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Final Blog Post: Reflection

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This was my first time designing and performing my own field experiment. I did experience some issues with implementation. First of all, I was unsure whether I would have enough sample units to collect.  However, I was able to find enough rose bushes to sample when I extended the study area.  The quadrat sampling method proved to be more difficult for measuring samples on bushes, because the surface is not flat like the ground.  I had to re-define the sample area in order to make each sample collection the same.

 

Engaging in the practice of ecology has definitely changed my perspective on the development of ecology theory.  I find myself noticing more patterns within the environment, and designing mini experiments in my head on how I would attempt to explain such patterns.  It has also opened my eyes to just how complicated, intertwined and sophisticated natural ecosystems are.

Blog Post # 6

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Over the past 2 weeks I have completed 5 transects of the ecological reserve. This included 25 circular plots with a 5.64 m radius. I am wondering if I have over sampled the reserve for the purpose of my research. After reading published research papers that use transects to assess edge effects it appears I could have simplified my design and taken collected less replicates. My plots and observations continue to indicate that most of the invasive species occur close to forest edges and disturbed areas such as old skid roads and foot trails.

Theoretical Perspectives (#7)

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Disturbance and succession are the main ideas which serve as the primary theoretical framework of my project. My hypotheses, which predicts that the size and abundance of rosa acicularis bushes will vary in relation to specific conditions and the presence or absence of specific plant species, is based on the idea that certain plant species can be attributed to specific seral stages, and that these stages are definable by measurable biotic characteristics. Interactions such as competition, mutualism, and facilitation also underpin the ideas guiding my observations about the plants found growing near prickly roses. Because this project is being conducted in the most populated area in the southern Yukon, the boreal forest ecosystem and anthropogenic influence are also useful elements in this project’s framework.

Keywords include: disturbance, succession, boreal forest, competition, mutualism, facilitation, pioneer plant, rosa acicularis, prickly rose.

Ongoing Observations

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The organism that I would like to study is the Wolf Willow (Elaeagnus commutata). I chose three areas that are along the Bow River in the southwest of Calgary, Alberta that have a large population of E. commutata. The first area (1) was between two pathways, and a medium distance from the river; the second area (2) was at a much higher elevation than the river, close to the river; and the third area (3) was at a higher elevation than the river and far away from the river.

The plants that were closer to the river in area 1 appeared to be taller, and still had some berries present on the tallest branches. I didn’t bring a measuring tape but the plants here are taller than I am, so they are at least 6’ tall. The plants in area 2 were around 4’ tall, and much more abundant than either of the other areas. Only a few scattered berries were present, again on the tallest branches. In area 3, the furthest from the river, the plants were quite short – only around 2’ – and there were no berries present.

It’s unusual to see berries on plants during winter, but the wolf-willow’s berries seem to remain throughout the winter and into the spring. They are a pale silver colour.

From these observations I hypothesize that the growth of E. commutatais heavily reliant on a nearby water source. I predict that the tallest E. commutataplants will be in close proximity to the river. The responding variable would be the average height of the plants, which is a continuous variable. The explanatory variable would be the adequate water present in the form of the Bow River.

Data Collection (#6)

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Preparation for collecting data took almost as long as data collection itself. First, I made tables in Excel with which to collect my data, but ended up forgetting to include two rows for boreal climax species (birch and aspen). This was not a significant issue as I had included blank rows in the table which I used for this purpose. Then, using google’s random number generator, I determined which 6 blocks I was going to collect data from within. I then I used the random number generator again to determine the origin point of the transect axes. When this was finished I knew exactly where I was going to collect my data from before I went out. Finally, I made a 1x1m collapsible square out of thick cardboard and bolts to use as a frame to define my plots, much like the squares made of PVC tube and elbows in the video.

I was fortunate to have a friend come out with me and perform a lot of the recording as I called out my observations. Finding the blocks and starting points for the transects was occasionally difficult, but my gridded map and the GPS on our phones helped. We then strung a tape line down the transect axis and placed the plot square into the first position, recorded the relevant variables, measured the rose bush height with a measuring tape and calculated their average height, then moved the plot square to the next position. This was repeated until the transect was complete, at which point we found the starting point for our next transect and repeated the process. In total, 120 replicates were sampled over the course of 4 hours.

The main difficulty I encountered was determining which category certain variables fell within, especially about light and moisture. On several occasions I found myself wanting to assign a variable a value between two discrete categories by adding a .5. I did not do this. Aside from that, occasional game trails were encountered in the undisturbed areas, and I considered whether or not they may make an impact on the distribution and size of rose bushes. In the end I made a note of the game trails but did not alter the designation of the block they were found in.

My companion commented that solitary rose bushes seemed on average larger than those found in close proximity to others. I did not notice this pattern, but I will look for this when I analyse the data. If there is a discernible relationship, it may indicate intraspecific competition.

All in all, collecting the data was a relatively straight forward event due to planning it out ahead of time. No significant obstacles or set-backs were encountered.

Design Reflections (#5)

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The acquisition of the initial data in module 3 was relatively uncomplicated, though I think I could improve the way I collect the data in a few mays. First by refining the categories; variables such as percentage of exposed soil and potentially relevant attributes of other species present were not recorded, and the method I used to categorize the moisture regime was imprecise. I may make changes to my tables to better isolate the relevant variables, and I will likely modify my technique to collect my data to allow for better numbers and accuracy.

