Category: Uncategorized

What the source is: This is an unpublished report found online by the professional Biologist and Ecologist Nick Page of Raincoast Applied Ecology. This report, written by an expert in this field, advocates for natural resource management with suggestions for shoreline and vegetation restoration at Iona Beach Regional Park in Richmond, B.C.. The following is a link to the report PDF online.

http://www.raincoastappliedecology.ca/wp-content/uploads/2012/05/Iona-Beach-Vegetation-Management-Report-March-20111.pdf

Source Type Classification: Non-peer reviewed academic material

Documentation supporting classification: By following the flow chart provided by the Module 1 Tutorial: How to Evaluate Sources of Scientific Information, reading the report, and researching the Raincoast Applied Ecology company webpage, it became clear that this report is in fact academic in nature. However, as there was no mention in the Acknowledgements section, and the suggested citation indicated so, it has not undergone peer review or publishing. Additionally, this report contains both in-text citations and a References list, but no methodology was carried out. As such, this report must be classified as non-peer reviewed academic material.

 

References

http://www.raincoastappliedecology.ca/company-profile/

http://www.raincoastappliedecology.ca/wp-content/uploads/2012/05/N-Page-Short-Resume-Jan-2012.pdf

https://barabus.tru.ca/biol3021/evaluating_information.html#1

As part of my sampling strategy, I decided to use the simple random technique in which a random number generator drew numbers from 1-360 and 1-40. The numbers would then determine my compass coordinates. The technique was relatively straightforward and easy to use however, I would often find myself randomly selecting areas that were inaccessible to me. I overcame this barrier by simply redrawing numbers and sampling the ferns which were accessible. Although, instead of redrawing numbers, I could have saved some time by sampling ferns that were as close to the randomly selected coordinates as possible. I was not really surprised by the data I collected as it correlated with my initial hypothesis however, I did not expect there to be such a big difference in moisture levels between the larger growing ferns and the medium sized ferns. I had also expected there to be a slightly larger difference between the pH levels in each sample. This was not the case as each sample had a pH reading of about 8-7.5.

Moving forward, I will continue to use the random sampling technique with slight modifications. First, I will not redraw numbers when I encounter coordinates to areas which I cannot access. Instead, I will sample the closest fern and record how many paces it takes for me to get there. Another modification will be to wipe down the hydrometer after each use, which was something I had overlooked in my data collection. By wiping down the hydrometer I can ensure the hydrometer reading is accurate for the one specific fern. Lastly, I had received a comment on my last blog post to which someone had mentioned that there may be more nutrients in the middle of the forest than in the two other locations I had chosen for my field observations. This was something I had never taken into account and to address this issue, I will be limiting my samples to the middle of the forest instead of the entire forest so that I can limit the amount of confounding variables which may also be affecting fern growth.

1. Which technique had the fastest estimated sampling time?

Systematic sampling had the fasted sampling time as each sample was taken in a linear transect. The estimated sampling time for the systematic technique was 12 hours 35 minutes while the estimated sampling time for the random and haphazard technique took 12 hours 38 minutes and 12 hours 40 minutes respectively. In comparison to the random and haphazard technique, the systematic technique was faster by only 3-5 minutes.

 

2. Compare the percentage error of the different strategies for the two most common and two rarest species

The two most common species was the Eastern Hemlock and Sweet Birch.

% Error for Eastern hemlock

Systematic sampling: 20.0%

Random sampling: 13.1%

Haphazard sampling: 10.0%

% Error for sweet birch

Systematic sampling: 18.3%

Random sampling: 7.8%

Haphazard sampling: 7.8%

 

The two rarest species found were Striped maple and White Pine.

% Error for Striped Maple

Systematic sampling: 8.6%

Random sampling: 90.2%

Haphazard sampling: 66.7%

% Error for White Pine

Systematic sampling: 90.5%

Random sampling: 142.9%

Haphazard sampling: 48.8%

3. Did the accuracy change with species abundance? Was one sampling strategy more accurate than another?

The accuracy did change with species abundance as the two most common species gave some of the lowest calculated percent errors. Haphazard sampling was the most accurate sampling strategy for Eastern hemlock, and Sweet birch with percent errors of 13.1% and 7.8% respectively. It is hard to tell which sampling strategy was more accurate for rare species as systematic sampling gave the lowest percent error for Striped Maple at 8.6% and haphazard sampling gave the lowest percent error for White Pine at 48.8%.

