The paper I would like to use for analysis in this post comes from a well-recognized journal Proceedings of the Royal Society B and was placed in the US National Library of Medicine National Institutes of Health. Pollination services enhanced with urbanization despite increasing pollinator parasitism. Proceedings of the Royal Society B: Biological Sciences. 2016;283(1833):20160561. doi:10.1098/rspb.2016.0561. by Theodorou P, Radzevičiūtė R, Settele J, Schweiger O, Murray TE, Paxton RJ.
This paper fits the classification: Academic, peer-reviewed research material.
The fact that it is written by two Master degree students and two supervisors with doctorate degrees who specialize on pollinators and effects affecting them; Both in-text citations and bibliography present we can conclude that it is an Academic material. By the fact that journal that published the paper includes acceptation and publishing dates we can assume that it is peer-reviewed. The presence of methods and results section with field techniques included indicates that this is a research material.
For my research project, I chose the site that is designated as a City Park. McArthur island park is an area of 51 ha based on the parks official website data. It is surrounded by a sub-urban environment but is separated from it by a corridor – river pocket that makes it an island and connects to the big land by two bridges and a bridge with deranges which appears to control the water level in spring. Unfortunately, I didn’t find any information on the origin of this river pocket (man-made or naturally occurring). The GPS data for the site is Latitude 50,6960; Longitude -120,3785. I visited the site on Saturday July 22 at 15:30 for the primeral assessment, the weather was +29°C with 18 km/h of western wind, and humidity of 62%. The site appears to be a highly disturbed area because it contains 23 sport facilities as well as biking routs and a golf course. Therefore, majority of the area is covered by the man-made loan grass, ratio of green cover to concrete from the maps appears to be 5:1. The area of interest was mainly located on the western part of the park. It is a line of wild growth on one side bordering with the river valley and on the other side boarders with the cycling route that is 3,5 meters wide and then with the golf and soccer court (circled on the picture attached). The water level drops significantly in late September, creating a solid ground that connects the island to the sub-urban areas until mid-April. On the northern part of the area of interest man-made butterfly garden was assessed as well indicated by a dot on the map.
The vegetation is majorly represented by birch trees Betulla, young willow trees Salix, burdocks Arctium, low area by the water is covered in Polytrichum communis, Psilotum and Tetraphis pellucida. Middle height area is majorally represented by rough horse tail Equisetum.
The butterfly garden contained Verbena, Delphiniums, tiger lilies, Fleabane, poppy flowers, common mullein, and yellow daisies.
Young deer prints were found on the sand by the water and later was confirmed by a young deer found on the site, also squirrels, crows, ducks and woodpeckers were spotted.
On the butterfly garden, cabbage white butterflies Pieris rapae, wool carder bees Anthidium manicatum, western leafcutter bee Megachile perihirta, honey bees mostly male drones Apis, yellow faced bumblebees Bombus vosnesenskii and mixed bumblebees Bombus mixtus were spotted according to “Common pollinators of British Columbia visual identification guide”. It was noticed that the composition of pollinators in a suburb area neighboring the island is highly different.
Questions:
Abundance of some pollinators species were highly outnumbered in the garden and their composition (richness) is very different from the one found in front yard gardens in the Suburbs, could urbanization gradient effect pollinator species composition?
Which other effects could have impact on the population of pollinators in the study area (humidity, temperature, shading by human created structures by the site?
What are the factors affecting the plant community composition on both sides of the river pocket as the vegetation is slightly different on both sides.
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.
My hypothesis touches upon how environmental factors effect how an organism develops and survives. I think some of us are quite fascinated in how a little seed is able to grow into something that humans as consumers need in order to survive ourselves. The physiological aspects of plants are quite interesting to me and I’ll admit I do not know much about it.
Ideas that underpin my research are wondering how environmental factors change the morphological and physiological components of fruit as it grows and matures. Why and how does the amount of water determine the health of fruit? Would fruit trees be able to survive in extreme drought conditions? What is the optimal environment for fruit trees to survive and develop in?
Keywords: fruit trees, plant physiology, water stress
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.
Through extensive research of information online and gardening books from my parents I found out the exact amount of water each tree should be receiving and what counts as “excessive” and “the right amount”. In my study, the plum tree is the moderately watered fruit tree, in which it gets 8 liters of water per week. Ideally, a plum tree should be watered twice a week, which means each watering day the tree gets 4 liters.
The pear tree on the other hand gets less water, if it were the moderately watered tree. The right amount of water is 4 liters per week and watering twice a week, so 2 liters of water per watering. In this study, the pear tree is the “excessively” watered tree so I am watering it the same amount as the pear tree, which is 4 liters twice a week.
The cherry tree does not receive any watering, although would normally be maintained at 4 liters twice a week.
