1. Aspen Tree Well Influence on Microbial Respiration
Chloe Sommer, Aspen Tree Well Influence on Microbial Respiration, .ppt, 31 MB Keywords: tree wells, microbial respiration, aspen Sommer, C. Aspen Tree Well Influence on Microbial Respiration. Winter Ecology. University of Colorado at Boulder, 2018.
Chloe Sommer // Winter ecology, Spring 2018
Mountain research station, university of Colorado at boulder

2. Introduction
Tree wells = depressions in snow around tree trunks, formed by a tree’s reemitted longwave radiation
Microbial communities (bacteria, fungi) found underground flourish during winter months due to more stable conditions (Žifčáková, Větrovský, Howe, & Baldrian, 2016) BRINGING THEM TOGETHER
Deeper snow means more ground insulation, leading to more microbial activity (Lipson et al, 2006)
Because deeper snow means more insulation and subsequent microbial activity, the difference in snow depths in and out of tree wells could have implications for microbial respiration. Also referred to:
White, C. Variables Affecting Tree Well Formation. Winter Ecology. University of Colorado at Boulder, 2012.
For information on tree well formation and inspiration for this project.

3. So what?
Decomposition affects nutrient availability come spring growing season (Laganiere, Pare, & Bradley, 2009)
Affects distribution, composition of spring/summer vegetation
Are tree wells creating microenvironments for microbes?
Microbial CO2 output contributes to atmospheric CO2 levels
Climate change implications?
As we have discussed in this class, winter activity shapes the productivity of spring and summer growing seasons. Bioavailable carbon, nitrogen, and phosphorus provided by microbes affects distribution and composition of seasonal vegetation. These factors can have effects seen across the food web; vegetation quality and quantity attracts different birds and mammals. Because they’re tiny, microbes can be easily overlooked, but they are abundant all over the planet and, as we have learned, different microbes can be productive year-round. So, collectively, their respiration has the potential to contribute to the greenhouse gases in our atmosphere.

4. Background
Organic material (litter) affects distribution and survival of microbial communities (Laganiere, Pare, & Bradley, 2009)
Insulation, moisture, nutrient (N) availability = happy microbes
Quaking aspens produced fastest decaying, most nutrient-rich litter of trees studied (subalpine region) (Laganiere, Pare, & Bradley, 2010)
Highest likelihood of observing noticeable difference in & out of tree well
Question: Are there different rates of microbial respiration in vs. out of aspen tree wells?
According to past research, aspen litter was nutrient-rich enough to facilitate a lot of microbial activity. I decided that if there was more microbial activity taking place, I would have better odds of noticing differences; I would have more to measure & work with.

5. Methods Plot out 25 x 25m aspen grove near MRS
Select trees via randomly generated coordinates
Measure:
snow depth
soil surface temperature
soil respiration over 2 minutes
in & out of tree well at each site
5 replications
Before data collection days, I hiked around the Mountain Research Station to find a big enough, flat enough aspen grove to take measurements in. I wanted to find a grove dominated by aspens.

6. Methods Additionally, measure:
DBH
Tree well diameter
Find possible trends relating size of tree & tree well to microbial respiration differences inside vs. outside of well
I predicted a certain amount of variability in my data, and hypothesized that tree diameter and size could contribute to those differences. Really, I just wanted to collect as much data as possible in the parameters I was working with. The site was around 9,500 ft. in elevation. We collected data from 11:30am – 3pm on Saturday, February 17, The ambient air temperature outside was 2.7 degrees Celsius.

7. p-value: 0.0321  SIGNIFICANT!
Results
I analyzed this data using a paired t-test because each data set was paired, and from the raw data I could tell that the outside sites were all larger than the inside sites. This data fits with my background research because the snowpack inside tree wells was always shallower than the snowpack outside of tree wells, and deeper snow resulted in greater soil insulation and therefore greater temperatures.
p-value:  SIGNIFICANT!

8. p-value: 0.9269  NOT significant
Results
I analyzed this data using a paired t-test. Honestly, the standard error bars are almost a moot point. There is too much variation and no significant difference between the mean rate of respiration inside the tree wells, and the mean rate of respiration outside tree wells. Given the last graph, this is unsurprising. After the temperature results fit, but these results didn’t, I started to question what other variables besides snow depth and soil temperature could be affecting microbial respiration.
p-value:  NOT significant

9. Results
Three of the sites had greater rates of respiration inside of tree wells, whereas two sites had greater rates of respiration outside of tree wells. This graph further supports that there was no significant difference in means. However, by identifying which sites display which results, I looked for more trends and possible explanations for my data.

