Post Three: Ongoing Field Observations: Cates Park

The organism I would like to study is Tsuga heterophyllum and their growth distribution associated with nurse logs, a biological attribute.

After observing nurse logs throughout Cates Park / Whey-Ah-Wichen during previous visits, noting that Tsuga heterophyllum are the predominate trees to grow out of long-ago logged Thuja plicata, I grew curious to their habits, growing regions, need for sunlight or idea soil conditions to thrive. Because Cates Park is situated on a point that has varying degrees of sunlight and wind, I chose four gradients to observe distribution and abundance of local species: the west and east sides of the park, and both through the canopy on trail, and on the beach for the marine-terrestrial interface.

  1. Southest side of Cates Park, from west path to pier, along beach
  2. Northest side of park, from west path to pier, along trail
  3. Southeast side of Cates Park, from stairs to small point, along beach
  4. Northeast side of park, from stairs to small point, along trail

Southwest

Northwest

Southeast

Northeast

Tsuga heterophyllum

(Western hemlock)

4

19

2 on nurse log

4

21

3 on nurse log

Thuja plicata

(Western red cedar)

18

21

6

5

1 on nurse log

Picea sitchensis

(Sitka spruce)

1

0

0

0

Pseudotsuga menziesii

(Douglas fir)

0

3

0

1

Unidentified deciduous tree (either Alnus rubra (Red alder), Populus trichocarpa (Black cottonwood) or Acer macrophyllum (Broadleaf maple))

10

0

37

35

Hypothesis: Western Hemlock (Tsuga heterophyllum) are more common in cleared forest areas because they are better suited to such disturbances.

Prediction: If Tsuga heterophyllum trees are better suited to take advantage of open forest canopy following a disturbance, they will grow more frequently in areas that have experienced harvesting

The predictor variable is are the amount of canopy cover and the type of substrate, either nurse log or forest floor. These are both categorical variabilities.  The response variable is also categorical, as the relative abundance of hemlocks on nurse logs compared with forest plots.

This natural experimental design is a Tabular study. Sample units will be an equal number of haphazardly selected nurse logs, in order to reach their location, and simple randomly selected forest plots. Nurse logs and forest plots will analyzed in each region of the park: both east and west of the park’s central point, and north and south to account for the gradient away from the ocean.

Blog Post 5: Design Reflections

In designing a sampling strategy, time was of the essence.  I began the course in October when the vegetation had full foliage but I knew that within the next week or two, fall would begin, and the plants would begin to lose their foliage or die off for the winter.  I was able to go out for a couple of successive days to observe the environment and decide on a topic and strategy.  In deciding to investigate light levels with vegetation coverage, I realized that the most prudent approach would be to quickly obtain a photographic record of the study area and analyze the vegetation cover from the photographs rather than studying the plants in-situ.  This approach utilizes computer data processing tools with methodologies widely used in Remote Sensing studies and utilizing recognized academic software, giving it credence for a scientific inquiry.

I selected the starting point of the path (where it branched off another path segment) and recorded data at approximately 10m intervals.  Capturing the data and photos at each interval went quickly so rather than random sampling, I collected data samples along the entire transect and I can either use the complete data set or randomly select points along the transect and query the data collection at these points.  Again, a measure of expediency was directing my work because I realized that if there was a data deficit, I would not be able to collect the data again during the course of this study.

I would have preferred to construct an apparatus to ensure consistent height and angles for the camera but I compensated for this by using a highly coloured measuring stick in each photo where the spatial integrity can be confirmed.  Additionally, since the same colours are available in each photo, I can calibrate the images’ colour balance and luminosity in much the same manner as NASA used with the Mars rover images.

I would have preferred to use a laboratory-grade light meter whose calibration could be independently certified.  However, this was not possible due to the cost of such equipment, so I calibrated my meter statistically to ensure that its tolerances were of an acceptable level for the study.  Also, I am not actually interested in the specific Lux values from the meter, but rather the relative light readings from one station to another.  As such, it was only to necessary to confirm the light meter’s response relatively across the spectrum and not to specific laboratory standards.  In other words, if the same level of light gives the same results on separate readings, I am able to consider the instrument calibrated for the purposes of this study.

