Category: Percy Hebert

Post 7: Theoretical Perspectives

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My project looks at Salvelinus Fontinalis  presence in a creek that is heavily intruded on by humans. The ecological processes I intend to explore are nutrient cycling, reproduction and anthropogenic disturbances.

Nutrient cycling will hopefully allow a deeper inspection into the impacts of pollution, habitat destruction and reduction and what the aesthetic cleaning of the creek is doing to the health of the water and its inhabitants. I also hope to look at how it has affected the creek bed and sides. Is it possible that frequent pruning of trees has resulted in shallow root systems and potentially less support for the sides of the creek to withstand seasonal flooding?

When exploring reproduction of Salvelinus Fontinalis I hope to explore their historic breeding space. What pH is optimal for reproduction? Is there a preferred sediment base? Do they need a certain amount of cover from surrounding shrubbery? Historically, has this been a highly sought after spot for spawning?

Anthropogenic disturbances  play a role in every area I hope to explore, but specifically I hope to look at what the overall impacts are of cleaning debris from the creek on water flow, shrubbery health and the organisms which reside in the waters and surrounding grasslands. Does the frequent disturbance of the creek bed and surrounding land reduce viable spawning grounds for the fish? Has the area become too urbanized with walking paths, bridges and maintenance for the habitat to maintain viability?

Key words: Anthropogenic disturbances, Spawning, Habitat destruction

Post 6: Data Collection

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I have 20 replicates over a 2km stretch of creek and waterfall at Peterson Creek Park in Kamloops BC. I struggled to get my sample sizes as measuring across the creek was tricky and anything I would place in it would float away. Staking posts would damage the creek walls as I hoped to get the full range of creek for most samples. I ended up enlisting help and painting measurements on a stick then marking the edges with flagging tape. I noticed after my first walkthrough that my hypothesis could have varying results based on pollutants and human traffic which made me reevaluate. I also noticed there was virtually no wildlife which suggested the area may have underlying pollutants effecting multiple habitats. Soil and water sampling would be ideal if the resources to do so were available.

Design Reflections

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In module 3, I collected using point counting. I went out early in the morning and stayed for even increments of time at each plot. I found I got a good sense of surrounding wildlife and human activity but struggled to find the specimen I was looking for. I realized that this was further proof that my hypothesis is correct and thus persevere with my sampling strategy. I did some hiking following my samples to investigate the area further and found a sign stating dates the lake above the creek is stocked biannually and is about to be stocked in November 2020. I expect to find higher numbers of fry due to this and will resample to confirm.

While I do not feel the need to modify my approach, I do feel I should include human traffic in my official data as it was a significant finding and will show the overall impact on fish survival. I am also considering pollutants based on lack of aquatic plant life.

Blog Post 4: Sampling Strategies

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For the virtual forest tutorial, I used the area sampling technique.  The random sampling strategy had by far the fastest estimated sampling time at 4hours 51minutes compared to the systematic strategy (12 hours 37 minutes) and the haphazard sampling times (13 hours 2 minutes).

For the two most common tree species, the eastern hemlock and sweet birch, the percentage error was low for the systematic strategy (7% and 5%) and was highest for the random strategy (19% and 36%) (Figure 1).  The percent error from the haphazard strategy varied with the eastern hemlock having the lowest percent error at 6% and a high percent error of 21% for the sweet birch (Figure 1).  Based on the percent errors for the most common species, the systematic strategy seems to be the most accurate, the random being the least accurate and the haphazard being unpredictable with one of the percent errors being low and the other being high.

When looking at the percent error for the two most rare species, the striped maple and the white pine, all the sampling strategies had large percent errors for at least one of the species; this shows that accuracy increases with species abundance and decreases with species rarity.  The systematic strategy had large percent errors (178% and 100%) as well as the random strategy (185% and 48%) (Figure 1).  The haphazard strategy had a comparatively lower percent error for the striped maple at 14% but the white pine had a large percent error at 138% (Figure 1).  All the strategies for rare species were not able to accurately represent the population and the haphazard strategy having a high and low value again shows it is an unpredictable sampling strategy.

I think the systematic strategy was the most accurate when looking at the percent errors for all the tree species.  Surprisingly the haphazard strategy had lower percent errors overall than the random strategy which had the largest overall percent errors.

Blog Post 3: Ongoing Field Observations

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The organism I plan to study for the field research project is three types of large forest trees, the western red cedar, the ponderosa pine, and the Douglas-fir tree, within the Woodhaven Nature Conservancy Regional Park.

