Recent Posts

Fall Flowers

TRU Open Learning 1 Comment

User:  | Open Learning Faculty Member: 

I am planning on using the Guerin Creek area of the Thompson Rivers University campus in Kamloops, BC (see figure 1). I explored this region and found that it varies drastically in access to water sources, and I thought I could examine how the vegetation and pollinators differ as the proximity to the creek varies. Kamloops is a desert climate and it is currently the end of summer/beginning of fall. As I explored my area of interest I noticed all of these brilliant yellow flowers blooming. Rabbitbrush is a late flowering plant that supports a lot of pollinators through the fall season. They bloom from September-October, so I thought they could be the perfect topic for my field experiment. There are also wild yellow sunflowers blooming, and from my research so far it seems like they actually might be from the same genus as the rabbitbrush.

Figure 1. Thompson Rivers University and Guerin Creek in Kamloops, BC. The highlighted areas are those I will consider during my field experiment.

The vegetation includes sagebrush, wildflowers, and drought resistant grasses. It is a creek, so there is a fairly steep elevation grade difference as the proximity to the creek changes (see figure 2). I am thinking I could compare both vegetation at higher elevations and lower elevations both near water sources and farther from water sources. In the map, you can see the blue region near the creek, and the pink area further from the creek. I will look at blooming vegetation and pollinators in both areas.

Figure 2. A freehand diagram of the relative election change near Guerin Creek.

I will keep my observations during the day, between 10-2 and ensure that it isn’t too windy for the pollinators to collect and fly. I will also only observe on days where it isn’t overcast or raining.

A few questions about this area:

  1. How do the number and type of rabbitbrush pollinators vary closer to and farther from water sources?
  2. How do the pollinator types vary between the wild sunflowers and the rabbitbrush?
  3. How does elevation affect the pollinators of rabbitbrush?

Blog Post 4: Sampling Strategies

TRU Open Learning Leave a comment

User:  | Open Learning Faculty Member: 

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

TRU Open Learning Leave a comment

User:  | Open Learning Faculty Member: 

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

 

 

 

 

 

 

 

 

 

 

Post 9: Field Research Reflection

TRU Open Learning 1 Comment

User:  | Open Learning Faculty Member: 

Prior to physically conducting my field research, I actually underestimated how tough it is to put study designs into actions. I assumed that everything would go as planned, and it would not be challenging, but I was proven wrong. This experience has enlightened me on how challenging it is to come up with a hypothesis and design an experiment in order to determine how accurate the hypothesis is. Although it took more time than I expected, I did not have much issues implementing my design. Prior to beginning my data collection, I thought carefully about the sampling strategy and method that would best suit my objective, and then I made sure that I was confortable actually carrying out the method. I had to familiarize myself with the study sites, and the numerous species found at each study site. One challenge that I faced was interpreting and making sense of my results. I found this challenging because I know that some of the methods that I used were somewhat subjective, therefore adding some bias to the results, and leaving me unsure of whether or not my results were appropriate/acceptable.

Upon completion of my study, if I were to make one change, it would be to collect data throughout different seasons. This will allow for a more accurate depiction of how species distribution is actually impacted by climate. Engaging in the practice of ecology has definitely altered my appreciation for how ecological theory is developed. Unlike other ecology courses that I have taken, this course really helped me understand the implementation of research projects and how it is conducted. I was able to learn so much information and retain that information as this final project allowed me to apply the skills that I learned throughout the course. After taking this course, I now realize how difficult it is to design and actually conduct a study. I definitely appreciate the work that individuals do in this field, as I felt it was challenging even to conduct a minor experiment on my own.

Post 8: Tables and Graphs

TRU Open Learning Leave a comment

User:  | Open Learning Faculty Member: 

Upon collection of my data, summarizing the information obtained was not a challenging task. However, what I did find challenging was organizing the data that I obtained into a manner that could be easily read and understood by others. A 1m2 quadrat was used to measure percentage coverage, a 0.5m2 quadrat was used to measure the abundance of the species and a 0.25m2 quadrat was used to measure absence/presence. Each of the three quadrats was placed randomly five times at each site, and data was collected. Overall, my data did not reveal anything too surprising. Although the results obtained supported my hypothesis and predictions to some extent, upon analysis of the data collected, I do realize that other factors that impact each of the plant species directly play a more essential role in the distribution. As such, further exploration ideas consist of some factors such as, climate, soil condition, water exposure, invasive species, biological interactions, and etc. An example of my data regarding abundance, organized into a table is shown below:

 

Table 1: The table below depicts the abundance of each of the six species present at each of the three sites at Milliken District Park. The first site, Site A, is within the forest, the second site, Site B, is outside of the forest, just before a large pond, and the third site, Site C, is the area on the other side of the pond. The ACFOR scale was used to measure whether the species was Abundant, Common, Frequent, Occasional, or Rare. A species was considered abundant if it was present 10 or more times within the quadrat. It was considered common if it was present 7-9 times within the quadrat, it was considered frequent if it was present 5-6 times within the quadrat, it was considered occasional if it was present 3-4 times within the quadrat and it was considered rare if it was present 2 or fewer times within the quadrat.

Post 7: Theoretical Perspectives

TRU Open Learning Leave a comment

User:  | Open Learning Faculty Member: 

The overall theoretical basis of my research project is ultimately how different species are distributed in a community park, when there are various influential factors, such as sunlight, human disturbances, landscaping, etc. Based on the results that I have obtained and the research that I have done, it is evident that different species require different conditions in order to grow, survive, and reproduce, and as such, the abundance, and percentage coverage will vary depending on the species. I expected that all of the species would be mostly distributed in areas with high sun exposure, but upon analysis of the results, this is not always the case. Although sun exposure, is not the only factor influencing where a species is present, it is an important factor. As such, I chose to examine sites from a forest (more shade), near a pond (more moist and sun exposure), and the other side of this pond (more grass and sun exposure). I chose these sites in order to compare the influence of sun exposure, and moistness.

Three keywords that could be used to describe my research project are: species distribution, species abundance, and sun exposure.

Post 6: Data Collection

TRU Open Learning Leave a comment

User:  | Open Learning Faculty Member: 

Data collection thus far has been very enjoyable. I am investigating the species distribution of six species, Carex praegracilis, Andropogon gerardii, Gymnocarpium dryopteris, Elymus repens, Cyperus odoratus, and Sonchus arvensis, along the environmental gradient present at Milliken District Park, and am expecting to see a greater distribution of species along the gradient, as there is more exposure to sunlight.

In order to collect data, transect lines and square quadrats will be used to outline the study sites. I used survey poles and a line level in order to measure the distance and elevation.I’ve decided to collect data on percentage coverage, abundance, and presence/absence. Percentage coverage was measured using a 1m2 quadrat, the abundance of the species using a 0.5m2 quadrat, and absence/presence using a 0.25m2 quadrant. The measurements were determined based on the amount of plants, as well as the size of the plants present in the area selected. Each of the three quadrats was placed randomly five times at each site, and data was collected. Abundance was measured using the ACFOR scale (Abundant, Common, Frequent, Occasional, or Rare). A species is considered abundant if it was present 10 or more times within the quadrat. It is considered common if it was present 7-9 times within the quadrat, it is considered frequent if it was present 5-6 times within the quadrat, it is considered occasional if it was present 3-4 times within the quadrat and it is considered rare if it is present 2 or fewer times within the quadrat. When looking at the variable of presence/absence, an ‘X’ represents the species that were present, and no ‘X’ represents that the species was absent in that region. I initially decided to repeat this procedure on three different days, but decided that 5 data sets for each study site on one collection date would be sufficient to obtain the information needed.

The data collected on percentage coverage, abundance, and presence/absence all seem to follow a similar trend. To some extent, my hypothesis and prediction has been supported and proven upon data collection and analysis, however, other factors that impact these plant species directly such as the climate and condition in which the species are found, have been seen to play a more essential role in the distribution.

Although I did not face any major difficulties implementing my sampling design, some minor issues that I was able to overcome include challenges with the weather and physically choosing the correct area to collect my sample. However, after these issues were overcame, I was able to successfully gather results.

Post 5: Design Reflections

TRU Open Learning 1 Comment

User:  | Open Learning Faculty Member: 

After walking around Milliken District Park and observing my potential sampling sites, I got a better idea of how I would collect my data and implement my sampling strategy. Prior to doing this, I was a little confused on how I could collect data, but my initial observations helped me make more sense of it. As such, I did not face much difficulty in actually implementing my sampling strategy. I believe that the data that I collected was actually not surprising in any way. I expected some discrepancies, and was somewhat expecting to see some differences in the distribution of the six species, as there are factors such as sun exposure and climate that come into play. As a result, I plan to continue using the same technique in order to collect data. The same technique can also promote consistency in the result obtained. I believe that the time and weather that samples are collected in will have an impact on the results obtained, and thus I will have to take this into consideration when analyzing.

