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BLOG POST 4

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In the virtual forest exercise, of all the three sampling methods on which I performed the sampling analysis, the haphazard sampling technique was the shortest with an estimated  time of 1hr, followed by the area random or systemic which was 11 hours , 29 minutes and then a systemic sampling along a topographic gradient at 21 hours 23 minutes.

Of the two most common species, Red Maple and Witch Hazel, the hapharzard sampling had a percentage error of 0.9% for Red Maple and 0.3% for Witch Hazel. With random sampling, the percentage error was 1.4% for Red Maple and 1.5% for Witch hazel. With the systemic sampling along a topographic area, the Red Maple had a percentage error of 0.92% while the Witch Hazel had a percentage error of 1.53%.  for these two common species, it would appear that the Haphazard sampling method had the lowest percentage error for both the Red Maple and the Witch Hazel.  If you average the percentage error of the two sample techniques, the haphazard sampling method had the lowest percentage error for the common species of trees.

Of the two rarest species, White Ash and Yellow Birch the percentage error for the systematic sampling technique was -100% for both species. Random sampling had a percentage error of -100% for White Ash and 5.6% for Yellow Birch. For haphazard or subjective sampling, the percentage error for White Ash was 52.8% and -100% for Yellow Birch. The systemic sampling techniques failed to record any occurrences of both the White Ash and Yellow Birch trees. Random sampling had the smallest percentage error for White Ash making it the most effective sampling technique for this rare species.

Accuracy for all species was relatively consistent with the 3 sampling techniques except for the rarest species of the Yellow Birch and White Ash that was not detected with all methods. The most abundant species were more accurate while the least accurate was the haphazard sampling technique for White Ash which was at 52.8%.

Based on the results, all three sampling techniques showed fairly consistent results although random sampling appeared to be the most effective for the most abundant tree type. For the Yellow Birch, the random sampling method was the most effective with only a 5.6% percentage error. The White Ash tree had a percentage error of 52.8% with the haphazard sampling method which was the highest percent error for the rarest trees even though this method was the fastest method.

Blog Post 2: Sources of Scientific Information

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For my second blog post I chose a journal article entitled ‘The impact of river regulation on the biodiversity intactness of floodplain wetlands’ by Jan J. Kuiper, Jan H. Nanse, Sven Teurlincx, Jos T. A. Verhoeven and Rob Alkemade, published in Wetlands Ecology and Management in 2014.  I first considered the nature of my Field Research Project and then began a Google Scholar search of relevant material.  After finding and reading several relevant articles, I chose this one; a meta-analysis that includes data from other relevant articles that I had read.  A PDF was not readily available directly through Google Scholar, nor the Thompson Rivers University Library database.  However, a link to the author’s Research Gate profile provided open access to the article, from which I accessed the PDF.  This publication is academic, peer-reviewed, research material.

https://www.researchgate.net/profile/Rob_Alkemade/publication/272040214_The_impact_of_river_regulation_on_the_biodiversity_intactness_of_floodplain_wetlands/links/54ef84df0cf25f74d7227d13/The-impact-of-river-regulation-on-the-biodiversity-intactness-of-floodplain-wetlands.pdf

Academic:  This publication was written by experts in the field: a university professor, a postdoctoral research fellow, a project manager and an independent researcher.  It includes in-text citations: “Moreover, measures of flow modification are mostly inconsistently reported in the literature (Olden and Poff 2003; Poff and Zimmerman 2010).”; “Poff et al. (2009) remarked that ecological changes may also be formalised and empirically tested when they are expressed as categorical responses.”.   A bibliography is provided.(see pages 656-658 in above link).

Peer-reviewed: This publication was peer-reviewed by two anonymous reviewers as stated in the acknowledgements section (see page 656 in above link).

Research Material: This publication includes both ‘methods’ and ‘results’ sections.

Post 5: Design Reflections

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While performing my initial data collection survey I had no issue implementing my multiple transect line survey. The data collected was somewhat surprising as the amount of observed paper birch along the disturbed open canopy area was much great that expected. After receiving feedback I plan on changing some of the aspects of my study. I plan on incorporating more transects and plots that my initial sampling method. This change should ensure that the data collected is more accurate. Another change I will make in the future is to look at more species than just paper birch in order to determine if it is simply this tree that is observed greater due to open canopy or if there are others that also will see an increase. This change will allow me to determine whether open canopy has a change in overall forest composition or if it simply favours certain growing conditions for some species.

