Category: Robyn Reudink

Blog Post 8: Tables and Graphs

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For my research project, I am studying the correlation between soil moisture and polypore quantity on individual trees. I collected soil samples from the bases of 24 trees: 16 with polypore fungi, and eight without. For assignment 5, I submitted both a graph to depict the data for the polypore-infected trees and a table for the polypore-free trees. Creating the graph for the polypore infected trees was quite simple using Excel. I inserted the x and y values into a table and then converted them to a scatter plot. This process nicely displayed my data in a manner that is easy to interpret.  However, I had a more challenging time trying to create a graph for the replicates without polypores. I struggled with figuring out how to present the data since the response variable was different than the first set of replicates. Since the fungi quantity for all eight replicates is “0”, it did not make sense to present fungi quantity on the Y axis. I decided that the information I wanted to convey for these replicates was soil moisture and whether or not they were clustered near polypore-infected trees (a simple yes/no variable). Since I could not figure out how to best graph this, I opted to create a table for this set of replicates. I will still play around with the data to see how best to display it for the final report.

The data was surprising to me as no clear patterns emerged between soil moisture and bracket fungi quantity per tree. I was hoping to see a clear trend wherein the higher the moisture content in the soil, the greater number of visible brackets on a tree. Similarly soil moisture was just as variable for the trees without bracket fungi, as many trees in very moist environments did not have any fungi. This has given me a lot to consider for further research which I will discuss in my final report. Variables such as (but not limited to) polypore-infected tree density, slope, canopy cover, soil pH, proximity to the watercourse, diameter at breast height and age of the trees could also impact bracket fungi quantity, and would be worthy of further exploration.

post 7: theoretical perspectives

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For my research project I am exploring the relationship between soil moisture and bracket fungi (Polyporales) growth in a section of Boreal Forest in the southern Northwest Territories. My study site is comprised of mixed wood trees, a creek that drains into the Great Slave Lake and a boggy area south of the creek; I have taken soil samples and bracket fungi counts from these three distinct areas. Bracket fungi can be saprophytic or parasitic, meaning they absorb soluble organic nutrients from the host species, which in my case are intact trees, snags or stumps (Allaby, 2019). Through my hypothesis I am exploring the theoretical perspective that increased soil moisture is positively correlated with polypore quantity on trees in this region.  Extrapolating on this, the research also explores the possibility that moister environments lead to higher rates of decay, as evidenced by greater fungi quanity. My hypothesis therefore touches on the biotic processes of parasitism, decay, decomposition and fungi reproduction as well as the abiotic factors of soil moisture and position of affected trees within the study area. Based on the theoretical idea that fungi proliferate in moist environments which promote a more rapid rate of decay, my prediction is that there will be an increased count of polypores in wetter areas.

Keywords:  fungi growth, polypore/bracket fungi, soil moisture

Allaby, M. (2019). A Dictionary of Plant Sciences (4 ed.). Oxford University Press. DOI: 10.1093/acref/9780198833338.001.0001

Blog Post 6: Data Collection

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Data collection at Mission Creek Regional Park is ongoing. Sample collection has been more efficient since reducing plot size to 100m^2. An additional area was selected to study approximately 500m east from the original site to increase the data pool, though this site has thicker brush which will make sampling challenging. To date, one of two study areas has been sampled (12 quadrats). Soil sample sites in each zone (riparian, floodplain, uplands) were selected, any further sampling is awaiting completion of a percolation test apparatus.

While it was initially observed Pinus ponderosa concentration was fairly constant through the gradient, it was since noted the tree characters change significantly. These observations have caused me to reflect upon my original hypothesis, warranting further investigation into stand make-up and quality, versus only tree concentration.

Post 1: Observations

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Date: 14/05/2021

 

Time:  4:30 PM

 

Weather: 26 °C, Sunny, Humidity: 34%, Wind: 14km/h

 

Location: King’s Park in Winnipeg, Manitoba.

