Category: Robyn Reudink

Post 7: Theoretical Perspectives

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My study investigates the effect of soil moisture on Polystichum munitum abundance along a slope gradient. After collecting my data, I realized that my hypothesis was wrong so while my main focus is soil moisture, I will also have to take into consideration how other factors such as slope and canopy cover affect both soil moisture and fern abundance. It’s important to understand that species growth and abundance is dependent on a number of different factors. Some other ecological influences that I might briefly touch on in my paper and that underpin my research are soil pH, soil nutrition, interspecies competition, and disease. Therefore, my study would fall under a form of population ecology that focuses on how both abiotic and biotic factors affect a species or organism.

My keywords are the following: Polystichum munitum, soil moisture, slope gradient 

Post 6: Data Collection

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My data collection went quite well. Soil moisture can be affected by rainfall so I had to make sure I completed my data collection at one time. I collected my data on May 28th at around 1pm PST. It was a cloudy day, but it had rained quite a bit the day prior. I used pre-measured string to establish three transects about 10 m apart from each. One was along the top of the upper-slope, one in the middle, and one along the creek at the bottom. I placed five 16m2 quadrats on each transect, 4 meters apart from each other. This gave me a total of 15 replicates. 

The biggest struggle I encountered was that the rain from the previous day had made the slope quite muddy and slippery. This made it especially difficult for me to place my quadrats and transect in the middle of the slope. I slipped a few times and got mud all over me. Another small difficulty was the insertion of the soil moisture meter. At some quadrats, I really had to push hard to get the meter all the way into the soil to the marker. 

A pattern I noticed was that the soil moisture was around the same at both the top and bottom of the slope. However, the number of ferns was a lot more abundant at the top than at the bottom. This does not align with my hypothesis and I will have to reflect on some other factors on why this could be while writing my paper. I will take into consideration the greater shade at the top, as well as the bottom of the slope not being drained enough for ferns to grow. 

Post 5: Design Reflections

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I collected my initial data on May 20th, 2021 around 1:15pm. I decided on using quadrats along transects for my study. I brought with me a pre-measured 36m string, four 4m strings, and a soil moisture meter. There is a trail that goes along the top of the bank, which is where I chose to place the transect. I used a random number generator to choose the number of footsteps I would take from the entrance of the trail and placed the 36m string there, along the top of the bank. I placed my quadrats along the transect about 4m from each other and collected my data. I used the soil moisture meter directly in the centre of the quadrat to measure how moist the soil was and then I counted how many ferns were in that quadrat. In order for a fern to be counted, more than 50% of its total size had to be within the quadrat.

One of the struggles I had was that the bank was quite steep at some parts which made it difficult to place the quadrats safely. I was afraid I would slip and hurt myself. I think I might bring somebody with me to help me navigate the terrain safely next time. I also realized later that I should have made sure that the soil moisture meter was inserted into the soil at the same depth in every quadrat in order to reduce any inaccuracies in the moisture readings. I will mark the meter with a Sharpie next time and make sure I push the meter up to that point during each of the readings. Overall, I was quite happy with my study design as it is not overly difficult for me to conduct and is very interesting.

I did realize I will have to revise my predictions about my hypothesis. I had originally predicted that as soil moisture increases, fern abundance would decrease. However, after also choosing a quadrat by the creek that had a lower soil moisture level and observing a lower number of ferns, I will now predict that as soil moisture increases, fern abundance also increases.

Blog Post 5: Design Reflections

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The hypothesis for my research project is the length of time a Robin spends foraging in the meadow will differ from in the dog park. I predicted that the length of time a Robin spends foraging in the meadow location will be greater than in the dog park location due to the greater number of dogs present within the dog park than the meadow. The sampling method I have chosen will be the Point Count method. I visited the Meadow 5 times, approximately the same time between 5:00-7:00 PM and observed the Robins in the meadow for 30 minutes on May 3, 4, 5, 7 and 8, 2021. The sampling strategy was relatively simple. I sat at a picnic bench with my binoculars and timed the presence or absence of Robins foraging. Considering the time of day, I was surprised by the number of Robins actively foraging and how easily they would return from the meadow once a dog had left the area. I also observed some competitive behaviour between Robins, which I also thought was very interesting. Given the simplicity and lack of resources available, I have chosen to continue using the same sampling method. 