Blog Post 7: Theoretical Perspectives

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Blog Post 7: Theoretical Perspectives

 

From a theoretical perspective, my research touches on competition, the differences between vascular and non-vascular plants, and how the topography of an area affects species composition. Competition is when organisms interfere with each other while trying to access resources. This seems to be apparent in my field research because the ornamental hedges on the side of the field opposite to the slope have grown taller and left the plants at the base of the slope in the shade, therefore outcompeting them for access to sunlight. One of the major differences between vascular and non-vascular plants is the presence of vascular tissue (xylem, phloem, etc.) and therefore the ability to move water in a larger body. In my opinion, this presence of vascular tissue is what allowed the  Lodgepole Pine (Pinus contorta) and Paper Birch (Betula papyrifera) found in my study area to grow tall enough to avoid the shade produced by the ornamental hedges and have sufficient access to sunlight. The topography of this area is important because as the elevation increases along the slope there is an apparent shift in the dominant and most plentiful species.

Three keywords that reference my research are elevation gradient, species coverage or percent coverage, and Athyrium filix-femina, one of the dominant species I am studying.

BLOG POST 3

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I visited the study site which was the area located near my house. Due to high industrial activity and its proximity to my house, I decided to evaluate the type and abundance of plant species in this area. One of the most notable species which I identified was the nodding onion (Allium cernuum). My field study was to evaluate the growth pattern of this plant. I will be determining the abundance of the plant at different locations, plant integrity and the proportion of land that is covered with this plant relative to its proximity to the industrial site. I have observed that the distribution of the plant differs with regards to the proximity of the area to the industrial sites.   Upon inspection, the nodding onion plant was most abundantly located at locations distal to the industrial sites. One possible explanation was an increase in the concentration of heavy metals in the surrounding soil located at proximity to the industrial site. Heavy metal concentration in the soil can be facilitated by the transport of heavy metal particles by the rain and the wind.  Increased heavy metals can impact soil integrity by affecting key microbial processes leading to a decrease in soil microorganisms. Heavy metals can also inhibit plant metabolism leading to stunted plant growth.  Given the fact that this plant is found most abundantly in areas distal to the industrial sites, I hypothesize that heavy metal concentration in the soil will be higher in areas at close proximity to the industrial site which will, in turn, lead to less abundance of the nodding onion plant in this site. The response variable in this study will be the abundance of nodding onions relative to the proximity of the site to the areas of high industrial activity. This variable can thus be classed as categorical. One potential explanatory variable will be the rain while the wind can be classified as another explanatory variable. These two variables are thus classified as continuous variables.

Blog Post 8: Tables and Graphs: Cates Park

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Although I intend to focus on the success of Tsuja heterophylla on nurse logs versus the forest floor, I collected data on the presence and absence of all species found within the quadrats I studied in four regions of Cates Park in North Vancouver. Limiting the data to one species in a chart helps with the ease of interpretation, but limits the understanding of species richness in the microsuccessions of nurse logs versus the forest floor. Organization was simple due to the presence and absence data collected, and would have been more difficult had I included other species present. I will likely discuss this in my final paper to address the succession species found in Cates Park.  The outcome was as I expected: Tsuja heterophylla were present more often on nurse logs than not. Further exploration could include canopy cover in relation to this tree’s success or competition with other species in the region.

Blog Post 5: Design Reflections

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I visited my site for the third time on July 23rd, 2019 at 1511 hours to collect initial data for the small assignment submission. I chose the Stratified Random Sampling technique to select 5 plots that were then sampled for Common Fern Moss using 1m2 quadrats. My reasoning behind choosing Stratified Random Sampling is that my backyard is not homogeneous- it receives higher amounts of sunlight in specific areas and there also seems to be a reoccurring pattern in the locations where my dog urinates. I believe this technique of sampling would help avoid underrepresentation of the vegetation in my yard. I took 1m2quadrats comprised of a golf driver and a measuring stick and gave my best estimation of the percentage of cover of Common Fern Moss relative to the entire area of the quadrat. I then took the percent cover values of each replicate and calculated the average percent cover of Common Fern moss. This was done to make somewhat of a generalization about its abundance in my backyard. The response variable is percent coverage of the Common Fern moss relative to the quadrat area and the predictor variable is the absence or presence of grass. One difficulty I ran into during sampling was the tough decision on whether or not to include ‘Density’ in a table on my datasheet. Moss is a very tricky plant to measure or count individuals within a species, as the individual stems are hidden in the soil, small and can be closely surrounded by other stems. I originally visited the site thinking I could find a way to measure the abundance of the individuals using a count method. However, I came to the conclusion that the most efficient way to sample moss in this experiment was to use percent cover. The data received from this type of data collection showed that two plots closer to the South fence had a higher percent cover, and this did not come as a surprise to me as these areas receive less shade relative to the other plots, and are areas with bigger patches of dead grass. I plan to continue using this method of sampling as I continue working on my Field Research Project, however I hope to modify my approach by finding another measure of abundance that is time efficient and more accurate. By adding another common measure to the data collection process, I believe that my data will become more representative of my site and will allow for a more in-depth final report.

