Category: Percy Hebert

Blog Post 1 – Observations

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Although I had a different location planned, I noticed the amount of life in the courtyard at TRU so I decided to switch my location. Therefore, the area I chose to observe is the courtyard on the TRU campus between Old Main, the library and the Clock Tower. The area is approximately 1 acre (measured with the scale on google maps), once you account for the cement walkways and buildings on it. The topography is very slight hills, filled with thick grass. There are human planted flower beds which include a variety of flowers and ornamental grasses. There are also a handful of trees left in the courtyard.

I first visited this courtyard in respect to this course on September 13th, 2017 at 10:36 am. It was around 20 degrees celsius. The sun was shining and the sky was clear however the was a slight wind.

In my field journal (click – ecology) I took notes on many bees and insects I saw. My first question would be, can this type of urban ecosystem support other larger organisms? Secondly, what is essential to provide a habitat in an urban environment? (e.g., is just a grass lawn enough, are flowers essential, are trees needed?). Lastly, what would be the main food source for these other organisms, if they are present? Aside from the pollen in the flowers for the bees.

Blog Post 4: Sampling Strategies

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In the virtual forest tutorial, the most efficient sampling method in terms of time-spent sampling was systematic sampling as seen in the results below, however the overall difference is marginal:

  • Systematic – 12 hours, 5 minutes
  • Random – 12 hours, 46 minutes
  • Haphazard – 12 hours, 29 minutes

Percent Error calculations for top two most common and most rare species:

Most Common Species Most Rare Species
Eastern Hemlock

(RF = 33.8%)

 Sweet Birch

(RF = 19.9%)

 Striped Maple

(RF = 2.8%)

 White Pine

(RF = 1.9%)
Systematic 4.23% 14.89% 100% 98.80%
Random 10.30% 25.53% 28.57% 50%
Haphazard 0.68% 17.02% 42.85% 1.19%

*RF = Relative Frequency

For the two most common species combined the most accurate sample strategy appears to be systematic sampling (i.e.: lowest percent error calculations for both Eastern hemlock and sweet birch at 4.23% and 14.89% respectively).  It should be noted that if just examining the single most common species that haphazard sampling appears to be the most accurate with Eastern hemlock receiving a remarkably low percent error of 0.68%, this is likely due to its high relative frequency in the forest. However, I would not conclude that haphazard is the best sampling strategy for common species in general since when examining the the top two most common species together systematic sampling appears to be the most accurate.

For the two most rare species combined the most accurate sampling strategy appears to be random sampling on average with striped maple having a percent error of 28.57% and white pine a percent error of 50%. Again it should be noted that haphazard sampling produced a remarkably low percent error for white pine at 1.19% but this accuracy was not reflected in the second least common species, striped maple. Overall haphazard sampling as the most accurate strategy for rare species makes very little sense since species with a very low relative frequency are statistically unlikely to be found identified with this sampling strategy and actually haphazardly sampling the correct plots to get such a low percent error repeatedly is very unlikely . That is why I would not conclude that haphazard sampling it is the best sampling strategy despite this low percent error.

Overall the accuracy declined with more rare species except for the outlier of white pine with the haphazard sampling strategy.

In total 7 species were captured with all species being captured in each sampling strategy expect for stripped maple which was not captured during the systematic sampling technique. As a result I would say that 24 samples were enough to capture the number of species in this community since almost all species were captured during all sampling techniques. However, I don’t think it was accurate enough to capture the abundance of species in each community as is shown in the percent error for white pine whose percent error varies widely from 1.19% to 50% to 98.8%.

 

Blog Post 3: Ongoing Field Observations

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During my initial field visit to Surrey Bend Regional Park I noticed that there appeared to be more bird activity (pattern) within the Wetland Complex area then in the Entrance Area. This was despite the fact that both of these locations appear superficially similar in that they are dominated primarily by grass species, and represent open landscapes. I am interested in examining how the composition of major habitat features influences bird species presence, therefore the organism I have chosen to study is the bird species present within these two habitats.

The site gradient begins at the parking lot and large mowed fields at the south end of the Entrance Area and runs approximately 400m to the north through the site. At this point it transitions into the Wetland Complex. I developed four observation locations along the gradient, two in the Entrance Area and two in the Wetland Complex. I used a systematic sampling strategy to randomly select the first observation point in each habitat along the trail that runs through them (acting as a transect). This was accomplished by using a random number generator to generate a point between 0m and 400m. The second observation point was placed 200m away from the first along the trail as this is the minimum distance required for independence between bird survey sites as outlined by the Resource Inventory Committee Standards. The sampling unit at each observation location is a point count survey where all birds seen and heard within a 50m radius of the observation point are recorded during a 5-minute period.