The excerpt from the field journal can be found here: https://drive.google.com/drive/folders/1xbUUajwJ8BOtYKSs8DY5s1f7doOIsc72?usp=sharing. Observations were recorded on the left-hand pages, including weather and activity within the meadow. The right-hand pages document when the foraging time (FT) began, which is defined when at least one Robin was present in the meadow. The foraging time stopped (FTS) when no Robins were present in the meadow. Time was recorded as minutes and seconds. The number of birds and dogs was recorded during one complete cycle of FT to FTS. The FT would begin again when at least one Robin returned to the vacant meadow. Please refer to table one for a list of acronyms. 

Table 1. List of Acronyms

Acronym

 Meaning
FT Forage Time
#B Number of Birds
#D Number of Dogs
FTS

Forage Time Stopped

Blog post 2: Sources of Scientific Information

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The source I found was an eBook from the online library through TRU. The book is called “Source of Birds of British Columbia: A Photographic Journey” by Glenn Bartley. This source will be useful while I am trying to determine bird species at the Esquimalt Lagoon. This source is considered as non-academic material because it does not follow the criteria of having a bibliography or in-text citations.

Link to the eBook https://ezproxy.tru.ca/login?url=https://search.ebscohost.com/login.aspx?direct=true&db=nlebk&AN=561136&site=eds-live&scope=site&ebv=EB&ppid=pp_53

Post 1: Observations

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I have selected an area of Esquimalt Lagoon located in Victoria on Vancouver Island, B.C. The area of interest is beside the ocean and in a little nook with a wetlands area some rocky shoreline and a grassy patch that is close to the road. There is fresh water run off from a drain that leads to the ocean shore. There is abundance of plant species including Oregon Grape and lots of tall grasses. The location was visited at noon on a sunny spring day in May and is approximately 50 ft by 40 ft. The spot I am interested in is full of birds of various species which makes sense since the lagoon is considered a bird sanctuary and I believe the birds would be great potential subjects. Three questions that could be formed are; What are the different bird species found to be eating and why?, Which is the proportion of strictly migrant birds vs strictly native ones in the area and suppose why?, Which birds more frequently stay in the area at different times of the day and suppose why?

Blog Post 4: Sampling Strategies

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Create a blog post describing the results of the three sampling strategies you used in the virtual forest tutorial. Which technique had the fastest estimated sampling time?

Systematic sampling was found to be faster than random or haphazard sampling. Systematic sampling took 12 hours and 35 minutes, random sampling took 13 hours and 50 minutes, and haphazard sampling took 12 hours and 54 minutes.

Compare the percentage error of the different strategies for the two most common and two rarest species.

Systematic Sampling:

Two Most Common Species:

Eastern Hemlock density actual was 469.9 versus 388.0 calculated is a 17.4% difference.

Sweet Birch density actual was 117.5 versus 148.0 calculated is a 20.6% difference.

Two Rarest Species:

Striped Maple density actual was 17.5 versus 40.0 calculated is a 56.2% difference.

White Pine density actual was 8.4 versus 20.0 calculated is a 58% difference.

Random Sampling:

Two Most Common Species:

Eastern Hemlock density actual was 469.9 versus 496.2 calculated is a 5.3% difference.

Sweet Birch density actual was 117.5 versus 107.7 calculated is an 8.3% difference.

To Rarest Species:

Striped Maple density actual was 17.5 versus 7.7 calculated is a 56% difference.

White Pine density actual was 8.4 versus 3.8 calculated is a 54.8% difference.

Haphazard Sampling:

Two Most Common Species:

Eastern Hemlock density actual was 469.9 versus 484.0 calculated is a 2.9% difference.

Sweet Birch density actual was 117.5 versus 140.0 calculated is a 16.1% difference.

Two Rarest Species:

Striped Maple density actual was 17.5 versus 32.0 calculated is a 41.7% difference.

White Pine density actual was 8.4 versus 8.0 calculated is a 4.8% difference.

Did the accuracy change with species abundance?

Both systematic and random sampling had greater accuracy with species abundance. However, haphazard sampling resulted in both the most common and rarest species having greater accuracy.

Was one sampling strategy more accurate than another?

Random sampling can be more accurate than systematic due to periodic ordering. However, haphazard had greater accuracy, which may be due to increased homogenous communities, leading to a greater community representation.

Blog Post 9: Field Research Reflections.

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Doing a field research was a great experience for me, not only as a student fascinated by Biological processes, but also as an individual who did not always pay much attention to the ecosystems around her. Some words that I could use to describe the overall experience include eye opening, intellectually challenging, and inquisitive.

