Category: Nancy Elliot

Blog 4 – Forest Tutorial

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I used the distance based method. The systematic sampling technique took the least amount of time, at 4 hrs, 5 mins, followed by haphazard at 4 hrs, 26 mins, and finally random which took 4 hrs, and 40 mins. Eastern hemlock and yellow birch were the two most common trees for each sampling technique. The sampling error was lowest for random (-1.7%, 29.8%) which would make it the most accurate, followed by haphazard (-6.5%, 31.7%) and systematic which had the highest error (-22.2%, 55%).

Striped maple and white pine were the two least common species for each sampling technique. Again, random (11.9%, -100%) was the most accurate, however systematic (60.6%, 123.8%) was more accurate than haphazard (118.3%, 124.7%) for the least common species. In general, the accuracy declined for rare species.

The percent error calculations are all quite large aside from the ones obtained in random sampling, and I believe this is due to the fact that 24 is too small a sample size. Generally as your sample size increases, your margins of error decrease (Statsoft, 2018) so I think increasing the sample size would yield more accurate results.

Systematic Sample time: 4 hrs, 5 mins
Actual Density Data Density % Error
Common Eastern Hemlock 469.9 365.8 -22.2%
Yellow Birch 108.9 168.8 55%
Rare Striped Maple 17.5 28.1 60.6%
White Pine 8.4 18.8 123.8%
Random Sample time: 4 hrs, 40 mins
Common Eastern Hemlock 469.9 461.8 -1.7%
Yellow Birch 108.9 141.4 29.8%
Rare White Pine 8.4 9.4 11.9%
Striped Maple 17.5 0 -100%
Haphazard Sample time: 4 hrs, 26 mins
Common Eastern Hemlock 469.9 439.7 -6.5%
Yellow Birch 108.9 143.4 31.7%
Rare Striped Maple 17.5  38.2 118.3%
White Pine 8.4 19.1 127.4%

 

StatSoft. (2018). Designing and Experiment – Power Analysis. Retrieved February 2, 2018 from: http://www.statsoft.com/Textbook/Power-Analysis#power_doe3

Blog post 1

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I am choosing to do my field study in Mount Douglas Park, located in Victoria, B.C. I visited the park on February 6th, 2018, at around 12:30 pm. It was overcast, lightly raining at times, with a temperature of 8C. Mount Douglas Park is quite a large park, with an area of 188 hectares, and the summit reaches an elevation of 225 m (District of Saanich, 2018). From what I observed, the lower areas of the park are lightly rolling hills, with flat areas, and are covered in forest. The forest is predominantly douglas fir (Pseudotsuga menziesii) and there are a few big leaf maples (Acer macrophyllum). The understory is dominated by Oregon grape (Mahonia aquifolium), sword fern (Polystichum munitum), snowberry (Symphoricarpos albus), and Indian plum (Oemleria cerasiformis) which I identified when I got home. The top of Mount Douglas Park transitions into a more open, rocky ecosystem with garry oak (Quercus garryana) and arbutus (Arbutus menziesii) trees, with scotch broom (Cytisus scoparius) becoming prominent. Lichens tended to favour one side of the tree, which usually faced more open areas, but could be a NSEW preference. The Oregon grape leaves seemed to be smaller at the summit, and had a reddish hue.

The park is disturbed with a high presence of invasive species such as English holly (Ilex aquifolium) and English ivy (Hedera helix).

There are an infinite amount of possibilities here, but three areas that seem most feasible to explore are:

  1. The size of the Oregon grape leaves/plant is smaller in the open areas at the top of Mount Douglas, compared to the lower, closed forest.
  2. The green dust/or crust lichen prefers certain sides of trees, however the sides that the lichen prefers seems to vary in the park, therefore, is it a NSEW preference, or a light availability preference?
  3. Do the areas surrounding the heavily used trails have less species diversity (or more invasive species) than the less frequently used trails?