Blog Post 3: Ongoing Field Observations

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My second visit to my study site took place on July 17th, 2019. It had rained in the area about an hour and a half prior, leaving the ground quite moist. The sky was grey, and the temperature was 14 degrees Celsius. I have chosen to base my Field Study project off of the moss present in the dead patches of grass in shaded areas of my backyard. I am observing what I identified to be Common Fern moss (Thuidium delicatulum) across the gradient from healthy grass to dead patches of grass or areas of strictly soil. I will be looking specifically at the percent cover of species, structural integrity and abundance at different locations along this gradient. The response variable of my Field Study project is the percent cover of Fern moss. Due to the fact that this moss is only found in the shaded areas of my yard and strictly in the dead patches of grass where my dog urinates, one possible explanatory variable of this occurrence may be the lower pH soil composition in these areas causing low soil fertility and optimal growth conditions for this type of moss. These variables would be considered continuous data (measured on pH scale, percent coverage of moss at certain locations in the yard) as well as categorical data (presence or absence of species).

I chose the Southwest corner of my backyard for my first location. This area receives plenty of shade under the columnar aspen tree. The moss is thicker, and it seems to be growing along the transition between grass to no grass. It is very abundant in this location.

For the second location, I chose an area in between the Japanese lilac tree and the columnar aspen by the South fence. This area receives relatively the same amount of shade as location 1. The grass is lacking in this area and there are mainly patches of soil. I see rotten moss in this area, and there is a very small amount of healthy moss.

Location 3 is to the right of the Japanese lilac tree where the grass meets the border of the garden. There is barely any Fern moss in this area, however Pincushion moss (Leucobryum glaucum) is growing in the garden.

These observations have led me to the hypothesis that moss grows in specific levels of moisture, sunlight and acidity. When these factors exceed or fall short of the desired conditions, moss may react to these changes by rotting, stunting its growth or not growing altogether. A change in percent cover of Fern moss between three different locations in my yard may be a result of nonoptimal levels of these factors.

I predict that if my backyard lacked trees, a two-meter-high fence, and did not have burnt spots from my dog’s urine, the Fern moss would be less abundant, would have a low percent cover or be completely absent.

Blog Post 6: Data Collection

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Blog Post 6: Data Collection

I have collected data on 10 additional replicates, five at Location 2 and five at Location 3 from my initial field observations. This brings the total number of replicates to 15. Replicate quadrat locations were still chosen using a simple random scheme. I modified quadrat size to 4m2 for quadrats near and around Location 2 (approx. 3 metres from the base of the slope) because the vegetation in that area included Saskatoon berry bushes (Amelanchier alnifolia) dominantly, a larger plant than the ferns sampled using 1m2 quadrats. In addition, at Location 3 (approx. 10 metres from the base of the slope) I modified quadrat size to 25m2 because I was beginning to sample fully grown trees. I would have liked to increase quadrat size to 100m2 but to accommodate 5 replicates within the physical constraints of the lot and slope size, I had to downsize. After quadrats were selected and sectioned off, I took measurements of area of species found within the quadrats, compared that to the total area of the quadrat, and converted this to a percentage of coverage. So far, my results and observations have not led me to reconsider my hypothesis. In fact, they support it. At higher elevations the species composition nearly entirely changes. Non-vascular common ferns (Athyrium filix-femina) were found to be dominant at location 1, whereas at location 3 the dominating species are highly vascularized and developed trees such as Lodgepole Pine (Pinus contorta) and Paper Birch (Betula papyrifera). This supports my hypothesis that the complexity of species found increases at higher elevations along the slope. A possible explanation for this is that plants at lower elevations are shaded from the sun by ornamental cedar hedges, standing at approximately 8 metres high, on the opposite side of the field.

Blog post 5: Design Reflection

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During my data collection in the field, the systematic sampling strategy proved to be efficient at surveying the area. The few difficulties I encountered during the sampling did not damage the quality of my data in any way. First, the determination of transects was simple, but keeping that transect straight as I collected my subsamples across the field seemed to be a challenge. For the last three transects, I established three or four checkpoints along each transects in order to keep me straight. Having closer targets greatly improved the quality of my transects. Secondly, making my way along a transect turned out to be slightly more challenging than I expected. The vegetation got pretty dense in some portions of the field. I always managed to make my way through it but I had to push through some plants and small shrubs. Applying the quadrat down never was an issue. I would simply drop it over the vegetation of the area, however tall or dense that was.

The data was not surprising to me. These first samples even seem to play in favour of my initial hypothesis – more flowers appeared as I sampled away from the beach. One noticeable aspect of my data was that all types of flowers seemed to be displayed in clusters.

I think that my systematic approach to survey the site was the best option. The data collection was performed with minimal difficulties that were all overcame to maintain the essence of the systematic method. It eliminates the possibility of bias, and more samples will only add to the reliability of my data.