Category: Nancy Elliot

Blog; 3

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Blog Post 3: Ongoing Field Observations

The organism I am going to study is the large Eastern Grey Squirrel in areas of the View Royal Park. The Eastern Grey Squirrel (Sciurus carolinensis) is an invasive species from Eastern Canada which out-competes our native squirrels. They are better suited to the city environment than our native red and brown squirrels according to the BC SPCA, so their invasive ecological impact is not as critical in urban settings. I’ve noticed the distribution of squirrels around the park is not equal and they tend to be found in different parts at different times of the day.

The environmental gradient I will use is three locations along the park. The first location in the middle of the off-leash park where no squirrels have yet to be observed at any time of day; the second location is the trees surrounding the off-leash park where squirrels have been observed at certain times of day, and finally the third gradient location which is outside the off-leash area near the childrens play area, where the most squirrels have been observed at most times of day. At busy times in the off-leash area of the dog park, no squirrels have been observed. Even if the park is unusually quiet at that time of day. these times include 0600-0800 and again at 1530-dusk. The area of the park where off-leash dogs are prohibited, squirrels are observed at constant numbers at all times of the day.

Hypothesis: The distribution of squirrels throughout the park is influenced by the occurrence of off-leash dogs. as squirrels are prey animals and dogs are predators. The squirrels avoid the off-leash area of the park at times of day when dogs are more likely to appear.

Response variable- The squirrel distribution behaviour Explanatory variable- The occurrence of off-leash predators (dogs)These variables are categorical as they have a finite category to fall into. Whether the squirrels are or are not there and whether the dogs are likely or unlikely to be there based on the time of day

1: Observations

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Blog Post 1: Observations of my chosen area.

The area I chose for my research project is my local dog park in Victoria’s View Royal area. The city park is approximately the size of two football fields or ~2-3 acres. The dog park makes up about 2/3 of the total park. It is a flat field with few leafless, planted, deciduous trees in the center and various wild shrubbery surrounding it. On one side there is a man-made ditch to collect rainwater and on the other side, separating the dog park field and the rest of the city park, there is a slow-moving stream which is approximately 50 feet wide at its widest and 3 feet at its narrowest. The field itself is flat and contains only green grass and clover weeds but the edges are home to various large coniferous trees and various shrubbery. Around the park, there is the stream with high, steep embankments which drastically slope down into the water. The water itself is brown in colour as it picks up mud from the banks moving through the park. Around the banks are large trees and thick shrubs which hide the view of the stream.

 

 

When you leave the dog area of the park, there is a slightly hilly field containing a child’s play area and old, large trees, like the ones surrounding the off-leash field, scattered around approximately 10 feet or more from each other. Surrounding the park on the opposite side from where the dog park is there are row townhouse homes. Many young families live here and are often outside in their yards even in the winter. In the northeast part of the park, there is an island of vegetation in the open field. It contains a douglas-fir and another type of western coniferous

I visited this park today at 14:00, it was a sunny, moderate winter afternoon at approximately 10°C. This weather is warmer than a usual Victoria winter day. There were a few humans accompanied by large dogs. There were two children on the playground. The wildlife observed were small birds, a rabbit and at least two squirrels. The birds were found in one group and were small and mostly brown. There were approximately 20-30 of them flying between a bush and a group of deciduous trees in the west corner of the park. The rabbit was seen near the road at the entrance of the park it was also brown. The squirrel was seen on a large coniferous tree near the children’s playground.

Observations

In my observations, I noticed that there are no observable prey animals (squirrels and rabbits) near the off-leash dog area compared to the many squirrels which inhabit the trees surrounding the area of the park where dogs must be leashed.

The plants surrounding the off-leash area seem to be native plants whose growth is not disturbed by landscaping efforts by the city unlike within the field which is mowed grass and hand-planted young trees.

 

The ditch on the north side of the park is man-made and contains stagnant, rainwater; which, if full enough, empties into the natural stream.

My Field Notebook Drawing

 

2: Sources of Scientific Information

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Blog post 2: Sources of Scientific Information

Amy Laycock.

A.  The source I have chosen is a research paper published in the Forest Ecology and Management Journal: Long-term time series of annual ecosystem production (198502010) derived from tree rings in Douglas-fir stands on Vancouver Island, Canada using a hybrid biometric-modelling approach.

