Recent Posts

Reudink, Post 7: Theoretical Perspectives

TRU Open Learning 1 Comment

User:  | Open Learning Faculty Member: 

My project is investigating the gradient of increasing Populus alba density seen in a forested area and if that is associated with soil moisture content. There is an empty dyke near the west perimeter of the study area and P. alba density increases linearly westward, so I’m testing to see if the same gradient can be seen in the soil moisture content. My hypothesis is that P. alba density is associated with soil moisture. This is investigating a form of population ecology that is primarily concerned with the ecological process of how abiotic factors can affect a population. If no correlation is found between soil moisture and P. alba density, then I would consider other abiotic factors as explanatory factors such as soil pH, nitrogen content, sunlight exposure, etc. Biotic factors could also be considered to affect this population such as interspecies competition or the incidence of infectious disease.

Keywords: Populus alba, soil moisture, density gradient

Reudink, Post 6: Data Collection

TRU Open Learning Leave a comment

User:  | Open Learning Faculty Member: 

To collect my field data, I established three transects through the 0.68 ha forest area under investigation and systematically placed six circle plots with a 5m radius 20 paces apart in each transect. Altogether there were 18 replicates. I am interested in the density of large Populus alba trees and the associated soil moisture, so at each circle plot I extracted a soil sample at the centre of the plot and measured the circumference of each large tree at breast height (above 25cm in circumference). I made sure to dig at least 10cm deep when collecting soil samples and removed any gross organic material before taking any measurements. My sampling design went quite smoothly; however, there was a recent snowstorm that covered my study area in snow, so walking and digging was more time consuming and I also had to be careful when extracting soil samples to not contaminate them with the surrounding snow. Once I got back to my house, I sorted through the soil samples to make sure there was no organic matter and then weighed them all, put them in the dehydrator at 115˚ F, then weighed them again. I used the resulting value to calculate the soil moisture content percentage.

While walking through the dense forest and seeing my data unfold before my eyes, I noticed that the centre transect was having a greater density of P. alba then my east transect. This was surprising to me because I initially believed that my peripheral transects were both denser in P. alba than the centre transect. When reflecting back to my current hypothesis (P. alba density is associated with soil moisture), this reaffirmed my suspicion that increasing soil moisture content was going to be associated with increasing P. alba density. This is because the tree density was increasing from east to west and there was a dyke near the west perimeter, so I assumed that soil moisture would similarly be increasing in a westward fashion.

Sampling design schematic

Blog Post 2: Sources of Scientific Information

TRU Open Learning 1 Comment

User:  | Open Learning Faculty Member: 

A) say what the source is (and/or link to it),

 The source is Scott, Virgil E., Keith E. Evans, David R. Patton, and Charles P. Stone. Cavity-Nesting Birds of North American Forests. Washington: U.S. Government Printing Office, 1977. Print. Ser. 511.

The book is available at http://www.gutenberg.org/files/49172/49172-h/49172-h.htm.

 B) classify it into one of the four types of information discussed in the tutorial.

 I have classified the source as non peer-reviewed academic material.

 C) provide documentation to support your classification.

The source is non peer-reviewed academic material based on the following observations:

  • The authors’ institutional affiliations indicate they have been paid to do the research.
  • There are in-text citations.
  • The information source contains a references section.
  • The book is a government document and does not include an accepted date. However, the reviewers are mentioned, but they are not anonymous. After reviewing the publication’s editorial policies, the book was not peer-reviewed before publication (https://www.govinfo.gov/about/policies).
  • The article does not include a field or laboratory study (i.e. missing methods and results sections).

 

Blog Post 1: Observations

TRU Open Learning 2 Comments

User:  | Open Learning Faculty Member: 

The area that I observed was Edgewater Bar, located in Derby Reach Regional Park in Langley, BC (10 N 527496 5450356). The site includes walking trails, a dog park, picnic tables, and fishing along the Fraser River. I arrived at the site at 12:50 pm on Sunday, April 25th. The weather was overcast with slight rain, and the temperature was 11°C. The study area was approximately 400m2 and consisted of grassland, forest, and the bank of the Fraser River.

Among the grasses were dandelions randomly distributed throughout the landscape, with blackberry bushes and trees in the background on a slight hill surrounding the park’s perimeter. I noted that the dandelions seemed to have established more abundantly on the flat meadow than the surrounding hills. I wondered how the slope might affect the establishment of the dandelions.

As I made my way along the trail, I observed cherry blossoms in bloom with white flowers amongst other trees, including Sitka Spruce (Picea sitchensis), Grand Fir (Abies grandis), Western Redcedar (Thuja plicata), and Lawson’s Cypress (Chamaecyparis lawsoniana). I spotted two American Robins (Turdus migratorius) foraging for earthworms on the grass, then retreating onto a tree branch once they gobbled up their meal. The Robins did not appear to be phased as people walked by with their dogs. As dogs frequent the area, I wondered how dog barking might affect the courtship behaviour of the robins.