Entrance Area Point Count Survey Sites

 

Wetland Complex Point County Survey Sites

 After setting up these observation sites I completed my first round of official observations. The results of one observation in each habitat site can be seen in the data sheets below.

EA1 Point Count Survey Results
WC2 Point County Survey Results

During point county survey bird names are recorded in standardized acronyms to accommodate quick data recording, a list of acronyms can be found here:  https://www.birdpop.org/docs/misc/Alpha_codes_eng.pdf

Based on these more formal observations, my hypothesis is that grass species composition, and habitat features present within a site will influence bird species presence.

I predict that there will be a higher diversity of bird species present within the Wetland Complex where there are less anthropogenic influences. In addition, I predict that the bird species found within the Entrance Area will contain more generalist species whereas the bird species identified in the Wetland Complex will contain more specialist species.

The response variable in this observational study will be the presence/absence of bird species (categorical variable) present within each habitat.

The potential explanatory variables will include the percent cover (continuous variable) of the following coarse scale habitat features:

  • Agricultural Grass Mix
  • Wetland Grass Mix
  • Gravel/Mowed Grass (i.e.: cleared land)
  • Buildings
  • Open Water
  • Shrubs/Young Forest

 

 

 

 

 

 

 

 

 

 

Blog Post 2: Sources of Scientific Information

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On my bookshelf at work we have a number of volumes from Restoration Ecology – The Journal of the Society for Ecological Restoration. Within volume 20, Number 5, September 2012 I chose the following research article: How does the Restoration of Native Canopy Affect Understory Vegetation Composition? Evidence from Riparian Communities of the Hunter Valley Australia.

This manuscript classifies as academic, peer-reviewed research material for the following reasons:

The source is academic material because:

  • It was written by experts in the field. The authors of the article are Carla J. Harris1, Michelle R. Leishman1, Kristie Fryirs2, and Garreth Kyle1,3 and are members of the 1Department of Biological Science at Macquarie University, the 2Department of Environment and Geography at Macquarie University, or the 3Arthur Rylah Institute for Environmental Research.
  • There are in-text citations throughout the document.
  • There is a Literature Cited section.

It was peer-reviewed by two anonymous referees as indicated in the “Acknowledgements” section.

It is research material as indicated by both a “Methods” and a “Results” section within the manuscript.

Reference:

Harris, C.J., M.R. Leishman, K. Fryirs, and G. Kyle. 2012. How does the restoration of native canopy   affect understory vegetation composition? evidence from riparian communities of the hunter valley Australia. Restoration Ecology 20:584-592.

Blog Post 1: Observations

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Field Research Project – Site Visit #1

  • Recorder: Brian Titaro
  • Location: Surrey Bend Regional Park, Surrey, British Columbia
  • Visit Date: 09-06-2017
  • Visit Time: 14:45
  • Weather: Smokey skies from forest fires, no wind, 25oC

My field research project location will be Surrey Bend Regional Park (SBRP) located in Surrey, British Columbia on the south shore of the Fraser River. Surrey Bend is managed by the Metro Vancouver Regional District and is 348 hectares in size. SBRP consists of 5km un-dyked shoreline, medium bench floodplain ecosystems, and the third largest relatively undisturbed bog in the region. Nearly 80% of the park is closed to public access and within the accessible area there are three main ecological communities in which I will perform my study.

Surrey Bend Regional Park

The first is the Entrance Area (49.195301oo  N, 122.728121o W) characterized by mowed grass fields, gravel parking lots, and old field habitat. The dominate vegetation includes Achillea millefolium, Lupinus spp., Secale cereal, Anaphalis margaritacea, and Grindelia stricta and ornamental Acer spp.

Entrance Area

The second site is an open Wetland Complex (49.198919o N, 122.730074o W ) with man-made sloughs built by the Transportation Investment Corporation (TICorp) as a compensation projection for the fisheries damage that took place during the construction of the Port Mann Bridge. The wetlands are dominated by Phalaris arundinacea and Spiraea douglasii, interspersed with small Picea sitchensis, Rubus spectabilis, and Alnus rubra that were planted as a re-vegetation project.

Wetland Complex

The third site is a dense, closed canopy Riparian Forest along the Fraser River (49.199970o N, 122.727928o W). The dominate tree species are Populus trichocarpa, Picea sitchensis and Alnus rubra, with Symphoricarpos albus, Rubus spectabilis, and Acer circinatum making up the shrub layer, and Rubus ursinus covering the forest floor.

