Category: Nancy Elliot

Blog Post 5: Design Reflections

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Blog Post 5; Design Reflections

 

My sample strategy was Systematic sampling which was easy to design. I found a few problems with the design and statistics sample sizes. Statistically speaking, “the sample should be no more than 10% of the population” (De Veaux et. al, 2014, p.411). To obtain a sample of only 10%, I needed to create a smaller quadrate, decrease the amount of transects of increase my plant coverage.

I decided to divide my single plot into 2 separate plots. Both plots will be 5m x 5m. One which contained soil with a large amount of moisture and one which contained soil with low moisture. To make sure I had less than 10% of the population within my sample units, I will place 4 transects East/West and 4 North/South. This also allows me to obtain 16 samples in each plot, which is larger than the required 10 samples per area. My quadrate must then be 17centimeters x 17centimeteres to give me a total of 2.72m2. This puts my sample under the 10% of the population.

I also altered the plots so that the sample areas were not on the boundaries, and did not overlap between the “Wetter” and “Drier” areas. I will continue to use the Systematic sampling techniques as it worked well for my data documentation.

The modification will help me to easily distinguish between the two areas of moisture, while allowing to be obtain a proper sample amount in comparison to the total population.

 

Citation

De Veaux, D., Velleman, P., Bock, D. Intro Stats Fourth Edition. Copyright 2014, 2012, 2009. Pearson Education, Inc. Upper Saddle River New Jersey.

Post 8: Tables and Graphs

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I did not have any difficulties summarizing my abundance data in a simple bar graph, categorized by the three kinds of soil upon which my hypothesis is based. I graphed the relationship between the soil texture at each site along my environmental gradient and the abundance of individual trees sampled. The outcome supported my hypothesis that western redcedar trees would dominate areas of loamy soil that have better moisture-retaining properties than the sandy sites. The bar graph neatly summarizes the presence and absence of the three main species of the area: western redcedar (Thuja plicata), Douglas fir (Pseudotsuga menziesii), and ponderosa pine (Pinus ponderosa). The data did not reveal anything unexpected, but it inspired me to look into why western redcedar was completely absent from the sandy site (site 1) but was represented in the silty site (site 3). This prompted me to research competition between species in the interior cedar-hemlock biogeoclimatic zone, specifically between shade-tolerant and shade-intolerant species. It also inspired me to think critically about the overlapping niches of each species and how their evolutionary history has played a role in the spatial distribution of individuals within a mature stand.

Blog Post 4: Sampling Strategies

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Adrienne Burns

August 21, 2019

 

The first sampling method I conducted was the ‘Area; Systematic” approach. I choose one randomized number ‘y’ axis, and received my subsequent data from adding 10 to each of the ‘x’ axis and alternating between the randomized number and ‘y+10’. The density data from this sampling method has some very accurate of methods for certain species of trees, but very inaccurate data for others. When comparing it to the ‘Actual density’ data, for example, the actual density of Sweet Birch was 117.5, and sampling density found 116, and for White Pines species, the actual density was 8.4 and the data showed a density of 28.0. I found it interesting that for the species Striped Maple, this method did not count any of the trees. The density for Striped Maple was 17.5 and this method accounted for 0.0. This type of sampling didn’t correctly depict the distribution of tree species over the entire forest area. Also, the ‘Area; Systematic’ method took a long time to complete. It took 12 hours and 35 minutes to complete the sampling.

 

The second method was the ‘Distance; Random’ sampling technique. This method had given me 24 random ‘x, y’ axis to sample. It was the fasting sampling method which took 4hr 38minutes. This would be the preferred method of sampling if the ecologist had time constraints. Along with the first method this one also showed varying correctness for the distribution of the trees. For example the actual Hemlock density was 469.9 and the data showed a density of 445.1, but for the Red Maple the actual density was 118.9, but the data showed 145.2. Of all 3 of the sampling methods I used, the ‘Distance; Random’ technique was the most accurate especially with regards to frequency.

 

The last method, ‘Area; Haphazard’ took the longest timeframe to complete 13h and 1minute. It also had the largest variation in results. For instance, Eastern Hemlock actual density was 469.9. Both ‘Area: Systematic’ and ‘Distance; Random’ data were close in proximity to 440.0 and 445.1, yet the ‘Area; Haphazard’ showed 669. As it had the largest variation and the longest timeframe, I would need to seriously consider I was going to use this method.

 

None of the methods were very accurate. All had some tree species data that was accurate, and others that were far from the actual data.

