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A Dendrochronology Study of East and West Facing Slopes in Glacier
National Park: A Case Study Examine the Effects of Microclimates in
High Elevation Subalpine Fir (Abies lasiocarpa) Stands
University of Victoria, Geography Department
Geography 477
Michael Guindon & Mike Kit
November 8, 2012
1
Abstract
Subalpine fir (Abies lasiocarpa) tree cores were collected from two Englemann Spruce Subalpine
Fir sites in Glacier National Park, British Columbia. Dendrochronology techniques were used to
examine growth limiting factors at each site. Low series intercorrelation values were calculated
for most trees, indicating that there were no common growth patterns found between tree cores.
Therefore, individual trees within the stand behave differently and are influenced by microsite
conditions. Differences in exposure, topography, soils, nutrient availability, moisture level,
competition and genetics are likely mechanisms causing different growth rates between trees in
both study sites. The behaviour of trees within these sites contradicts most subalpine and alpine
tree growth studies and has implications for the Biogeoclimatic Ecosystem Classification system
and climate change modelling in subalpine environments.
2
Table of Contents
Abstract…………………………………………………………………………... 1
Table of Content…………………………………………………………………. 2
List of Figures & Tables…………………………………………………………. 3
Acknowledgements……………………………………………………………… 4
1.0 Introduction……………………………………………....................................... 5
2.0 Literature Review……………………………………......................................... 5
2.1 Dendrochronology…………………………………….................................... 5
2.2 Biogeoclimatic Ecosystem Classification……………………………………. 6
2.3 Influence of Microsites on Tree Growth…………………………………….. 7
3.0 Methods……………………………………......................................................... 9
3.1 Study Site……………………………………................................................. 9
3.2 Sample Collection…………………………………….................................... 11
3.3 Sample Preparation & Analysis……………………………………................ 13
4.0 Results……………………………………………................................................ 13
5.0 Discussion…………………………………………….......................................... 15
5.1 Cross Dating…………………………………………..................................... 15
5.2 Exposure as a Limiting Factor…………………………................................ 16
5.3 Topography as a Limiting Factor…………………………............................. 17
5.4 Pedogenesis as a Limiting Factor…………………………............................. 17
5.5 Competition and Genetic Variation as Limiting Factors…….......................... 18
5.6 Implications for Dendrochronology and the BEC System……....................... 19
6.0 Conclusion……………………………………………......................................... 20
7.0 References……………………………………………......................................... 22
3
List of Figures and Tables
Figure 1: Map depicting the locations of both study sites within Glacier National Park
10
Figure 2: Images of study sites where samples were collected. (a) Abbott Ridge (b) Avalanche Crest
11
Figure 3: Common distribution of tree species at Abbott Ridge study site.
11
Figure 4: Common distribution of tree species at Avalanche Crest Field Site
12
Figure 5: Tree core sample taken at Abbot Ridge. Note the diameter of tree.
12
Table 1: Series intercorrelation values from tree cores collected at both sites
14
Table 2: Autocorrelation and mean sensitivity values from tree cores collected at both sites
14
Figure 6: Comparison of series intercorrelation, autocorrelation and mean sensitivity values
calculated for Abbot Ridge and Avalanche Crest
15
4
Acknowledgements
We would like to extend our thanks to Dr. Dan Smith, Dr. James Gardner and Dr. David
Atkinson for organizing the field course in Glacier National Park and for the invaluable learning
experience they provided us. We would also like to thank Bethany Coulthard for her guidance
and assistance with our field work, data analysis and interpretation of our results. The success of
our research study would not have been possible without her assistance. Lastly, we would like to
thank the remaining teaching assistants and Parks Canada staff for making this learning
experience possible.
