Category: Nancy Elliot

Post 3: Ongoing Field Observations

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The organism that I plan to study for this research project is Nucella lapillus or commonly known as dog whelk. As per observation dog whelks are small and their shell colour is creamy brown. Upon walking around the beaches, I observed that the dog whelk shells are less pointy at Castle beach compared to Jetty beach and the shell size is also smaller at Castle beach than Jetty beach; the aperture of the shell is broader at Castle beach than Jetty beach.

The three locations that I selected are the upper shore, the middle shore, and the splash zone at both shores. I noticed that the dog whelks on the upper shore of both beaches were fairly distributed and not very abundant compared to the middle shore of both beaches. The middle shore had a high distribution and abundance of dog whelks at both Castle beach and Jetty beach. The splash zone had the lowest distribution and abundance of dog whelks at both beaches. The reason dog whelks are mainly found in the middle shore may be due to the balance in emersion and immersion and the decrease in harshness of the environment. The upper shore and splash zone may have harsher environments, so the dog whelks may move to the part of the shore that is the middle ground for survival. I hypothesize that the exposure to wave action influences the length to aperture ratio of dog whelks. Thus I predict that the length to aperture ratio will be smaller in the exposed beach. Based on my hypothesis and prediction a potential response variable is the length to aperture ratio of the dog whelks. A potential explanatory variable is the exposure to wave action on the shores of Castle beach (exposed) and Jetty beach (sheltered). The response variable is continuous and the predictor variable is categorical.

Post 2: Sources of Scientific Information

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The source of ecological information I have chosen is a scientific peer-reviewed research paper.

The paper is as follows:

Crothers, J. H. 1985. Dog-whelks: an introduction to the biology of Nucella lapillus (L.). 6: 291-360. https://learning.watfordboys.org/pluginfile.php/20239/mod_resource/content/2/Dogwhelk%20Biology%20Crothers.pdf

 

The author is an expert in the field as he has published several other studies in the field. He is part of the Field Studies Council in the UK. There are several in-text citations included in the paper. The paper also consists of a bibliography with a list of all the sources used. Furthermore, under the Acknowledgements section on page 45, the author lists the names of people who have reviewed the paper. The following is another one of several papers he has published:

http://fsj.field-studies-council.org/media/344189/vol2.5_55.pdf

 

Upon googling the author’s name, J. H. Crothers, a long list of published content can also be found with papers edited by him. Also one can find many of his papers in the Mendeley software.

Post 1: Observations

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The study sites that I have chosen for this research project are two rocky shores in Pembrokeshire, United Kingdom: Castle beach and Jetty beach. The beaches are in close proximity to one another and they are roughly a ten-minute walk apart. Each study area is approximately 0.6 metres by 15 metres. Castle beach is an exposed shore whereas Jetty beach is a sheltered shore. Castle beach consists of lower biodiversity compared to Jetty beach. It is Jetty beach has an abundance of animal and plant species. The vegetation at Jetty beach is composed of mainly seaweeds and lichens. Both beaches consist of a fair number of dog whelks. Dog whelks are also known as rock snails. The weather at the beaches in winter was sunny but cold. The temperature was about 10 °C. The beaches were visited on February 17, 2018 at 10:30 AM.

Three questions that are interesting or striking and could form the subject of my research project are:

  • How do edaphic characteristics affect the dog whelks’ abundance on Castle beach and Jetty beach?
  • How does rocky shore exposure to the tide at Castle beach and Jetty beach affect the size of dog whelks?
  • Does the sheltered shore consist of more soil nutrients than the exposed shore thereby supporting more biodiversity?

Castle beach

Jetty beach

Blog 4: Sampling Strategies

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Used the area-based method. The systematic sampling technique took 12 hr 37 min, random took 12 hr 43 min, and haphazard took 12 hr 28 min making it the fastest. Note that the different in time between the 3 different techniques is only a range of 15 minutes. Easter hemlock and sweet birch were the two most common tree species. The systematic sampling gave the lowest percent error (13.2%, 21.7%) making it the most accurate of the 3 samples.

Striped maple and white pine were the two rarest species. The haphazard sampling gave the most accurate experimental density have the lowest percent error (76.0%, 1.2%) from the 3 samples. In general the accuracy declined for the rare species and the vary low percent error for the white pine in the haphazard sample may just be luck.

