1. The Effects of Topography on Forest Cover in Subalpine Forest
Jason Farrell
Mountain Research Station | University of Colorado Boulder
Winter Ecology Spring 2016
Jason Farrell
Spring 2016
“The Effects of Topography on Forest Cover in Subalpine Forest”
pptx: 1.7 MB
Vegetation, topography, tree density, slope, aspect
**Note: all images by me, unless noted otherwise

2. Background Soil moisture and aspect = forest cover
Climate change = unknown changes
Predict growth given climate change?
What areas have the most growth now?
Does the topography of the land have an influence on forest cover (the amount of trees)?
After elevation, the most significant abiotic factor on forest cover in the subalpine is wetness1, followed by aspect (Bader and Ruijten 2008). While competition is a significant factor on forest growth patterns at lower elevations (with less extreme abiotic conditions), topography is still important in determining forest cover (Callaway 1998). Differences in slope and aspect result in variable soil properties, notably soil moisture, and because resulting microclimates affect subalpine forest cover, namely tree density (Bader and Ruijten 2008). Previous studies correlate increased soil moisture with higher tree density (Tyagi et al. 2013), and some mountain systems with warm, dry summers have shown increased tree density where snowpack is highest, especially on topographic convexities (Rochefort and Peterson).
Having a deeper understanding of where and why trees thrive (and thus act as carbon stocks) will allow for better understanding of which areas will see increased or decreased growth in light of current and future changes in climate and soil moisture (Adams et al. 2014). This is significant due to the ecosystem services that subalpine forests provide, such as habitat, watershed protection, and carbon sequestration, and the need of governmental agencies to manage land with a subalpine zone.

3. Experiment
H0 = tree density/basal area will have no significant relationship with aspect, angle, drainage character, or snow depth
H1 = tree density/basal area will have a significant relationship with one or more of the following: aspect, angle, drainage character, or snow depth
This project will examine the affects that slope aspect, slope angle, drainage character (a proxy for soil moisture), and snow depth have on tree density and basal area. Given that aspect, angle, and snow depth can also be proxies (or indirectly affect) soil moisture in some manner, the project’s main goal is to determine if tree density is affected by soil moisture, which is best accomplished by performing a variety of tests. The hypotheses are:
H0 = tree density will have no significant relationship with aspect, angle, drainage character, or snow depth
H1 = tree density will have a significant relationship with one or more of the following: aspect, angle, drainage character, or snow depth
Pictures (left to right)

4. Setup
Definitions:
Tree density: number living trees of trees per m (pic 1)
Basal area: DBH height, biomass estimate (pic 2)
Snow depth: surrogate indicating soil moisture
Drainage character: relative to surrounding landscape, either flat, concave, or convex (pic 3)
Procedure
Site Selection
Walk north of MRS to access south, east, and north facing slopes (pic 4)
15 sites in total
Identified by drainage character; 5 flat samples, 5 concave, 5 convex
Use transect tape to measure 10m2 plot
Measure aspect, angle, elevation from center of plot
Measure snow depth at all 4 corners and center, then find average depth for each plot
Count all living trees (having needles/buds)
Due to time and logistical constraints, random selection is not present in this project. This creates bias that may mean that the data does not accurately reflect the actual tree density of the subalpine, even after statistical tests are performed.
Pictures (left to right):

5. Results (Slope, Snow Depth)
Linear regression
Density vs Slope: no relation, p =
Density vs Snow depth: no relation, p =
Basal area vs Slope: no relation, p =
Basal area vs Snow depth: no relation, p =

6. Results (Aspect, Drainage)
2 Factor Analysis of Variance (ANOVA)
Examined aspect and drainage effects on tree density and basal area
3 categories each
Aspect = N ( deg), E ( deg), S ( )
Drainage = mid, bottom, top slope
Aspect nor drainage had significant effect on tree density
Aspect no effect on basal area
Drainage did have effect on basal area
P =
Overall trend shows that while aspect is variable, a clear trend is seen with drainage character; means/SE are far enough apart, not due to chance
Bottom slopes had the most biomass, followed by mid slope and top slopes

7. Results (Aspect, Drainage)
Slope is tied to drainage character
Top/bottom slopes tend to be flatter than mid slopes
Shows trend that basal area increases w/ drainage character

8. Results (Aspect, Drainage)
Aspect, no matter the slope, is (surprisingly) uncorrelated with basal area

9. Discussion Drainage Character: bottom vs. top slope Top slope
Possible that bottom slopes supported more biomass because water collects there, whereas top slopes tend to shed water
Previous studies correlate increased soil moisture with higher tree density (Tyagi et al. 2013)
However it is also possible that sampling bias interferes with reality, and there may be no correlation on a larger scale
Anecdotally (based on my observations), bottom slopes tended to have a higher number of smaller/thinner trees
Mid slopes had larger, more spaced trees
Top slopes were variable, but often more sparse with exposed ground
Top slope
Mid slope
Bottom slope

10. Discussion Snow Depth: potential significance?
While there was no significant relationship between basal area and snow depth, when the top left data point was excluded from analysis the p value dropped to
While still not significant, given that bottom slopes accumulate more snow, it is possible with larger sampling that snow depth would show a relationship with basal area
Note the general trend
Aspect did not have a significant influence on any measure of forest cover
It is likely that aspect is more significant on a meso-scale, not a micro-scale
Slope also had no effect on forest cover, although this could be due to sampling homogeneity; not enough variation in slope angles

11. Conclusion Basal area is better measure of forest cover
H0 true for slope,
aspect, snow depth
H1 true for drainage
character
Basal area is likely a more accurate proxy for forest cover/tree density, as it measures biomass
Forest cover appears to be related directly to the water accumulating potential of the land
Logically would accumulate more snow/rain water (my data does not quite show this to be true)
No significant effect of slope, aspect, or snow depth
Significant effect on forest cover due to drainage character

12. References
Adams, H. , H. Barnard, and A. Loomis Topography alters tree growth–climate relationships in a semi-arid forested catchment. Ecosphere 5(11): 148.
Bader, M. and J. Ruijten A topography-based model of forest cover at the alpine tree line in the tropical Andes. Journal of Biogeography 35: 711–723.
R. Callaway Competition and facilitation on elevation gradients in subalpine forests of the northern Rocky Mountains, USA. Oikos 82(3):
R. Rochefort and D. Peterson The temporal and spatial distribution of trees in subalpine meadows of Mount Rainier National Park, Washington, U.S.A. Arctic and Alpine Research 28(1):
Tyagi, J. V., N Qazi, S. Rai, and M. Singh Analysis of soil moisture variation by forest cover structure in lower western Himalayas, India. Journal of Forestry Research 24(2):