 

Topography: beside the bank of the Red River Lake

 

Vegetation: Forest + grassland

 

Observations:

The site that I chose to conduct my research in is King’s Park Winnipeg, Manitoba. It is a park and residential subdivision located on the Western side of the Red River bank. The park includes walking trails, an off-leash dog park area and marshland and some ponds creating edge habitats.  The space is about 592 x 270 m.

 

As I entered the park, the first tree species that caught my eye was White Spruce trees. Following the trail, I noticed the most abundant tree species to be Jack Pine trees. As I walked around the park, I noticed some ponds some of which were dried up next to the off-leash dog area. There are many different species of shrubs that can be seen near the forested area by the lake. Some of the shrubs that I identified are the Virginia Creeper (Parthenocissus quinquefolia), Common moonseed (Menispermum canadense), Poison Ivy, Garden Rhubarb, Common lilac, and Mercurialis perennis. Other species that can also be found at King’s Park are the Red-winged black bird, ground squirrels, and monarch butterflies. As I was walking through the forested area, I noticed a high abundance of different types of worms hanging from strings. Some of these worms were also seen on the ground since their strings might have been cut off due to human disturbances.

 

Questions:

 

  • Which shrub species dominate the area and what are the reasons behind it?
  • What are the anthropogenic effects on the lifecycle of worms?
  • Do the tree species composition change from the entryway of the park towards the forested area near the river?

 

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Blog Post #5 – Experimental Design/Data Collection Reflections

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The original study area had to be re-evaluated as area size was noted to be a possible confounding variable, and also because one of the city parks staff completely destroyed one of the proposed study sites in early June. As a result, I decided to take a closer look at the main study area, and in doing so I noticed that there was a gradient in vegetation species richness already present in several areas of the Dufferin Wetlands Park. I decided to divide the main study area into four quadrants to conduct my data collection, and before collecting bird species data, I  surveyed each quadrant and counted the number of vegetation species present. Bird species data was collected from June 5-12, 2021 using the point counts sampling method.

The most pronounced difficulty in data collection that I noticed was the initial identifications of the bird species in the area. This was easily the most time-consuming task as some birds were extremely active and harder to identify than others. Once identifications were complete, I did not find the actual data collection replicates to be a difficult task, and found it to be relatively straight-forward.

At this point in time, I plan to make a few small changes but will ultimately stick to using this technique to collect data for my experiment. To explain, I will be adding a control site to the data collection, which will be a nearby parking lot. I will also attempt to control for the time of day by sampling data at the same times for each replicate, and also plan to standardize the point count sampling times for each area to 5 minutes. Cumulatively, I feel that these changes will help to produce more consistent data.

 

Blog Post 6: Data Collection

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Hypothesis:  Soil moisture affects presence and quantity of bracket fungi on mixed species trees in the Oxbow Trail Park.

Due to flooding that submerged large sections of my original study site, I elected to find a new site to complete my project. The area I chose is the Oxbow Trail park on Vale Island in Hay River, Northwest Territories. This park is comprised of wild mixed wood forest and creeks that drain to the Great Slave Lake and adjacent Hay River. It is largely untouched and sees very little foot traffic. For this reason, it is a good place to spot wildlife, including lynx, black bears and beavers. The other great thing about my new site is that unlike the first location, it is teaming with fungi. While I had a challenging time locating enough replicates at my original study site along the Kiwanis Trail, I quickly realized this would not be a problem in the Oxbow park.

For my initial study site I planned to run multiple transects and find the nearest polypore-infected tree for each transect. This strategy was chosen since the polypore-infected trees were quite rare, occurring only every 50-100 trees.

