1. The Effects of Slope Aspect on Tree Density in the Subalpine Forest
Alex Sandberg-Bernard
Winter Ecology, 2018
Mountain Research Station, University of Colorado Boulder
Alex Sandberg-Bernard
Winter Ecology, 2018
Mountain Research Station, University of Colorado Boulder
.pptx: 6.1MB
Tree density, subalpine forest, basal area, vegetation, aspect
All images © Alex Sandberg-Bernard, unless noted otherwise

2. BACKGROUND Subalpine forest Highest elevation forests
Subalpine fir – Abies lasiocarpa
Engelmann spruce – Picea engelmannii
Limber pine – Pinus flexilis - (Peet 1981)
Subalpine forests in the Colorado Front Range of the Rocky Mountains make up the highest elevation group of trees before forests give way to the exposed and treeless areas of alpine tundra.
These forests are dominated by engelmann spruce (Picea engelmannii) and subalpine fir (Abies lasiocarpa), as well as limber pine (Pinus flexilis) (Peet 1981).

3. BACKGROUND Topography can control abiotic factors
Slope aspect
N slopes – less solar radiation, deeper snow pack
S slopes – more solar radiation, shallow snow pack (Måren et. al. 2015)
Vegetation & species distribution
Spruce/fir stands on moist slopes
Limber pine in drier areas (Peet 1981)
More moisture, higher tree density (Måren et. al. 2015)
Forest diversity and distribution in mountain ecosystems can be affected through several abiotic factors, including climate, solar radiation levels, and moisture availability. Topography plays a direct role in controlling those abiotic factors. In the northern hemisphere, north-facing slopes receive less solar radiation than south-facing slopes, and as a result often experience deeper and longer lasting snow packs, which favors moisture-loving plants (Måren et. al. 2015).
Engelmann spruce and subalpine fir tend to occur together in mixed stands on cooler, wetter slopes, whereas limber pine dominates dry and exposed sites (Peet 1981).
Moisture has been shown to affect tree density, with wetter slopes having higher tree densities than drier slopes (Måren et. al. 2015).

4. Does tree density depend on aspect?
This project will investigate whether slope aspect affects tree density.
In addition to measuring density, snow depth will also be measured in order to gain information about differences in moisture availability.
This project will also investigate whether the effect of slope aspect on tree density is dependent on tree species.
H0 = there is no relationship between tree density and aspect
H1 = there is a relationship between tree density and aspect
H0 = there is no relationship between tree density and aspect
H1 = there is a relationship between tree density and aspect

5. SITE SELECTION & SETUP Niwot Ridge – north and south slopes
Two plots just below tree line
Three 50 m transects per plot
Three observation points per transect
Pseudoreplicates – no time for true replication
Two plots were selected: a north-facing plot and a south-facing plot on opposing slopes of Niwot Ridge. Both plots were chosen at a low enough elevation from tree line to ensure the exclusion of Krummholz, as well as any ribbon forest dynamics. The plots were also high enough in elevation to ensure that no Lodgepole pine would be present.
Within each plot, three 50 m transects were measured, running from East to West (parallel to the slope).
Along each transect, three points were randomly chosen as “observation points.”
The replications used in this project are pseudoreplicates. In order to truly compare aspect’s effect on tree density, I would have needed to select three separate mountains, with a north-slope and south-slope plot on each. Due to time constraints, this was not possible for this project.

6. METHODS Bitterlich sampling method ID all “in” trees
Bitterlich stick
Rotation around fixed observation point
Count “in” trees
Density measured as basal area (m2/ha)
ID all “in” trees
Snow depth measurement
Proxy for moisture
The Bitterlich sampling method was used to calculate density, as measured by basal area.
Basal area is the cross-sectional area of a tree at breast height.
From a fixed observation point, trees are counted in a circle utilizing an angle-gauge or “Bitterlich stick.” This instrument is a stick with a cross-piece on one end, with a specific ratio between the length of the stick and width of the cross-piece (Mueller-Dombois et. al. 1975).
The stick is held up to one eye and aimed at each tree approximately 1.5 m up the trunk from the ground. Only trees that appear wider in diameter than the cross piece are counted (Mueller-Dombois et. al. 1975).
This method uses simple geometric principles to obtain an even sampling of the forest, accounting for smaller trees that are close to the observer as well as larger trees that are farther away (Mueller-Dombois et. al. 1975).
The Bitterlich stick I used had a ratio of 50:1, which give the stick a Basal Area Factor (BAF) of 1. This means that each “in” tree represent 1 m2/ha (Mueller-Dombois et. al. 1975).
All “in” trees were also identified in order to measure species composition.
Snow depth was measured at each observation point using a snow depth probe. This measurement provides a proxy for moisture availability.
Image 1: Wikimedia commons,
Image 2: Yang, et. al. 2017
Yang, et. al. 2017