 

Error Percentage Eastern Hemlock

 

‘Area; Systematic’

(440-469.9)/ 469.9*100 = 6.36% Error

 

‘Distance; Random’

(445.1-469.9)/469.9*100 = 5.28% Error

 

‘Area; Haphazard’

(664.0-469.9)/469.9*100 =41.31% Error

 

 

Error Percentage White Pine

 

‘Area; Systematic’

(28-8.4)/8.4*100 = 233.33% Error

 

‘Distance; Random’

(9.7-8.4)/8.4*100 = 15.48% Error

 

 

‘Area; Haphazard’

(4.0-8.4)/8.4*100 = 52.38% Error

 

 

 

Blog Post 3: Ongoing Research Material

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Blog Post 3: Ongoing Research Material

Adrienne Burns

August 20, 2019

 

I have decided to do my research field study on the plant species Hydrocotyle heteromeria (Wax weed or Pennywort). I found it in a large patch around a wet soil area, underneath the mature Pyrus communis (pear tree). There were only a few areas I spotted with Waxweed species in large quantities, but perhaps with the field research project I may find smaller patches within the grassy areas. After I had completed a Tru.ca Library and internet research, it sounds as if the plant species prefers moist areas and grows in areas of yards, golf greens or forests that do not have well drained soil.

I found that by documenting the observable gradient of the landscape (attached photos), the plant species is clustered around areas 1 and 2. Both of the first two selected sites are in areas of lower soil levels. I notice that in area 1, where I first noticed the large clusters of Pennywort, there are small pockets of even lower soil levels around the base of the Pyrus tree. The Hydrocotyle heteromeria is found in large abundance in these pockets. In observation region 2, there is still large amounts of the plant found, but it looks as though there is a decreased amount of large clusters. It seems as though the plants are clustered around the base of the tree. There could possibility be a symbiotic relationship with the tree or the plant may prefer nutrients received closer to the mature tree. The nutrient level in the center and drier area of the landscape may differ from the nutrient level near the tree, especially because there are many large trees on the non-study side of the fence (approximately 4 feet from the location of found Waxweed). In both observational regions 3 and 4, there was no sign of the species, so distribution and abundance has decreased drastically.

I believe that these pockets of lower soils levels catch and contain more water. There would be an abundance of water especially around the base of the tree as the area receives less sunlight, and the lower soils levels would accumulate more water. There would also be an accumulation of water in areas 1 and 2 because of the winter water run-off from the tree.

 

Hypothesis: The distribution of Hydrocotyle heteromeria in the Christchurch New Zealand backyard landscape is limited to areas of soil with high moisture content. My

Prediction: H. heteromeria is seen in areas of high moisture and the plants abundance decreases at the soil becomes increasing dry.

Prediction Variable: Soil moisture. High moisture content or Low moisture content is a Categorical Variable.

Response Variable: Plant numbers decrease as soils moisture decreases. The sample units would be Categorical as “absent or present.”

 

 

Blog Post 2: Sources of Scientific Information

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Blog Post 2: Sources of Scientific Information

Adrienne Burns

August 19, 2019

Citation

Gao, Jun-Qin; Duan, Mu-Ying; Zhang, Xiao-Ya; Li, Qian-Wei; Yu, Fei-Hai. CATENA. May 2018. ‘Effects of frequency and intensity of drying-rewetting cycles on Hydrocotyle vulgaris growth and greenhouse gas emissions from wetland microcosms.’ Vol. 164, p44-49. 6p. DOI: 10.1016/j.catena.2018.01.006. , Database: Academic Search Complete. Accessed TRU Library; Science Direct. August 19, 2019.

‘Effects of frequency and intensity of drying-rewetting cycles on Hydrocotyle vulgaris growth and greenhouse gas emissions from wetland microcosms,’ is an Academic, peer reviewed research paper.

 

The article is Academic material. It has been written by experts in the field of ecology. They are affiliated with two Universities, one in Beijing and one in Taizhou China.

Author Affiliations:

1School of Nature Conservation, Beijing Forestry University, Beijing 100083, China
2Zhejiang Provincial Key Laboratory of Plant Evolutionary Ecology and Conservation, Taizhou University, Taizhou 318000, China

There is both in-text citations and a bibliography.

“Changes in intensity of drying-rewetting cycles can also alter ecosystem functioning (Ciais et al., 2005; Breda et al., 2006; Schwalm et al., 2010; Shi et al., 2014; Sun et al., 2016).”

The article has been peer reviewed. In the Acknowledgements, the authors thank 2 anonymous reviewers for their contribution.

We thank Ning Mai, Yi-Xuan Zhu and Cheng-Fu Wei for assistance with the experiment and the two anonymous reviewers for their valuable comments.

It is a research paper because it has a ‘Methods’ and ‘Results’ section in the article.

2. Materials and methods 2.1. Experimental microcosm set-up

3.  Results 3.1. Effects of frequency and intensity on plant growth

 

 

BIO 3021 Blog Post 1: Observations

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BIO 3021 Blog Post 1: Observations

Adrienne Burns

August 19, 2019

 

I have selected to observe a Christchurch, New Zealand, backyard landscape. I live in the city center and it is an easily accessible area which I can monitor every few days. It is currently winter in New Zealand and the weather varies drastically from below freezing temperatures to 18 degrees Celsius.