5
Introduction
1.0 Introduction
The growth of subalpine fir trees (Abies lasiocarpa) in the Canadian Rockies is limited
by a number of factors at both the stand and individual tree level. Most dendrochronology
research describes temperatures during the growing season as the dominant factor affecting tree
growth at high elevations (Harsch & Bader, 2011; Martinelli, 2004). As is evident on the
landscape, individual trees can behave differently within a stand due to the presence of different
microclimates. Factors such as exposure, snow accumulation, sunlight, temperatures, topography
and nutrient availability vary across a stand and can result in different growth rates in trees
within close proximity to one another (Hotmeier & Broll, 2010; Peterson, Peterson & Ettl, 2002;
Resler, Butler & Malanson, 2005; Malanson et al., 2007). Unfortunately, the classification of
ecosystems based on similar characteristics promotes a more generalized approach when
describing how these systems function. This approach results in the creation of generalized
models to characterize the effects of global warming on the movement of tree line in alpine
environments (Hamann & Wang, 2006). These models are not entirely accurate as individual
stands can behave differently. Through the use of dendrochronology techniques, it is possible to
analyze tree growth responses across a stand and to predict the future growth responses of trees
based on predicted climate models.
The purpose of this study is (1) to use dendrochronology to determine the influence of
climate on the growth of Abies lasiocarpa on east and west facing slopes in Glacier National
Park and (2) to determine the likely factors affecting the growth of Abies lasiocarpa on an
individual tree level.
2.0 Literature Review
2.1 Dendrochronology
6
Dendrochronology techniques can be used to understand the influence of climatic
conditions on tree growth within a particular area (Gruber, Baumgartner, Zimmermann &
Oberhuber, 2008). By measuring variability in tree ring growth, it is possible to correlate
variations in tree ring width with climate data (Splechtna et al., 2000). This analysis allows
researchers to understand how climate influences tree growth in these environments. Multiple
dendrochronology studies have been conducted in subalpine and alpine environments (Peterson,
et al., 2002; Martinelli, 2004) with the assumption that climate is generally the limiting factor
affecting tree growth at high elevation. Based on the analysis of 28 tree ring chronologies, it was
determined that the growth of trees in the subalpine of the Cascade and Olympic Mountains is
limited primarily by short growing seasons (Peterson et al., 2002). This trend is apparent in
multiple dendrochronology studies; however, other factors can influence tree growth dynamics
within stands in the alpine environment.
2.2 Biogeoclimatic Ecosystem Classification
The Biogeoclimatic Ecosystem Classification (BEC) system is a scheme developed to
classify ecosystem types in British Columbia (Pojar, Klinka & Meidinger, 1987). The BEC
system groups similar areas based primarily on climate, vegetation and soil (Pojar, Klinka &
Meidinger, 1987). The areas examined in this study fall within the Engelmann Spruce Subalpine
Fir (ESSF) BEC zone. The use of the BEC system is challenged for a number of reasons,
including its tendency to invoke a linear thinking to complex ecosystems (Haeussler, 2011). This
linear approach is of particular concern when predicting the effects of climate change on tree line
systems, including the ESSF zone. By subdividing ecosystems into homogenous spatial units, it
is expected that these zones will respond to climate change in the same manner (Hamann &
Wang, 2006). Based on climate change models, the ESSF Zone is predicted to shift 86m in
7
elevation by 2025 and 225m by 2085 (Hamann & Wang, 2006). As will be discussed in the
following section, stand dynamics at tree line are impacted by a number of variables,
highlighting the potential for individual Abies lasiocarpa stands to behave differently to changes
in climate conditions.
2.3 Influence of Microsites on Tree Growth
Tree growth is controlled by climate and local environment factors, with individual trees
responding differently to environmental stressors based on local site conditions (Tessier, Guibal
& Schweingruber, 1997; Lloyd & Fastie, 2002; Peterson et al., 2002; Malanson et al., 2007;
Stueve et al., 2011; Elliott, 2012). These environmental influences can limit individual tree
growth within a stand, concealing large scale climate conditions. Based on this influence, it is
possible to have small scale tree growth variation in an area, with limiting factors varying
between individual trees.
Local topography and the distribution of trees throughout a site results in the formation of
microsites by either protecting or exposing individuals to stressors including sunlight, wind,
snowpack and moisture (Resler et al., 2005; Malanson et al., 2007; Stueve et al., 2011).
