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Blog Post #9

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There were a few bumps along the road as I designed and carried out my field experiment. I changed my hypothesis and experimental design multiple times in order to better suit the goal of my research. I struggled to really narrow down exactly what it was I was looking for and what I was predicting. There seemed to be so many connections and not enough time to explore them all. However, I was finally able to pinpoint my hypothesis and come up with a straightforward prediction. Before I completed this course, I had little to no experience in carrying out field research. Engaging in the practice of ecology has helped me to appreciate how much effort goes into the development of ecological theory. It is much more complex and difficult than I had originally assumed. I am sure that the skills I gained and the information I learned during this research project will help me as I continue my degree. 

Blog Post #3: Ongoing field observations

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The organism that I plan to study is Vincetoxicum nigrum or Dog Strangling Vine. More specifically, the seed production of the vine.

Along the north/south length of my study area, I can find the vine growing in the densely vegetated area between the creek and the pathway on the west side of the study area as well as along the hill side, on the east side of the study area. I do not see it growing in any substantial way in the manicured grass area between the slope and the pathway, however it is possible that the vine is trying to grow there but is impacted by the grass cutting.

I have noticed that the vines in the densely vegetated area appear to be healthier and more productive than the vines growing along the slope. In the vegetation the leaves are stiff and the vines are tall, wrapping around many other plants and spreading out. On the slope, the leaves are wilted and soft. The vines do not grow as tall on the slope either. Event where a tree or bush provides a possible climbing aid.

A few things may be causing this difference in plant health. Perhaps the amount of sunlight on the slope is too high. Or maybe there is more nutrient available in the wooded area. During site observations, I noticed that the soil on the slope is very hard and dry whereas the soil in the wooded area is noticeably wetter. This is consistent along the north/south length of the study area. It is a common sight in the surrounding area to see large patches of Dog Strangling Vine growing in full sun, on slopes. The difference is probably not too much sunlight. I suspect that reduced water availability would impact the plants ability to perform transpiration, which as a result, would impact the level of nutrients brought into the plant, with the water, for growth and reproduction.

Considering the above, I hypothesize that differences in water availability are impacting the vines ability to grow and thrive. My prediction is that plants in drier soil will produce fewer seed pods.

Based on my hypothesis and prediction. The predictor variable is soil moisture and the response variable is the number of seed pods per plant. The number of seed pods would be counted on a numerical scale and so would be a continuous variable. Depending on the measurement device, soil moisture could be categorical – in the case where a moisture probe simply displays one of a discrete set of value: dry, moist, wet, etc..) or continuous  – in the case where a moisture probe displays a spectrum of out puts ranging on a scale from dry to wet. In this case, the moisture probe in use displays a spectrum and so would be considered continuous.

notes August 16 notes August 23 Photos August 16-23

Blog Post #8

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Below are the figures I created to summarize the results of my data collection:

 

My data was fairly easy to summarize with figures. I struggled with excel (as I don’t have much experience with the system) and creating the graphs took longer than it likely should have. However, for the most part, I think it went well.

 Looking at Figure 1 above, it can be seen that species diversity increases as distance from the creek increases. This supports my prediction for the most part, however, I did expect 8 m from the creek to have a greater diversity than 6 m. Looking at my data, it appears that 6 m from the creek is where plant diversity begins to drop off. It is possible that the area right next to the walking trail usually supports a larger number of species, but that anthropogenic influences such as spraying chemicals and mowing have decreased this number.

Looking at Figure 2 A through N, it can be seen that while some species grow all over, others appear to have a preferred distance from the creek in which they grow. Besides grasses, Elymus canadensis and Trifolium repens were by far the most common species and were able to survive in all transects. Graphs F through N show that some plants had specific living conditions. None of them were present in quadrant 4 and some were also not present in quadrant 3. These plants likely do not have the adaptations necessary to survive flooding. There were also some that only grew within a certain quadrant, such as Plantago major (that only grew in Quadrant 1) and Aristida purpurea (that only grew in Quadrant 3). As I continue with my research, I will look into what specific conditions (besides flooding) make these quadrants ideal for these plants. As I continue to analyze my data, I plan to calculate and examine the correlation between distance from the creek and plant diversity. 

