Category: Nancy Elliot

Blog 7: Theoretical Perspectives

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This research project on moss richness on the tree trunks with different levels of tree top exposer touches on understanding the affects sunlight, rainfall, to snowfall has on moss richness in Canada. Where if there is direct exposer to the weather conditions how would this effect the richness of moss found growing on the trunks of trees that were observed at the end of British Columbia winter and the beginning of spring were the temperatures ranged from 5-15 C and during the 2 weeks the experiment was conducted rainfall, snowfall, and clear skies had all occurred at the location.

 

key words: moss richness, weather conditions, canopy coverage

Blog Post 5: Design Reflections

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There were no major difficulties in implementing my sampling strategy in the field. Using the quadrat method, I subjectively chose 5 different locations, 2 grazing and 3 non-grazing, in order to observe the damaged caused to Ryegrass by geese feeding habits. I laid out a 100cm x 100cm grid and estimated the amount of damaged area by measuring it and estimating area. The only difficulty experienced was that getting an exact measurement of the damaged area is tough as it is not always in a square shape. However, I do not expect this to be a major detriment to the effectiveness of the experiment as the estimates will be fairly accurate and it appears that the data still shows accurate trends. The data trends were close to expected, but the total area of damaged grass was slightly higher than I originally expected. I plan on continuing to collect data using this technique as it is effective as well as time efficient. Overall, I think the sampling strategy was highly effective.

 

Quadrat from observation of non-grazed Ryegrass

Blog Post 4: Sampling Strategies

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The technique with the fastest sampling time was the random sampling method. The Red Maple and the Eastern Hemlock were the two most common species and the Striped Maple and White Pine were the two rarest. The percentage error for these with the different sampling techniques are as follows;

 

  Systematic Random Subjective
Eastern Hemlock 11.5% 21.7% 10.8%
Red Maple 4.1% 13.4% 30%
Striped Maple ?? 347% 42.9%
White Pine 47.5% ?? ??

?? denotes the PE was unable to be calculated because the species was not found in sampling.

 

The accuracy of the sampling appeared to increase with increased species abundance. The rare species had much higher PE values than the common species and some were unable to be calculated at all because the species was not found using certain sampling techniques.  The Random and Systematic sampling techniques were on average about 4-5% more accurate than the Subjective/Haphazard method of sampling for common species. However, when calculating rare species the Systematic and Haphazard method were much more accurate than the Random method, but due to the lack of species abundance and data it is difficult to read too much into this.

Blog Post 3

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The organisms which I plan on studying are Canadian Geese, B. Canadensis, and Ryegrass, L. perenne. I will be observing effects that the Canadian Gooses grazing habits have on the growth and success of the Ryegrass. I have chosen to study this at the location near McMaster University, as it is nearby my home and is easily accessible. I believe that the feeding habits of Canada Geese in the park area greatly damages the growth and success of the Ryegrass, as they feed specifically on the roots. I predict that the areas in which the geese feed will have much higher percentages of bare spots and damaged grass due to the grazing behaviour. The potential response variable in this study is the Ryegrass and the explanatory variable is the geese feeding behaviours. The response variable is continuous in nature as it will be measured in m2 and then converted to a percentage of the area of the different test sectors. The predictor/explanatory variable is categorical in nature as it depends on the presence or absence of the geese feeding in the control areas. Given this information the experiment will use a ANOVA design with a one-way layout that compares the health of the grass in grazing and non-grazing areas.

Blog post 9

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My field research project on Sagebrush definitely increased my appreciation for the ecological importance of this ecosystem I’ve been taking for granted. Kamloops is full of dry, brownish hills in the summer that can be mistaken for drab. When you look closer, you see an amazing amount of diversity and persistence through incredibly difficult growing conditions. Late last summer we didn’t receive any precipitation for over a month. However, these huge bushes sustain themselves and then flower at the beginning of fall. It’s amazing.

I had to make changes when I was carrying out the study, including changing the sampling method from quadrats to linear transects. This made the data collection a lot simpler. In terms of the redoing the study, I would do it a lot differently next time. I would sample at a different time of year and include more transects at different places in the creek. I would also obtain a degree of incline along the hillsides to have more control over extraneous variables like flat spots. I think, ultimately, it would be nice to have had more measures to help control aspects of my study.