Microsites can be created by cliffs, avalanches, other trees, draws and streams. In these locations,
tree growth in individuals varies depending on varying degrees of exposure to various
environmental conditions such as light and wind. Exposed trees are prone to desiccation and cold
induced photo-inhibition as well as other mechanical damage (Resler et al., 2005; Malanson et
al., 2007; Holtmeier & Broll, 2010; Harsch & Bader, 2011; Stueve et al., 2011). Topography and
environmental conditions also influence the distribution of soil nutrients across a stand, resulting
in variable amounts of nutrients available to trees within a stand (Malanson et al., 2007; Stueve
et al., 2011; Elliott, 2012). Depending on the degree of variability within a site, the impact of
8
microsites on individual tree growth within forest stands can be quite high.
Mechanical controls on tree growth often result in a negative feedback response as they
lead to biomass loss through damage and dieback (Harsch & Bader, 2011). Avalanches are
powerful disturbance agents, reducing tree growth and tree density by opening up the forest in
subalpine areas (Christian et al., 2007). In these open environments, wind is a particularly
powerful limiting agent as it creates microclimates by altering local temperatures, altering
moisture levels through increased transpiration and evaporation, and causing mechanical damage
such as flagging, sand or ice blasting (Holtmeier & Broll, 2010). Neighbouring interactions can
also provide mechanical protection for individual trees, as a windward tree is capable of
protecting sheltered trees from wind damage or other hazards (Alftine & Malanson, 2004).
Depending on the amount of exposure, wind can significantly reduce growth rates in individual
trees within a stand.
Varying moisture levels can influence the rate of growth of individual trees within a stand.
Snowpack levels can vary within an area based on their location across the landscape, either
promoting or discouraging snow accumulation (Peterson et al., 2002). The addition of moisture
from snow aids in soil formation and produces favourable conditions for the growth of conifers
(Whiteside & Butler, 2010). On the contrary, high snowpack can also result in a shorter growing
season, limiting the growth rate of trees (Harsch & Bader, 2011). Moisture content is controlled
by climate, local topography and geomorphological conditions, with various features resulting in
different rates of water accumulation or dispersal in an area (Malanson et al., 2007; Elliot, 2012).
One study conducted in Alaska noted that there is a positive correlation between tree growth and
proximity to water because thermoregulatory effects from water bodies created a favourable
microclimate (Stueve et al., 2011). This is further confirmed by the fact that extremely dry areas
9
result in reduced growth rates in trees (Lloyd & Fastie, 2002; Peterson et al., 2002; Malanson et
al., 2007; Elliott, 2012). Overall, varying moisture levels within a stand can influence the growth
rates of trees in an area, which is largely controlled by local climate and topography.
Biotic interactions also influence tree growth rates, with competition and genetic variability
resulting in different growth patterns throughout a stand (Tessier et al., 1997; Alftine &
Malanson, 2004; Malanson et al., 2007; Stueve et al., 2011). Competition between individual
trees for energy, nutrients, moisture and space results in different growth rates, especially when
individuals have an advantage over other trees (Stueve et al., 2011). Also, genetic variation
causes individuals to behave differently compared to neighbouring trees. This is particularly
evident in a trees tolerance level to limiting factors such as nutrient or moisture availability
(Tessier et al., 1997; Malanson et al., 2007). Trees that are able to adapt to local conditions and
compete with other species will have higher growth rates compared to other individuals.
3.0 Methods
3.1 Study Site
Tree ring cores were collected from Abies lasiocarpa trees in Glacier National Park.
Glacier National Park is located within the Selkirk and Purcell Ranges of the Columbia
Mountains in southwestern British Columbia. Sample sites were located below tree line, within
an Engelmann Spruce Subalpine Fir Ecoregion, in the high subalpine zone at Abbott Ridge and
Avalanche Crest (Figure 1)
Abbott Ridge samples were collected at N51o 15.572’ W117
o 30.565’, on the western
aspect of Mount Abbott (Figure 2 & Figure 3). The tree cores were all collected within a draw
with a stream running through the base. The draw was likely part of an ancient rock fall deposit,
over which soils and forest have developed. Outside the draw, mountain hemlock (Tsuga
10
mertensiana) was more abundant. Within the draw, Abies lasiocarpa was dominant, with
decreasing numbers of Abies lasiocarpa present with increasing elevation. Three distinct cohorts
of Abies lasiocarpa were found, with diameters of 40-50cm, 20-30cm and less than 15cm. A
young cohort of Tsuga mertensiana appeared to be developing within the stand. There was a
high occurrence of downed trees at this site.