 

I began the study of the backyard landscape on 14/08/19 at 5:22pm, which is the winter season. The temperate was 9 degrees Celsius with no strong winds. The study area is 35 meters by 18 meters. Most of the landscape is grassland, with 2 areas of mixed evergreen trees and shrubs. Amongst the grassland, there are 4 fruit trees; Pear, Plum, Lemon and Limes. The grassland is uneven terrain, with the section through the middle containing higher levels of soil. The upper right and lower right quadrants, to the right of the fruit trees have a small dip, where the soil level is approximately 3 inches lower than the middle of the lawn.

 

I found it interesting that even though the grass landscape is mostly a level surface area, there are pockets that seem to hold more moisture. On the upper right quadrant, the grass is softer with more water than the middle section of the site. Are there different plants in the dry areas as opposed to the wetter soil areas? I noticed a large area of Wax weed (Hydrocotyle heteromeria) in the areas of higher moisture content. I also noticed that there was an extremely large amount of White clovers (Trifolium repens) all over both of the lawns wet and dryer areas. It seemed as if they preferred the sunny areas, but is there a pattern to their distribution as they were rarely found in the shady areas? I also observed large areas of Couch grass (Elymus repens). I found it odd that they seemed to have a pattern of being more present near concrete edging. They were noticeable around the edges of the concrete block that held up the clothesline and near the walk ways. Is Couch grass more tolerant to unhospitable environments that allow it survive in these areas where common lawn grasses are found less?

I am most interested in the large patches of Hydrocotyle heteromeria in my lawn, so I may do my Field study on this interesting plant.

 

 

 

Post 7: Theoretical Perspectives

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My research project focuses primarily on how soil properties affect Western redcedars distribution, but also touches on succession as Site 2 has been logged in the last 10 years. This relates to the evolutionary fitness (their adaptation/resilience to disturbances) of Western redcedars as well as competition/niche overlap between it and the other two most dominant species: Ponderosa Pine and Douglas Fir. My hypothesis focuses on how soil moisture content influences the spatial distribution of Western redcedars in the ICH-zone of British Columbia, but the specific research site I have chosen involves other variables such as aspect, elevation and anthropogenic influences. As I collected my data, I observed that while Western redcedar is completely absent from the site with the sandiest soil, it is distributed densely in the lowest elevation site with loamy soil and exists in moderate numbers in the silty site. This leads me to believe that competition for nutrients and sunlight are factors in determining the realized niche for the three most dominant tree species of the area.

The three keywords I would use to describe my research project are: soil moisture, realized niche, and inter-competition.

Post 6: Data Collection

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I sampled 30 replicates (10 from each site). The problems I experienced implementing my sampling design were the same as in Blog Post 5, where the uneven ground of Site 2 was difficult to maneuver as I was pacing out my steps. The thick vegetation around the rocky outcrop of Site 3 was also a challenge, but ultimately did not stop me from collecting any samples. Some patterns that I have noticed include the complete absence of Western redcedar trees from Site 1, and the domination of Site 2 by the Western redcedars. In my hypotheses, I predicted that the lower elevation and higher moisture content of Site 2 would promote the growth of the Western Red Cedar, which has been supported so far. Because Site 1 is so sandy and sand doesn’t retain as much moisture as loam or silt, the complete absence of Western redcedars is not very surprising. Elevation and aspect could also play a part in their distribution, as Site 1 is at a higher elevation than Site 2 but equal to that of Site 3. Site 3 receives more sun (aspect) than Site 1 however, which may explain the species distribution patterns I have noticed.

Post 5: Design Reflections

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I used a distance-based random sampling method to gather information about the species diversity along the gradient of my research area. I chose a point in roughly the center of each sub-site to measure from, just to make sure I didn’t wander too far out of the research area and skew my data. I set the random number generator on my phone to have a maximum of 4, then chose two cardinal directions. (1 = N, 2 = E, 3 = W, 4= S). I then set the number generator to have a maximum of 25 and walked the generated number of steps in both random directions, then recorded my data on the closest tree and marked it with a ribbon.  I experienced difficulties collecting data in the second sub-site because the terrain was so uneven and the vegetation that grew around the rocky outcrop in sub-site 3 was very thick.  The data was not very surprising, as I’ve spent most of my life walking through the forest of my research area and have become familiar with the species that grow there and their spatial patterns. The random distance-based sampling technique I used was easy to implement and I will continue using it to collect further data. By using a random number generator on my phone and beginning from a predetermined center point, the abundance of each species of tree was easy to categorize and record in my field journal as I marked each tree that I had already sampled with a ribbon, as to avoid double-counting.

Blog Post 9!

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I was really happy with how my field experiment was designed and carried out. I only needed to change minor things along the way. I decided to make the quadrat bigger and only stick to categorical response variables so I could use the ANOVA statistical framework. It did take me awhile to find the right tide pools because there is variation between the distances from the low-tide mark that the certain pools would be at. I have great appreciation for all ecologist out there because it is not easy developing a theory since the data need to be in replicates but those are not always easy to find. I now understand the time and effort that goes into ecological theory.