The trees change along an environmental gradient.  The first location (Figure 1) has many western red cedar trees and is dense with trees (Figures 2 and 3).  The location is shady with lots of dead fallen trees.  The ground cover are plants with dark green leaves; this seems to occur where there is sun exposure.  Much of the ground does not have plant growth due to the shade.  The distribution seems somewhat even.

The second location (Figure 4) is up a steep incline where the main tree is ponderosa pine (Figures 5, 6, and 7).  The soil appears sandy and the ground cover is more grass-like.  These trees are sparse and less dense than locations 1 and 3.  The distribution appears more uneven than locations 1 and 3.

The third location (Figure 8) is densely populated with Douglas-firs but is less dense than location 1 with the western red cedars (Figures 9 and 10).  The ground cover is a mix between grasses and the shrubs with dark green leaves.   The distribution appears even.

An underlying process which may cause the changing of the dominant tree type pattern could be changes in elevation which could influence soil moisture. My hypothesis is elevation influences the types of large trees that grow within a forested area.  My prediction is the first location with the western red cedars has the lowest elevation, the second location with the ponderosa pines has the highest elevation, and the third location with the Douglas-firs has an elevation in between the first and second locations.

The response variable would be the tree type (western red cedar, ponderosa pine, or Douglas-fir) that is growing within an area of the environmental gradient and the explanatory variable is elevation.  The tree type is categorical as the three trees I’m interested in are western red cedars, ponderosa pines, and Douglas-firs and if they are present or absent at different elevations.  Elevation would be continuous as it is measured on a continuous numerical scale.

Blog Post 8: Tables and Graphs

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Overall, I am happy with the outcome of the Figure I created. I initially knew quite quickly what information I wanted to convey, namely soil texture results in relation to slope, however, I struggled with the actual representation of this information. The biggest challenge was deciding how to organize my data in a way that would be discernible to any given audience.

Another challenge, though less so then the data organizing, was the formatting of the caption. Finding the balance of giving enough information without describing things unnecessarily is a practiced skill that I am a rookie at.

Hopefully with time and practice this becomes easier!

 

Blog Post 2: Sources of Scientific Information

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a. The article I chose is Citizen Science in Ecology: A Place for Humans in Nature and the source is from the online TRU Library. The article is from the Annals of the New York Academy of Sciences  The link to the article is below:

https://nyaspubs-onlinelibrary-wiley-com.ezproxy.tru.ca/doi/full/10.1111/nyas.14340

b. Based on the tutorial, I classified the article as an academic peer-reviewed review article.

c. The article is academic due to the authors being experts in their field; I was able to click on each of the authors and see that all of the authors were affiliated with an academic institution, the School of Biological Sciences, University of Utah, Salt Lake City, Utah (Figure 1). The article is also considered academic because it includes in-text citations and has a reference list (Figures 2 and 3).  I was able to determine the article was peer-reviewed by the article having the publication history including the manuscript received date, the manuscript revised date, a version of online record date, and the online issue date (Figure 4).  I was also able to refine my search in the online TRU Library to only search for articles that have been peer-reviewed which also helped to verify the article was peer reviewed (Figure 5).  The article is a review article based on there being no methods or results section; the article also stated at the top that it was a review article (Figure 6).

References:

Adler, F. R., Green, A. M., & Şekercioğlu, Ç. H. (2020). Citizen science in ecology: a place for humans in nature. Annals of the New York Academy of Sciences, 1469(1), 52–64. https://doi-org.ezproxy.tru.ca/10.1111/nyas.14340

Blog Post 1: Observations

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The area I have selected to observe is the Woodhaven Nature Conservancy Regional Park.  The park is 29.8 hectares and is located in the Lower Mission area of Kelowna, British Columbia (Parks Services, n.d.).  The park is comprised of woodland areas, riparian areas, and steep slopes.  The park has two small creeks running through it, Bonaparte Creek and North Fork Creek, as well as the larger Bellevue Creek is located on the south perimeter of the park (Figure 1).  The park is designated as a regional park.

An interesting aspect of Woodhaven Park is there are four distinct bio geoclimatic zones which are considered sensitive habitats that are threatened and endangered in the region: a black cottonwood zone, a Douglas-fir zone, a ponderosa pine zone, and a western red cedar zone (Figure 2) (Parks Services, n.d.).  Black cottonwoods grow in damp riparian areas whereas Douglas-firs can grow in a wide variety of soils but prefer partial shade and soils that are well drained (Parks Services, n.d.).  The ponderosa pines are the only pine trees in the area and prefer dry conditions; they are located up the steep sandy hillside (Parks Services, n.d.).  The red cedars are able to block out sunlight resulting in less shrubs where the red cedars are growing (Parks Services, n.d.).