10. Results
For this graph, I attempted to look at a relationship between tree size, as measured by DBH, and difference between microbial respiration in and out of tree wells. My thought was that perhaps there was a threshold of size above which tree well’s effects would be more pronounced. However, as demonstrated by this scatterplot, there was no pattern or relationship. All of the results were pretty variable. It is possible that, with more points added to the scatterplot, a trend could be observed between DBH and microbial respiration rates in vs. out of tree wells.

11. Discussion: Methodology
All observations in one grove at one point in time
Subjective selection for most prominent tree wells
Insufficient amount of replications
Difficult to measure litter depth
Willows spotted nearby aspen grove
Accidentally in a riparian zone? Soil moisture implications?
Struggle to seal CO2 monitor due to hard, frozen soil  gas escape? Inaccurate readings?
As the results showed, I did not find any significant difference in microbial respiration in vs. out of aspen tree wells. However, it is worth noting these several limitations to the methods implemented in my study. The photos on the right demonstrate some of our difficulties in collecting data, and potential sources of error. We confronted ice layers, mixed litter and soil, and frozen soil. Also, deep snow made it difficult to get a good angle to get a seal on the soil with the CO2 monitor.

12. Discussion
No significant difference in microbial respiration in vs. out of wells
Aspens had generally small and shallow tree wells; not large enough to make a real difference?
Snow depth in vs. out of wells may not be influencing microbial respiration...but other factors might
Wind exposure (transport of aspen litter)
Tree density / canopy cover
Nutrient availability / ground litter depth
In the context of my data possibly being accurate, there could be some explanations and further steps to take from this study. Possible explanations for no significant differences in respiration could include nutrient availability. Perhaps aspen litter is more of a controlling factor than snow depth, and wind disperses aspen litter throughout the grove. If aspen litter has been dispersed by wind, I think that wind exposure could be a variable to be looked at in the future. Tyler’s research on aspen tree canopy cover (and indirectly density) could be a drop in the bucket of exploring that variable’s effect on microbial respiration. Mention his study when discussing possible tree density/canopy cover for future research. The last bullet point references the last slide’s photo: green shoots underneath the snow

13. Future Research
Tree well “microenvironments” surrounding different tree species?
Tree density / canopy cover effect on microbial respiration?
Wind exposure & litter depth/distribution?
How deep underneath snow will you find photosynthesizing plants?

14. Summary Deeper snow depth = greater soil temperature trend supported
No significant difference found in microbial respiration rates in vs. out of quaking aspen tree wells  other factors at play
No trend in aspen tree size & its tree well’s effects on microbes
Photosynthesis occurring near aspens & underneath snow
Ample opportunity for future research

15. Acknowledgements Huge thanks to: Tim Kittel, instruction & guidance
Derek Sweeney, CO2 monitor whiz
Cloe Dickson, data recorder & deep snow survivor
Tyler Piehl, glorified manual labor
“The real significant finding was the friendships we made along the way”

16. Literature Cited
Laganière, J., Paré, D., & Bradley, R. L. (2009). Linking the abundance of aspen with soil faunal communities and rates of belowground processes within single stands of mixed aspen–black spruce. Applied Soil Ecology, 41(1), /j.apsoil
Laganiere, J., Pare, D., & Bradley, R. L. (2010). How does a tree species influence litter decomposition? separating the relative contribution of litter quality, litter mixing, and forest floor conditions. Canadian Journal of Forest Research, 40(3), /X09-208
Lipson, D. L., Schmidt, S. K., Williams, M. W., Delany, A. C., Monson, R. K., Burns, S. P., & Turnipseed, A. A. (2006). Winter forest soil respiration controlled by climate and microbial community composition. Nature, 439(7077), /nature04555
White, C. Variables Affecting Tree Well Formation. Winter Ecology. University of Colorado at Boulder,
Žifčáková, L., Větrovský, T., Howe, A. and Baldrian, P. (2016), Microbial activity in forest soil reflects the changes in ecosystem properties between summer and winter. Environ Microbiol, 18: 288–301. doi: /