Category: Nancy Elliot

Blog Post 8: Tables and Graphs

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Some initial findings of my data collection in which the mosses occurring on different slope positions on several rock outcrops were identified and their percent cover classified are shown in Figure 1 (included in Assignment 5). Specifically, Figure 1 illustrates the number of plots on which each species occurs within each slope position, summarized across the 4 replicate plots.

I did not have any difficulty organizing, aggregating or summarizing my data, although I did have to manually calculate the number of plots in which each species occured based on my field data. I also had to separate out the results in order to see the results per slope position instead of just as an overall total.

I found it interesting that the three most abundant species overall (PYLSP, PLESCH, DICSCO) occurred on all slope positions and that these were the only species to occur on the west-facing slopes. I also found it interesting that of all of the other species that occurred, each of these occurred only in one slope position. These include RACCAN, which only occurs on the crest, HYPSUB and HETPRO, which only occur on the eastern slopes, and KINORE and RHYLOR, which only occur in the depressions.  This was only unexpected in that it does illustrate what I had predicted, which is a pleasant surprise. This confirms, at least initially, that I am on the right track in my investigation.

As a separate study, it could be interesting to specifically target the species of moss that were found only on one slope position elsewhere within the study area, and to collect data on the same environmental attributes (i.e. slope position, slope, aspect, substrate, overstorey and understorey cover) in these locations. Analysis of that data could reveal whether the occurrences of these species on a particular slope position are a trend or just isolated occurrences, and also to tease out which, if any, environmental attributes are correlated with the occurrences of these species.

Blog Post 6: Data Collection

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Data Collection

I collected data on the species of moss present and their abundance on varying slope positions on rock outcrops. For the purposes of data collection, the slope positions of the rock outcrops were divided into discrete categories for data collection and included the west slope, crest, east slope, and depression between outcrops. The faces of the slopes were distinguished from the crest and the depressions by an increase in slope to greater than 20%.

A total of 4 rock outcrops were sampled, providing 4 replicate study plots. Note that these were the only rock outcrops in the area that included all slope positions; others nearby were embedded in the slope and consisted only of a west face and crest. These are expected to be independent of each other, but it can be noted that they will not be independent of other external factors affecting all of the replicates, including overstorey and understorey cover and proximity to forest edge. The percent cover and species of overstorey and understorey vegetation were recorded for each replicate, as well as the distance to the cut forest edge.

A randomized strategic sampling strategy was used to select the sample locations along the environmental gradient of the slope positions on the rock outcrops. The number of samples collected for each slope position on each rock outcrop was determined based on the relative size of the given slope. At least 2 samples were collected per slope position, while those greater than 5 m2 in area had 3 samples and those greater than 10 m2 in area had 4 samples. The locations of the sample within each slope position was randomly assigned in order to capture the randomness of the moss cover.

The sample unit is an 18 x 18 cm quadrat because this is the size which was readily available and was a reasonable size of similar scale to plots used in the literature reviewed. The quadrat was placed on the ground parallel to the slope. All species of moss occurring within each quadrat sampled were identified and the cover determined for each. The nomenclature used was from the field guide Plants of Coastal British Columbia by Pojar and MacKinnon (1994). Cover was estimated using a cover classification scale based on the percent cover of each species, as used in the Daubenmire method (Daubenmire 1959).

Reflections
I did not have any problems implementing my design, but I had hoped that I would have found more suitable rock outcrops in order to have more replicate plots. Patterns that I have noticed right away are that the most dominant species occur in all slope positions (PYLSP, PLESCH, DICSCO), while some of the less common species of moss occur only in one slop position. These include RACCAN, which only occurs on the crest, HYPSUB and HETPRO, which only occur on the eastern slopes, and KINORE and RHYLOR, which only occur in the depressions. I also noticed that the abundance of PYLSPL increases across the environmental gradient (from western slope to depression). This difference in the species of moss occurring in the different slope positions is what I had predicted and is encouraging as it indicates that a significant trend may occur.

Previously I had stated my hypotheses to be:
1. There is a significant difference in the percent cover of moss species between plots.
2. There is a correlation between any significant differences in percent cover and slope position.
My prediction was that there will be a significant difference in the mean percent cover of mosses of different species between plots in different slope positions.

Based on feedback and the results of field sampling, I would like to change these to be:
1. Different species of moss will grow on different slope positions on rock outcrops.
2. The density of cover of moss species growing on rock outcrops will be different on different slope positions.
My new prediction is that there will be differences in the mean percent cover of several different species of mosses between sample locations on different slope positions on rock outcrops.

