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Blog Post 2

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a. This source examines how emerald ash borer (EAB) have proliferated in North America since the early 2000s. Drawing on an improved understanding of EAB physiology the authors discuss how management strategies to mitigate the effects of EAB have developed over time to either slow ash mortality down, or attempt to use biological agents to try and protect desired ashes from infection.

https://www.annualreviews.org/doi/pdf/10.1146/annurev-ento-011613-162051

Herms, Daniel, and Deborah McCullough. “Emerald Ash Borer Invasion Of North America: History, Biology, Ecology, Impacts And Management”. Annual Reviews 59 (2014): 13-30. doi:10.1146/annurev-ento-011613-162051.

b. This is an example of non-peer reviewed academic material.

c. First, the authors, Herms and McCullough are associated with The Ohio State University and Michigan State University and have been paid to do research thereby making them experts in the field.

Second, the article uses in-text citations which it references as numbered citations that correspond to the full citation at the end of the paper.

For example:

Three species are currently being mass reared and released :an egg parasitoid(Oobius agrili Zhang and Huang)(Hymenoptera: Encyrtidae), a larval endoparasitoid (Tetrastichus planipennisi Yang) (Hymenoptera: Eulophidae), and a gregarious larval ectoparasitoid(Spathius agrili Yang)(Hymenoptera:Braconidae)(33,109). Asian parasitoids were first released at sites in southeast Michigan in 2007 (109,110).Production increased annually, and in 2012, more than 350,000 wasps were released in 14 states. Several releases appear to have resulted in successful establishment, although establishment of S.agrili in Michigan has been limited, possibly because of cold weather(25–27).

Third, the article includes a list of bibliographic sources referenced at the end of the paper.

For example:

2. Anulewicz AC, McCullough DG, Cappaert DL. 2007. Emerald ash borer (Agrilus planipennis) density
and canopy dieback in three North American ash species. Arboric. Urban For. 33:338–49
3. Anulewicz AC, McCullough DG, Cappaert DL, Poland TM. 2008. Host range of the emerald
ash borer (Agrilus planipennis Fairmaire) (Coleoptera: Buprestidae) in North America: results of
multiple-choice field experiments. Environ. Entomol. 37:230–41

Fourth, the article is not peer reviewed since it does not thank any reviewers but instead, thanks edits that were made to the publication.

For example:

We thank Cathy Herms for editorial expertise in producing the finished manuscript.

 

 

Blog Post 1

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On December nineteenth 2018 I went to the Marshlands Conservation Area in Kingston Ontario. It is located west of Queen’s University and Kingston Penitentiary stretching just shy of Lake Ontario (southern extent) northwards towards Princess Street (main street leading you to the downtown hub if you head east along it). The conservation authority is wedged between the Cataraqui Golf and Country Club to the east and the Little Cataraqui Creek to the West (for most of the property). The vegetation in this region includes woodlands, wetlands, and commercial lands (roads or private property). The Conservation Area is relatively low lying than surrounding land because it’s proximity to water. It does not have drastic changes in elevation.

https://crca.ca/wp-content/uploads/PDFs/maps/Marshlands.pdf (map of Marshlands Conservation Area)

I arrived at the site around 2 p.m. in the afternoon. The temperature was 3 degrees Celsius with broken cloud cover in the sky. The temperature was slightly warmer than average for December but there was no snow cover since there had been little precipitation of any kind in the previous week.  I walked along the Rideau Trail up until it intersected with the train tracks before heading back. On my walk I noticed that some of the butternut trees and ash trees had large fissures in the trunk and some were leaning to one side or have already fallen over.

Figure 1: Field Journal

Figure 2: Rideau Trail

Figure 3: Leaning Tree

Figure 4: Damaged Trunk

 

I’m interested in answering the following:

-What effect do emerald ash borer and butternut canker have on recreational trails?

-What are the ecological costs and benefits to removing those hazard trees and potentially reforesting the area?

-Can the risk of further infection to other trees be mitigated in any way?

2: Sources of Scientific Information

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Blog post 2: Sources of Scientific Information

Amy Laycock.

A.  The source I have chosen is a research paper published in the Forest Ecology and Management Journal: Long-term time series of annual ecosystem production (198502010) derived from tree rings in Douglas-fir stands on Vancouver Island, Canada using a hybrid biometric-modelling approach.