I did the image analysis later at my home using the ImageJ scientific image analysis software.  Ideally, I would have liked to write a macro to bulk process and analyze the images automatically but the complexity of this task was too much for the scope of this project.  Therefore, I used personal judgement in some of the image processing which unfortunately could introduce bias or error but I endeavoured to follow the level of precision in the analysis and I believe that any discrepancies in analyses are statistically insignificant and do not affect the overall analysis.

Blog Post 4: Sampling Strategies

I tried to incorporate as many of the sampling strategies of the virtual forest tutorial as possible.  However, due to the nature of my study some do not fit into the context of my investigation.  Collecting data along the study transect is a systematic sampling.  I collected data at all of the stations along the transect and could now apply a random aspect to the study by querying random samples from the complete data set.  At each interval, I conducted an Area-sampling by analyzing data from a square metre sample.   I am not concerned with specific species so the dispersion, succession and diversity sampling is not relevant.  There are topographical and edaphic factors which undoubtedly impact the ecology of the area but they are outside the scope of my study.

Blog Post 3: Ongoing Field Observations

For my field study, I am going to examine whether there is a correlation between available light in a forest and the amount of ground cover in continuously disturbed areas.

Since the vegetation along the footpath in the study area undergoes continual but somewhat random disturbance from pedestrian traffic I am wondering if the amount of available light is the key resource that determines whether the forest floor revegetates after it is trampled by humans and pets.

My field observations consist of light meter readings at each interval and photographs of ground cover along a gradient extending perpendicular to the footpath.  The photographs will be digitally process to determine the percentage of ground cover at each interval.

Therefore, my null hypothesis is:

There is no connection between available light levels in the forest and the percentage of forest floor covered by plant leaves.

I predict that there will be a correlation between available light and ground cover.

My explanatory variable is Light level (measured in Lux) and my response variable will be the percentage of ground cover in each delineated area (measured in percentage).

Blog Post 2: Sources of Scientific Information

The resource Climate is a stronger driver of tree and forest growth rates than soil and disturbance (https://www.jstor.org/stable/41058855) is a peer-reviewed report published in the British Journal of Ecology.  It is co-authored by eleven ecology academics from organizations with excellent credentials.  Since this was a study conducted by numerous professionals, published in a leading journal, peer-reviewed, and based on extensive primary research, I found that this resource to be a top-quality and reliable scientific source.  Its conclusions are important in the age of climate change.  The one possible drawback of this paper is that it was published in 2011 and while still presenting valid conclusions, there may be newer resources incorporating more recent data.

Post 1 – Observations at Jerseyville Park in Hamilton, ON

My intended study area is a four hundred metre length of the Spring Valley Trail which is located in Jerseryville Park in the City of Hamilton and part of a conservation area administered by the City of Hamilton and the Dundas Valley Conservation Area.  The study area is part of an irregularly shaped, mostly-contiguous protected area covering over 1200 hectares of conservation area and approximately 1500 hectares of private and crown land.  The conservation area has numerous streams and waterfalls and is comprised mostly of forests with small meadows which are artifacts of previous agricultural activities and human habitation.

Soil in the area was not studied but probably ranges from clayey to clayey-loam as it was once a riverbed and this would be consistent with other similar parcels in the general vicinity.

The study area runs linearly, approximately north-south, along a formal unpaved (municipally maintained) footpath called the Spring Valley Trail which connects to numerous other trails in the protected area.  The study area is bounded on the east side by Sulphur Creek which runs roughly parallel to the footpath and an irregularly shaped ridge line running roughly parallel to the study area to the west.  The height of the ridge is approximately 10-20 metres along its course creating a defined boundary to the study area ecosystem.  The study area itself has undergone significant human disturbance in the past and as a public-use facility, continues to undergo significant disturbance from high pedestrian and bicycle usage.

The actual study area is the disturbed area running adjacent to the public footpath.  Even to an unqualified observer, the difference in vegetation is apparent along a gradient from the pathway to the forest along the ridge.  The vegetation in the study areas appears to be mostly invasive species of which I am having trouble accurately identifying.  Queries to online forums have yielded only a common-catchall term of “hogweed” which apparently is a common term for unidentified low-value plants.  Dispersed throughout the study area are maple saplings which generally do not have the opportunity to mature due to human disturbance and the prevalence of herbivores (deer) in the area.