Riparian Forest

After visiting the site, the topics I’m interested in further researching would be:

  1. Does the bird species diversity change between the three ecosystems listed above?
  2. What fish species are using the recently constructed sloughs and are there features within the sloughs to which they are attracted?
  3. Which of the three ecosystems listed above hosts the largest diversity of non-native, invasive plant species?

Blog Post 7: Theoretical Perspectives

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Blog Post 7: Theoretical Perspectives

Since my last blog post I have completely changed by study focus and sampling design. For my new project I will be looking at how sun exposure effects the growth of Fescue grass (Festuca L.). The study area for this project is the same as the previous study, which is the Student Services Building (SSB) courtyard at Durham College (DC) located in Oshawa, Ontario.

Seeing that my study aims to examine factors influencing the growth of grass, some ecological processes that my study may touch on may include photosynthesis, soil composition and rainfall. There are many factors and processes that effect the growth of grass and sun exposure is only one factor to consider. During my observations and data collection so far, the effects of sun exposure do have significant impact on the growth of fescue grass.

Three key words that could be used to help identify this work could include: Festuca L., sun exposure, grass growth

Field Research Reflections

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As I am currently in the midst of assembling my final report there seems to be no better time to reflect on the process that has brought me to this point. It has been my first experience doing any ecology in the field and I have certainly gained a lot of respect for the mental and physical rigour that must go into even the simplest of experiments. Mine, for example, is extremely simple in comparison to the level of experiments being done by individuals my age or younger, and it has taken a great deal of time and energy to ensure that it was carried out to the best of my ability.

I’m amazed at the complexity involved in carrying out a basic experiment, as randomization and elimination of confounding variables can require much more work than I initially would have thought. The more one thinks about an experiment it seems the more one thinks up ways it may be confounded, so it is essential to pick a few important factors right from the start, and ensure they are accounted for before data is collected, otherwise a whole day (or more) can be wasted. I learned this first hand after my first day of collections, when I discovered that there was a better way to measure my independent variable (light), and also forgot to account for things like weather and time of day. Moving forward I will try to be much more rigorous in my study design before stepping out into the field, should I undertake a similar endeavour in the future.

The hardest part for me was getting started. Finding a pattern worth examining was tricky for me, and I wish I was able to notice the asymmetry of branches sooner, as it took me several months to even gain this inspiration, it was valuable time that I could have spent on better designing/carrying out my study etc.

I am also realizing more and more the value of a strong statistical background in this field. Many of the papers I scanned used statistical analyses that I’ve long since forgotten (or never knew) the meaning of, and it would be worthwhile on gaining a stronger foundation in this area.

One point worth noting is that carrying out my experiment on my own has been both a blessing and a curse; while I have had complete control over the experiment it can a lot of work to perform on one’s own, and especially as a first timer, the learning curve felt steep (which is good!). When I now read academic papers with only one author I am now often impressed by the level of work they have achieved with little help, whereas before I never gave the number of authors much of a thought.

Overall, a great learning experience, which still requires many more hours of my attention in assembling the final report. Thanks for reading.

Blog Post 6: Data Collection

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At this point in my data collection I have collected 12 replicate samples. I am almost half way done my 30 sample collection. At this point I have not had any trouble implementing my sampling design. Upon initial collection my sampling was lining up with my hypothesis, the buds were continuing to produce with the increasing temperatures. However this past week the number of buds has drastically decreased. My initial assumption is this is due to the time of year. Typically the growth of trees slows as we move into summer and away from spring. With this new trend I do not believe my initial hypothesis will be correct as I don’t foresee temperature being the cause of bud growth, more the change in season.

Blog Post 5: Design Reflections

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The initial sample collection went well and I had no difficulties implementing the sample strategy. The data I collected was very surprising as two of the four trees had buds and those trees were at opposite ends of the courtyard. I expected to collect similar data from trees at similar point in the courtyard, where that was not the case. Tree four had buds which is at the highest point in the courtyard and tree three had buds which is at the lowest point. I plan to continue sampling the trees based on the same approach I used in my initial data collection. Sample collection was easy and I feel like it was effective use of my time.

Blog Post 4: Sampling Strategies

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In the virtual forest tutorial I used three different sampling techniques. All samples were collected using area mapping. The first was systematic sampling along a transect, the second was systematic sampling using random quadrant points and the third was haphazard sampling. Twenty-four samples were collected in each sampling.

Systematic sampling along the transect was the most efficient method and used the last amount of time. Densities were commonly higher than the actual densities; with transect sampling being the most accurate.

Transect sampling had the lowest percentage error for common and uncommon tree types. Haphazard sampling had the greatest error for uncommon tree types and random sampling had the greatest error for common tree types.

Twenty-four samples appears to be enough for transect sampling but not for the other two sampling methods.