Blog 3: Ongoing Field Observations

Today I visited my field study area given. Given that I hadn’t visited in a month there were several changes since the last time. The ground vegetation is fully covered and consists of grass, clover and dandelion. The clover was much heavier at the top of the grass mound located at the south side of the courtyard. Due to heavy volumes of rain and ground was very moist.

The attribute I plan to study if the honey locust trees at the south side of the courtyard. The six honey locust trees have leaves on most of the tree, however the top foot of each tree did not have leaves. This was a common pattern and uncommon for the tree variety. There are no buds visible on the top of the trees. The remainder of the tree looks healthy with flowers beginning from the trunk.

In looking at the trees I believe the lack of leaves on the top of the trees is the result of the excessive rain and cool temperatures we have experienced. I predict that once the weather warms up and the ground dries up the trees will continue to bloom. In this study the response variable is the six honey locust trees. A potential explanatory variable is the temperature and soil moisture, these variables would be continuous.

Post 8: Creating Figures

After some messing around in Excel for a bit I created two figures, which contain two and three graphs respectively, though there is significant overlap between the two. They both contain a graph that displays the relationship between measured sunlight and branch growth, a graph showing the relationship between the distance to the nearest neighbour[ing tree] and branch growth and the second figure includes a graph showing the relationship between distance to nearest neighbour and measured sunlight.

I was surprised at first to see a stronger correlation between distance to “nearest nieghbour” and “branch growth” than between “measured sunlight” and “branch growth”, however this surprise quickly dissipated when the second graph measuring these variables (created from data taken at a second, lower elevation study area) actually showed a negative relationship, while that of “sunlight” and “branch growth” remained positive.

I was also quite surprised to see that the data did not fall into two distinct sets, or groupings, as I had initially predicted would occur (due to the observed distinction between number of branches on the uphill and downhill sides of each tree in the field). Prior to, and during my data collection, there seemed to be an obvious schism between the two sides of nearly every replicate. While the data still show a positive relationship between light measurements and frequency of branch growth, I suspect the sample size was not large enough to reflect this apparent discrepancy I noted in the field.

I know it sounds simple, but I actually struggled a bit with the question of how to properly label the axes. “Sunlight?” “measured sunlight?” “light”? After some deliberation I settled on “sunlight (W/m2)”, though as with which elements I will include in the figures that I put in the final report, I may change this.

I also was unsure about the whether or not to include the third graph (which shows relationship between “distance to nearest neighbour” and “sunlight”). I am still unsure whether both figures will include this graph, or if it will be included as a separate figure in the final report.

I also plan to take a harder look at the captions below each figure when putting together the final report to determine if they require further elaboration.

Theoretical Perspectives on Measuring Branch Growth Frequency

 

Being that my study aims to examine factors influencing the growth of tree branches, some pertinent areas of tree physiology may include photosynthesis, allometry and hormonal regulation. Naturally, these fields are all well documented in the scientific literature, and while I don’t expect to be breaking new ground in regards to vascular plant biology, I am excited to be broadening my personal knowledge base in this field, which I find more and more interesting the more research I do. I am quickly becoming appreciative of the fact that we are very privileged to live in a time where access to so much scientific knowledge is so readily available, in addition to rudimentary material for the budding student as well!

Even within the context of this course I am finding there to be some overlap with similar projects recently undertaken by fellow students. In particular, Doug’s study of insolation on species diversity has helped shed some light on the slope effect for me (pun intended).

While this blog post is supposedly on the theoretical perspectives of this project, I can’t help but ponder what possible practical angles it may hold as well. So far, the research I have done suggests that the measurement of biomass is a regular subject in the field of ecology, and is particularly of interest to the forestry and silviculture industries. The ability to manage biomass production is core to the practice silviculture and the better this process is understood the more effectively this process can be achieved.

Some tags that could be used to help identify this work could include Branch Growth, Sunlight, Pseudotsuga Menziesii and gymnosperm (one extra for good luck).

 

 

Blog Post 6: Data Collection

After tweaking some aspects of my study design, I returned to my study area 3 times over the past two weeks for some more data collection. I recorded data from 10 new replicates (based on the “rule of 10”) from the SE flank of Rainbow Mountain, as well as an additional 10 from the same are but at a lower elevation. I will not be including the data I collected a month ago for my “initial data collection assignment” in my final report (there are several reasons for this, including the fact that initially I was collecting my measurements too close to the ground, between 1 & 1.5m).