Since the presence of polypore-infected trees is plentiful at the Oxbow site, I decided to revise my strategy to incorporate stratified random sampling using randomly placed plots. I chose the stratified random technique because there were three distinct areas that I wanted to include: 1) The creek bed, 2) the forested area north of the creek and 3) the swampy forest south of the creek. I found plot coordinates using a random number generator. I sampled a total of 24 replicates, 4 from the creek bed, 10 from the north forest and 10 from the swampy south forest. This stratified breakdown gave a more accurate representation of the overall spatial context and distribution of trees.  16 of the replicates had polypores on them and 8 did not. I chose to study soil moisture content for trees without polypores to have a more complete understanding of the soil moisture distribution throughout the area.

Initially I only planned to count the number of brackets on each replicate and then take a soil sample from the base of the tree. However, during my field collection activities I felt it was also important to record additional details such as whether the tree was deciduous or coniferous, if the tree was alive or not, and if it was clustered amongst other infected trees. These additional findings may add more context to the study, however for the time being I am focusing only on the variables of # of fungi brackets and soil moisture content. I quickly discovered that many trees had brackets that extended far higher than I was able to count. Therefore, I only counted brackets up to diameter at breast height (DBH = 1.3) and then noted if multiple brackets were observed above this.

I initially planned on obtaining soil samples that were 20cm deep, however I found getting to this depth to be challenging due to roots, organic litter and the size of my spade. I therefore adapted my strategy and obtained all samples at a depth of 15cm, and tried to obtain approximately 100g of soil from each replicate.

To obtain soil weight and moisture content, I dried all the samples at 400 Celsius for 2 hours. Prior to drying, I weighed all the samples in the baggies that I collected them in, accounting for the weight of the bag. Once weighed, I placed the samples in the oven in batches. A few samples needed slightly longer to dry as they were very saturated. I considered the soil samples sufficiently dry when they crumbled easily, and no moisture could be felt.  I reweighed the dry samples, accounting for the weight of the bowl, and then calculated the moisture weight and the soil moisture content percentage.

Now that my samples have been collected and calculations are complete, the next stage will be graphing the data and looking for any patterns or trends which will either support or reject my initial hypothesis.

Post 9: Field Research Reflections

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Overall, my study went quite well, but of course not perfect. I ended up having quite different results than I had expected and found it difficult to find journal articles that supported my study. I do wish I had spread out my course load and did not have to rush my project at the end, as I think I could have done a better job. I did have to adjust my hypothesis while planning my study design but not at any point afterwards.

I really enjoyed this course. It did feel like a lot of work at times but I really appreciated having such a hands-on online course. It is often difficult to stay engaged during online courses, but the field research project made it a lot easier. I have a great appreciation for all of the work that ecologists do.

Blog Post 4: Sampling Strategies (Robyn Reudink)

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Systematic sampling was slightly faster than the other sampling techniques – taking a total of 12 hours & 4 minutes. Whereas both the random and haphazard sampling techniques took a total of 2 hours & 41 minutes.  This is likely because the quadrats in the systematic sampling technique are laid out in a linear transect, which potentially reduces the amount of time that is spent walking between quadrats.

The percent error of the different strategies for the 2 most common species, Eastern Hemlock & Sweet Birch and the 2 least common species, Striped Maple & White Pine, are outlined in the attached table. The random sampling technique was the most accurate of the strategies, as it had the lowest percent error for all species. For all of the sampling strategies, the accuracy was on average higher for species that were more common in the study area, than less abundant species.

Table – blog post 4

Blog Post 3: Ongoing Field Observations (Robyn Reudink)

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  1. Identify the organism or biological attribute that you plan to study.

The organism that I choose to study is the growth rates of Sunflower plants (sp. Helianthus annuus).

  1. Use your field journal to document observations of your organism or biological attribute along an environmental gradient. Choose at least three locations along the gradient and observe and record any changes in the distribution, abundance, or character of your object of study.

