A Dendrochronology Study of East and West Facing Slopes in Glacier

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

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.

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

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 15 calculated for Abbot Ridge and Avalanche Crest

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.

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’ W117o 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’ W117o 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.

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 Autocorrelation Mean Autocorrelation Mean Tree ID Tree ID Sensitivity 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

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.

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.