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Post 4: Artificial Reality

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According to my digital field experiments in the synthesized Snyder-Middleswarth State Park Natural Area, the systematic sampling method was the most time-efficient (12:o6, hh:mm), followed by haphazard (12:23) and random (12:48) methods.

The percentage errors for estimates of the most common and most rare species are shown in the table below:

Percent Error of
Sampling Methods		 Species Systematic Random Haphazard
Most Common Species Eastern Hemlock

37%

 36%

3%
Sweet Birch

43%

 22%

26%
Least Common Species Striped Maple

100%

 100%

43%
White Pine

100%

 100%

49%

As the data suggest, accuracy of estimates were poorer when the species was more rare. Estimates are more accurate when the species in question occur frequently relative to other species.

Consistently, haphazard sampling produced the sample that most closely reflected true species abundance.

Post 3: Observing Trees and Lichen It

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I observed a series of trees along the 1100 block of Meares St. in Victoria, BC. From my observations, I have determined that there are three different species of lichen growing on the bark of the plum trees in this area. Their distributions on the bark of the trees seems consistent with patterns of direct sunlight and shade. Regions of lichen growth inhibition near the bottoms of the trunks are not consistent between trees and follow no discernible pattern of gradient along the street.

 

All of the plum trees seemed to have lost some of their leaves and I wonder if there is a relationship between the number or size of leaves that are being dropped and the position of the tree relative to a nearby construction site and busy roadway. Most of the trees along the street are of similar size and trunk diameter, suggesting they are of similar age. The trees at the west end of the street, near the construction and major roadway are also some of the most heavily-shaded, which may be a confounding variable to any comparisons with this location. The number of leaves dropped by trees in different areas appears fairly equal, but it is hard to say without making measurements if there is a relationship between dropped leaf size and tree.

If there is a difference in the size of dropped leaves, and assuming all trees are of a similar age, this might suggest that trees that are dropping smaller leaves are doing so prematurely, or their leaves are not achieving as large a size at maturity. Either way, the difference might be caused by the growing conditions of the tree (light, water, soil type) or perhaps something is affecting the trees directly. The area of the street near the construction site is noticeably dustier than other areas. We know that trees rely on transpiration through the stomata on their leaves to draw water up from their roots. Perhaps the dust is interfering with this process and leading the trees to drop leaves earlier than normal.

I hypothesize that the size of dropped leaves from trees near the construction site and busy roadway is smaller than the size of dropped leaves from trees at the eastern end of the street. I predict that trees near the construction site will drop leaves of a smaller mean size than trees away from the construction site.

A response variable for this experiment would be the mean length, in millimetres, of leaves (continuous). An explanatory variable would be the distance of the tree from which to leaves are dropped, in meters, to the construction site (continuous).

 

Blog Post 8 for Katarina Duke

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Compiling the table was relatively easy; however, establishing a ranking system for algal growth significance required some thought. In the end, I chose to use a ranking from 0 to 5 with 5 indicating “very significant quantity of algal growth.” Summarizing the data within the table was easy as the SonoTek Flow Tracker 2 used takes the 20-25 discharge and depth measurements taken within the creek and provides an average depth and total discharge.

Deciding on a graph format to use was completed with trial and error. Initially I had completed a graph plotting both discharge and depth against algal growth significance. Instead, I chose to create two separate graphs (i.e. discharge vs. algal growth significance and depth vs. algal growth significance) to convey the data as algal growth significance showed a correlation with discharge but no relationship could be inferred between depth and algal significance. This surprised me as water temperature increases with shallower water and temperature increases encourage algal growth, thus making me presume that a relationship between algal growth and water depth could be established.

Many abiotic factors influence the growth of algal. It would be interesting to determine at what temperature does the influence of temperature on algal growth surpass the influence of discharge on algal growth (or vice versa). I would also be curious in exploring further if there is in fact no relationship between water depth and algal growth by conducting a controlled experiment where few abiotic factors are changing such as observing algal growth in a stagnant tank with only the water level changing.

The influence of discharge on algal growth was as expected; increase in discharge inhibits algal growth.