During the process of designing the field experiment, I decided to use the systemic sampling strategy to help me avoid experimenter bias while choosing the samples. Initially, I thought I could randomly select the first bean plant, and then systemically select the next samples. However, later in the experiment I realised that the garden beds were not large enough for the samples to be spread out perfectly in fives (the random number generated using excel). Thus, I decided to use the same approach, but this time recording every third plant instead of the fifth.

Another change that I made while implementing the experiment was that I only collected data from 2 garden beds (locations) instead of 3, which were from the original plan. This was due to the inaccessibility of the garden bed because of the long fence around it, unfortunately I could not reach individual beans without making damage.

Finally, I can confidently say that engaging in the practice of ecology increased my appreciation for how ecological theory is developed. I learned that it starts as a simple process from observation, which grows over time as the experimenter finds certain patterns and organizations that sometimes represents significant processes in the surrounding communities, and even ecosystems.

Blog Post 3 – Ongoing Dufferin Wetlands Observations

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I returned to the Dufferin Park Wetlands on May 13, 2021 at approximately 16:40 hours, and decided to sketch a map (attached) to assist with further observations. I must note that the majority of the vegetation in this area is still in the process of recovering from the winter season.

On my way over to the wetlands, I noticed a “trough” that paralleled the sidewalk and tennis courts which featured some of the same vegetation that had I originally noted in my first blog post. I also made note of the two circular canal areas near the information/shade hut as they featured many similarities in vegetation to the wetlands, but to a greater degree than the “trough” noted earlier. Furthermore, during my observations, I noticed that only one bird attended the “trough” area and that two species of birds attended the circular canals.

These observations lead me to thinking that the diversity in wetland vegetation between these sites may have an affect on the diversity of bird species that interact with them. In short, I was lead to the following hypothesis and prediction:

  • A greater degree of biodiversity in wetland vegetation will lead to a greater degree of biodiversity in bird species that will interact with the vegetation.
  • I predict that more birds will attend areas that have more biodiverse vegetation more often than areas with less biodiversity.

The predictor variable in this case would be the number of plant species in a given area, and the response variable would be the number of birds that interact with the vegetation. I believe that the predictor variable will be continuous, but this may change as the vegetation develops over the spring and summer seasons. As such, this variable may change marginally (which remains to be seen) and may in fact become a categorical variable in time. The response variable in this case is categorical, so I believe that this will be either a logistic regression or tabular experiment.

I plan to use sections of the main wetlands area, the circular canals, and “trough” as there is a clear gradient in the biodiversity of plants between these areas.

Blog Post #4 – Virtual Forests Exercise

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Of the systematic, random, and haphazard sampling techniques used, I noted that each method presents its own advantages and disadvantages. For example, the systematic sampling strategy appeared to be the most straight-forward and least time-consuming method, but only focused on a centralized area of the landscape. The random and haphazard methods presented as very similar (especially because I opted to use no bias in my haphazard site selections) and appeared to be more complex, labour-intensive, and time consuming than the systematic method. However, these methods appeared to give a more complete picture of the landscape as the samples were not limited by any criteria, save for chance (which can unfortunately not work in our favour at the best of times, it seems).

I was under the impression that the sampling times would greatly vary, but was surprised to find that the estimations generated by the virtual program were marginally different. The sampling methods clocked in at the following times:

  • Systematic: 12 hours, 36 minutes
  • Random: 12 hours, 53 minutes
  • Haphazard: 12 hours, 37 minutes

I was unsurprised to find that the systematic method was estimated to be the fastest, but was even more surprised to find how close the haphazard method measured in. Regardless, I feel that the random and haphazard sampling methods could be highly variable due to the randomness of how sites are selected.

When examining accuracy, I had assumed that the random sampling method would be best, which, judging by the data comparisons appeared to have been somewhat correct.

The percentage error for the two most common tree species measured as:

  • Eastern Hemlock
    • Systematic: 17.4% error
    • Random: 19.7% error
    • Haphazard: 16.1% error
  • Sweet Birch
    • Systematic: 38.7% error
    • Random: 18.5% error
    • Haphazard: 41.9% error

The percentage error of the least common tree species measured as:

  • Striped Maple
    • Systematic: 60.0% error
    • Random: 4.6% error
    • Haphazard: 4.6% error
  • White Pine
    • Systematic: 100% error
    • Random: 100% error
    • Haphazard: 1.2% error

Overall, the random method appeared to be the most accurate sampling method for measuring the most abundant species, while the haphazard method appeared to be the most accurate when measuring the least abundant species. With all things considered, the random and haphazard sampling methods appear to be the most accurate and holistic methods to use, even though they are more time consuming than the systematic method.