Samples from Avalanche Crest were collected at N51o 66.228’ W117
o 29.014’ (Figure 2 &
Figure 4) representing an eastern aspect of Avalanche Mountain. Tree cores were taken from a
relatively high graded slope surface. Abies lasiocarpa and Engelmann spruce (Picea
engelmannii) were the dominant species, with sparse Tsuga mertensiana throughout the site. On
all trees, branches were mostly found on the downslope side where sunlight was most available.
As with Abbott Ridge, this site was also located on an old fall deposit. Downed trees and a
cohort of predominantly Picea engelmannii snags were also found on this site.
Figure 1: Map depicting the locations of both study sites within Glacier National Park.
11
Figure 2: Images of study sites where samples were collected. (a) Abbott Ridge (b) Avalanche Crest
Figure 3: Common distribution of tree species at Abbott Ridge study site.
3.2 Sample Collection
Thirteen tree ring samples were collected using a standard 5 mm increment borer at both study
sites (Figure 3). Abies lasiocarpa trees were selected if they had a minimum diameter at breast
height (DBH) of 40 cm, were alive and healthy. Two samples were taken from each tree (180
degrees to each other) perpendicular to the slope in order to ensure that slope creep would not
affect ring width (Figure 5).
12
Figure 4: Common distribution of tree species at Avalanche Crest Field Site
Figure 5: Tree core sample taken at Abbot Ridge. Note the diameter of tree.
13
3.3 Sample Preparation and Analysis
Once relatively dry, tree core samples were glued to wooden boards. Cores were sanded
using a belt sander beginning with 80 grit sandpaper, continuing with progressively finer
sandpaper, to expose tree rings as per standard dendrochronology procedures (Speer, 2010). The
samples were then scanned and measured using WinDendro software, a digital tree ring
measurement program.
Ring measurements were analyzed using COFECHA, a computer program designed to
analyze tree ring measurements for cross dating and statistical analysis (Grissino-Mayer, 2001).
Due to technical problems, only 11 cores were analyzed from each site. Initial cross dating and
measurement corrections were contracted to a specialist in the University of Victoria Tree Ring
Laboratory. Based on statistical outputs, it was determined that there were no common growth
patterns within the tree rings and that cross dating of our samples was not possible.
4.0 Results
Series intercorrelation (SI) values were low in most tree cores at both study sites (Table
1). The mean SI value was 0.179 at Abbott Ridge and 0.303 at Avalanche Crest. As a result of
these low numbers, it was not possible to cross date samples taken from the same trees. Of the 22
trees examined, only four of these had significant SI values (AR05, AR13, AC04 & AC10).
Since the computed SI values were low and the cores do not correlate with other trees, it was not
possible to cross date the trees across the stand. Only AC04 and AC10 were able to cross date,
with an overall series intercorrelation of 0.491.
Within individual trees, autocorrelation values were high while mean sensitivity values
were low (Table 2). The mean autocorrelation value was 0.730 at Abbot Ridge and 0.707 at
Avalanche Crest. On the other hand, the average mean sensitivity value was 0.233 at Abbot
14
Ridge and 0.218 at Avalanche Crest. By examining these two stands, it is evident there are no
significant differences in autocorrelation and mean sensitivity values at both stands. See Figure 6
for a comparison of the mean SI, autocorrelation and mean sensitivity values for both sites.