Overall, the haphazard sample gave the more constant and lowest total percent error of all 4 tree species, also this took the shortest amount of time as stated in the beginning.

Note the majority of percent errors were very high which may be due to the sample size ( n=24) being too small. To experimentally collect a more accurate findings the sample size should increase to a large value, i.e. n=50.

Ongoing Field Observation

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Hypothesis: How does living moss population growing the the trunks of trees differ among trees that are sheltered, partially sheltered, or exposed to the weather?

Prediction: There will be a high population of moss on trees that are sheltered.

Response variable: moss population

(categorical)

Explanatory variable: trees snow/ rain fall exposer

(categorical)

 

 

Blog 5 – Design Reflections

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My sampling day went fairly well. I think I worked out some of the kinks in my mind beforehand, however once I was in the field collecting data I realized there were certainly things I needed to change. First of all, I was only recording presence/absence of the three lichen types on each aspect of the tree (NSEW). I have decided I want to record the percent cover of each type on each aspect of the tree, because sometimes all three types would be on one side but one was much more dominant and that information was being lost.

Secondly, I need to determine how far up and down the tree I want to sample so that there is consistency in the data. I could focus on the base of the trees, or perhaps one metre above and below breast height. I could even make transects on each tree.

Thirdly, I may need to only sample in the upper and lower forest strata, or focus my studies in the rocky outcrop only. The rocky outcrop, or Garry Oak ecosystem, at the top of Mount Douglas is quite a different community than the closed forests. All the trees were deciduous and the foliose lichen was present on every tree, whereas in the closed forest most of the trees were coniferous and the foliose lichen was only present on one of the ten trees which just so happened to be very close to the top of the mountain.

I think for my final data collection I will use the same sampling strategy that I used which is the distance based method. I used a random number generator on my phone to tell me how many paces to take on the trail, and how many paces to take perpendicular to the trail on the right or left side of the trail, then once I walked the paces I sampled the closest tree to me. I treaded carefully in the forest and was minimally invasive. Sometimes it was hard to walk a straight line because of downed logs or ditches which may have made it less random because I would sort of guess which way to walk and for that reason I may need to follow a compass bearing (I’ll think about this some more).

Finally, I would like to take replicates from more places in the park to get a more representative sample. I only sampled the southern portion for this preliminary data.

Blog Post 5 – Design Reflections

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On January 23rd from 2pm to 3pm (MST), I did my first field data collection. I chose to use the haphazard sampling method. It made it easy to select five distinct point counts across the area of study using Google maps. Point counts was an effective way of sampling bird population and human traces. However, because the haphazard method does not provide a true randomization, I am aware that the data collection might have been more effective and accurate if I had selected more than five point counts. In the future, I would either use a true random sampling method, or I would use the haphazard method while doubling the number of watch points. I think that will generate more accurate results.

Prior to collecting the data with four other observers, I pre-defined “human traces” as being any of the following: debris, food waste, a pair of footsteps, a passerby, pet or pet feces, a motorized vehicle, or any human-installed unit such as a garbage bin, picnic table, and what not. Bird feeders was one human-installed unit which was a category on its own since we assume it has a direct impact on bird population. After collecting the data, I reflected with the other observers, and we all agreed that the footsteps category was not useful, hard to count, and confusing since with the snow, there were many confounded footsteps. Counting hikers would have been sufficient. Moreover, we concluded that if this data collection had to be done again, we should count the number of nests observable at eyesight as well, and possibly the number of bird caches. I had not included those, because the species observed was the black-billed magpie exclusively, and I was worried that we would confuse other species’ nests or caches with the ones that actually belonged to the black-billed magpies. I would like to try including them next time around.

All in all, the results were not surprising as the point count which featured the most traces of human presence and also a bird feeder was the one with the highest black-billed magpie population, as expected. Still, for a second data collection, I would double the number of watch points, or use a true random sampling method, for more accurate results. Also, I would revise the pre-defined categories of human traces and keep track of nests and observed caches as well.