Blog Post 7: Theoretical Perspectives

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The theoretical basis of my research project is to demonstrate how species richness and diversity differs along a spatial gradient. The Thompson Rivers University (TRU) campus has different spatial gradients – from grasslands to wooded areas – causing a distribution of bird species throughout the campus. Dominant species at each of the sites can be determined via species abundance at each of the sites. Further research can then be done as to why the dominant species prefers that type or landscape over another.

It is also important to note that human activity can affect the distribution of bird species as some of the study sites were more heavily influenced by human contact than others. Furthermore, weather patterns can also affect species abundance. If one study area is more exposed than another it will experience more wind which could further influence the bird species associated with that location.

Keywords: bird species, species abundance, spatial gradient

Blog Post 6: Data Collection

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My field data collection activities consisted of sampling three sites for the presence of seven different bird species over five consecutive days. Point counts were taken at the same time (10:30am) for each of the consecutive sampling days. Species abundance was determined from the resulting data.

Overall, my sampling strategy was quite easy to implement. I was able to borrow a set of binoculars from the Thompson Rivers University science faculty. This aided in my point counts as I was better suited to see and identify the birds present. The most challenging thing for me was identifying the bird species. For the most part I was able to identify the species present, however, there were other times when I had to use a species identification sheet. This could lead to inaccurate data if incorrect identifications occurred.

Through the sample collections, I was able to notice that there were trends in which bird species were present at the various sites. It became obvious early on in the study that certain bird species favoured one of the three sites. Each site had a different dominant bird species. This demonstrates how differing landscapes alters bird species abundance. This follows my prediction in that the different sites will have different bird species that are associated.

Blog Post 5: Design Reflections

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In my study, I will be sampling three different sites on Thompson Rivers University (TRU) to determine bird species abundance at each site. Point counts were made for seven bird species at the three sites. In other words, I monitored the presence or absence of seven bird species at three different sites on the TRU campus. In this case the predictor variable was the site of study and the response variable was the species abundance at each site. I found it challenging to narrow my focus area to just three distinct sites. When implementing my sample strategy I had to consciously make strict restrictions as to what was considered part of each of the three sampling sites. I plan to continue using the same technique, of recording which of the seven bird species are present at each site using the point count method. After sampling the site for the first time on March 21ist, I ensured that I continued to sample the three sites at the same time of day (10:30am) to remain consistent temporal boundaries.

Blog Post 4: Sampling Strategies

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In the virtual forests tutorial, the three sampling strategies used were Systemic, Random and Haphazard with an area-based approach. According to the results, the random sampling technique had the fasted estimated sampling time of 4 hours and 45 minutes. The other two sampling methods, systemic and haphazard sampling had a much slower estimated sampling time of 12 hours and 35 minutes and 12 hours and 44 minutes respectively. In this tutorial the most common species were Eastern Hemlock and Red Maple. The calculated percent error for Eastern Hemlock and Red Maple for each of the sampling methods were:

  • Systematic
    • Eastern Hemlock – 6.36%
    • Red Maple – 24.47%
  • Random
    • Eastern Hemlock – 23.26%
    • Red Maple – 42.72%
  • Haphazard
    • Eastern Hemlock – 8.07%
    • Red Maple – 12.53%

In contrast, the two rarest species were White Pine and Stripped Maple. Their calculated percent error for each of the sampling site were:

  • Systematic
    • White Pine – 233.33%
    • Stripped Maple – 100.00%
  • Random
    • White Pine – 100.00%
    • Stripped Maple – 21.14%
  • Haphazard
    • White Pine – 138.10%
    • Stripped Maple – 31.43%

Based on these results, it can be concluded that the Haphazard or Systematic sampling methods were the most accurate for the most common species and the Random or Haphazard techniques were the most accurate for the two rarest species. However, as demonstrated by the above results, the accuracy of the sampling methods declined when looking at the rarest species. The high variation between the percent error values could be a result of the small sample points. 24 was not a sufficient number of sample points; in order to produce more a accurate estimation of abundance  more sample points is necessary.

Post 2: Sources of Scientific Information

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Blog Post 2:

 

The article, Estimates of Movement and Site Fidelity Using Mark-Resight Data of Canadian Geese, is a study which looks at the wintering habits of geese and their movement. The author, Jay Hestbeck, has held many positions within government organizations and specializes in bird migration and wildlife management. He has also made over 20 contributions in terms of scientific studies and articles. The study is classified as research material as it contains both a Methods and a Research section. However, it does not appear that the study was refereed by anyone, so it is classified as being non-peer reviewed academic material. I then went and searched both the journal and the article on Ulrich’s Web, which confirmed the fact that the article is not peer reviewed.