B.  This article is an academic, peer-reviewed, research source.

C.  It has been written by experts in the field (authors who work in the Canadian Forestry Service and forest and ecology researchers out of UBC). It has been published in a scientific journal with a satisfactory impact score (3.169), which edits and peer-reviews papers before publishing. It includes in-text citations throughout the paper, citing other credible peer-reviewed sources. This article contains a section which outlines their methods in a way that other researchers could replicate the study and a results section which summarize the relevant data they collected. Therefore, the article contains all the required criteria to be a primary academic, peer-reviewed, research source.

source:

https://www-sciencedirect-com.ezproxy.library.uvic.ca/science/article/pii/S0378112718308405

Metsaranta, J., Trofymow, J., Black, T., & Jassal, R. (2018). Long-term time series of annual ecosystem production (1985–2010) derived from tree rings in Douglas-fir stands on Vancouver Island, Canada using a hybrid biometric-modelling approach. Forest Ecology And Management, 429, 57-68. doi: 10.1016/j.foreco.2018.06.040

Post 9: Field Research Reflections

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Elevated view of the open scrublands in Scottsdale, AZ.

I was lucky in that I got to explore not only a foreign (read interesting) environment, but that the sparse vegetation and flat land made my job quite easy. I did not have to change much of my design other than that I was a bit ambitious initially. I had planned to measure substrate densities and root moisture as well in the beginning. Perhaps, by myself the scope of my experiment was a bit ambitious. I am happy that I could refine it into a product that I am proud of!

Engaging in my own field research is a first for me in my years of education. Ecology was initially a subject I had little interest in despite my background in Biology. Through the process, I began to contemplate not only origins of life but how to care for and preserve it. This course also taught me that ecology was not simply a science of preservation, but also in very detailed relationships between organic and non-organic processes. The complicated relationships between species and their environment, rivals and abiotic factors reminds me of physics and how everything affects each other.

By going out into the desert, I also learned the field ecologists have quite a difficult job. The concentration it takes to sample while exposed to the elements could be draining and frustrating at times. My appreciation of the dedication to ecological theory has increased by leaps and bounds.

Thank-you for a wonderful class,

Darren Hildebrand

Post 8: Tables and Graphs

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Figure 1. As soil moisture increases, height of Larrea tridentata increases. Soil moisture is given as a ‘reading’ from the garden moisture reader with a scale of 1 (driest) to 10 (wettest). Height is given in meters (m). The R² value of the graph is 59%.

 

Above is one of the graphs created from my data. As per my prediction, creosote plants that grew in soils with higher moisture levels tended to be taller than their drier counterparts. The graph was relatively easy to construct and interpret. Further regression analysis is needed to see if the line is truly statistically significant by analyzing the residual plots, but an R^2 value of 0.59 or 59% indicates that it is probable.

Post 7: Theoretical Perspectives

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My research proposal focuses on not only abundance of Larrea tridentata but also to developmental success based on height (dried mass would be preferable but difficult and illegal in the scope of this course). These factors are being tested based on soil moisture in a semi-arid environment, namely the Sonoran shrublands of Arizona, USA. It was my hypothesis that creosote would be more successful in size and number with more access to moisture provided by the man-made oasis in Papago Park, Arizona. I tested this hypothesis through counting and measurement of creosote plants in pre-determined areas of varying distances from the water source. The shrublands have on average 11 inches of rain per year which is defined by some sources as arid and others as very semi-arid. This will limit the impact that unseasonal weather can have on soil moisture as more rain than usual can affect soil moisture.

My research touches on resource availability as a factor of reproductive success as well as growth. It also could be used in further research on competition for resources like water which are beyond the scope of this study. 3 keywords that apply to my proposal are arid shrublands, soil moisture, and reproductive success.

Post 6: Data Collection

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3 areas which are 10m x 10m in size were chosen at Papago Park around a man-made oasis. Area 1 was 5 meters south of the oasis. Area 2 was 20 meters south of the oasis. Area 3 was 50m south of the oasis. These 3 sites were chosen in a southern direction because south had the most unimpeded land (either by road or rock). The three sites were arranged in a line and did not veer substantially to the south-east or south-west. Each area was divided into grids of 25 subplots each measuring 2m x 2m. Each grid was assigned coordinates of x and y values. To pick the initial subplot in each area, the google number generator with n = 5 was rolled. I rolled it twice, with the first number acting as the x coordinate and the second number acting as the y coordinate. From there I used a systematic sampling method where each individual individual Larrea tridentata was counted and measured. From the first subplot, I would increase and decrease the x value until I have x = 1, 2, 3, 4 ,5. Y-values were y and y-1 (where y – 1 = 0, would wrap around back to around to y = 5).

5 subplots were selected in each of the three areas for a total of 15 replicates. The total time for the sampling and recording of data took approximately 1 hour and 35 minutes. Distance between each individual in the each chosen subplot to its closest neighbour was recorded, as well as the number of Larrea tridentata individuals and each plants height. There were few difficulties with this method of sampling. The only issue was that the number of individuals in area 1 was quite low and 2 of the chosen subplots ended up being empty which may skew the estimates of the height as empty plots had to be disregarded.