Not depicted within the graphs but displayed in the table is the relationship between turbulent or laminar flow and algal growth. As expected algal growth was observed in areas of laminar flow.

 

Blog Post 8 Tables and Graphs

BIOL3021- Sampling Locations

Blog 5: Design Reflections

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After collecting my initial field data, I noticed an issue with my methods. I counted the ducks 5 times in one day, at two hour intervals. I found that since ducks have the ability to walk and not stay stationary like plants, I had some trouble counting the ducks without error. I alleviated this problem for the most part by taking pictures of the areas and counting the ducks that way, but some could have been missed if they were in the bushes surrounding the water. I noticed that the ducks at the bridge preferred to be in the water around noon and 4pm but being in the shade or the sun didn’t seem to be a factor at these times even with the warmer water temperature, but at the other two study sites, there didn’t seem to be enough ducks to make a solid hypothesis, so I have decided that for my next data collection, I will count the ducks at 10am, 2pm, and 6pm to account for the changes in behaviour, and I will mainly focus my studies on the site of the moat with the bridge. I also believe that my initial hypothesis had too many variables, and the food source variable will be much harder to test for, so I decided to condense my hypothesis to just include water quality. In doing so, it made my study much easier to conduct. Overall, I do believe my systematic sampling method to work and though I found a few of my observations to be surprising at the time, looking back on them, they do make a lot of sense when I think about what I know about how ducks behave.

Design Reflections

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I conducted my research using a simple random sampling technique to sample how many bees were around different types of flowers. To limit my bias, I used a random number generator on my computer to come up with the number of steps to take (between 1-20 steps) and the compass bearings (between 0-360). I used a .5 meter squared quadrate to analyze how many bees were surrounding the flower of interest. I also used a point count sampling technique to observe how many bees were either on the flowers or an inch away from them for a time period of five minutes. I located 6 flower samples using the random sampling technique and measured the amount of bees surrounding them three times.

I had a couple difficulties implementing my sampling strategy. Some of the coordinates from the random number generator lead me to areas with no flowers. For example, the 3 steps and 213 degree compass bearing led me to the middle of the playground. Another difficulty that interfered with my data collection was disruption from children. Some kids playing around the park would approach the flowers I was observing which may have scarred the bees away. The data I collected did not surprise me in any way because it matched my hypothesis. Overall, I believe that my sampling technique works really well for my research. The one modification I will make to improve my research is to make my observations earlier in the morning to limit the disruption from children.

Blog Post 1: Observation

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Location: Riverlot 56, St. Albert, Alberta

Date: August 6, 2018

Time: 1700

Temperature: 29 Celcius

Weather: Sunny with a few clouds

 

Riverlot 56 is located with the city limits of St. Albert on the northeast side.  It is located on Poundmakers road. This particular park is managed by the province as a natural area.  It has several uses including cross-country skiing, snowshoeing, hiking and wildlife viewing.

The total size of the park is 266.86 Acres (108 Hectares).  

The area that was chosen is an open field in the park that is surrounded by trees on three sides.  On the fourth side is a fence with farmland on the other side of this fence.

There are many gopher holes that can be seen from the pathway.  

This land is mostly made up of tall and short grasses with Canada Thistle scattered throughout.  On initial appearances it appears to be a healthy natural grassland area. However, on closer inspection there appears to be large areas of thistle.

Potential Subjects:

  • Amount of Canada thistle present compared to other plants
  • Number of gopher holes and the effect they have on the surrounding grassland
  • There will be more invasive plants closer to the trails than the untouched pasture
  • pH in the soil affects what will grow

 

Overall facing South

Overall Facing East

Overall Facing NorthEast

Riverlot 56 sketch 1

 

 

Blog Post 7: Theoretical Perspectives

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Good Afternoon, Professor Elliot and Class

Now that I have finalized my data collection, I have been reflecting on the theoretical basis of my research project. The theoretical perspective of my final project will focus on answering the question as to what factors influence riparian vegetation abundance. The ecological processes that my hypothesis will look at includes studying predictors such as elevation and aspect and their impact on the amount (presence or absence) of large woody vegetation in a riparian area. An interesting factor came up during my on-going observations and field data collection, which is the presence of higher-elevation riparian meadows on both sides of the creek. The environmental gradient is not homogenous so I am interested to see how this influences (or does not influence) the outcome of my research.