The technique I used was to overlay a map of my chosen area with a grid of squares, each measuring 20×20, and designating each square as either disturbed or undisturbed. I selected one of each in close proximity and I divided each of these squares into a grid of 400 1x1m squares from which 3 were randomly selected in the disturbed square and 2 in the undisturbed square. These 5 plots were my samples, and I recorded the light exposure, moisture regime, and the other plant species present as my predictor variables, and the number and the average height of rose bushes present as my response variables. Because undisturbed squares outnumber disturbed squares, by selecting an equal number of each to collect an equal number of samples from, I hope to reduce the number of samples necessary to see relevant trends in the data.
Changes I will make to this technique will include the number of samples I record and the way I select them. I will still use randomization, but instead of recording observations from 2 and 3 randomly selected replicates per square, I will likely record 2 transects of 20 plots per 20x20m square, providing more data and an equal number of observations from disturbed and undisturbed areas. 

Sampling Strategies (#4)

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Comparing the three sampling methods employed in the virtual forest tutorial, the haphazard method had the fastest estimated sampling time at 12 hours 26 minutes, then systematic at 12 hours 36 minutes, and finally random with the slowest estimated sampling time at 12 hours 43 minutes.

For the two most common species (Eastern Hemlock and Red Maple), the systematic method was the most accurate, with p = 1.30% and 12.53%. The least accurate was the haphazard method (18.81% and 19.43%), with random falling between the two (12.26% and 15.90%).

For the two least common species (White Pine and Striped Maple), the systematic method was still the most accurate (42.86% and 37.14%) the haphazard was still the least accurate (98.81% and 114.29%), and the random method still fell in the middle (50.00% and 100.00%).

The accuracy of all methods declined along with species abundance, and the systematic approach remained the most accurate regardless of abundance.

Ongoing Field Observations (#3)

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I have chosen Rosa acicularis (prickly rose) as the organism I will study. It is common throughout the southern Yukon and can be found easily in most areas that have not been heavily developed. Around pumphouse pond, the area I have chosen to conduct my observations, I have observed this rose in various densities and morphologies. It appears most frequently along the sides of walking trails, power-line clearings, cleared lots, and at the edges between undisturbed and developed sites. It appears infrequently in the midst of stands of tall coniferous trees, far from trails and other disturbances.
Almost everywhere I found Rosa Acicularis growing, I also found Rhododendron groenlandicum (Labrador tea), though the inverse was not true. In fact, in many of the darkest, wettest parts of the forest, where prickly rose was least abundant, Labrador tea had grown leaves and appeared to be further in its seasonal development than in areas where the prickly rose was more abundant, where Labrador tea was still bare.

One area in particular, on the top of a bank at a clearing to the east of pumphouse pond, had a thicker-than-usual stand of rose bushes, most of which were above average in height, interspersed with fire weed (Chamaenerion angustifolium), a known pioneer species.

My hypothesis is that Rosa acacia is also a pioneer species which tolerates and/or requires many of the conditions present early on during a secondary succession. I predict that a random sample of plots representing gradients which include regimes of light, moisture, and inter-species interactions, will reveal discrepancies in the size and abundance of rose bushes.

Potential predictor variables include: light exposure, moisture regime, and other species present (# and type). Response variables include rose plant abundance, average plant height, and average fruit density. I am curious to see if, with sufficient replicate plots, any of these predictor and response variables can be specifically related to each other. For the sake of simplicity, all three predictor variables will be categorical, and all response variables will be continuous.
I will continue to use pumphouse pond as a general study location, though I will apply a grid over a map of the area and divide it into blocks which contain disturbances (roads, trails, developments) and blocks which do not, and randomly select an equal number of each category to sample 10 or more randomly selected sub-plots with respect to the predictor and response variables listed above. 

Blog Post 2: Sources of Scientific Information (Percy)

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The source of scientific information is referenced below:

Ding, Y., & Peng, J. (2018). Impacts of Urbanization of Mountainous Areas on Resources and Environment: Based on Ecological Footprint Model. Sustainability,10(3), 765.

Based on what I have learned on how to evaluate sources of scientific information, I have determined that this article is peer-reviewed, academic review material. The information was written by two authors who have knowledge on the subject, as Jian Peng is the one who submitted the data analysis and it was reviwed by Yu Ding who wrote the paper and handled the manuscript submissions. The paper had been reviewed by at least one referee before publication, as we can see the submission dates and the publication dates are different. The source also reports results of an experiment by including a methods, results, and discussion section. The research is supported by in-text citations, and followed by a bibliography at the end of the paper.

Blog Post 6

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Collecting the data for my study has so far gone pretty smoothly. It has been a little challenging to lay the sampling line as the vegetation is fairly dense and quite a bit of scrambling has been required. I have sampled 6x 15m lengths at each site, and on each sampling line I have taken 5 measurements of fern frond size. As I began sampling next to the creek site, I realised that the fern growth became more abundant as the distance from the path increased, so I made sure that I always recorded the site closest to the road as sample 1 and the one farthest from the road as site 5. From my initial observations, it appears that the fern size variability seems greater at the creek site compared to the interior site, however, this is yet to be determined if it is a statistical difference.