I visited Woodhaven Park on October 24, 2020 at 1:40pm.  It was overcast and there was approximately 15cm of precipitation in the form of wet snow within the previous 48 hours.  There was still snow on the ground and the ambient temperature was -1˚C.

The first aspect I think would be interesting to study is the different bio geoclimatic zones within the park and what is the cause for the different zones?  Upon my initial visit I saw the western red cedar trees and Douglas-firs (Figures 3 and 4), but still need to see the ponderosa pines and black cottonwoods.  My first question is what influences each of the bio geoclimatic zones within Woodhaven Park?

I read the information board at the entrance of Woodhaven Park and it provided information on wildlife trees which look like dead trees that have holes in them (Figure 5).  Although these dead trees can pose a hazard to the public, they are not all removed due to the habitat they provide to the screech owl (Parks Services, n.d.).  The screech owl, which is an endangered species, uses these wildlife trees for nesting and roosting (Parks Services, n.d.).  There are only 200 screech owls left in the Okanagan Valley (Parks Services, n.d.).  The screech owl and the wildlife trees they use as habitat would be an aspect of Woodhaven Park I would like to further study.  My second question is will I be able to see a screech owl during my visits and do other species use wildlife trees in addition to the screech owl?

Upon my visit I also saw three sets of tracks in the snow and wondered what type of animal made those (Figure 6).   They were all headed in the same direction, north.  I also saw two deer without antlers (Figure 7) and a grey/brown squirrel (Figure 8).  My last question is what are the different types of mammals that inhabit Woodhaven Park?

References

Parks Services. (n.d.). Woodhaven Nature Conservancy Regional Park. In Regional District of Central Okanagan. Retrieved from https://www.regionaldistrict.com/media/19817/woodhaven%20brochure.pdf

Post 4: Sampling Strategies

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When participating in the virtual forest tutorial activity, I used three sampling strategies, haphazard area sampling, stratified-random sampling and systematic sampling.

When looking at the haphazard area sampling method results, I found the sampling time to be the fastest at 18 hours 59 minutes. Following this was systematic sampling at  26hours 58 minutes and finally random at 63 hours 18 minutes. With haphazard, I found reducing bias selection was difficult when considering the topography and cluster images. I was drawn to selecting those areas first in hopes of greater concentration of results. Unfortunately this was not the case and haphazard proved to be the least accurate method of sampling for common and uncommon species. The most accurate method was also the most time consuming. When filling in the random sampling selections, I found the greatest variation in discovered species as well as the highest accuracy in percentages.

The two most common species were:

Red maple 

Haphazard-9.0%

Random-1.0%

Stratified-3.25%

Chestnut oak

Haphazard-34.0%

Random-3.25%

Stratified-3.75%

The two rarest species were:

Sweet birch

Haphazard-90.0%

Random-0.1%

Stratified-82.0%

 White ash

Haphazard-90.0%

Random-0%

Stratified-100%

When reviewing the effects of density on the accuracy of species sampling I found higher density species had a greater accuracy in recordings. The lower density species, when found have a very high accuracy, but often are not found which greatly reduced the accuracy.

Post 9: Field Research Reflections

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Some of the challenges that I experienced during the research project was that the amount of different species that was being collected was too many to accurately tabulate my findings. I had to modify my hypothesis to only focus several specific species of vegetations to avoid getting lost in the data.
One thing that I struggled with and still do but not as much was with identifying plants and vegetation. I found it difficult trying to figure out what plant species I was looking at or looking for.
Another challenge was that the soil samples were collected in one day and therefore will only reflect the soil moisture on that given and will not represent an average moisture content for a season or month.
A speed bump that happened for me was that some of my data was collected over time as I tried to space it out but in October in Calgary we experienced a fair amount of snow which covered the ground for about 2 weeks in Fish Creek. So this snow coverage prevented me from gathering some of my data until a little later than expected. It also killed and wilted some vegetation we made species a little more difficult to identify and tabulate as some species were now laying dead on the ground instead of upright.
I think if I was enrolled in this class in spring and had collected my data during April or May, I would have seen a more distinct response of vegetation to the flooding being experienced as it would have been more common with the consistent melting of snow.