I have found an abundant collection of literature related to my research topic, for example some topics / ideas that underpin my research include:

  • Riparian vegetation in upper mountain zones;
  • Links between lateral vegetation zones and river flows;
  • Longitudinal- and transverse-scale environmental influences on riparian vegetation across multiple levels of ecological organization;
  • High-elevation riparian meadows;
  • Elevation, competition control, and species;
  • Structure and composition of vegetation along an elevational gradient; and,
  • Exotic and native plant community distributions within complex riparian landscapes.

Three key words that could be used to describe my study are: riparian ecosystems, elevation gradient, and freshwater streams.

Blog Post 7: Theoretical Perspectives

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The observance of the long-term impact of a former landfill on the surrounding environment will form the theoretical basis of my research project.

My research project will specifically focus upon the impact on a forested ecosystem following the anthropogenic effects of deforestation and pollution, focussing on the similarities and differences between two plant communities and soil composition of the former landfill area and a nearby historically forested area, which are connected by the Alfred Howe Greenway trail.

My hypothesis, that former landfills have a long-term negative impact on plant health, will include the study of the ecological processes of primary succession, soil degradation, and nutrient cycling.

Ideas that underpin the research being conducted for this project include: the impact of soil toxicity on different plant species, species richness and comparative biomass production in a community recovering from a disturbance, and the interrelationships between soil nutrient levels, bacteria, fungi, and diseased plant species.

Keywords: ecosystem recovery, biomass production, soil composition.

Sampling Strategies

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For this assignment, I sampled tree species virtually be means of three sampling techniques: simple random, systematic and haphazard. I selected an area based method for Snyder-Middleswarth natural area. The technique that was the most efficient in terms of time spent was the systematic sampling method which took 12 hours, 35 minutes. The next fastest sampling technique was haphazard sampling at 12 hours, 39 minutes, while the slowest method was random sampling which took 12 hours, 49 minutes.

The following is the percentage error calculated using (E – T)/T*100, where E = estimated value and T = true value

Most common specie – Eastern Hemlock

systematic: 6.3% error

random: 26.7% error

haphazard: 2.0% error

Second most common specie – Sweet Birch

systematic: 1.3% error

random: 24.0% error

haphazard: 27.7% error

Most rare specie – White Pine

systematic: 233.3% error

random: 49.7% error

haphazard: 48.8% error

Second most rare specie – Striped Maple

systematic: 100.0% error

random: 76.0% error

haphazard: 28.6% error

From the results, the most accurate sampling strategy for common species was systematic, while the most accurate method for rare species was haphazard. The accuracy declined substantially for rare species, especially in the systematic sampling method. Accuracy increases with greater species abundance.

I was surprised to see that the systematic sampling method had the highest percentage error for rare species. This might be due to a low species density distribution along the two y coordinates used in the systematic method. Additionally, it would be interesting to observe a change in accuracy for species in the community from using more then 24 sample points.

Post 2: Sources of Scientific Information – A Flowery Website

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I have selected a resource that is very much not a peer-reviewed scientific document, but is nonetheless informative. It is the type of document that I regularly see my high school students consult, though its use is limited in higher academic programs.

The webpage is part of The Victoria Nikkei Cultural Society, an organization celebrating Japanese-Canadians in the Victoria area. As part of its guide the Japanese past time of “Hanami,” or cherry blossom viewing, the site offers information on some of the different species of cherry and plum trees that exist in the area. The information includes latin names of the plants and physical descriptions of the leaves and blossoms.

Although the authors are listed, their qualifications and affiliations are absent. They may happen to be very capable botanists but that is not possible to assess with the information provided. The article does not include citations or a bibliography. This document is unquestionably non-academic material.

http://www.vncs.ca/wordpress/activities/hanami-%E8%8A%B1%E8%A6%8B-cherry-blossom-viewing/