As I travelled northward, I entered the picnic area. The area consisted of grasses and flowering plants, including Creeping Buttercups (Ranunculus repens), Meadow Buttercup (Ranunculus acris), Greater Plantain (Plantago major), and Ribwort Plantain (Plantago lanceolata). Other trees present in the area included Japanese Maple (Acer palmatum), Red-berried Elders (Sambucus racemose), and a Paper Birch (Betula papyrifera) with a Hoof Fungus (Fomes fomentarius) growing on it. I wondered if tree clearing for the picnic area might contribute to the succession of invasive plant species.

As I approached the Fraser River, I could see filter fabric topped with gravel which capped the natural clay ground of the river bank. There was a fisherman upstream to the right who had just caught a small fish and dogs splashing downstream to the left. Looking back up from the river, I could see grasses growing amongst Western Sword Ferns (Polystichum munitum) and Creeping Snowberries (Symphoricarpos mollis). Throughout the observations, I could hear sounds of birds chirping, dogs barking, and people talking.

Link to images: https://drive.google.com/drive/folders/1q2c8m_LmNkOEtyvapqD9d15cPJy7CUMl?usp=sharing

Blog Post 8: Tables and Graphs

TRU Open Learning Leave a comment

User:  | Open Learning Faculty Member: 

My project involves looking at the surface density of springtails (Collembola) in response to the presence or absence of cover. The data collection consisted of counting individual arthropods on the snow surface within 10 quadrats in two treatments (5 each), three times a day, over the course of five days. So though I had 150 data points, I organized them into 10 rows (corresponding with the quadrats) and divided the data up into columns according to their respective categories (date, time of day, treatment) in Excel and found this visually easy to manage. However, trying to analyze these data points in Excel was not as straightforward, partly because I’m no expert at Excel as a data management tool, and partly because “visually easy to manage” seems to be more of an endpoint of data analysis (the table or graph) rather than a starting point of data management. My “data whiz” friend informed me that data input is easiest to manage when each data point has its own row (in my case that meant 150 rows) and is only located in one column, and to try to ensure that the rest of the data (treatment, date, time-of-day) is specific to its own column – even though that means that the values within these cells would get repeated. This information allowed me to at least partially understand the way a program like Excel reads data, and I began to see how powerful a tool it can be to process, analyze, and display data, especially when datasets are large.

The graph I produced with Excel showed me that there definitely was a trend in my data, possibly a significant one. Though I need to run a p-test to see if I can reject the null hypothesis (the standard error bars between treatments appear to almost overlap), there certainly appeared to be a springtail preference for full sunlight rather than cover. This is the opposite to my prediction of a preference for shade based on observation, as well as the shade preference seen in the results of certain experiments done in the literature (Salmon and Ponge 1998). However, upon further researching this fascinating order of arthropods, I’ve come to understand that there are over 5000 species, some of whom live their lives totally subterranean, some of whom live in surface layers of soil and organic matter, and some of whom live above ground and with a multitude of life strategies and abiotic tolerances (Hopkin 1997).

The small graph I was able to generate from my data reveals to me that my experiment would most certainly be improved with more replicates done over a greater time span and in different habitats. Having more expertise at species identification and sampling in different habitats would also provide more robust scientific knowledge to the ecology of Collembola, as different species likely have different preferences for light and darkness depending on life events that may be occurring at different times throughout the winter (rearing, migration, reproduction etc.).

 

References:

Hopkin, S.P., 1997. Biology of the Springtails (Insecta: Collembola). Oxford University Press, Oxford.

Salmon, S., Ponge, J.F. Responses to light in a soil-dwelling springtail. European Journal of Soil Biology 34: 199-201.

Post 9: Field Research

TRU Open Learning Leave a comment

User:  | Open Learning Faculty Member: 

While conducting the field research on moles and their predators,  I learned a great deal more than I expected about research techniques and ecology.

It was necessary to change my design a few times, as I acquired feedback from my instructor. Primarily the adjustments included how to conduct the samples in an accurate manner, and how to gather data efficiently while ensuring replicates were conducted to limit the possibility of errors due to small sample sizes. In retrospect I may have complicated my project by selecting a predator and prey model rather than something more simplistic such as non moving organisms like grasses or lichen in microhabitats. Regardless the challenge (and fun) was to find a way to sample my communities accurately.

Participating in this course and engaging in these activities has given me an appreciation for ecology.  The rich complexities of how sampling, research, statistics, natural history, geography and even geology are brought to bear on a problem.

While I do not consider myself an ecologist, I have enjoyed the process and will likely look at the natural world differently now. The blessing in all of this has been that I have learned some basic tools on how to see how communities interact and have a new found appreciation for ecology.

Blog Post 8: Tables and Graphs

TRU Open Learning 1 Comment

User:  | Open Learning Faculty Member: 

For the small assignment on tables and graphs, I made a table comparing the gravimetric soil water content of sites with and without cedar trees. To do this, I used basic statistical analysis, including the minimum and maximum value, mean, median, and standard deviation.