Table 1: Series intercorrelation values from tree cores collected at both sites
Abbot Ridge Avalanche Crest
Tree ID SI Value Tree ID SI Value
AR01 0.168 AC01 0.287
AR02 0.053 AC02 0.095
AR03 -0.016 AC03 0.282
AR04 0.438 AC04 0.514
AR05 0.163 AC05 0.350
AR06 0.182 AC06 0.231
AR07 0.101 AC07 0.150
AR08 0.143 AC08 0.321
AR09 0.021 AC09 0.233
AR10 0.264 AC10 0.498
AR11 0.455 AC11 0.377
Table 2: Autocorrelation and mean sensitivity values from tree cores collected at both sites
Abbot Ridge Avalanche Crest
Tree ID Autocorrelation Mean
Sensitivity Tree ID
Autocorrelation Mean
Sensitivity
AR01 0.447 0.237 AC01 0.635 0.283
AR02 0.927 0.205 AC02 0.78 0.285
AR03 0.794 0.276 AC03 0.582 0.175
AR04 0.848 0.230 AC04 0.577 0.206
AR05 0.688 0.306 AC05 0.914 0.212
AR06 0.663 0.244 AC06 0.799 0.262
AR07 0.861 0.185 AC07 0.557 0.248
AR08 0.752 0.232 AC08 0.860 0.191
AR09 0.771 0.188 AC09 0.380 0.196
AR10 0.677 0.240 AC10 0.900 0.174
AR11 0.855 0.221 AC11 0.788 0.162
15
Figure 6: Comparison of series intercorrelation, autocorrelation and mean sensitivity values
calculated for Abbot Ridge and Avalanche Crest
5.0 Discussion
5.1 Cross Dating
Stand growth is thought to be controlled by a limiting factor which affects all individual trees in a
similar manner (Speer, 2010). If climate is the limiting factor affecting tree growth in an area, it would be
possible to correlate tree ring growth with local climate data. However, tree ring growth is determined by
both climate and ecological factors (Tessier et al., 1997). When it is not possible to match tree growth to
climate data it is assumed that ecological or environmental effects are limiting tree growth. Cross dating
between samples collected from Abbott Ridge and Avalanche Crest was not possible, signifying that no
stand-wide limiting factor exists, or at least micro-limiting factors are more limiting compared to climate
conditions. It was hypothesized that Abies lasiocarpa growth in both sites would be limited by climatic
fluctuations; however, it was not possible to cross date our samples. The low series intercorrelation
16
values calculated in COFECHA from tree cores at both sites indicate that tree growth in both
stands is a function of individual factors, rather than stand wide climate influences. This does not
mean that climate influences are irrelevant; rather it signifies that other factors are more
influential in controlling the rate of growth of Abies lasiocarpa at both sites.
The presence of different microsites and genetic variability within Abies lasiocarpa at both study
sites are likely contributing to different growth patterns in individual trees. The concept of thresholds is
very pertinent to this investigation, as it is possible that individual trees are responding to the same
environmental factors differently due genetic variations (Tessier et al., 1997; Malanson et al., 2007). As
well, patch scaled tree stands react differently to large scale factors such as climate or temperature due to
certain site specific variables. These physical micro-factors alter individual responses to factors in a
similar way that genetic thresholds alter growth behaviour. Micro-scale growth limiting factors could be
due to abiotic or biotic elements, resulting in to the development of microsite conditions within a stand
(Tessier et al., 1997; Lloyd & Fastie, 2002; Peterson et al., 2002; Malanson et al., 2007; Stueve et al.,
2011; Elliott, 2012).
5.2 Exposure as a Limiting Factor
Exposure levels at Abbott Ridge and Avalanche Crest contributed to different growth rates in
individual trees as a result of mechanical and physiological influences. Mechanical factors disrupt tree
growth and can lead to broken branches, topping, blowdown and sand and ice blasting (Holtmeier &
Broll, 2010). Downed trees were present throughout both study sites, likely as a result of wind and
avalanche disturbance. Physiological disruptions through wind action can lead to altered local climate and
moisture. Variations in temperature across a site, created by differential wind action, can lead to enhanced
or reduced growth depending on local topography. Certain geomorphic features, such as the draw at
Abbott Ridge, would protect tree specimens from wind exposure depending on their location within the
draw. High wind flow leads to increased transpiration and evaporation (Holtmeier & Broll, 2010) and the
removal of moisture from the system inhibits tree growth in areas limited by moisture (Lloyd and Fastie,
17
2002). The variations in climate as a result of exposure levels on both sites likely contribute to differential
growth rates amongst trees in the stand.