B.  This article is an academic, peer-reviewed, research source.

C.  It has been written by experts in the field (authors who work in the Canadian Forestry Service and forest and ecology researchers out of UBC). It has been published in a scientific journal with a satisfactory impact score (3.169), which edits and peer-reviews papers before publishing. It includes in-text citations throughout the paper, citing other credible peer-reviewed sources. This article contains a section which outlines their methods in a way that other researchers could replicate the study and a results section which summarize the relevant data they collected. Therefore, the article contains all the required criteria to be a primary academic, peer-reviewed, research source.

source:

https://www-sciencedirect-com.ezproxy.library.uvic.ca/science/article/pii/S0378112718308405

Metsaranta, J., Trofymow, J., Black, T., & Jassal, R. (2018). Long-term time series of annual ecosystem production (1985–2010) derived from tree rings in Douglas-fir stands on Vancouver Island, Canada using a hybrid biometric-modelling approach. Forest Ecology And Management, 429, 57-68. doi: 10.1016/j.foreco.2018.06.040

Post 9: Field Research Reflections

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Elevated view of the open scrublands in Scottsdale, AZ.

I was lucky in that I got to explore not only a foreign (read interesting) environment, but that the sparse vegetation and flat land made my job quite easy. I did not have to change much of my design other than that I was a bit ambitious initially. I had planned to measure substrate densities and root moisture as well in the beginning. Perhaps, by myself the scope of my experiment was a bit ambitious. I am happy that I could refine it into a product that I am proud of!

Engaging in my own field research is a first for me in my years of education. Ecology was initially a subject I had little interest in despite my background in Biology. Through the process, I began to contemplate not only origins of life but how to care for and preserve it. This course also taught me that ecology was not simply a science of preservation, but also in very detailed relationships between organic and non-organic processes. The complicated relationships between species and their environment, rivals and abiotic factors reminds me of physics and how everything affects each other.

By going out into the desert, I also learned the field ecologists have quite a difficult job. The concentration it takes to sample while exposed to the elements could be draining and frustrating at times. My appreciation of the dedication to ecological theory has increased by leaps and bounds.

Thank-you for a wonderful class,

Darren Hildebrand

Post 8: Tables and Graphs

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Figure 1. As soil moisture increases, height of Larrea tridentata increases. Soil moisture is given as a ‘reading’ from the garden moisture reader with a scale of 1 (driest) to 10 (wettest). Height is given in meters (m). The R² value of the graph is 59%.

 

Above is one of the graphs created from my data. As per my prediction, creosote plants that grew in soils with higher moisture levels tended to be taller than their drier counterparts. The graph was relatively easy to construct and interpret. Further regression analysis is needed to see if the line is truly statistically significant by analyzing the residual plots, but an R^2 value of 0.59 or 59% indicates that it is probable.

Post 7: Theoretical Perspectives

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My research proposal focuses on not only abundance of Larrea tridentata but also to developmental success based on height (dried mass would be preferable but difficult and illegal in the scope of this course). These factors are being tested based on soil moisture in a semi-arid environment, namely the Sonoran shrublands of Arizona, USA. It was my hypothesis that creosote would be more successful in size and number with more access to moisture provided by the man-made oasis in Papago Park, Arizona. I tested this hypothesis through counting and measurement of creosote plants in pre-determined areas of varying distances from the water source. The shrublands have on average 11 inches of rain per year which is defined by some sources as arid and others as very semi-arid. This will limit the impact that unseasonal weather can have on soil moisture as more rain than usual can affect soil moisture.

My research touches on resource availability as a factor of reproductive success as well as growth. It also could be used in further research on competition for resources like water which are beyond the scope of this study. 3 keywords that apply to my proposal are arid shrublands, soil moisture, and reproductive success.

Post 6: Data Collection

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3 areas which are 10m x 10m in size were chosen at Papago Park around a man-made oasis. Area 1 was 5 meters south of the oasis. Area 2 was 20 meters south of the oasis. Area 3 was 50m south of the oasis. These 3 sites were chosen in a southern direction because south had the most unimpeded land (either by road or rock). The three sites were arranged in a line and did not veer substantially to the south-east or south-west. Each area was divided into grids of 25 subplots each measuring 2m x 2m. Each grid was assigned coordinates of x and y values. To pick the initial subplot in each area, the google number generator with n = 5 was rolled. I rolled it twice, with the first number acting as the x coordinate and the second number acting as the y coordinate. From there I used a systematic sampling method where each individual individual Larrea tridentata was counted and measured. From the first subplot, I would increase and decrease the x value until I have x = 1, 2, 3, 4 ,5. Y-values were y and y-1 (where y – 1 = 0, would wrap around back to around to y = 5).

5 subplots were selected in each of the three areas for a total of 15 replicates. The total time for the sampling and recording of data took approximately 1 hour and 35 minutes. Distance between each individual in the each chosen subplot to its closest neighbour was recorded, as well as the number of Larrea tridentata individuals and each plants height. There were few difficulties with this method of sampling. The only issue was that the number of individuals in area 1 was quite low and 2 of the chosen subplots ended up being empty which may skew the estimates of the height as empty plots had to be disregarded.

