Category: Nancy Elliot

Post 4: Sampling Strategies

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After completing the different sampling techniques and comparing the results, the fastest estimated technique was systematic with an estimated time of 12hr 5mins the next fastest method was haphazard with a sampling time of 12hr 44 minutes. The final and longest sampling method was random with an estimated time of 12hr 55minutes.

 

The most common species sampled was Eastern hemlock, systematically sampling gave a percentage error of -4.2%, randomized sampling gave a percentage error of -16.6% and haphazard sampling gave a percentage error of 27.7%. For the second most common species sweet birch, systematically sampling gave a percentage error of -14.9%, randomized sampling gave a percentage error of 2.8% and haphazard sampling gave a percentage error of -29.1%. When comparing these two data sets for the most common trees we can see that systematically sampling gave the lowest error percentage for eastern hemlock and randomizes sampling gave the lowest percentage for sweet birch.

 

The most least species sampled was White pine, systematically sampling gave a percentage error of 98.8%, randomized sampling gave a percentage error of 98.8% and haphazard sampling gave a percentage error of 98.8%. For the second least common species Striped maple, systematically sampling gave a percentage error of -100%, randomized sampling gave a percentage error of 18.9% and haphazard sampling gave a percentage error of -4.5%. When comparing these two data sets for the least common trees we can see that all sampling methods provide the same results for White pine and haphazard sampling gave the lowest percentage error for Striped maple.

 

Overall as species abundance decreased percentage error of all sampling methods increase dramatically, from this data set randomized sampling appears to be the most effective

Blog Post 3: Ongoing Field Observations

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I plan on studying the amount of paper birch in the area surrounding disturbance in my site. Disturbed areas consists of two large areas in which trees were removed in order to accommodate for housing to be developed. I plan on surveying along the edge of the disturbed area in 5m,10m and 20m intervals( this variable is classified as continuous )  . I predict that due to paper birch being a shade intolerant species it will only be found on the edge of the disturbed area due to the fact that without adequate sunlight it does not thrive. One potential explanatory variable that could affect the growth of paper birch in this area could be percipitation.

Post 2: Source of Scientific information

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A) Jenerette, G. D., and Weijun Shen. “Experimental Landscape Ecology.” Landscape Ecology 27.9 (2012): 1237-48. ProQuest. 5 May 2019 .

B) This paper is Academic, peer-reviewed review material

C)

1. This article was written by two experts indicated by their work at universities

2. This article included in-text citations

3. This article contains a complete bibliography

This article was peer reviewed, which can be determined by examining the acknowledgements sections in which other professionals who had input into the article were thanked. Due to no methods or results this article was deemed to not be research material.

Post 1 Observations

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I have decided to study a forested area adjacent to my rural house in Clearwater BC. The area is about 9.1 hectares in size, located at valley bottom on the base of a slope. The forested area chosen is primarily private land which backs on 3 rural homes with one edge of the area running alongside a large power line corridor. There is also a small subsection of forested area that runs between two private properties.  The forested area is primarily a second growth Douglas fir stand with some Lodge pole pine and Paper birch within the stand. The site was visited from 12:30 to 14:40 on April 30 2019, the weather was mainly sunny with a few scattered clouds.

Figure 1

Three possible questions for this area could be,

  • Is there a difference in tree species/species concentration in the forested area between the cleared homestead and the forested area deeper within the site (See Figure 2)?
  • Do observed American robins nest within the forested area in the same concentration as the homestead area?
  • What are the observable human impacts in the homestead area compared to the forested area?
                                                   Figure 2

Post 3 – Ongoing Field Observations

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Organism– Western Red Cedar (Thuja plicata)

Environmental Gradient– Slope position of the organism (Upper, Mid, Lower/Toe)

Hypothesis

The recent logging has intensified the environmental stressors (drought and intense sun exposure) causing the existing Cedar to thrive under their new conditions.  I predict that, if BC experiences another heat wave, the onsite Cedar trees will weaken or die completely.