While walking through the area on numerous prior occasions, the difference in vegetation adjacent to the trail from the forest floor became obvious.  I also noted that some areas along the trail are much more sparsely vegetated and I wondered why.  Some possible questions regarding the observed phenomena are:

Is there a correlation between amount of available light and ground cover?

Are variations in ground cover due to recurring disturbances?

Are variations in ground cover due to topographical influences?

I would like to explore the available light aspect for my study.

The study area was visited on several occasions in early October to reconnoiter the area and evaluate specific study plots.  The main study visit was conducted on October 11, 2018 between 2-3PM.  The weather was sunny with very little cloud cover, 23°C, with very little or no wind.  Data collection consisted of taking photographs and measurements.  Although the floor was partially covered, it appears that the leaf litter was not due to seasonal autumn activities as most trees and plants had not shed their leaves giving the opportunity for plant identification.

Blog Post 4: Sampling Strategies

1. Which technique had the fastest estimated sampling time?

The technique with the fastest sampling times was systematic with 12 hours and 35 minutes.

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

Common / Rare Sampling Technique % Error
Common (Eastern Hemlock) Random 28.6%
Haphazard 20.6%
Systematic 17.4%
Common (Sweet Birch) Random 4.3%
Haphazard 4.3%
Systematic 26.0%
Rare (White Pine) Random 197.6%
Haphazard 48.8%
Systematic 138.1%
Rare (Red Maple) Random 8.9%
Haphazard 19.2%
Systematic 14.4%

3. Was one sampling strategy more accurate than another?

Based on the information presented in the above table, no single sampling technique was more accurate than another.

Blog Post 2

The source is “Controlling Cattail Invasion in Sedge/Grass Meadows” and can be found here: https://link-springer-com.ezproxy.tru.ca/content/pdf/10.1007%2Fs13157-017-0971-8.pdf . This source is an academic, peer-reviewed research paper. Since the author is affiliated with a college in New York I know that the paper is written by an expert in the field. This along with the fact that the paper contains in-text citations and a bibliography I know that it is academic material. In the acknowledgments, two anonymous reviewers are thanked which makes this peer-reviewed academic material. And the paper reports results from a field or lab study completed by the authors (contains methods and results section) which overall, makes this academic, peer-reviewed research material.

Blog Post 6: Data Collection

Blog Post 6: Data Collection

The field data collections at the View Royal Park have been occurring over multiple days at various times of the day. Squirrel abundance in response to dog walking has been measured. Data collection started on Saturday, February 23, 2019, while the weather was clear but chilly. following collections happened on Monday, Tuesday and Wednesday at 10:00, 1330, and 0700 respectively. The weather was clear and windy at approximately 4-5 degrees Celsius.

The predictive variable, dogs, will be organized into intervals of 0-1, 2-4 and 5+ dogs present at the park. The number of squirrels observed within these intervals will be measured and analyzed.

Each interval will be replicated at least 4 times. therefore data collection will continue until each interval (0-1, 2-4 and 5+ dogs at the park) has been noted and squirrel abundance has been measured 4 times within the intervals.

The most difficult part of implementing the sample design is the uncertainty of the number of dogs present at the park at a time. Without the ability to manipulate the number of dogs present data collection must be done over many days and times of the day.

Over four days of data collection patterns appear to support the hypothesis that squirrel abundance declines in presence of dogs as they pose a threat of predation. Although, The outlying intervals of 0-1 and 5+ have much higher replicate data than the median interval of 2-4. Number of humans without dogs in the park have also been collected as a control to show that the decrease in squirrels is not due to humans alone. The number of humans has shown no effect of squirrel abundance so far in data collection.

 

 

Blog Post 5: Design Reflections

Blog Post 5,

After reading the Blair article, which is very similar to my experiment and data collection, I realized how my sampling strategy was correct however, I could have replicated my collection not only in time but also in space by observing from different areas in my sample space. There were no difficulties in implementing my sampling strategy, I chose a place close to my home which was easy to frequent as often as I needed. I also picked a species to observe which is easy to spot and count. The results were also not surprising, as my hypothesis was supported by the data. The squirrels are less abundant in areas with high numbers of predator species like dogs. I will continue to collect data the way I have but I will also enter the park from the other entrance, walking into my sample space from another way.