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Blog Post 1 – Observations

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The area I have chosen to observe is the Chinook Rotary Nature Park in Calgary, Alberta. Once a gravel pit, this 40-acre park in the southeast corner of the city was is now part of Fish Creek Provincial Park and contains engineered wetlands that help filter run-off water from surrounding areas before it enters the Bow River.

Chinook Rotary Nature Park (Google Maps)

The park is located along the eastern bank of the Bow River.  It is flanked to the east by a steep incline, with a residential neighborhood at the top. The north end of the park runs alongside Highway 22x, while the southern park land continues as natural land beyond park boundaries. The land within the park consists of a combination of flat fields and small rolling hills.

Small pond with green algae visible

The focal point of the park are the 2 man-made ponds, a small one at the north end of the park and a larger one to the south. The ponds are connected by a narrow straight, however their waters are separated from each other by a small dam-like structure.    There is a walking path around both ponds, and a small bridge across the connecting point of the two water bodies. The majority of land within the park is covered by long grasses with patches of small shrubs.  There are deciduous trees, in both small groups and individually, found intermittently around the park as well.

I first visited this site today, June 2.  The weather was approximately 22 C, the sun was out and there was minimal cloud cover. The air had a smokey haze due to wild fires north of Edmonton.  I noted that there wasn’t heavy human presence in the park, with only 2 small groups seen during my observations.

Three questions that came to mind while I was in the park:

  1. I noted that the smaller pond had more green algae on its surface compared to the larger pond. I wondered if this was because the small pond was closer to the highway, and would therefore get more run-off from the roads in the winter, potentially changing the water quality in some way? Alternatively, I thought perhaps this pond water was more stagnant than the bigger pond, which could be favorable for this type of growth.
  2. I noted a lot more birds, both in density and number of different species, present in the larger pond. What is it about the larger pond that is more desirable to these birds?
  3. I noticed small minnow-sized fish in the deeper waters of the large pond, as viewed from the bridge between the 2 ponds. This being a man-made wetland, I wondered if these were human-introduced species (ie: stocked fish) vs natural fish (perhaps from the nearby Bow River that made their way upstream during high water levels or flooding). Since the larger pond was where all the birds were congregating, I wondered if the smaller pond had fish as well, or could this be a reason they were all drawn to the large pond?

Blog Post 9: Field Research Reflections

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This project, and the course in general, gave me a greater appreciation for ecology as a discipline of science.  I didn’t really have a good idea of what it was about before I started this course.  Once I got into the project I didn’t have any trouble implementing the design and didn’t find any reason to change it too much.  The focus of the project changed slightly due to my observations once out in the field.  The overall theme remained the same but I did narrow my focus.  I would have liked to collect more data: sample more sites, in more locations, to get a better representation of the true forest ecology in my data.  This, I think, is the struggle in science.  Juggling time and cost with efficient and accurate data collection.

I found the project very interesting once I had all my data and began analyzing it in the office.  This is an aspect of ecology that I really like.  I’m a numbers guy so I really like the statistical analyses of the data, looking for patterns and correlations.  To me this is really interesting; quantifying and testing patterns we observe in the field.

Blog Post 3: Ongoing Field Observations

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  1. The organism that I plan to study is the white spruce (Picea glauca).
  2. The gradient that I will be analysing is the amount of space between trees from very crowded to 3m apart. This distance is an average of the distance between tree trunks at ground level. The most crowded location (location 1, annotated in red, Figure 1) is the forest stand at the north end of my study site; the mid-level spacing (location 2) is a cluster of trees near the house (annotated in blue, Figure 1); the location with the furthest distance between trees (location 3) is at the north west corner of the study site (annotated in black, Figure 1). Figure 1.

These trees were all planted by my family about 10 years ago. I am planning to study and compare various patterns within the white spruces. These patterns consist of tree height, new growth/bud abundance, and DBH (diameter at breast height). I plan to use tree height and DBH to calculate biomass, which can be used to determine productivity through a regression model based on the relationship between DBH (cm) and biomass (kg). There are many opportunities for comparison.