 

District of Saanich. (2018). Mount Douglas Park. Retrieved February 6, 2018 from: http://www.saanich.ca/EN/main/parks-recreation-culture/parks/parks-trails-amenities/signature-parks/mount-douglas-park.html

Fish Production and Primary Productivity

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I have selected a paper titled ‘Fish Production Correlated with Primary Productivity, not the Morphoedaphic Index’ (Downing et al.,1990). This paper is classified as academic, peer-reviewed material. It is academic material because the authors are experts in this field and the paper includes in-text citations as well as a reference list. The paper was published in the Canadian Journal of Fisheries and Aquatic Sciences which would require a peer-review process. This paper includes methods and results sections; however, no field or laboratory experiments were performed. The authors analysed data gleaned from previous studies to discover new correlations. Given the distinguishing characteristics between ‘research material’ and ‘review material’ detailed in the tutorial, this paper would technically be classified as review material; however, I argue that the statistically analysis methods were able to generate novel information, suggesting that this paper makes a contribution to ‘research’ as opposed to simply offering a review of findings by others.

http://www.nrcresearchpress.com/doi/abs/10.1139/f90-217#.Wmi2hainGUk

Post 9: Field Research Reflections

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Designing and implementing a field research project for this class was a great way to provide practical experience in the work required, and difficulties encountered by a practising field biologist.While I had a concrete idea of what I wanted to study (impact of different habitats on bird species presence and abundance) it took quite a while to determine the correct location in which to implement this study to minimize confounding variables and ensure that the results between study sites would truly be comparable. I began my project at Stanley Park’s Lost Lagoon which would essentially be comparing species diversity and presence between 3 different sites within one habitat (Lost lagoon) with differing levels of anthropogenic influence.   The surrounding areas of the Lagoon were observed and evaluated for bird species presence and abundance along an urbanized gradient.

Once my study site was selected I had no real difficulty in implementing the project design (point count surveys within each of the three habitat types representing different levels of urbanization). However, despite all my sites being relatively close to one another it still took a considerable amount of time to visit two point count survey locations in each of the three sites on a number of different days. This really helped me understand the difficulty in ensuring that enough replicate samples are taken in a study to ensure that the data collected is truly representative of the conditions on the site.

This research project has given me an appreciation for the amount work and forethought that is required in developing and implementing successful research projects whose results can be robust enough to help develop and further the principles in ecological theory. Overall, it was an interesting hands-on experience that will give me insight as a future biologist.

Blog Post 8: Tables and Graphs

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The results of my field data were easy to summarize and visually represent in tables and graphs. The bar graph I submitted summarizes bird abundance (number of individuals) observed at the three different sites along the urban gradient representing different levels of urbanization. I predicted that bird abundance would follow a gradient with the lowest number of individuals observed in the urbanized area (Site 3) and the highest number of individuals observed in the natural area (Site 1) . When I initially graphed this data I found that the highest abundance was in fact at the most urban site. However, further examination of the data indicated that this was due to the large portion of observations (roughly 2/3) in the urban area that consisted of seagulls and crows. As a result, the graph I created displays the overall abundance along the urbanization gradient but highlights the proportion of each bird species at each site so that the underlying trend becomes apparent, which confirms my prediction

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Blog 7: Theoretical Perspectives

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Blog Post 7: Theoretical Perspectives

The theoretical basis for my research project examines how varying levels of urbanization impacts bird species (especially seabirds) presence and abundance. To examine this, I’m collecting data on bird species presence and abundance (response variable) within three areas within Stanley Park that represent different levels of urbanization as determined by the percent cover of natural and anthropogenic habitat (explanatory variable).

Based on other research related to bird species presence and abundance along urban gradients (Tryjanowski et al, 2013) there theoretically should be a difference in the species richness and abundance between sites with the 3 levels of urbanization (West, South, East Lagoon). More particularly, the most urbanized sites should theoretically have the lowest species richness, and the most natural sites should theoretically have the highest species richness. It will be interesting to see where the results from my research align in this respect. While theoretically abundance should also be highest in more natural sites, previous studies (Tryjanowski et al, 2013) found that highly urbanized sites often have the highest overall abundance due to large flocks of a single species (Example, Large flocks of Seagulls and Crows near urbanized areas). Again, it will be interesting to see how my results compare to the other literature on the topic and if they align with the theoretical perspectives on bird species richness and abundance along urbanized gradients.