5.2 Topography as a Limiting Factor
Topographic relief from draws, boulders and trees were present at both Abbott Ridge and
Avalanche Crest, contributing to variations in growth rates among individual trees. Variations in
topography encourage conditions where individuals will have different exposure levels from potential
growth altering factors (Resler et al., 2005). Exposure to growth factors affects tree growth differently
depending on the factor. Sunlight for example is beneficial up to a threshold level, with both low and high
sun exposure limiting growth (Malanson et al., 2007). The draw within the Abbott Ridge study site was
of particular importance when considering the effects of exposed versus protected trees. Trees on the
slope down into the draw experience more exposure than trees found within the basin. Highly exposed
trees witness more sunlight and less protection from wind. The microclimate within the draw basin is also
different compared to what would be found throughout the rest of the subalpine stand. The presence of a
draw within the Abbott Ridge site contributed to variations in growth rates throughout the stand. The tree
stand at both sites also creates topographical relief from wind for protected trees behind windward trees
(Resler et al., 2005). At both Abbott Ridge and Avalanche Crest, a high amount of downed trees was
documented. When a tree is removed from the stand a gap is left in the canopy, exposing once protected
individuals to elements such as wind or sunlight. The differences in topography across the stand likely
contributed to variations in growth across the stand.
5.4 Pedogenesis as Limiting Factors
Soil development is not homogeneous, and thus, nutrient availability and moisture content are not
evenly distributed throughout the forest canopy (Elliott, 2012). Soils within Abbott Ridge and Avalanche
Crest would have different nutrient concentrations and moisture levels depending on their location within
the stand. Precipitation levels in Glacier National Park are high (1700-2100mm annually), with
approximately 68% of precipitation falling as snow (Environment Canada, 1984). The high
18
amount of snowfall in this region influences moisture levels within soils. The addition of
moisture from snow aids in soil formation and produces favourable conditions for the growth of
conifers (Whiteside & Butler, 2010). Topography and canopy openings throughout both sites
influence the snowpack depth throughout the forest stand. Within the Abbot Ridge site, there was
an intermittent stream present, which likely directs a considerable amount of snowmelt during
the warmer months. This stream impacts moisture levels throughout the site and would create
more optimal conditions for conifer growth in areas with optimal moisture levels. As well,
depressions and steep slopes throughout the site can result in high water levels in some areas and
the rapid movement of water in other areas. Canopy openings within the site increase sunlight
exposure, resulting in drier soils in these regions (Carter & Smith, 1987). Abies lasiocarpa grow
best in low light conditions where moisture levels are higher (Carter & Smith, 1987). Differences
in light exposure throughout a stand can influence growth rates between individual trees within a
stand. Exposure to frost followed by intense sunlight can result in depressions in photosynthesis
for trees growing in exposed sites (Maher & Germino, 2006). Furthermore, when nutrient or
water supply is reduced, sudden or abrupt decreases in yearly growth-ring increments occur
(Bollschweiler & Stoffel, 2010). Although moisture levels, canopy openings and soil profiles
were not examined at either site, differences in these characteristics throughout the site may have
a more direct influence on tree growth when compared to larger scale climate influences.
5.5 Competition and Genetic Variation as Limiting Factors
Competition and genetic variations in individual trees at both sites can lead to differential
growth rates amongst tree species. Competition amongst trees for light, nutrients and moisture is
an important factor in high elevation environments (Holtmeier & Broll, 2010). In these
environments, resources are limited, and having a competitive advantage over other trees is
beneficial for growth. Competition with other vegetation for water and nutrients can result in
19
decreased growth levels in areas where competition is high (Lloyd & Fastie, 2002; Harsch &
Bader, 2011). Genetic variations amongst individual trees can also influence growth rates in both
stands. Trees that are more equipped to deal with local stressors, including decreases in nutrient
and moisture availability, will likely have high growth rates compared to individuals unable to
cope with these stressors (Tessier et al., 1997; Malanson et al., 2007). Interspecific differences in
photosynthetic tolerances to light can impact tree growth and stress tolerance in alpine
environments (Maher & Germino, 2006). Within both stands, understory vegetation and the
presence of other trees likely resulted in competition between individuals, contributing to
varying growth rates amongst trees. Unfortunately, detailed notes for individual trees were not
taken and the genetic variation throughout the stand was not examined, making it impossible to
confirm these responses. However, variations in growth rates amongst individual Abies
lasiocarpa were likely influenced by both of these factors.