Ecological theory development is way more complex than I originally thought. There are so many variables that interact to create what we see around us. This semester I had the opportunity to do another project on the human microbiome and I found the ecology of this system to be fascinating. By designing my own study with the brush bushes and doing research on the topic, I gained a better understanding all of the variables impacting what had once seemed to be a simple question of depth to water.

Blog Post 7: Theoretical Perspectives

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In my field study, I am investigating the species composition of mosses occurring on differing slope positions on rock outcrops.  My hypothesis is that there will be different species of mosses growing in the different slope positions of the rock outcrops.  The ecological theory is that abiotic environmental factors vary with slope position, such as the slope, aspect, and substrate, which may affect the suitability of the habitat for each species.  Additional abiotic factors that may influence which species of moss will grow are the micro-climatic conditions, which is further influenced by the distance to the recently cleared forest edge and the resulting edge effect.  In addition, biotic factors such as interspecific competition and the cover of overstorey and understorey vegetation may also influence which species of moss will grow.  Each species may require a particular set of growing conditions or occupy a particular ecological niche, which thus influence where it will grow.

3 keywords are: mosses, rock outcrops, species composition

Tables and graphs

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For my project I have decided to use graphs to represent a summary of my raw data. Because of my statistical tests used, I created a graph that shows the mean number of brush bushes per square meter at various elevations from the creek bottom. This graph shows the differences between the six elevations I compared.  When analyzing my data, I decided to remove the highest 6m counted because I only had ~6 samples. This made my comparisons a lot more representative of the un-paved study area. I used a bar graph, and feel like this is the best way to visually represent how the density of brush bushes changes as the height from the creek increases.

I will also include a table denoting the significant differences between elevation categories for the big sagebrush bushes. There were no significant differences in the rabbitbrush bushes across the different elevations, so I will just report that in my results section.

This data took me a long time to go through and figure out how best to analyze it. I chose an ANOVA over t-tests because they are a more powerful statistical test. I also compared the valley bush distribution to a Poisson distribution.

Blog Post 9: Field Research Reflections

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Before starting this blog post I must admit that Ecology is not one of my strong spots. I am currently in my last semester of a Cellular, Molecular, Microbiology degree; therefore, I am more interested in the molecular process that occur. Because of this, I found this field project very difficult. With that being said, I think the majority of my difficulties rooted from not being as interested in this discipline of Biology.

I must say though, that I was able to learn a lot about trouble shooting and independent learning throughout this course and field project.

I had many time constraints, therefore, I decided to implement a study design that I was able to best understand. I found it easy to implement my study design and carry out the point counts. The hardest part of the field project for me was analyzing the data without using statistical tests. I found it difficult to compare my results with literature as my individual study was proceeded on such a small scale.

Overall, this class was able to open my eyes to another area of biology. I was able to determine different ways in which the ecological theory is developed; however, I still need lots more practice to facilitate my overall knowledge.

Blog 6 Data Collection

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From the three tree categories (sheltered, partially sheltered, and exposed) 10 trees were randomly selected and examined for the presence of living moss. Data collection was on March 14 and started at 4:00 and finished at 5:30 when all 30 locations were examined, the weather was cloudy and slightly rainy that day. Currently the living moss present on the three different tree categories shows no significant different. Right now the presence of living moss seems to be fairly constant across the different categories. This goes against my hypothesis that there will be an increase of living moss on more sheltered trees. More research is needed to further determine the relation of living moss on different levels of exposed trees.

Blog Post 8: Tables and Graphs

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The table I created included all of the data I collected over the five days. It was a summary of the various bird species abundance at each of the study sites. By producing a graph that summarizes all of the data collected, it enables for trends and patterns to be clearly outlined to draw conclusions from. However, from this data I found it to be confusing how to incorporate it into a graph to obtain a more visual demonstration of the species abundance over the three different sites.

Nevertheless, I noticed that each study site had different bird species associated with it. More specifically I noticed that each study site had a dominant species that inhabited the area. This was the outcome I was expecting, however, that leads to further questions such as why particular bird species favour one site over another? What is different about each site that a spatial gradient is created?

As a secondary research project it would be interesting to monitor the bird species and their migration patterns. Since the seasons are in the midst of changing the species abundance at each of the sites must also be changing; therefore, it would be interesting to determine which site the bird species favour as their migration patterns change. In addition, it would be interesting to see the displacement of the bird species as new birds migrate into the area. I’m assuming that depending on the bird species the migration patterns are different; therefore, if a smaller bird favoured a particular site it would be interesting to observe what would happen if a larger bird slowly started to inhabit the area.