May 13 5:55 pm

Weather: 18 degrees, mostly sunny

I have chosen to study the factors that affect sword fern (Polystichum munitum) growth. From my previous trip, I noticed that sword ferns are densely populated in the middle of the forest and grow sporadically away from the center. This difference in fern density leads me to believe that there are conditions that favor fern growth in the center of the forest as opposed to the outskirts of the forest.

I have chosen 3 different areas to study. Each having similar composition in topsoil but differ in elevation and position.

The first area is close to the northern entrance of the forest at about 20 m elevation. It is heavily shaded by trees and only one fern is seen growing on a mound next to a covered manhole. I have counted 8 fronds on this fern, each of which grows at about less than 2 feet. The surface of this soil seems dry and is covered heavily by sticks, pebbles, and smaller unidentifiable plants growing around the fern.

The second area is at 25 m elevation moving west. This area is the closest to the center of the forest where there is a higher population of sword ferns growing closer together with longer fronds (approximately 4 feet). The area is moderately shaded with few spots where sunlight can peak through. Many of the ferns in this area appear to have spores. The fronds here are fuzzy in appearance and curl inwards at the tips. Soil in this area is composed of mostly sticks and pebbles, though in comparison to the first and third area, the soil looks darker.

The third area is at 30 m elevation. Here, there are only 3 ferns growing about 6 feet away from each other and there is little shade. Frond length is similar to the first area at about 2 feet or less in length with some fronds looking wilted/drooping. The soil here is mostly covered by sticks and there is little vegetation surrounding the ferns.

Patterns I have observed from this trip are that ferns found toward the center of the forest look much healthier and their fronds grow larger in comparison to ferns grown away from the center, which are smaller and have a larger portion of wilting/drooping fronds. Most of the ferns I had observed in all 3 areas grew on a slope or a mound. The soil in the center of the forest is also much darker looking than the other two areas. I am particularly interested in this difference as I suspect the difference in soil properties plays a role in fern growth. In addition to the varying soil properties, I believe slope and light variability also affect how favorable fern growth will be. However, I would like to focus my studies on how soil moisture and pH affects the length at which fronds grow as I believe it would be the easiest factor to study. I hypothesize that the availability of soil moisture will have an effect on the frond length of sword ferns (Polystichum munitum). I predict that as the level of moisture in soil increases, frond length will also increase.

My response variable will be the length at which fern fronds grow and my predictor variable will be the level of soil moisture. The response variable would be continuous, and the predictor variable would be categorical.

The paper I have chosen is titled  “Effects of Bark Beetle-Caused Tree Mortality on Wildlife”. I have identified it as an academic peer-reviewed research paper as it satisfies the following criteria:

The paper is written by Jefferey A. Hicke, an associate professor at the University of Idaho, who specializes in climate change, global environmental change, and Forest disturbance research. The paper is also supplemented by research from the Pacific Wildland Fire Sciences Laboratory and the Pacific Southwest Research Station. There are various in-text citations throughout the article and a bibliography found on pages 9-10. Referee’s are mentioned in the Acknowledgements section but are not credited by name. The Author clearly states a methods section followed by a discussion on the results.

Reference:

Hicke, Jefferey A., et. all. “Effects of Bark Beetle-Caused Tree Mortality on Wildlife.” Forest and Ecology Management. Science Direct. Feb 1 2012. pp 82-90. https://www.firescience.gov/projects/06-2-1-20/supdocs/06-2-1-20_Effects_of_bark_beetle-caused_tree_mortality_on_wildfire.pdf

My initial data collection was after the transect sampling strategy. I marked out my transects and separated the transects into 9 quadrants. In each quadrant I marked the presence of flora. As the examples have previously shown, one is to count the amount of each flora within each transect, but for the purpose of my research, I was merely interested if there is a correlation between the flora that grows further away from the dyke water and the consistency of the soil.

Some difficult aspects I observed throughout my collection was the difficulty in discerning the different types of Poaceae (Grasses). Many seemed quite similar and as the grass within my area was cut short, it was difficult to make out each feature appropriately. I also observed plenty of dried, brown and dead grasses. In my notes, I make note of the dead grass, but unfortunately am not able to tell what type of grass it is. When I return later for more samples, I will attempt to see if there is new growth. Another observation I made was that when one looks closer, the grass has other flora mixed as well. I observed Taraxacum officinale (common dandelion) and Brachythecium frigidum (golden short-capsuled moss).

I believe I will continue with the transect method. It allows me to properly lay out an organized method of measuring instead of randomly sampling. I believe it suits my research study appropriately.