3. The most obvious underlying process that may cause observed patterns is the amount of direct sunlight received by an individual. Another might be any limiting of a resource due to a higher density of individuals in the area. It is hypothesized that overcrowding of white spruce (Picea glauca) decreases overall productivity and ability for seasonal growth (budding). If trees have more space between each other, they will be more productive due to more available sunlight and resources. Trees that are subject to crowding will be less productive than those that have ample space to themselves. For example, I predict that location 1, the most crowded, will have higher competition for soil resources, which may restrict growth. In contrast, trees in location 3 may have more room to spread their roots and absorb sufficient resources.

4. One potential response variable is whether the white spruce (sample unit) is crowded or spaced. A potential response variable is the abundance of new buds or tree height. These variables will both be continuous, as they will both be measured on a numeric scale (centimetres or metres for distance between trees and height; number of buds).

Post 4

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Tree Species Actual Density Distance Systematic Data Distance Random Data Distance Haphazard Data
Eastern Hemlock

(Most Common) 

 

469.9

  

308.6

 % Error

 

34.3

  

395.7

 % Error

 

15.8

  

427.4

 % Error

 

9.0
Red Maple 118.9 105.8  

11.0

 45.7  

61.6

 63.7  

46.4
Sweet Birch 117.5 167.5  

42.5

 60.9  

48.1

 127.3  

8.3
Yellow Birch 108.9 114.6  

5.2

 159.8  

46.7

 127.3  

16.9
Chestnut Oak 87.5 141.1  

61.3

 68.5  

21.7

 90.9  

3.9
Striped Maple 17.5 8.8  

49.7

 0.0  

100

 27.3  

56.0
White Pine

(Most Rare)

8.4 0.0  

100

 0.0  

100

 9.1  

8.3
Survey Time 4 hours, 5 min 4 hours, 44 min 4 hours, 11 min

All three sampling strategies appear to have little difference in time.  However, the Random and Haphazard sampling strategies should take longer overall if travel time between plots is considered.

The most accurate sampling strategy for the most common and most rare species was found using the Haphazard sampling strategy and the sampling error for both were similar.

The sampling error greatly increased from the most common to the rarest species in both the random and systematic sampling strategies.  However, no real pattern was observed.

The number of plots was sufficient in capturing the number of species in the community but to improve the accuracy of the data more plots should be added.

Blog Post 7: Theoretical Perspectives

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My project deals with the effect temperature has on bird activity. This type of research is important to the field of ecology because with the threat of global warming, the effect this has on bird species will be extremely important to understand. As average temperatures across the globe increase, bird habitat including breeding grounds, food and resource availability will be affected. Some birds such as woodpeckers are keystone species and therefore threats to their environment could wreak havoc on other dependent species including some birds such as wrens and sparrows who use the holes created by woodpeckers as nesting habitat. If temperature does not have an effect on bird activity, such as foraging, it may suggest that certain species of birds are better able to adapt to changes in climate. By understanding the effect that increases in global temperature have on some species of birds, ecologists and other scientists will be better equipped to predict the snowball effect that climate change will bring universally.

Blog Post 8: Tables and Graphs

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I used regression analysis to quantify the correlation between birch distribution over varying aspects across a hillslope.  On the graph I included a logarithmic trendline and the coefficient of determination (R squared) value.  A R^2 value of 0.4198 does not indicate a strong correlation between aspect and birch distribution.

I didn’t have any trouble organizing my data and felt like this was a straightforward exercise.  When I first started this project I expected to see a stronger correlation between aspect and birch distribution but now I think there are other factors that are more influential than aspect alone.  I still think that soil moisture is a very dominant factor and is correlated with aspect, however; drainages, depressional terrain, or other areas where water accumulates will likely create suitable habitat for birch trees regardless of aspect.

That being said, this is a small sample size over a small area.  More samples over a greater area may yield a stronger correlation between aspect and the distribution of birch.

Blog Post #4 – Sampling Strategies

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For the Virtual Forests tutorial, I chose to use the area-based methods for my 3 samples. The fastest technique for sampling was the systematic technique along a topographic gradient with a time for 12 hours and 36 minutes.  What surprised me about the results was that the random and haphazard techniques, each taking 13 hours and 14 minutes, did not take much more time than the systematic approach.

The two most common species I found in my samples were the Eastern Hemlock and Sweet Birch.

Systematic Random Haphazard
Actual Density Measured Density Percentage error (%) Measured Density Percentage error (%) Measured Density Percentage error (%)
Eastern Hemlock 469.9 388.0 17.4 304.0 35.3 436.0 7.2
Sweet Birch 117.5 72.0 38.7 96.0 18.3 112.0 4.7

Analysis of the data collected for the 2 most common species indicates that the haphazard method of sampling was the most accurate strategy, with both common species having percentage errors in the single digits.