I have begun collecting my data from between 4-5m to mitigate possible confounding factors, including the slope angle near the base of the trees. This proved challenging at first, as making measurements higher up the tree was initially difficult to do with any degree of accuracy. I brought along a stepladder and a tape measure to assist with my measurements this time out, and after some practice I was able to devise a system for counting branches higher up the trees. I also used a different app to collect sunlight data to record in different units (watts per meter squared), which I think will provide a better representation of my predictor variable (“sunlight received”).

At the suggestion of professor Hebert, I also began taking measurements of the distance to the nearest neighbouring trees, as their presence may be a confounding variable in the growth of branches on the replicates being studied. In selecting the “nearest neighbour” I deemed only those trees that were 5m or taller to qualify, as any trees smaller than this would be unlikely to block sunlight from potentially reaching the replicates.

During my “initial observations” assignment, I was collecting on a day with some clouds, and their passing between taking measurements would create large inconsistencies in my light readings, even within the two sides of the same tree. In order to ensure the most uniform measurements of light, I collected on days with similar weather (clear, no clouds), and at the same time of day (12:00). (My first day of data collection took place at 14:00, so I returned at a later date to repeat the light measurements).

 Field note book measurements

I noticed several nuances during my data collection that complicated the process more than I initially anticipated: The first one being that trees don’t always grow perfectly vertical. They often grow at an angle, which can make placement of the light meter somewhat difficult. Secondly, the nature of light filtering through a forest means that a slight difference in where the meter is placed can have vast implications on the reading it generates (i.e. the difference of being directly in a sunbeam or in the shade can be a matter of only a few cm). And furthermore, the location of where light filters through changes constantly throughout the day. Being consistent with the location of the light meter and time of data collection, as well as trying to move quickly without allowing haste to affect the quality was all I could do to ensure uniformity of results.

The topography in the lower elevation study area varied somewhat from the upper one, as did the species that populated it. While the slope was fairly uniform at 850m, closer to the valley bottom at 610m there existed many rolling microfeatures (small knolls) that affected the ways the trees caught the light. I chose to continue with my randomized sampling method in both areas, however it was more difficult to come across the species I was studying (Pseudotsuga menzeisii) at the lower elevation area, and several times I would have to re-enter compass bearing and number of paces in order to find a replicate. This was not an issue at the higher elevation.

One ancillary pattern I noticed during my data collection was that it is not merely the number of branches that seems asymmetrical on the two sides of the trees, but also the length and foliage of branches as well. While the data collection seems to have strengthened my belief in the prediction that more branches grow on the downhill side of the trees, they also seem to be significantly longer as well as more likely to be covered in foliage. I did not notice this trend until well into my data collection, and did not take any measurements regarding branch length however, as it would be quite difficult to do at a height of 4-5 meters and I was unprepared to do so. It is an interesting pattern nevertheless and I will consider if there is a way I can return to incorporate it into the project going forward.

Example of a replicate with asymmetrical foliage

Blog 2: Ecology Article

For this blog post I looked at the article, “Ecological Integrity, Visitor Use, and Marketing of Canada’s National Parks”.

a) This article was found from the Thompson Rivers University Library. The article is part of the Journal of Park & Recreation Administration. 2003, Vol. 21 Issue 2, p63-83. 21p. The following is a link to the article, http://ezproxy.tru.ca/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=hjh&AN=32547365&site=eds-live.

b) Article classification, academic, peer-reviewed, review material.

c) Article classification explanation
Academic – The author is a professor at York University, the paper contains in-text citations and a reference section.
Peer-Reviewed – The ‘Journal of Park & Recreation Administration’ was peer reviewed.
Review – The paper does not have results from a field or lab study.

Blog Post 1: SSB Courtyard

The area I have selected to observe is the Student Services Building (SSB) Courtyard at Durham College. I first visited this site on May 5, 2017 at 11:00. The day I visited was a very rainy day with 80mm expected to fall over 48 hours.

The area is a mainly flat grass area that is approximately 70m long by 20m wide. The grass area is man-made and has a slight elevation on the south side. Sidewalks that lead to adjoining building surround the area and there is a parking lot at the south-west corner. At this time of year, the area is home to two Canadian Geese to protect the area for their nesting eggs. The area also frequents several bird species. The vegetation in this area is grass, weeds and there are nine trees. See pictures attached.

Three questions that come to mind when observing this area are as follows,

  1. How is the vegetation effected by the use of the courtyard by students and staff
  2. Are there any negative effects on the space due to the surrounding sidewalks and parking lot
  3. Is there different vegetation is shaded versus sunny areas.