I would have liked to put this data in a graph, as I think that would have displayed the data better. However, upon a preliminary search of how to do logistic regression graphs, I quickly realized that this was far out of my current level of comprehension. This produced the difficulty of having to put everything that would be represented in this type of graph in a table. I don’t think I fully achieved this, as I ended up leaving out all the separate data that I collected to keep the table simple and easy to read. I am currently brainstorming other methods that will fully represent the data for my final.

The outcome was what I expected, although not to the same magnitude. The mean for the results from sites with cedar trees was 52% compared to 41% for sites without cedar trees. I was expecting the soil to be more moist in the sites with cedar trees by about 20% as opposed to 11%. Foolishly forgetting that I live on the “Wet Coast”, I was also expecting both values to be lower overall.

It was interesting that the data from the sites with cedar trees had a fairly higher standard deviation than the ones without cedar trees. This may mean that other factors are affecting the soil moisture on sites with cedar than that aren’t affecting the sites without cedar trees. These other factors could be further explored in the future by doing a study focused on sites with cedar trees.

Blog Post 8: Tables and Graphs

TRU Open Learning Leave a comment

User:  | Open Learning Faculty Member: 

After entering my data into excel I found that it was difficult to display the data as a whole without breaking out the separate data sets gathered. Since I had gathered information on predators and a separate group of data on prey, I had to find a way to display this in a way that showed the relationship. Eventually I settled on the average of the number of signs of predator activity and also the average number of signs of prey activity.

The result in graph showed an immediate trend between the two, and I was pleasantly surprised to see how clear the relationship was. However, I also had to reconcile that I had gathered only a single weeks worth of data from 35 point counts (Conducted each day). While there was a lot of separate data to draw from I realized that a longer term study over a month or two in less areas may have given my data more weight and allowed me to see a more longer term trend such as is predicted in Lotka-Volterra models.

Overall, even with a shorter time duration of data gathering, I came away with a better understanding of why long term studies really hold alot more weight than shorter duration studies.

Reudink, Blog Post 5: Design Reflections

TRU Open Learning Leave a comment

User:  | Open Learning Faculty Member: 

I collected data in the forested area on my property off of Clandeboye rd, MB, on April 15th, 2021. There was snow on the ground (up to a foot in height in certain areas) after a snowstorm. The day’s weather was 5 °C with clear skies. My study area is approximately 200m in length and 40m in width, so I made three transects and systematically sampled every 20 paces along each transect. The data I collected were soil samples and measurements of tree circumference at breast height (CBH) for trees over 25cm in CBH. Initially, I was planning on doing square plots along each transect but changed my mind during the first sample. It was very difficult to mark down a square plot with the tools I had and the highly dense forest, so I decided to do circle plots (5m radius) instead. By doing this, I was able to stand in the middle of a plot, collect my soil sample (10cm depth), and measure whether any of the trees of interest were within 5m from me. If they were within 5m, they would be within my plot so I included them in my sample. The only logistical difficulties I encountered was having to walk through snow in a dense forest (and dig through it) and making sure that there was no organic matter in my soil samples. My cat kept me company during the expedition and I made sure to remove any gross organic matter from my samples the next day before I weighed them. I plan to continue this approach for my study.

The data I collected was surprising because I was expecting both the EAST and WEST perimeter transects to have a greater mean CBH, but instead it was rather an increasing gradient from EAST to WEST for CBH (i.e., EAST mean CBH 40.4cm, CENTRE mean CBH 51.7cm, and WEST mean CBH 82.8cm). I am currently dehydrating my soil samples after measuring their initial mass so I will not know the moisture content associated with each transect for a few more days.

Transects and Datasheets

Blog Post 5: Design Reflections

TRU Open Learning Leave a comment

User:  | Open Learning Faculty Member: 

My initial data collection was after the transect sampling strategy. I marked out my transects and separated the transects into 9 quadrants. In each quadrant I marked the presence of flora. As the examples have previously shown, one is to count the amount of each flora within each transect, but for the purpose of my research, I was merely interested if there is a correlation between the flora that grows further away from the dyke water and the consistency of the soil.

Some difficult aspects I observed throughout my collection was the difficulty in discerning the different types of Poaceae (Grasses). Many seemed quite similar and as the grass within my area was cut short, it was difficult to make out each feature appropriately. I also observed plenty of dried, brown and dead grasses. In my notes, I make note of the dead grass, but unfortunately am not able to tell what type of grass it is. When I return later for more samples, I will attempt to see if there is new growth. Another observation I made was that when one looks closer, the grass has other flora mixed as well. I observed Taraxacum officinale (common dandelion) and Brachythecium frigidum (golden short-capsuled moss).

I believe I will continue with the transect method. It allows me to properly lay out an organized method of measuring instead of randomly sampling. I believe it suits my research study appropriately.