5.6. Implications for Dendrochronology and BEC System
The low series intercorrelation values calculated in COFECHA from tree cores at both
sites indicate that tree growth in both stands is a function of individual factors, rather than stand
wide climate influences. Much of the research conducted in subalpine and alpine environments
demonstrate that growth rates at tree line are most influenced by growing season temperatures,
with factors such as moisture and nutrient availability being secondary (Harsch & Bader, 2011).
However, this was not evident in tree cores taken from Abbott Ridge and Avalanche Crest. High
autocorrelation values in the majority of trees on the site indicate that growth in trees is highly
correlated with events in prior years. On the other hand, low mean sensitivity values indicate that
the variability within the rings is low. There were no considerable differences in calculated
statistics for both sites, indicating that trees at both sites are likely influenced by similar factors
and that individual tree growth is largely controlled by factors other than climate. Based solely
20
on the examination of tree cores on both sites, it is not possible to determine the limiting factors
for individual trees within the site. The variations in growth rates within the stand are likely a
result of a combination of exposure, topography, soil, competition and genetic variation
throughout the stand. This contradicts other research that indicates that climate is the dominant
limiting factor in subalpine and alpine environments. Although, some studies have found that the
sensitivity of high-latitude tree growth to temperatures has declined in recent decades, with non-
climatic factors or factors other than temperature becoming increasingly important limits to tree
growth (Lloyd, Fastie, 2002). This sensitivity change can influence the growth of trees in the
subalpine and alpine zones of high latitude areas, including areas in Glacier National Park. As
mentioned earlier, the BEC system promotes a linear approach to understand stand complex
ecosystems (Haeussler, 2011). Based on our study, it is evident that ESSF stand dynamics can be
influenced by a variety of factors, affecting individual trees within a stand differently. Climate
change models will have to take these types of stands into consideration in order to more
accurately predict the responses of tree line environments to global warming.
6.0 Conclusion
In conclusion, this study highlights the influence of microsites on the growth of individual
Abies lasiocarpa trees in the subalpine of Glacier National Park. Although growing season
temperatures are generally the dominant mechanism influencing tree growth at high elevation;
other factors can result in variable growth rates throughout a stand. Factors such as topography,
exposure, soils, competition and genetic variation can have a greater influence on tree growth in
individual stands compared to larger scale climate patterns. As was evident at Abbott Ridge and
Avalanche Crest, small scale variations were the dominant factors influencing growth patterns in
Abies lasiocarpa. This study highlights the need to take both stand level and individual tree level
21
scales into consideration when modelling the response of alpine environments to global
warming. The overall accuracy of this study could have been increased in a number of ways. Our
results are based on the analysis of 11 tree cores from each site; however, the inclusion of more
tree cores would have increased the statistical significance of our results and would have made it
possible to make more definite conclusions. Furthermore, knowing the locations of individual
trees and having detailed notes on potential factors influencing growth rates for each tree would
have allowed for a more detailed analysis of growth factors in these areas. Unfortunately, this
information was not recorded as it was hypothesized that growing season temperatures were the
limiting factor in both stands. Lastly, sampling additional locations within the valley and
collecting cores from trees of other species would have made it possible to better understand tree
growth patterns in this area. Overall, this study highlighted the presence of microsites within
Abies lasiocarpa stands in Glacier National Park, and can be used by resource managers to
further understand tree line dynamics within this area.
22
References
Alftine, K.J. & Malanson, G.P. (2004). Directional positive feedback and pattern at an
alpine tree line. Journal of Vegetation Science. 15(1), 3-12.
Bollschweiler, M. & Stoffel, M. (2010). Tree rings and debris flow: Recent 7
developments, future directions. Progress in Physical Geography. 34(5), 625-645.
Carter, G.A. & Smith, W.K. (1987). Microhabitat comparisons of transpiration and
photosynthesis in three subalpine conifers. Canadian Journal of Botany. 66(5),
963-969.
Christian, R., Susanne, H., Dominik, K. & Peter, B. (2007). Natural avalanche disturbance
shapes plant diversity and species composition in subalpine forest belt. Journal of
Vegetation Science. 18(5), 735-742.