It is also important to think about how both species richness and natural habitat is examined and characterized. Theoretically, species richness includes all species, both native and non-native, but it might be beneficial to tease these categories apart. For example, if an intermediately urbanized site has the highest species richness but hosts exclusively non-native species then its value as bird habitat would likely not be comparable to natural areas where species richness might be lower but is dominated by native bird species. Additionally, when classifying habitat it is important to think about the impact native and non-native plant species play. While I won’t have the ability to examine these issues in my research project their theoretical impact on bird species presence and abundance, and the ways of evaluating overall richness and abundance do provide something to think about and will be mentioned in the final report.

Keywords: urbanization, Stanley park, bird species presence, bird species evenness, richness and abundance.

Citations

Tryjanowski, P., Sparks, T. H., Kuźniak, S., Czechowski, P., & Jerzak, L. (2013). Bird Migration Advances More Strongly in Urban Environments. PLOS ONE, 8(5), e63482. https://doi.org/10.1371/journal.pone.0063482

Post 4 ; Sampling Strategies

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In the online forest sampling tutorial given, I have chosen to do 1. Random sampling using area, 2. Systematic sampling along a topographic gradient using distance, and 3. Haphazard sampling using area. The Haphazard method had the fastest estimated time to sample at 2h38min, compared to 12h47min for the random sampling method, and 4h7min for the systematic sampling.

According to actual data, the two most common species in the Snyder-Middleswarth Natural Area were Eastern Hemlock and Sweet Birch. Let us use tables to compare the % error of the different sampling strategies for both.

Species Measures Actual

Data

 Data for

The Random

Sampling Method

 Data for

The Systematic

method

 Data for

The

Haphazard

method

 % Error

Random

Sampling

 % Error

Systematic

Sampling

 % Error

Haphazard

Method
Eastern

Hemlock

 Density 469.9 354.2 479.0 380 24.6% 1.94% 19.13%
Frequency 73% 71% 70.8% 80% 2.7% 3.01% 9.6%
Dominance 33.3 19.8 35.5 39.6 40.5% 6.61% 18.92%
Relative Density 50.6 44.0 54.2 43.2 13% 7.11% 14.62%
Relative Frequency 33.8 32.1 37.0 33.3 5.1% 9.47% 1.48%
Relative

Dominance

 44.4 45.6 53.6 54.7 2.7% 20.72% 23.2%
Importance

Value

 42.9 40.6 48.2 43.7 5.4% 10% 1.86%
Morisita Index 1.89 2.33 1.05 1.35 23.3% 44.44% 28.57%
Sweet Birch Density 117.5 41.7 64.5 60.6 64.51% 45.11% 48.43%
Frequency 43.0% 25% 29.2% 20.0% 41.86% 32.09% 53.49%
Dominance 20.2 5.1 11.3 8.4 74.75% 44.06% 58.42%
Relative Density 12.7 5.2 7.3 6.8 59.05% 42.52% 46.46%
Relative Frequency 19.9 11.3 15.2 8.3 43.21% 23.62% 58.29%
Relative

Dominance

 26.9 11.8 17.1 11.6  56.36% 36.43% 56.88%
Importance

Value

 19.8 9.4 13.2 8.9 52.53% 33.33% 55.05%
Morisita Index 2.27 3.20 0.00 5.00 40.97% 100% 120.26%

 

 

 

 

 

 

 

 

Then, let us do the same thing for the two most rare species; Striped Maple and White Pine.