Cultus Lake – Initial Observations

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January 26, 2018
12:30 – 13:15
Weather: 5°C and overcast; rain earlier in the day

I have chosen Cultus Lake as my research site. It is 6.3 km2 with a maximum depth of 44 m. The lake basin is bound by International Ridge to the east, Vedder Mountain to the west, the agricultural lands of the Columbia Valley to the south, and a heavily used recreational beach to the north. The mountains around Cultus Lake are forested with mostly coniferous trees and patches of regenerating deciduous trees. The vegetation at the north end of the lake is maintained with almost no understory and only select mature coniferous trees remaining. Portions of Cultus Lake are within a Provincial Park. The park areas are largely occupied by campgrounds.  The lake attracts between 1 and 3 million tourist visits per year. The lake is subject to anthropogenic nutrient loading from agricultural activities and septic leaching.  It is home to two species at risk, the Cultus Pygmy Sculpin (Cottus aleuticus, Cultus population) and the Cultus population of sockeye salmon (Oncorhynchus nerka). The littoral areas of the lake have been invaded by invasive Eurasian milfoil (an aquatic plant). My questions are as follows:

  1. Is eutrophication of the lake leading to deep water oxygen depletion?
  2. Do fish, specifically the Cultus Pygmy Sculpin, favour portions of the lake that have higher concentrations of dissolved oxygen?
  3. If oxygen depletion does occur, does the lake fully recover during winter overturn?

 

Dissolved Oxygen vs. CPS Capture Frequency

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My project includes fish capture data (for Cultus Pygmy Sculpin; CPS) and corresponding dissolved oxygen levels.  The most challenging part of creating the graph was organizing the data into an appropriate format. I am analysing the data using Tableau Public (a free data visualization tool) which is very effective once the data is formatted.  I made a regression plot comparing CPS occurrence and dissolved oxygen concentrations. I removed the data points for minnow traps that did not yield any CPS captures, as they made the results confusing and I wanted to focus to be on where CPS are occurring as opposed to where they are not occurring.  CPS is a species at risk, so inherently it is not observed in many locations. The results were surprisingly clear.  Only 1 of the 169 captures occurred in dissolved oxygen levels of less than 7 mg/L, suggesting that CPS may have an aerobic threshold of around this level.  I find this a little surprising. I know that salmon (in general) have an aerobic threshold of around 5 mg/L. I expected CPS to be similar. Notably, this is not a huge dataset and further investigation is required before determining the aerobic threshold of CPS. This was, however, a great start.

Blog Post 3

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After observing that certain lichens tend to prefer certain sides of trees, I plan to study whether it is a NSEW preference or simply a light availability preference. This is a snapshot, observational study. After the realization I had in Haida Gwaii regarding the difficulty of identifying lichens, even to the genus level, I have decided to stick to very general growth forms: crustose (dust), foliose (leaf), and fruticose (shrub).

Date: Feb 8, 2018, Time: 1130 hrs, Weather: sunny, partly cloudy, 11C

To collect my initial field data I used a stratified random sampling method. Mount Douglas is already divided into three areas including the lower forest, upper forest, and rocky outcrop, which I used as my strata. I used a distance based method to sample trees in each strata. To assure randomization I used a random number generator phone application where first I generated the amount of steps forward on the path I would take, then I randomly generated a second number that would tell me how many steps perpendicular to the path I would take, and a third number to tell me whether I would go right or left on the path.

For the initial observations I sampled 5 trees, or replicates, in each strata. In the lower and upper forest, most trees were coniferous except 1. Foliose lichens were not present in the lower and upper forests, except for the very last tree in the upper forest that I sampled that was quite close to where the rocky outcrop started. In the rocky outcrop, foliose lichens were present on all the trees, and all the trees were deciduous garry oaks (quercus garryana). The crustose lichens were present in all three strata and on all sides of each tree.

I estimated percent canopy cover to get an idea whether light availability has an effect on where the lichens grow. In the rocky outcrop garry oak ecosystem, the trees were all deciduous, much shorter, and there was much more opening in the canopy. Foliose lichens were present on all the trees, which could be a correlation.

My hypothesis will be (Ha, alternate hypothesis): There is a significant difference in percent cover of three lichen growth types depending on the aspect of the tree trunk.

Ho (null hypothesis): There is no significant difference in percent cover of lichens depending on aspect of tree trunk.

Response variable: Percent cover of lichen (continuous)

Predictor Variable(s): Aspect of tree (categorical)

I predict that I will accept the alternate hypothesis and reject the null hypothesis.

I could add more predictor variables, such as whether the tree is deciduous or coniferous, and the layer of the forest, but this might be too complicated and require too many replicates. I have to think about this one!