I noticed that the total number of plants (of any species)  increased dramatically in area 1 relative to the other 2 areas. However, the number of creosote bushes dropped substantially which was against my set out hypothesis. There was no ancillary pattern in the distribution of individuals but in terms of height, creosote closer the water were larger than those further away.

Post 5: Design Reflections

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My experiment takes place over 3 areas which are 10m x 10m in size. I subdivided each area into grids of 25 subplots each measuring 2m x 2m. I gave each grid coordinates of x and y values. To pick the initial subplot in each area, I used the google number generator with n = 5. I rolled it twice, with the first number acting as the x coordinate and the second number acting as the y coordinate. From there I used a systematic sampling method as I found it to be the most accurate in the virtual forest tutorial. From the first subplot, I would increase and decrease the x value until I have x = 1, 2, 3, 4 ,5. Y-values were y and y-1 (where y – 1 = 0, would wrap around back to around to y = 5).

A sample of the data and plot choice method.

I measured the number of individuals, the distance between the each individual to its closest neighbour and the height of each individual. I included averages of the last two measurements.

The soil moisture was previously determined at each area using a simple garden moisture probe in the geographic center of each area. The moisture probe had a scale of 1 (driest) to 10 (wettest). Area 1 (nearest to the man-made water source) measure at 6.0, area 2 ( 2om from the water source) measured at 3.5, and area 3 (farthest from the water source) measured at 1.8.

I found this method extremely easy to carry out in regards to resources and time required. The data did surprise me in that it seems to adhere to my expected results based on my hypothesis. I intend to sample area 1 and area 3 in the same manner.

 

Post 4: Sampling Strategies

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After completing the virtual forest sampling tutorial, the data was as follows:

Sampling Time (hr:min): The fastest sampling methods was the systematic sampling methods at 12hrs 36mins estimated.

Systematic = (12:36)

Randomized = (13:12)

Haphazard = (13:02)

Percentage Error of density of species:

Eastern Hemlock – Systematic (1.30%) Randomized (6.41%) Haphazard (37.1%)

Red Maple –           Systematic (-12.5%) Randomized (-49.5%)   Haphazard (27.8%)

White Pine –           Systematic (42.9%) Randomized (-4.76%) Haphazard (-4.76%)

Striped Maple –     Systematic (37.1%) Randomized (82.9%) Haphazard (37.1%)

Sample Calculation: Eastern Hemlock (systematic) = (estimated (476.0) – actual (469.9)) / actual (469.9) x 100 = 1.30%

Populations with greater numbers of individuals had much more accurate estimations than the rare species.

The systematic methods was the quickest as well as the most accurate sampling method. Surprisingly the randomized methods seemed substantially less accurate than the haphazard method. I believe it may be limited to this one trial however. I would expect the haphazard to be the least accurate because of bias whether intentional or subconscious.

 

 

Blog Post 9: Field Research Reflections

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First of all, I would like to say that I enjoyed conducting my field research and that I feel it has been a valuable tool in my understanding of how ecological theory is developed. There are so many factors to consider when developing and implementing sound,  scientific research and so yes, I have certainly developed a greater appreciation for the hard work and knowledge that is required.

I have to admit that I struggled in the beginning to even generate a feasible topic. Observing patterns in nature was not something that came readily to me, and I realized quickly that it was a skill I needed to develop. Once I had a topic and a general method, I had initially planned to randomly select my point count locations by overlaying a grid system onto the park map. This did not work as the randomly selected locations I had chosen on paper did not provide the best vantage points in he field and caused unnecessary disturbance to the ducks within the drainage channels.  I also had assumed that diurnal sampling, particularly during the early morning hours would be best suited, as it is well known that bird activity is greatest during the morning hours. I quickly discovered that this was indeed the case for passerines, however, the dabbling ducks were much slower to wake. I conducted a couple of trial sampling events in the hours before dusk and this seemed to be when the ducks were most active.

My study area posed several challenges for me as well, as public access was limited to the upper dike areas. This made visibility slightly more challenging, and it was unlike a forest setting where you can potentially access more areas for data collection. Perhaps with permission from parks staff, I could have measured other aspects within the drainage ditches, including water quality and or depth to see if these influenced duck abundance. Once I had decided on my experimental design, the actual data collection was quite simple. I incorporated randomization into my study by using a random number generator to decide the order in which I visited my selected sample locations.

If I had the chance to conduct the research over again, I would have conducted my sampling during the fall months when overwintering waterfowl are typically more prevalent within the park. This potentially would have given me a greater sample size to work with when analyzing my data, as overall duck abundance at all point count locations was lower than I had expected.