Species Measures Actual

Data

 Data for

The Random

Sampling Method

 Data for

The Systematic

method

 Data for

The

Haphazard

method

 % Error

Random

Sampling

 % Error

Systematic

Sampling

 % Error

Haphazard

Method
Striped Maple Density 17.5 0.0 18.4 60.0 NA 5.14% 242.86%
Frequency 6.0% 0.0% 4.2% 20.0% NA 30% 233.33%
Dominance 0.7 0.0 0.6 3.6 NA 14.29% 414.29%
Relative Density 1.9 0.0 2.1 6.8 NA 10.53% 257.89%
Relative Frequency 2.8 0.0 2.2 8.3 NA 21.43% 196.43%
Relative

Dominance

 0.9 0.0 1.0 5.0 NA 11.11% 455.55%
Importance

Value

 1.8 0.0 1.7 6.7 NA 5.56% 272.22%
Morisita Index 17.00 NA 24.00 5.00 NA 41.18% 70.59%
White

Pine

 Density 8.4 8.3 0.0 20.0 1.19% NA 138.09%
Frequency 4.0% 4.0% 0.0% 20.0% 0% NA 400%
Dominance 0.9 1.1 0.0 0.4 22.22% NA 55.55%
Relative Density 0.9 1.0 0.0 2.3 11.11% NA 155.55%
Relative Frequency 1.9 1.8 0.0 8.3 5.26% NA 336.84%
Relative

Dominance

 1.2 2.5 0.0 0.6 108.33% NA 50%
Importance

Value

 1.3 1.8 0.0 3.7 184.62% NA 184.62%
Morisita Index 16.13 24.00 NA NA 48.79% NA NA

 

For the Shannon-Weiner diversity index (not shown in above tables), the most accurate measure was the one given by the random sampling method using area which was giving the exact same figure as actual data: 1.5. However, looking at the % error for the two most common and two rarest species, accuracy greatly varies within the three sampling strategies depending on the measure and the species concerned. For the Sweet birch, the % error was extremely high for all three methods, and in all measures. As for the striped maple, the systematic method was the most accurate, given that the random sampling method did not account for any tree of that species, while the % error of the haphazard method was considerably higher than for the systematic sampling. Finally, the random sampling method was the most accurate for the white pine species. Its percentage error was noticeably lower than in the systematic sampling, and the haphazard method did not provide any data for the white pine. Before doing this tutorial, I was expecting that accuracy would increase in the same direction as species abundance, so I was quite surprised to see how far off were the results for the sweet birch species measures. After doing this tutorial, I realized that for an area as wide as the Snyder-Middleswarth Natural Area, it would have been preferable to use more than 24 samples for better accuracy.

H. Zulfiqar

7 Theoretical Perspectives

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My research project is exploring the survival and maturation of rabbitbrush and sagebrush in Guerin Creek. Some of the underlying theoretical perspectives I will consider are water availability, interspecies competition, predation (herbivory), and disturbance-succession dynamics.

The water requirements of brush bushes and water availability at the creek site both interact to change germination rate, seedling establishment, and ultimately the maturation of brush bushes (McLendon et al. 2008).

Since both big sagebrush and green rabbitbrush bushes live together, they are in direct competition for space (access to sunlight), access to water sources, and pollinators (Young and Evans 1974). When examining my study area, there were clearly more big sagebrush than rabbitbrush in the creek valley. This was confirmed when analyzing my data and suggests that sagebrush is better adapted to life in the creek valley.

These two species are also subject to predation. Predators are similar between the two brush bushes including insects, grazing animals and rodents (Johnson 1979). Differential predation could influence the successful maturation of both brush plants, however in the literature I have reviewed, the predators are very similar for both plants. Because the brush bushes are extremely aromatic, most undulates do not graze on them, herbivores like deer and cattle are more likely to eat sagebrush over rabbitbrush, but consuming either in excess leads to significant decline in digestion.

Rabbitbrush is known to invade established sagebrush habitat following a disturbance such as a wildfire or construction, as it is much faster to grow from its underground roots (Young and Evans 1974). Sagebrush establishes more gradually following the disturbance. Research on the pre- and post-disturbance climax communities suggest that invasive grasses and plants lead to a significantly different composition in terms of vegetation following a disturbance. Because I was only able to see the mature plants, the species composition of the Guerin Creek ecosystem could not be measured.

Some interesting notes in performing the literature review for my project, I have found the research lacking specifically when looking at the water requirements for the brush bushes. In the reading I have completed, sagebrush and rabbitbrush are often considered pests, despite their significant ecological role in the stage-steppe ecosystems.