Blog Post 9: Field Research Reflections

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I am so glad that I took this course, although it was incredibly challenging for me. I have conducted several wildlife studies, habitat assessments, etc., however, I have never designed one. I spent the whole summer collecting data, and I have a greater understanding of how difficult it is to come up with and test a hypothesis. I changed my focus NUMEROUS times-the world is a big place, and narrowing down just WHAT to study was the most challenging. I am finalizing my research paper, and seeing all my data in one place is incredibly rewarding. I adore being out in the field, and I plan to repeat this study for my day job next year, with some changes-I made a LOT of mistakes along the way, but I do believe you learn more from your failures.

Blog Post 8: Tables and Graphs

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I conducted a call survey at 10 locations throughout PEI. The information I gathered was a bit challenging to piece together to present it in a meaningful way. I took 5-minute recordings at each location, then listened later, and assessed abundance based on the calling. I am fortunate that my day job allowed me access to a YSI meter to collect nitrate levels at each of the locations. I then used mapping software to measure the distance from each calling site to the closest active farming site.
I am presenting my nitrate levels at each location in a table. I plotted my distance to farming (independent variable) on my X-axis and the number of anurans on the Y-axis (dependent) variable. The correlation to farming and species abundance that I predicted, does not appear to exist. PEI has been more involved in the past 20 years of restoring wetlands, establishing guidelines, and enforcing best management practices for the farming industry, which is a possible explanation as to why there is no correlation. I am hoping to return to my same job next summer as a wildlife technician and using this framework to set up another abundance study, to include all amphibian species on the island, not just anurans.

 

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Blog Post #7 Theoretical Perspectives

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The basis for my research on amphibians, specifically frogs and toads (anurans) on Prince Edward Island, is that our landscape is predominantly farming, with the majority of that farming being potato farming. My research has been to study the abundance of four species of frogs and one species of toad. These anurans only call during mating season, and are most active after sunset, so I went out to ten locations during their mating season to assess abundance. I chose 10 sites at random, however, I did have to choose the sites based on their ability to host frogs and toads-freshwater, riparian zones. I was curious to see if there was a relationship to active farming sites and species abundance. I am pretty sure that my research will show no correlation-of which I am pretty upset about, as I based my whole summer on this. I will endeavor to show that BMP (best management practices) may have something to do with this, as we had our mandatory buffer zone increased to 15 meters in 2005. My research keywords would be

Anuran, farming, buffer zone

Post 8: Tables and Graphs

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The graph i submitted displays the data from one of my 4 sample plots (Plot 3). The predictor variable, elevation from the lake waterline, is presented on the X axis with the response variable, species composition (by percentage), on the Y axis. The sample plot was divided into 5 elevation zones, which made it easier to determine changes in species composition as elevation increased. This also made the data relatively simple to organise and graph. I took the raw data from each of these elevation zones and calculated the percentage abundance of each of the species in each zone. While the other 3 sample plots produced results that aligned closely with my prediction, the results from Plot 3 were quite surprising. I had predicted that the relative abundance Alnus rubra would decrease with increasing elevation, while the abundance of conifer species would increase. However, the graph showed a spike in conifer abundance and a sharp decrease of Alnus rubra abundance in the 2-3m elevation zone, and exactly the opposite pattern in the 3-4m elevation zone. This prompted me to analyse the substrate descriptions that I had recorded for each species in each zone. In the other 3 sample plots, substrates had progressively transitioned from deep, spongy and moist soil in the lower elevations to drier, sandier and rockier substrates in the higher elevations. However, in Plot 3 there was a patch of drier, sandier substrate in the 2-3m elevation zone, which prompted a decrease in Alnus rubra and an increase in conifer abundance, and a patch of moist, spongy substrate in the 3-4m elevation zone which saw an increase in Alnus rubra and decrease in conifer abundance. Hence, this graph prompted me to give more consideration to the influence of substrate on species composition, and make another graph that depicts changes in species composition in relation to changes in substrate type – from the most moist and spongy soils to the driest and rockiest substrates.