Elliott, G.P. (2012). The role of thresholds and fine-scale processes in driving upper
treeline dynamics in the Bighorn Mountains, Wyoming. Physical Geography. 33(2)
129-145.
Environment Canada. (1984). Ecological Land Classification of Mount Revelstoke and
Glacier National Parks, British Columbia. Vol. I: Integrated Resource Description.
Edmonton: Environment Canada.
Grissino-Mayer, H.D. (2001). Evaluating Crossdating Accuracy: A Manial and Tutorial
for the Computer Program COFECHA. Tree-Ring Research. 57(2), 205-221.
Gruber, A., Baumgartner, D., Zimmermann, J. & Oberhuber, W. (2009). Temporal
dynamic of wood formation in Pinus cembra along the alpine treeline ecotone and
the effect of climate variables. Trees. 23(3), 623-635.
Hamann, A. & Tongli, W. (2006). Potential Effects of Climate Change on Ecosystems
and Tree Species Distribution in British Columbia. Ecology. 87(11), 2773-2786.
Harsch, M.A. & Bader, M.Y. (2011). Treeline form - a potential key to understanding
treeline dynamics. Global Ecology and Biogeography. 20, 582-596.
Haeussler, S. (2011) Rethinking biogeoclimatic ecosystem classification for a changing
world. Environmental Reviews. 19, 254-277.
Holtmeier, F. & Broll, G. (2010). Wind as an ecological agent at treelines in North
America, the Alps and the European Subarctic. Physical Geography. 31(3), 203-
233.
Lloyd, A.H. & Fastie, C.L. (2002). Spatial and temporal variability in the growth and
climate response of treeline trees in Alaska. Climate Change. 52, 481-509.
23
Maher, E.L. & Germino, M.J. (2006). Microsite differentiation among conifer species
during seedling establishment at alpine treeline. Ecoscience. 13(3), 334-341.
Malanson, G.P., Butler, D.R., Fagre, D.B., Walsh, S.J., Tomback, D.F., Daniels, L.D.,
Resler, L.M., Smith, W.K., Weiss, D.J., Peterson, D.L., Bunn, A.G., Hiemstra, C.A.,
Liptzin, D., Bourgeron, P.S., Shen, Z. & Millar, C.I. (2007). Alpine treeline of Western
North America: Linking organism-to-landscape dynamics. Physical Geography. 28(5),
378-396.
Martinelli, N. (2004). Climate from dendrochronology: latest development and results.
Global and Planetary Change. 40(1-2), 129-139.
Peterson, D.W., Peterson, D.L. & Ettl, G.J. (2002). Growth response of subalpine fir to
climatic variability in the Pacific Northwest. Canadian Journal of Forest Research.
32(9), 1503-1517.
Pojar, J., Klinka, K. & Meidinger, D.V. (1987). Biogeoclimatic Ecosystem Classification
in British Columbia. Forest Ecology and Management. 22(1), 119-154.
Resler, L.M., Butler, D.R. & Malanson, G.P. (2005). Topographic shelter and conifer
establishment and mortality in an alpine environment, Glacier national Park, Montana.
Physical Geography. 26(2), 112-125.
Speer, J.H. (2010). Fundamentals of Tree Ring Research. Tuscon: University of Arizona
Press.
Splechtna, B.E., Dobry, J. & Klinka, K. (2000). Tree-ring characteristics of subalpine fir
(Abies lasiocarpa (Hook.) Nutt.) in relation to elevation and climatic fluctuations.
Annals of Forest Science. 57(2), 89-100.
Stueve, K.M., Isaacs, R.E., Tyrrell, L.E. & Densmore, R.V. (2011). Spatial variability of
biotic and abiotic tree establishment constraints across a treeline ecotone in the
Alaska Range. Ecology. 92(2), 496-506.
Tessier, L., Guibal, F. & Schweingruber, F.H. (1997). Research strategies in
dendrochronology and dendroclimatology in mountain environments. Climate Change.
36, 499-517.
Whiteside, C.J. & Butler, D.R. (2010). Adequacies and deficiencies of alpine and
treeline studies in the national parks of the western USA. Progress in Physical
Geography. 35(1), 19-42.
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