine
Bow
Sangre de Cristo
Front Range
• Elliott, G.P. (2012) Extrinsic regime shifts drive abrupt changes in
regeneration dynamics at upper treeline in the Rocky Mountains,
USA. Ecology, 93: 1614–1625.
• Paulsen, J., Weber, U. M. & Körner, C. (2000) Tree growth near
treeline: abrupt or gradual reduction with altitude? Arctic, Antarctic,
and Alpine Research, 32: 14–20.
• Tomback, D.F. & Resler, L.M. (2007) Invasive pathogens at alpine
treeline: consequences for treeline dynamics. Physical Geography,
28: 397-418.
Results
Table 1. Study site characteristics.
Figure 3. Annual maximum (Tmax) &
minimum (Tmin) temperature along with
annual temperature range (Trange: Tmax –
Tmin) data with linear trend lines for each
Figure 2. Study sites in Rocky
mountain range. Data obtained from
Mountains: Bighorn (BH); Medicine
www.prism.oregonstate.edu.
Bow (MB); Front Range (FR);
Sangre de Cristo (SDC).
Figure 4.(clockwise from left)
Treeline at northernmost site in
study area (Bruce Mountain in
BH); Prolific seedling/sapling
regeneration on south-facing
slope above timberline in MB;
Spruce regeneration below
timberline on Pike’s Peak (FR);
Treeline on Deception Peak in
SDC.
(Sub region)
Study site
Lat
(°N)
Long
(°W)
Elev.
(m)
a
b
AWC
(mm)
Annual
Precipitationc MAT
(mm)
(ºC)
Annual
PET
(mm)
Annual
AET
(mm)
Annual
Deficit
(mm)
(Central Rocky Mountains)
Bruce Mountain
44.6
107.5
3003
75
780.1
0.15
280
255
25
Central Bighorns
44.3
107
2990
75
748.8
0.08
270
254
16
44.1
107.1
3005
75
692.2
-0.26
259
238
21
41.4
106.5
3213
75
938.6
2
339
303
36
41.3
106.3
3327
75
1204
-0.61
259
248
11
Powder River
Pass
Kannaday Peak
Medicine Bow
Massif
(Southern Rocky Mountains)
Crown Point
40.6
105.6
3421
69
757.6
1.11
294
278
16
Mt. Evans Massif 39.5
105.6
3581
73
596.8
0.42
276
268
8
Pikes Peak
38.8
105
3605
50
737.4
1.17
289
285
4
Teddy’s Peak
37.3
105.1
3653
60
797.9
1.96
306
299
7
Gold Hill
36.6
105.4
3662
120
801.6
1.29
297
295
2
Deception Peak
35.7
105.7
3725
117
927.2
2.01
308
306
2
Acknowledgments
We thank Danny Margoles, Aaron Knoll, Susan Elliott, Chris
Crawford, Cary Reinemann, Adam Berland, and Brendan Yuill for
assistance with fieldwork. The University of Minnesota Cartography
Lab produced the study area map and the following organizations
provided funding for parts of this research: