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Blog Post #6

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I have collected data from three locations along Dallas Road, Victoria at varying distances from the ocean. At each location, I took 10 replicates using a 0.3m x 0.3m quadrat and a 3m transect in order to count the number of red rose hips and black rose hips. I employed a systematic sampling method.  It has been a few weeks since my initial observations and the winter has been hard on the rose bush. In particular, the bush closed to the ocean, which I defined as 0m from the ocean, was completely dead.  However, the dead rose hips were still present on the bush and hadn’t fallen off yet, so this bush actually provided a great “control” bush that I can compare further bushes to.

 

At first, I was set on having 3 locations and taking all my samples from these bushes; however, I will need to find more locations along Dallas Road as the 3 locations will not provide enough replicates solely from themselves.

 

I did notice how much the survival of the rose hips varied on a temporal scale, even within just 2 weeks. This observation will not directly affect my hypothesis, but makes me wonder how the survival of the rose hips varies based on the season.

Blog Post 5 – Design Reflections

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On January 23rd from 2pm to 3pm (MST), I did my first field data collection. I chose to use the haphazard sampling method. It made it easy to select five distinct point counts across the area of study using Google maps. Point counts was an effective way of sampling bird population and human traces. However, because the haphazard method does not provide a true randomization, I am aware that the data collection might have been more effective and accurate if I had selected more than five point counts. In the future, I would either use a true random sampling method, or I would use the haphazard method while doubling the number of watch points. I think that will generate more accurate results.

Prior to collecting the data with four other observers, I pre-defined “human traces” as being any of the following: debris, food waste, a pair of footsteps, a passerby, pet or pet feces, a motorized vehicle, or any human-installed unit such as a garbage bin, picnic table, and what not. Bird feeders was one human-installed unit which was a category on its own since we assume it has a direct impact on bird population. After collecting the data, I reflected with the other observers, and we all agreed that the footsteps category was not useful, hard to count, and confusing since with the snow, there were many confounded footsteps. Counting hikers would have been sufficient. Moreover, we concluded that if this data collection had to be done again, we should count the number of nests observable at eyesight as well, and possibly the number of bird caches. I had not included those, because the species observed was the black-billed magpie exclusively, and I was worried that we would confuse other species’ nests or caches with the ones that actually belonged to the black-billed magpies. I would like to try including them next time around.

All in all, the results were not surprising as the point count which featured the most traces of human presence and also a bird feeder was the one with the highest black-billed magpie population, as expected. Still, for a second data collection, I would double the number of watch points, or use a true random sampling method, for more accurate results. Also, I would revise the pre-defined categories of human traces and keep track of nests and observed caches as well.

Cultus Lake – Initial Observations

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January 26, 2018
12:30 – 13:15
Weather: 5°C and overcast; rain earlier in the day

I have chosen Cultus Lake as my research site. It is 6.3 km2 with a maximum depth of 44 m. The lake basin is bound by International Ridge to the east, Vedder Mountain to the west, the agricultural lands of the Columbia Valley to the south, and a heavily used recreational beach to the north. The mountains around Cultus Lake are forested with mostly coniferous trees and patches of regenerating deciduous trees. The vegetation at the north end of the lake is maintained with almost no understory and only select mature coniferous trees remaining. Portions of Cultus Lake are within a Provincial Park. The park areas are largely occupied by campgrounds.  The lake attracts between 1 and 3 million tourist visits per year. The lake is subject to anthropogenic nutrient loading from agricultural activities and septic leaching.  It is home to two species at risk, the Cultus Pygmy Sculpin (Cottus aleuticus, Cultus population) and the Cultus population of sockeye salmon (Oncorhynchus nerka). The littoral areas of the lake have been invaded by invasive Eurasian milfoil (an aquatic plant). My questions are as follows:

  1. Is eutrophication of the lake leading to deep water oxygen depletion?
  2. Do fish, specifically the Cultus Pygmy Sculpin, favour portions of the lake that have higher concentrations of dissolved oxygen?
  3. If oxygen depletion does occur, does the lake fully recover during winter overturn?

 

Dissolved Oxygen vs. CPS Capture Frequency

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My project includes fish capture data (for Cultus Pygmy Sculpin; CPS) and corresponding dissolved oxygen levels.  The most challenging part of creating the graph was organizing the data into an appropriate format. I am analysing the data using Tableau Public (a free data visualization tool) which is very effective once the data is formatted.  I made a regression plot comparing CPS occurrence and dissolved oxygen concentrations. I removed the data points for minnow traps that did not yield any CPS captures, as they made the results confusing and I wanted to focus to be on where CPS are occurring as opposed to where they are not occurring.  CPS is a species at risk, so inherently it is not observed in many locations. The results were surprisingly clear.  Only 1 of the 169 captures occurred in dissolved oxygen levels of less than 7 mg/L, suggesting that CPS may have an aerobic threshold of around this level.  I find this a little surprising. I know that salmon (in general) have an aerobic threshold of around 5 mg/L. I expected CPS to be similar. Notably, this is not a huge dataset and further investigation is required before determining the aerobic threshold of CPS. This was, however, a great start.

Post #5: Design Reflections

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I took my initial samples along Dallas Road and Beacon Hill Park (Victoria, BC) this week. The weather was sunny, 8°C and windy.  I used a 0.3m x 0.3m quadrat, systematic sampling strategy and counted the number of Nootka dead and alive rose hips at three locations along a gradient differing in distance from the ocean. When I arrived at the first site (an exposed bush along a coastal bluff near Dallas Road), I was surprised that nearly all the rose hips were dead. I observed that the coastal bluff had a higher proportion of red, alive hips earlier this month. It appears the winter has been hard on the Nootka Rose.

 

I was nervous that the other sites would also display a similar trend; however, the sites further from the ocean, an intermediate site called “deciduous forest” and the end range site called “Beacon Hill” did have some alive hips.

 

I came across a difficulty using my quadrat as I placed the quadrat on the top of the bush, and there would be hips present at different depths beneath the quadrat.  Therefore, I will have to define my sampling area as within the same plane as the quadrat.

 

As well, I will need to find more sites within each gradient for the final data.  There are not enough sample units from the single site I collected data from for the initial data.  I have confidence that there are other sites within each gradient where the Nootka Rose grows.

 

I will continue to collect data in the same manner; however, modify my definition of the quadrat region and search for additional sites within each gradient.  Redefining the area of the quadrat region will make the replicates more standardized. As well, collecting more data from additional sites will provide a more accurate measure.

Blog Post 3

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After observing that certain lichens tend to prefer certain sides of trees, I plan to study whether it is a NSEW preference or simply a light availability preference. This is a snapshot, observational study. After the realization I had in Haida Gwaii regarding the difficulty of identifying lichens, even to the genus level, I have decided to stick to very general growth forms: crustose (dust), foliose (leaf), and fruticose (shrub).

Date: Feb 8, 2018, Time: 1130 hrs, Weather: sunny, partly cloudy, 11C

To collect my initial field data I used a stratified random sampling method. Mount Douglas is already divided into three areas including the lower forest, upper forest, and rocky outcrop, which I used as my strata. I used a distance based method to sample trees in each strata. To assure randomization I used a random number generator phone application where first I generated the amount of steps forward on the path I would take, then I randomly generated a second number that would tell me how many steps perpendicular to the path I would take, and a third number to tell me whether I would go right or left on the path.

For the initial observations I sampled 5 trees, or replicates, in each strata. In the lower and upper forest, most trees were coniferous except 1. Foliose lichens were not present in the lower and upper forests, except for the very last tree in the upper forest that I sampled that was quite close to where the rocky outcrop started. In the rocky outcrop, foliose lichens were present on all the trees, and all the trees were deciduous garry oaks (quercus garryana). The crustose lichens were present in all three strata and on all sides of each tree.

I estimated percent canopy cover to get an idea whether light availability has an effect on where the lichens grow. In the rocky outcrop garry oak ecosystem, the trees were all deciduous, much shorter, and there was much more opening in the canopy. Foliose lichens were present on all the trees, which could be a correlation.

My hypothesis will be (Ha, alternate hypothesis): There is a significant difference in percent cover of three lichen growth types depending on the aspect of the tree trunk.

Ho (null hypothesis): There is no significant difference in percent cover of lichens depending on aspect of tree trunk.

Response variable: Percent cover of lichen (continuous)

Predictor Variable(s): Aspect of tree (categorical)

I predict that I will accept the alternate hypothesis and reject the null hypothesis.

I could add more predictor variables, such as whether the tree is deciduous or coniferous, and the layer of the forest, but this might be too complicated and require too many replicates. I have to think about this one!

 

This article is suitable to use for a reference ✔︎

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The article that I found is academic, peer-reviewed research material. The research was done following the flooding in 2005, when the macrophyte and water dynamics were changed by the influx of rainwater. Over a period of four months, samples of periphyton were collected bi-weekly from the Bow River at six different locations in the Southeast area of Calgary. The purpose of this study was to determine whether the Bow River water quality model (BRWQM) used by the City of Calgary was calibrated properly to detect dissolved oxygen and periphyton levels in the water. The BRWQM is an invaluable tool used to ascertain the quality of water that has been treated by the wastewater treatment plants.

The authors are all based out of the University of Calgary. Robinson is in the Geomatics Engineering department in the Schulich School of Engineering; Valeo, Chu and Iwanyshyn are in the Civil Engineering department in the Schulich School of Engineering; and Ryan is in the Geoscience department. This means that the article is an academic one, researched and written by experts. The acknowledgments section thanks the reviewers, as well as City of Calgary and the Natural Sciences and Engineering Research Council (NSERC) for funding the paper.

 

Reference Cited

Robinson KL, Valeo C, Ryan MC, Chu A, Iwanyshyn M. 2009. Modelling aquatic vegetation and dissolved oxygen after a flood event in the Bow River, Alberta, Canada. Canadian Journal of Civil Engineering [Internet]. [cited 2018 Feb 8]; 36(3), 492-503. Available from: http://www.nrcresearchpress.com/doi/full/10.1139/L08-126#.Wny4dmbMzOQ doi:10.1139/L08-126

Blog Post #2 — Cameron Purdy

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Academic Peer Reviewed Research Paper

Title:  Terminal Nerve GnRH3 Neurons Mediate Slow Avoidance of Carbon Dioxide in Larval Zebrafish

Source: Koide T, Yabuki Y, Yoshihara Y. Terminal nerve GnRH3 neurons mediate slow avoidance of carbon dioxide in larval zebrafish. Cell Reports, 2018 DOI: 10.1016/j.celrep.2018.01.019

Link: http://www.cell.com/cell-reports/pdf/S2211-1247(18)30036-6.pdf

 

The following paper is an Academic Peer Reviewed Research Paper for the following reasons:

a) The paper is written by experts in the field. Koide, Yabuki, and Yoshihara are all associated with the Laboratory for Neurobiology of Synapse in Japan. It was published in the journal “Cell Reports” which publishes high quality peer-reviewed material.

b) The paper contains a bibliography citing additional sources used as information. These sources are cited in text throughout the article. (Ex.  “This fast escape response is mediated by reticulospinal neurons, including the large, morphologically conspicuous Mauthner cells” (Gahtan et al., 2002; Liu and Fetcho, 1999; O’Malley et al., 1996).)

c) Acknowledgements thank two editors for their critical reading of the manuscript indicating that the paper had gone through the peer review process. This is further supported by the journal the article is posted in.

d) The paper is formatted as a research paper as it contains an introduction, results and discussion. The experimental methods were included within the results section. We can see that there are multiple intervention levels further leading us to believe that the paper is experimental in nature. *(See below)

(To examine what chemosensory signals affect behaviors of larval zebrafish, we applied various chemicals to the head of fish at 5 days post-fertilization).

Blog Post 1: Observations

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Blog Post #1: Initial Observations of Study Area

Cameron Purdy – T00028679

January 31, 2018

Address:  33844 King Rd, Abbotsford, BC, V2S7M7

Coordinates: 49.0291° N, 122.2854° W. ~40m above sea level

Weather: Light rain showers, ~ 4ºC.

Seasonality: Winter

Time: 3:20PM

Description of Study Area:

The area(s) I have decided to observe are two separate ecological islands on the University of the Fraser Valley campus. Prior to UFV being built, the location was comprised of mainly farmland. Historically, the Fraser River had a much larger footprint and had floodplains that covered much of Abbotsford including areas surrounding UFV. 

Location A is a temperate deciduous forest with area (A=440m²). It is bordered to the north by the Abbotsford Entertainment and Sports Center, and surrounded by parking lots to the east, west, and south. The general topography of the forest is flat, however there is a slight slope coming down from the parking lot on the east most side. The most prevalent vegetation found includes Convallaria majalis, Oemleria cerasiformis, Maianthemum racemosum, and Trientalis borealis. Additionally, tree canopy cover in this forest is quite dense and filters out much of the sunlight. Few species of birds could be seen flying amongst the trees. 

From left to right:

  1. Forest A looking north from the south. Parking lot can be seen to east with the slight slope leading down into the forest.
  2. Forest A looking north from south. Parking lot can be seen to west, Abbotsford Entertainment Center can be seen at the north end of forest.
  3. Forest A looking north from south. Proposed transect line through middle of forest.

 

Location B is also a temperate deciduous forest with area (A=540m²). It is bordered by buildings and a walkway to the west and south, and grass fields to the north and east. Centrally located in the forest is a small pond (A~200m²) that is surrounded by marshy wetlands. The general topography is relatively flat, with a slight slope on the east most side of the forest. The pond situated within the forest collects water that runs off the slope, and has a small stream that exits the forest to the south. The most prevalent vegetation found includes Rubus spectabilis, Rubus idaeus, Oemleria cerasiformis. The tree canopy cover in this forest is less dense than that of location A. While no wildlife was seen, frogs could be heard from the pond. 

From left to right:

  1. Forest B looking north from south. Open grass field can be seen to east, ground slopes downward towards the west.
  2. Forest B looking north-east from south-west. Pond and marshy surrounding areas seen.
  3. Forest B looking south-west from north-east. Proposed transect line through middle of forest.

Follow up Questions: 

1) What leads to the difference in vegetation among the two forests. How could they have a significantly different prevalence of plant species when they are located so close to each other?

2) While we know the vegetation differs between the two sample forests. How does the fauna differ between the two. Is there a higher prevalence of specific invertebrates in one forest over the other?

3) What are the differences in soil composition? If there are differences, could these in fact be linked to the the prevalence of specific flora and fauna in their respective forests.

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