 

Post 7: Theoretical Perspectives

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My research project looks at tree species composition in riparian ecosystems. Essentially, riparian ecosystems are highly dynamic and volatile environments due to the prevalence of natural disturbances, such as landslides and flooding. These ecosystems are highly competitive and the tree species that occupy them need to have adaptations to survive in the face of frequent disturbances and resource limitations. My project studies a stretch of riparian lake shoreline and investigates whether there is a relationship between flood frequency and species composition by analysing species composition at different elevations on the bank of the lake. My primary focus is on the species Alnus rubra, and determining first whether there is a correlation between more frequent flood disturbances on the lower elevations of the shoreline and increased relative abundance of Alnus rubra, in relation to conifer species.

Secondly, my research looks into potential reasons for such a pattern. I refer to a number of research studies that suggest levels of resilience to flood disturbance, tolerance to waterlogging, substrate preferences and reproductive strategies are responsible for the distribution of Alnus rubra and the conifer species across the flood prone, and upper elevations of the Nita Lake shoreline. Ultimately, riparian tree species composition is not stagnant, but always evolving through different stages of succession, which at any time can be disrupted by flood disturbance and turned back to the first stage. In order to predict species composition in riparian ecosystems, one must have an understanding of the life history strategies and adaptations of the different species that interact to produce these successional dynamics.

 

Keywords:

Riparian ecosystem

Flood disturbance

Life history strategies

 

Blog Post 5: Design Reflections

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When I went into the field to start implementing my field strategy, I didn’t feel as if I had any major difficulties as I had prepared well before going into the field and had the appropriate tools needed. I think where the difficulties have now arisen is in my confusion of understanding the process. I chose to use a distance-based method (as this is used for stationary organisms, such as trees) and to use the simple nearest individual method as mentioned in Module 3 Sampling Techniques Tutorial.

I then used the Vegetation Resources Inventory (VRI) Ground Sampling Procedures from the Ministry of Forests and Range, which was extremely detailed and helpful, to supplement my understanding of the sampling strategy. I ended up implementing an integrated plot centre (IPC) quarter method which is what is now confusing me, as I am unsure if my sampling strategy is correct. My IPC was randomly chosen by splitting the area on the west side of Lost Lake into 16 zones then by using a randomized number generator to choose the zone. From here I used google maps to collect my coordinates to implement my sampling strategy.

I sampled 16 trees in total, four at the IPC and four at each auxiliary plot that are 50 metres north, south, east and west of the IPC. I was unable to sample at the eastern auxiliary plot as this was located in the middle of Lost Lake. At the IPC and the auxiliary points, I quartered the area using cardinal directions, into 4 sections. In each quarter I measured the DBH of the nearest individual (4.0 cm DBH) and measured the distance to the centre point.

Using the VRI ground sampling procedures it actually gets quite complicated for the quarter method as the data that I am trying to collect is tree attributes and the recommended sampling methods are fixed-radius or variable. When I dig further into this, variable plot is a method in which sampling area (plot size) varies with tree diameter and fixed-area, is exactly that, and you need to determine which trees are in or out based a fixed-radius.

To modify my approach, I may need to increase my sample size or alter my methodology. Either way, I plan to use tree attribute cards that have been provided in the VRI ground sampling procedures to help collect data clearly. I also need to document my access point, tie point and reference point. As I am in a municipal park I am unable to leave permanent objects or markings in the forest. Instead, I will look for obvious landmarks or unique trees that can act as these points. I also need to assess if I should replace my dropped auxiliary point, but this also answers if I should increase my sample size. All of these discussed modifications will improve my research to be standardized, repeatable and with little bias as possible.

Blog Post 2- Sources of Scientific Information

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I found an ecology research paper in the online library (Cooke et al., 2016).

a) Cooke, J., DeGabriel, J. L., & Hartley, S. E. (2016). The functional ecology of plant silicon: Geoscience to genes. Functional Ecology, 30(8), 1270–1276. https://doi.org/10.1111/1365-2435.12711

b) This paper is academic peer-reviewed review-material

c) This is academic because it is written by experts in the field associated with the Department of Earth, Environment and Ecosystems, The Open University, Hawkesbury Institute for the Environment, Western Sydney University, York Environmental Sustainability Institute and University of York. There are in text citations and a bibliography. It does not have a “method” or “results” section so therefore would be considered a review article. There are no acknowledgments of a peer review process but the website for the British Ecological Society has a review process for the Functional Ecological journal.