7. Results: Basal area and aspect
Two-tailed t-test
p << 0.001
Higher density on N slope
Mean basal area on south slope = m2/ha
Mean basal area on north slope = m2/ha
Two-tailed t-test: p << 0.001
There is a significant difference between tree density on north and south slopes
Density tends to be much higher on north slopes

8. Results: Basal area, aspect, tree species
2 factor ANOVA with interaction
p << 0.001
Species is important
2 factor ANOVA with interaction
Looks at the effect that one independent variable has on the other, in relation to the dependent variable.
Does the effect of aspect on basal area depend on the tree species?
Yes, tree species is an important factor when examining the effect of slope aspect on basal area. Basal area is higher in total on the north slopes, but this is due mostly to Engelmann spruce.
p << 0.001
Strong interaction and significance
On the south slope:
Spruce and fir similarly affect basal area, with limber pine having less of an effect
North slope:
Spruce (mean = m2/ha) has more than twice the effect on basal area than fir (mean = m2/ha)
Limber pine has no effect on basal area on north slope (0 trees counted)
Overall, slope aspect’s effect on basal area absolutely depends on the species.

9. Results: Basal area and snow depth
Regressions
N slope: p = 0.087
S slope: p = 0.31
Opposite trends
Deeper snow on S slope
Does snow depth affect basal area?
Regression used to analyze relationships between basal area and snow depth on each slope
No significant relationships found on either slope
North slope
p = 0.087
Downward trend: increasing snow depth, decreasing basal area
South slope
p = 0.31
Upward trend: increasing snow depth, increasing basal area
Greater snow depths were found on south slope.
Greater snow depths found on south slopes, counter to expectation

10. DISCUSSION Greater density on N slope Tree species is important factor
Confirms expectation and previous studies
No moisture relationship found
Tree species is important factor
Spruce most important on N slope
Limber pine absent on N slope
Balanced ratio of spruce:fir on S slope
Why more south slope snow?
NW winds
Greater density on N slope
North-facing slopes have higher densities than south-facing slopes.
This confirms expectation and findings of previous studies that have found higher tree density on north-facing slopes (Måren et. al. 2015).
Måren et. al. (2015) found a positive relationship between moisture and tree density, but my study was unable to confirm this connection.
Density depends on tree species
When measuring the effect of aspect on density, it is important to consider the tree species.
Engelmann spruce has majority (over 50%) of effect on density on north-facing slopes, while limber pines are totally absent.
Spruce and fir have more of a balanced effect on density on south slopes, with limber pine playing a small role.
Why more snow on the south slope?
One possibility is that orographic precipitation on the westerlies bring more NW winds, which would have the effect of blowing snow from Niwot Ridge onto the south-facing slopes.

11. FUTURE RESEARCH More snow pack measurements True replication needed
In order to truly understand snow pack (and moisture) effect on vegetation, measurements would need to be taken throughout the winter.
Late spring storms often bring heavy snow fall. Reduced sunlight on north-slopes can cause persistence of snow pack into the summer, later than on south-slopes.
This project used pseudoreplication. In order to truly test the relationship between aspect and tree density, replication with additional mountain sites (each containing north and south plots) would be necessary.

12. CONCLUSION Aspect good predictor of basal area
Greater density on north slopes
Tree species is important
Moisture effects uncertain, warrant further study
Aspect is a good predictor of basal area, with greater densities being found on north slopes
Tree species is an important factor in the effect of aspect on basal area
Spruce and fir are similarly important on south slope
Spruce is most important species on north slope
In order to asses the effect of snow pack on basal area, more measurements are needed throughout the winter

13. REFERENCES
Peet, R Forest vegetation of the Colorado Front Range - Composition and dynamics. Vegetatio 45: DOI: /BF Måren, I.E., S. Karki, C. Prajapati, R.K. Yadav, and B.B. Shrestha Facing north or south: Does slope aspect impact forest stand characteristics and soil properties in a semiarid trans-Himalayan valley? Journal of Arid Environments 121: DOI: Farrell, J The Effects of Topography on Forest Cover in Subalpine Forest. Mote, P.W., A.F. Hamlet, M.P. Clark, and D.P. Lettenmaier DECLINING MOUNTAIN SNOWPACK IN WESTERN NORTH AMERICA*. Bull. Amer. Meteor. Soc. 86: 39–49. DOI: Mote, P.W Climate-Driven Variability and Trends in Mountain Snowpack in Western North America. J. Climate 19: 6209– DOI: Yang, W., H. Koba- yashi, K. N. Nasahara, R. Suzuki, and A. Kondoh Quantitative Evaluation of Bitterlich Sampling for Estimating Basal Area in Sparse Boreal Forests and Dense Tropical Forests. Open Journal of Forestry 7: DOI: Mueller-Dombois, D., Ellenberg, H Aims and Methods of Vegetation Ecology. John Wiley & Sons Inc., New York