The Cedar on the lower slopes that have adjacent mature trees along their southern boundary will have the highest probability of maintaining their established presence.

Response Variable– Stress indicators expressed in

the tree (Continuous).

Explanatory Variable– Weather (Temperature, cloud cover) (Continuous).

It was this small patch of Cedar trees that caught my attention. The Cedar appeared to be healthier and more abundant, in this particular area, than the Douglas fir or western larch trees.  This area has high exposure to the sun with shallow soils, which makes it prone to drought. This patch of Cedar appeared to have been outperforming the fir and larch prior to the harvesting of the adjacent stand that occurred in the fall of 2018.

Blog Post 5: Design Reflections

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The collection of my initial data for my research project did prove to be a little challenging and I quickly realized some of the mistakes that I made. I was using a point count sample method in my location to count bird presence with ambient temperature as the predictor variable. However the sampling area was too large and therefore not the most effective way to sample. I used a grassed backyard area around 24 feet x 30 feet as the location which proved to be too confusing as I didn’t know whether to include birds on the fence. Also with birds flying in and through the area I wasn’t sure if I was double counting them. Therefore sometimes I counted them and sometimes I didn’t as I wasn’t sure if I had already. It was difficult to know whether the birds I was counting were ones that had already been counted. In hindsight I should have used a bird feeder on one of the trees and counted bird activity at the feeder.
Secondly, I also realized that my hypothesis was not detailed enough. My focus initially was hypothesizing that bird activity would be increased with warmer spring temperatures above 12.5 degrees C but I should have used a temperature range of 10 – 15 degrees C to hypothesize that temperatures outside of these ranges would have decreased bird activity because I needed to include temperatures both above and below the range as bird activity may be diminished in extreme temperatures on either end. I also should have done my testing in the morning when temperatures were cooler but due to time constraints I tested in the afternoon when temperatures were warmer and therefore I mostly had temperatures above my hypothesis. In hindsight I should have tested early in the morning when the temperatures weren’t as hot.
The results that surprised me were that the bird activity was strongest on the coolest day. I had hypothesized that birds prefer warmer weather but in fact based on the initial results they seem to prefer cooler weather.
When I test again, I plan to adjust my point count method by using the bird feeder. This will make it easier to count the birds, eliminate confusion and I feel it will be a more effective method. I also plan to conduct the research in the morning when temperatures will be cooler and slightly more variable (before the temperatures are at the height of the day). This will ensure I get enough days both above, below and within the range of my hypothesis. I also need to clarify my hypothesis before I complete the research project as it is too vague and doesn’t account for hot weather.

Blog post #4 Sampling strategies

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After trying out the sample methods tutorial I was able to gain some insight in to the pros and cons of each sample method. Haphazard sampling was the fastest method, but as I could see when comparing accuracy it was low preforming in that area. This makes sense since I chose my sections based on areas with high tree density. The one that took the longest was the systematic survey this seems accurate since I chose to check every 7th grid. This created extra work and more grids were surveyed then the others types.

 

The percent error of the two most common trees based on the three sampling strategies the random sampling was the most accurate, for the two most common trees, and the haphazard was the least accurate.As for the least populous trees only the random sampling actually accounted for both trees in the survey. The haphazard sample picked up neither, and systemic survey only found one of the two.

 

From the result over view it appears that the random sample survey did a more accurate job that the other two types. In terms of hours spent on surveys it was in the middle. This is important to consider when I am  looking at collecting my data for my project. More time invested in to systematic survey with a increased sample size my not give you the most accurate results. On the other hand random samples fall to chance and a large are of the survey grid could be missed. This is something to consider when looking at the randomly chosen quadrants and collecting your data.

 

Haphazard while convenient and more efficient and economical has to be critiqued  for a large bias in selecting quadrants or zones for surveying, or risk an invalid data set and wasted time.

Post 1 Observations

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I chose to observe a forest ecosystem that has recently been harvested.