Keywords: Artemisia tridentata, depth to water (DTW), desert ecozone

References

Johnson, M. K. 1979. Foods of Primary Consumers on Cold Desert Shrub-Steppe of Southcentral Idaho. Journal of Range Management 32:365–368.

McLendon, T., P. J. Hubbard, and D. W. Martin. 2008. Partitioning the use of precipitation- and groundwater-derived moisture by vegetation in an arid ecosystem in California. Journal of Arid Environments 72:986–1001.

Young, J. A., and R. A. Evans. 1974. Population Dynamics of Green Rabbitbrush in Disturbed Big Sagebrush Communities. Journal of Range Management 27:127–132.

6 – Bush counting!

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I completed my data collection over 2 days, and got 22 replicate counts of the bushes coming up the hill from the creek. It was fairly treacherous in the deep snow, and I found that there were a lot of short plants that could not easily be counted. In addition, the snow also limited the sampling area, so I was only able to collect from two sites around the creek. Ultimately, I was able to sample approximately a quarter of the creek hillside. I recruited my partner to help me count, and it was really helpful because we could compare our numbers and discuss any discrepancies.

I was surprised to find that the number of brush bushes increased almost to the top of the hillside, and then dropped off quickly at the top. I’m not sure if this is caused by a previous disturbance on the hillside (it borders two roads and has possibly been sprayed or mowed to ease road maintenance). I haven’t analyzed any data yet, so I will have to wait and see what I see, but there definitely appears to be a relationship between the distance from the creek and the number of brush plants.

Getting exact distance measurements from the creek proved to be very challenging, and took some practice. Ultimately, I’m very happy with the sampling strategy I chose for this. Using the line count method was a lot faster than trying to set up area counts, especially since the bushes are quite large. I used 0.5m on either side of the measuring rope, which still allowed me to measure the number of bushes per square meter for each of the quadrats.

5 – Reflections on study design

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My sampling strategy was to use a 12m measuring rope to count the number of big sagebrush and green rabbitbrush along the hillsides coming up from Guerin Creek. I counted the number of plants within a 3m segment of rope, extending 0.5m on either side of the rope to give a 3m2 quadrat.

Sampling this number of quadrats was very doable, in total there were 8 unique lines measured and bushes counted and it took one hour. In implementing my sampling strategy, a few things went differently than planned. First, I misjudged the depth of the creek valley, so ended up with double the distance I was expecting to cover. My rope wasn’t designed for more than 12m of measurement, so I only measured the initial 12m as planned, and then counted bushes from an elevation of 12m to the top of the hillside. Additionally, there were between 15-30cm of snow cover, depending on the hillside. This prevented the counting of any young bushes, therefore only mature bushes grater than 40cm high were included in the count.

The data I collected was close to what I expected after doing some research (table 1). The intital 3m are likely flooded in the spring, and so there were few established brush plants right creekside. The number of plants actually then increased all the way to 12m, so clearly they are able to germinate and grow that far from the water table. However, there were 6.67 sagebrush plants per m between 9-12m; while from 12-45m there were only 1.13 bushes per m. When I take another sample I will include measures from 12-18m, 18-24m, 24-30m and 30-36m from the creekbed. This will help elucidate more information about how far above the water table the bushes thrive. Rabbitbrush is much less frequent on the hillsides, so it’s accuracy may not be as good as the big sagebrush measures.

I will need to sample around the entire creek, since there were significant differences between the topography of the two hillsides. The bushes in the second site were nearly double the size and the hillside was very steep compared to Site 1.

 

Table 1. Mean number of sagebrush and rabbitbrush bushes counted at various elevations from the Guerin Creek bed at Thompson Rivers University in Kamloops, BC.

 

<3m of creek

 3-6m 6-9m 9-12m

12m+

Mean sagebrush bushes per m2

2.7

 4.7 6.3 6.7 1.1
Mean rabbitbrush bushes per m2 1 2.7 0.7 1.67

0.24