The potted sunflower plants are located on a concrete slab in an area that is approximately 20 m2. There are a total of 8 individual plant pots setup for this experiment – located adjacent to each other – with ~0.5m of space left between individual pots and setback ~2m from any adjacent vegetation and/ or structures. Note: there are 3 sunflower plants being grown in each of the 8 pots – for a total of 24 individual sunflower plants in this study – there are 12 sunflower plants in each of the 2 study groups (a low-water volume application group & a high-water volume application study group).

Refer to the attached diagram for an overview of the study area design which shows: the plant pot setup with sunflower plants nomenclature, and adjacent vegetation/ structure. Plants replicates L1 through L12 are all in the low-water volume group and plant replicates H1-H12 are all in the high-water volume group.

There have been no visual changes observed, to date, in the distribution, character or abundance of the potted sunflower plants. This is likely because the sunflower plants seeds were recently planted on May 26th and have not yet sprouted. However, there are slight differences between the plant pot locations within the study area, including – the physical location of each pot, and the vegetation and/ or structure that is located adjacent to each pot on the perimeter of the study area. My observations at the different locations within the study area, include:

  • Sunflowers plants L1-L3, & H1-H3 are all located in the SE section/ quadrat of the study area. These plants are located immediately adjacent to ornamental cedar bushes and an ornamental grass lawn on the south and east perimeters of the study area.
  • Sunflowers L4-L6, & H4-H6 are located in the SW study area quadrat of the study area. These plants are located immediately adjacent to ornamental pine and cedar bushes on the south and west perimeters of the study area.
  • Sunflower plants L7-L9, & H7-H9 are located in the NE study area. These plants are located immediately adjacent to an ornamental grass lawn and a house on the east and north perimeters of the study area.
  • Sunflowers L10-L12 & H10-12 are located in the NW study area quadrat. These plants are located immediately adjacent to a house and cedar bushes on the north and west perimeters of the study area.
  1. Think about underlying processes that may cause any patterns that you have observed. Postulate one hypothesis and make one formal prediction based on that hypothesis. Your hypothesis may include the environmental gradient; however, if you come up with a hypothesis that you want to pursue within one part of the gradient or one site, that is acceptable as well.

The underlining process that may cause patterns for this study is the 2 different water volume applications (low & high), these are the studies predictor variables. My hypothesis is that any observed changes in the size of the above ground portion of the sunflower plants are likely due to the water level applications. This is considered to be a manipulative experiment – as there are 2 predictor variables – while the other factors that could potentially influence the response variable are controlled therefore, this will allow me to reject or accept my hypothesis with a high degree of certainty. My prediction is that the size and density of the above ground portion of the sunflower plants will be significantly larger in the high-water volume study group, when compared to the low-water volume study group.

  1. Based on your hypothesis and prediction, list one potential response variable and one potential explanatory variable and whether they would be categorical or continuous. Use the experimental design tutorial to help you with this.

The potential response variable for this study are the size of the above ground portion of the sunflower plants (continuous). The potential explanatory variable are the amount of water received (low or high group) by each plant (categorical) in the study.

blog post 3- diagram

 

Post 8: Tables and Graphs

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I had a hard time inserting my data onto a graph as my numbers were a little strange and I had multiple data points with the same x and y-value. I initially thought I would use a scatter plot but after trying that in Excel, I realized it looked quite messy and the data was difficult to understand. So I decided the best way to illustrate the patterns in my data would be two bar graphs that show the means of soil moisture and the means of number of ferns for each transect. I felt the trends in my data were much easier to understand this way. Although I only submitted the bar graphs figure for Small Assignment 5, I think I may also use a table in my paper to insert the specific data from each quadrat.

Based on my bar graphs, I could clearly see that both Transect A and C had similar levels of soil moisture, but Transect A has a much higher number of ferns than Transect C. Furthermore, although Transect B was the most dry, it had a similar number of ferns to Transect C. This outcome is not what I expected as I had hypothesized that as soil moisture increases, the number of ferns would also increase. I will have to consider other factors that may contribute to this pattern while writing my paper, including shade, degree of slope, and soil pH.