 

Systematic Random Haphazard
Actual Density Measured Density Percentage error (%) Measured Density Percentage error (%) Measured Density Percentage error (%)
Striped Maple 17.5 28.0 60 16.0 8.6 12.0 31.4
White Pine 8.4 0.0 100 0.0 100 4.0 52.4

Analysis of data collected for the 2 most rare species shows that all 3 sampling methods provided very inaccurate results. The second rarest species, the Striped Maple, was well sampled in the random method with a percentage error of only 8.6%. However, the rarest species, the White Pine was not found at all using this method. As species abundance decreased, percentage error of sampling using all 3 methods decreased.

 

Overall, 24 plots does not appear to be enough to get an accurate representation of species density across the range of species in the geographical area. I would predict that increasing the number of plots would increase the accuracy of all 3 sampling techniques.

To test this theory, I repeated both the haphazard and systematic techniques using 50 plots instead of 24. I found the same number of species (7) as before, however the haphazard method now yielded percentage errors of 0.02% for the most common species (Eastern Hemlock) and 19% for the rarest species (White pine). The systematic method now yielded a percentage error of 3% for the most common, and 19% for the rarest species.  I conclude, based on this observation, that more sampling plots, regardless of method, yield more accurate results.

Blog Post 2: Sources of Scientific Information

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I chose to review an article entitled “Spatial and Temporal Variation of Coyote (Canis latrans) Diet in Calgary, Alberta”, published in the journal Cities and the Environment.  I found this article online via Google Scholar. I was drawn to it in part because authors used Calgary’s Fish Creek Provincial Park in their research, a location I have chosen to observe for my research project.  I was also interested in the topic because I frequently see coyotes in the grasslands near my property and must keep in mind the safety of my pets when walking in the area.

This paper can be classified as peer-reviewed academic research material. Details of this statement can be broken down as follows:

  1. Peer-reviewed: Authors thank the three anonymous reviewers who provided feedback on their manuscript.
  2. Academic: Both authors are affiliated with the University of Calgary. An online search of their names confirms that both are accomplished researchers in the field of ecology.  In addition, the paper contains both in-text citations and a bibliography.  I noted that there seems to be some blank lines in their bibliography, however I’m not sure if this is an omission by authors or simply a formatting problem when downloading the paper.
  3. Research material: Authors are reporting on results of a field study. They include comprehensive information in the “Methods” and “Results” section that would enable readers to replicate their research if desired.

The article can be found at https://digitalcommons.lmu.edu/cate/vol4/iss1/8/

Citation: Lukasik, Victoria M. and Alexander, Shelley M. (2012) “Spatial and Temporal Variation of Coyote (Canis latrans) Diet in Calgary, Alberta,” Cities and the Environment (CATE): Vol. 4: Iss. 1, Article 8.

Blog Post 6: Data Collection

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I have collected ten replicates, and it is going well so far. We had some hail storms on the weekend so it gave me variable weather which is what my project is on. My parameters were raining/not raining so I have added  an “other” column just in case there is any other atypical weather patterns for this time of year. I think I will probably do another five replicates to give a total N of 15.

Post 2: Sources of Scientific Information

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The source of ecological information that I have selected is a paper entitled “Effect of local stand structure on leaf area, growth, and growth efficiency following thinning of white spruce.”

(Link:https://www-sciencedirect-com.subzero.lib.uoguelph.ca/search/advanced?docId=10.1016/j.foreco.2016.03.005). It was written by experts in the field. It also includes in-text citations (Tree growth is a function of the amount of foliage, the rate of photosynthesis per unit of foliage, allocation of photosynthate to components and conversion rates to new structural matter (Brix, 1983)) and a bibliography, making it academic material. It is not clear whether the article was reviewed before publication: “Acknowledgements: This research was funded by J.D. Irving, Limited and by a Natural Sciences and Engineering Research Council of Canada Collaborative Research and Development grant to a team led by D.A. MacLean. Kwadwo Omari was funded by a NSERC Industrial Post-graduate Scholarship. We thank the staff at J.D. Irving, Limited for their input and assistance with the project.” I would classify this source as non-peer-reviewed academic material.