 

Article:  Hestbeck, J. B., Nichols, J. D., & Malecki, R. A. (1991). Estimates of Movement and Site Fidelity Using Mark-Resight Data of Wintering Canada Geese. Ecology,72(2), 523-533. doi:10.2307/2937193

 

 

Ulrich’s Web Result: https://ulrichsweb-serialssolutions-com.libaccess.lib.mcmaster.ca/search/-710683931

Blog Post 1

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Blog Post 1:

 

I have chosen two locations at different elevations within the city of Hamilton, Ontario. The first is a grassy area located near the campus of McMaster University, located 90m above sea level. This area is very flat with some trees and short grass throughout. It is located in a suburban area sandwiched between the university on one side and residential homes on the other. I first visited the site at approximately 10am on March 27th. The weather was overcast with light rain and it is currently transitioning between winter and spring with temperatures ranging from 0-10 degrees Celsius.

The second location that I have chosen is called Inch Park, located approximately 200m above sea level. This area is also very flat with trees, shrubs, and short grass throughout. It is a park located in a suburban area surrounded by a recreation complex, playground, and other amenities. I first visited the site at approximately 12pm on March 27th. The weather was overcast with light rain, but the temperature is slightly colder and the season was the same as discussed previously. The area is designated municipal park so there is lots of foot traffic.

 

  • Does the elevation change and consequent temperature change affect the budding of trees and growth of elevation?
  • Does the rain and temperature affect the presence of animals, more specifically birds?
  • Does the difference in human presence between the areas affect the presence and behavior of animals?
  • Site #1, near McMaster University

     

    Site #2, Inch Park

Blog 5-Design Reflections

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My initial survey of a red squirrel’s area involved using rectangular quadrants that matched the property lines.  I have since changed to using a circular survey of 25 metres distance each and using 5 quadrants.  I have chosen this design to add  more ‘natural’ boundaries to my survey since a red squirrel’s territory is oval in shape.  I will be measuring the resources available in each quadrant from food availability, amount, cache areas, trees for both aerial walkways and protection from sky and ground predators.  I see using a circular design with the small distances  more informative as it also allows for a more detailed count of the resources in each area plus gives the distance of the food stuffs from the squirrel’s central ‘midden’.

The total area of 5 ha is slightly larger than a forest squirrel’s territory in a time of low food, but I believe the variety of food stuffs in an urban environment are far more than in the wild.

I am wondering why the red squirrel chose my woodpile as the central ‘midden’ or home cache considering there are a total of 5 wood piles in this area.  I believe it might have to do with the fact that my wood pile is very close to my home while the others aren’t.  This appears to be offering the squirrel more protection.

My predictor variable is the 1 red squirrel in this 5 ha territory. My response variable is the resources available to the squirrel.  My hypothesis is that my wood pile is the best because it offers a central location to radial access to all the variety of food resources within the 5 ha.  And I think a surprise will be that the human activity around my wood pile offers the squirrel more protection against predators.

Today is March 26, 2018, cool with a light snowfall.  This morning I noticed a smaller squirrel head poking out of the wood pile while the larger squirrel sat above on top of a post.  I believe the smaller squirrel is a female.

 

Blog Post 2 – Article classification

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Article:

Smith, L. S., Broyles, M. E. J., Larzleer, H. K., & Fellowes, M. D. E. (2015). Adding ecological value to the urban lawnscape. Insect abundance and diversity in grass-free lawns. Biodiversity and Conservation, 24(1), 47-62. 10.1007/s10531-014-0788-1

 

The article is published by Springer Netherlands in the Biodiversity and Conservation journal, which is international. Springer is recognized as an established publisher in the academic field. The Biodiversity and Conservation journal has an impact factor of 2.265, which is an indication that it is a well respected journal.

This paper is non peer-reviewed academic material.
-It was written by experts in the field who are associated with the School of Biological Sciences from the University of Reading, in Reading, UK
-There are numerous in text citations and a full bibliography of 78 references.
-The paper includes results from a field study that they completed and has supplemental information to show the study area and how the study was carried out
-There is a section for their methods and their results

Had this work been peer-reviewed (or labelled as such if it was), it would be Academic, peer reviewed research material.

 

Notes on whether or not it is peer reviewed:

Using the University of Victoria’s online library, the article is listed as peer reviewed. However, when attempting to verify this through the information provided about the journal and the article from Springer, there is no mention of the peer review process or that one was done.

Springer does engage in the peer review process, and for this particular journal, they do have an “editorial manager” program for authors and reviewers ([http://www.editorialmanager.com/bioc/default.aspx]).
The journal has an editor (David Hawksworth), however, there is no available information from Springer that lists this journal -or the article- as being peer reviewed, nor is there any indication of any referee other than the editorial process.