20-04-2019 – 1200pm – 1430pm

Sunny and cool 12 degrees Celsius

Geographic Location – Hills, BC (UTM Ref: 462075 E 5553782N) West Kootenays

Gross Area – 53.8ha

Harvested Area – 34.1ha (Harvested in the fall of 2018)

Wildlife Retention Area – 10.3ha (Retention areas were noted to have high-value riparian areas)

Deferred Area – 7.6ha (small opening, immature forests) harvested in the year 2000. Planted in 2002.

Ecological Description

  • Biogeoclimatic Ecosystem Classification (BEC) – Interior Cedar Hemlock (ICHmw2) zone
  • A complex site with four site series
  • Mid-lower slope
  • Hummocky terrain
  • Slope range 3% – short pitches of 55%
  • Leading Vegetation – Too early in the season to identify any early serial species established.

Observations (Stations (1-1 -1-5) are associated with a KMZ file from Avenza Maps)

Questions:

  1. What native plant species will establish on the heavily disturbed soil from the rehabbed road (Hills 4200)?

  1. Numerous Pine Siskins were noted within the deferred area (12-year-old plantation). What habitat value or features do advanced plantations have? Where would birds nest in immature forests?
  2. After the mature timber harvested, what new limiting factors are introduced to the adjacent plantations and understory trees?

Post 2: Sources of Scientific Information

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A)

Lindgren, P., Ransome, D., Sullivan, D., Sullivan, T., (2009). Stand structure and the abundance and diversity of plants and small mammals in natural and intensively managed forests. Forest Ecology and Management, 258, pp.S127-S141.  Retrieved From: https://www-sciencedirect-com.ezproxy.tru.ca/science/article/pii/S0378112709003983

B)

Academic peer-reviewed research material.

C)

  1. The article was written by the Department of Forest Sciences, Faculty of Forestry.
  2. The article included in-text citations.
  3. The article contains a bibliography (listing all sources used).

I assumed that because the article was published in the journal Forest Ecology and Management that it would have had to be peer-reviewed.

The article reports the results of a field study and contains “methods” and “results”

 

 

 

Blog Post 4: Sampling Strategies

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In the Virtual Forest tutorial, of the three sampling strategies that I used, the haphazard or subjective sampling technique had the fastest estimated sampling time at 4 hours and 26 minutes, followed by random sampling at 4 hours and 54 minutes and then systematic sampling along a topographic gradient at 12 hours and 37 minutes.

Of the two most common species, Eastern Hemlock  (EH) and Sweet Birch (SB), the systematic sampling had a percentage error of -22% for EH and -14.9% for SB. With random sampling, the percentage error was 2.5% for EH and 21% for SB. With haphazard or subjective sampling, the percentage error was 32% for EH and 80% for SB. Therefore for these two common species, it would appear that random sampling had the lowest percentage error for EH and systematic sampling had the lowest percentage error for SB. If you average the percentage error of the two sample techniques, random sampling presented the least amount of percentage error for the common species of trees.

Of the two rarest species, Striped Maple (SM) and White Pine (WP), the percentage error for the systematic sampling technique was 128% and -100% respectively. Random sampling had a percentage error of 25% for SM and -100% for WP. For haphazard or subjective sampling, the percentage error for SM was 141% and -100%. All three sampling techniques failed to record any occurrences of White Pine trees. Random sampling had the smallest percentage error for SM 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 most rare species of White Pine which was undetected in all methods. The most abundant species were more accurate although percentage error was high amongst all recorded species.

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. However, for the Red Maple, a more rare tree, the systematic sampling using a topographic gradient method was the most effective with only a 0.9% percentage error. However, this method took the longest so may not be the most feasible method to use in this case. For the Yellow Birch tree, a more common tree, the haphazard or subjective sampling method had the least percentage error at only 3.7%. This method was the fastest method but it could pose problems of bias amongst the researcher in the field.