I choose two nights per tree to water them, but never both trees on the same night. Each tree expands an area of 1 square meter, so my quadrats are split into 9 sections, and fruit is counted individually in each section. So far I have done 2 replicates, as the fruit is just starting to produce and grow. I plan on collecting data until August to get the maximum yield of fruit, so 10 replicates altogether. In the end I will do a final count of fruit on each tree to complete my study and most likely just use that number for my conclusion. The overall number throughout the whole study is mainly just for my curiosity.
So far my sampling design has been working out for me. If I were to redo this experiment I would net the trees so birds couldn’t pick at the fruit and potentially disrupt a true fruit yield. Patterns I have noticed come from more the leaves of the tree than what the fruit looks like, although it might yet be too early to tell how this is going to affect the fruit itself. The cherry tree and the pear tree both have unhealthy looking leaves that curl up, with some turning reddish/brown and wilting. The plum tree has healthy looking dark green leaves. In comparison to last year, the cherries growing on the tree don’t seem to be as abundant this year, but that can be due to other variables I haven’t accounted for in this study.
Cherry: no watering- drought
Plum: normal watering- control
Pear tree: excessive watering- too much water stress
Weather: 5.5 degrees C. 35 Km/hr wind. No recent precipitation. Snow still present on the North and East slopes. Ice cover on Eskers Lakes, but Pond 1 is ice-free. 5 diving ducks on Pond 1 and ducks are present on the open shoreline of the lakes where snow and ice is melting.
Photo 1: Sparse Labrador Tea growing in the open.
Photo 2: Higher density and abundance under the spruce trees.
Photo 3: Labrador Tea growing at the toe of the hill under the spruce trees, and not growing on the hillside.
The organism that I plan to study is Labrador Tea (Ledum groenlandicum). Walking along the bottom of the slope of Pond 1, the North slope has a lot of Labrador Tea, particularly under the canopy of spruce trees. There is not a lot of pooling water on the North side as there is a constructed drainage ditch that reports to the wetlands proximal to Eskers Lake West. Photo 1 illustrates the sparse occurrence of Labrador Tea in open areas with no canopy. Photo 2 illustrates the difference in density and abundance when there is spruce tree canopy cover.
Walking along the 300 m stretch of wetland below the east-facing slope of Pond 1, there is a very obvious pattern of Labrador Tea growing in dense patches directly below the smaller spruce trees. There is no drainage ditch along the East slope but there is also no pooling water. Further towards Eskers Lakes, the distribution and abundance of Labrador Tea greatly decreases as the ground becomes more flooded. Within the forested area Labrador Tea is beginning to grown green leaves.
Along the South-facing slope there are larger Englemen Spruce trees. The abundance of Labrador Tea is low under the larger trees. There appears to be a preference for the smaller Black Spruce. Again, the spatial distribution of Labrador Tea is greatest in moderately well-drained soil directly under the canopy of smaller spruce trees.
Underlying processes explaining why Labrador Tea is greater in density and abundance directly below smaller spruce trees:
soil moisture – Labrador Tea does not appear to thrive in flooded or saturated soil conditions
Slopes – Labrador Tea does not appear to grow on steeper slopes, though aspect does not appear to be a factor
Hypothesis (Inductive): The abundance and density of Labrador Tea is determined by substrate moisture.
Prediction: Areas proximal to wetlands will have greater abundance and density of Labrador Tea than either the flooded areas of the wetlands or the well-drained slopes.
Null Hypothesis: Soil moisture has no effect on the abundance and density of Labrador Tea.
Response Variable: Labrador Tea
Predictor Variable: Soil moisture.
The response variable, Labrador Tea, is categorical (may measure as presence/absence) and the predictor variable, soil moisture, is continuous. This appears to be a a Logistic Regression study design.
Above is my table of information obtained during my sampling period of 10 different randomized replicates. Increasing my replicates from 2 to 10 has really helped increase the amount of data that I have been able to obtain. This has helped increase the amount of African Elephants captured on the camera traps and has given me more information to utilize in my graph. The data obtained is exciting to see as there is definitely a trend as to what temperature the elephants drink at. The status quo is that most animals will drink at the hottest time of the day in order to cool themselves down and quench there thirsty that would be thought to be peaking at that particular time of day. However the evidence that I have collected shows that a majority of the Elephants are drinking at 20 degrees C. A great majority of the more sporadic drinking habits fall in from 20 degrees C down to the low teens. One would then think that Elephants prefer to drink at cooler temperatures in order to stay concealed during the hotter times of the day.
With my last samples collected a majority were breeding herds of elephants ranging from 5 members to 25 members. My one worry is that the larger breeding herds may skew the data as the larger numbers make a bigger impact. This could mean that even one fairly large breeding herd coming to drink at a specific temperature may bump the numbers up for that temperature. This could then lead to a misrepresentation of data in the long run, this is something I am keeping in mind whilst writing my discussion.
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.
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.