I noticed that the total number of plants (of any species)  increased dramatically in area 1 relative to the other 2 areas. However, the number of creosote bushes dropped substantially which was against my set out hypothesis. There was no ancillary pattern in the distribution of individuals but in terms of height, creosote closer the water were larger than those further away.

Post 5: Design Reflections

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My experiment takes place over 3 areas which are 10m x 10m in size. I subdivided each area into grids of 25 subplots each measuring 2m x 2m. I gave each grid coordinates of x and y values. To pick the initial subplot in each area, I used the google number generator with n = 5. I rolled it twice, with the first number acting as the x coordinate and the second number acting as the y coordinate. From there I used a systematic sampling method as I found it to be the most accurate in the virtual forest tutorial. From the first subplot, I would increase and decrease the x value until I have x = 1, 2, 3, 4 ,5. Y-values were y and y-1 (where y – 1 = 0, would wrap around back to around to y = 5).

A sample of the data and plot choice method.

I measured the number of individuals, the distance between the each individual to its closest neighbour and the height of each individual. I included averages of the last two measurements.

The soil moisture was previously determined at each area using a simple garden moisture probe in the geographic center of each area. The moisture probe had a scale of 1 (driest) to 10 (wettest). Area 1 (nearest to the man-made water source) measure at 6.0, area 2 ( 2om from the water source) measured at 3.5, and area 3 (farthest from the water source) measured at 1.8.

I found this method extremely easy to carry out in regards to resources and time required. The data did surprise me in that it seems to adhere to my expected results based on my hypothesis. I intend to sample area 1 and area 3 in the same manner.

 

Post 4: Sampling Strategies

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After completing the virtual forest sampling tutorial, the data was as follows:

Sampling Time (hr:min): The fastest sampling methods was the systematic sampling methods at 12hrs 36mins estimated.

Systematic = (12:36)

Randomized = (13:12)

Haphazard = (13:02)

Percentage Error of density of species:

Eastern Hemlock – Systematic (1.30%) Randomized (6.41%) Haphazard (37.1%)

Red Maple –           Systematic (-12.5%) Randomized (-49.5%)   Haphazard (27.8%)

White Pine –           Systematic (42.9%) Randomized (-4.76%) Haphazard (-4.76%)

Striped Maple –     Systematic (37.1%) Randomized (82.9%) Haphazard (37.1%)

Sample Calculation: Eastern Hemlock (systematic) = (estimated (476.0) – actual (469.9)) / actual (469.9) x 100 = 1.30%

Populations with greater numbers of individuals had much more accurate estimations than the rare species.

The systematic methods was the quickest as well as the most accurate sampling method. Surprisingly the randomized methods seemed substantially less accurate than the haphazard method. I believe it may be limited to this one trial however. I would expect the haphazard to be the least accurate because of bias whether intentional or subconscious.

 

 

Blog Post 9: Field Research Reflections

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First of all, I would like to say that I enjoyed conducting my field research and that I feel it has been a valuable tool in my understanding of how ecological theory is developed. There are so many factors to consider when developing and implementing sound,  scientific research and so yes, I have certainly developed a greater appreciation for the hard work and knowledge that is required.

I have to admit that I struggled in the beginning to even generate a feasible topic. Observing patterns in nature was not something that came readily to me, and I realized quickly that it was a skill I needed to develop. Once I had a topic and a general method, I had initially planned to randomly select my point count locations by overlaying a grid system onto the park map. This did not work as the randomly selected locations I had chosen on paper did not provide the best vantage points in he field and caused unnecessary disturbance to the ducks within the drainage channels.  I also had assumed that diurnal sampling, particularly during the early morning hours would be best suited, as it is well known that bird activity is greatest during the morning hours. I quickly discovered that this was indeed the case for passerines, however, the dabbling ducks were much slower to wake. I conducted a couple of trial sampling events in the hours before dusk and this seemed to be when the ducks were most active.

My study area posed several challenges for me as well, as public access was limited to the upper dike areas. This made visibility slightly more challenging, and it was unlike a forest setting where you can potentially access more areas for data collection. Perhaps with permission from parks staff, I could have measured other aspects within the drainage ditches, including water quality and or depth to see if these influenced duck abundance. Once I had decided on my experimental design, the actual data collection was quite simple. I incorporated randomization into my study by using a random number generator to decide the order in which I visited my selected sample locations.

If I had the chance to conduct the research over again, I would have conducted my sampling during the fall months when overwintering waterfowl are typically more prevalent within the park. This potentially would have given me a greater sample size to work with when analyzing my data, as overall duck abundance at all point count locations was lower than I had expected.