I decided to use the systematic sampling strategy as I felt it would be the best choice in my sampling areas. The first site, Site A, is within the forest, the second site, Site B, is outside of the forest, just before a large pond, and the third site, Site C, is the area on the other side of the pond. Percentage coverage was measured using a 1m2 quadrat, the abundance of the species using a 0.5m2 quadrat, and absence/presence using a 0.25m2 quadrant. These measurements were determined based on the amount of plants, as well as the size of the plants present in the area selected. Each of the three quadrats was placed randomly five times at each site, and data was collected. Abundance was measured using the ACFOR scale (Abundant, Common, Frequent, Occasional, or Rare), which will be explained in more details below. When looking at the variable of presence/absence, an ‘X’ represents the species that were present, and no ‘X’ represents that the species was absent in that region.

Blog Post 4: Sampling Strategies

TRU Open Learning Leave a comment

User:  | Open Learning Faculty Member: 

The three sampling strategies that I used in the virtual forest tutorial were haphazard sampling (area), random sampling (area), and systematic sampling (area). The fastest estimated sampling time was the systematic sampling strategy (12 hours 36 minutes), as it only covered a small area within the region. With regards to the rare species, the fasted estimated sampling time was determined to be the haphazard sampling strategy, although it had a poor accuracy (1 hours 52 minutes).

With regards to the systematic sampling strategy, the common species had percentage errors of 1.8% and 5.3%. The rare species had percentage errors of 100% and 82%. With regards to the haphazard sampling strategy, the common species had percentage errors of 23.4% and 26.7%, and the rare species had percentage errors of 48.6% and 32.4%. Lastly, with regards to the random sampling strategy, the common species has percentage errors of 5.4% and 8.3% and the rare species had percentage errors of 32.7% and 48.6%.

Upon comparison of the percentage errors for the common and rare species based on the three different sampling strategies used, it can be concluded that the rare species had higher percentage errors than the common species in all three strategies. As such, it can be suggested that accuracy increases as abundance increases. Based on the results, it can also be concluded that the systematic strategy is the most accurate, whereas the haphazard strategy is the least accurate from the three.

Blog Post 3: Ongoing Field Observations

TRU Open Learning Leave a comment

User:  | Open Learning Faculty Member: 

Upon field observations, I have decided that the biological attribute that I plan on studying involves species distribution. I am eager to learn and understand how species distribution (specifically looking at percent coverage, abundances, and presence/absence) differs in diverse areas, such as near the pond, and forest compared to other areas.

Based on the surrounding, the environmental gradient will start from near the forest, the second point will be around the pond, and the third point will be on the other side of the pond. Underlying processes that may cause any patterns observed include, human disturbances and maintenance/landscaping (people walking on plants, kids running around, plants being mowed), species submerging into the pond, opened versus closed land areas, and of course, seasonality and climate change.

Upon observation, I noticed that there is a lack of growth of plants and grasses around the playground and along the paved pathways. In contrast there is a higher abundance of vegetation near the pond and outside as well as inside of the forest. There are also more insects found near the pond and forest.

Based on these observations, my hypothesis is that six plant species, Carex praegracilis, Andropogon gerardii, Gymnocarpium dryopteris, Elymus repens, Cyperus odoratus, and Sonchus arvensis differ in the location that they are found in Milliken District Park. A formal prediction based on his hypothesis is that the areas with less disturbances and more exposure to sunlight will host a greater number of these plant species, as compared to the areas with more disturbances and less exposure to sunlight. Thus, it is predicted that there will be species that are only found within the forest, species that are only found near the pond, and species that are found throughout both areas.

A potential response variable that I plan to use for my experiment is percentage coverage, measured at each of the three sampling sites. The response variable is considered continuous. In contrast, a potential experimental variable that I plan to use is the level of disturbance as a result of human activity/disturbance. With fewer disturbances, I believe that species will be distribution more throughout the park. The experimental variable is considered continuous. The predictor/independent variable would be the location of the vegetation present. This variable is also considered continuous.