Category: Percy Hebert

Post 1: Observations

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Initial Field Observations

Date: January 12, 2021           Time: 2:00pm – 2:30 pm                     Temperature: 0°C

Weather: overcast                   Location: yard around my house        Season: Winter

Side view of initial observation area
Aerial view of initial observation area

The yard is approximately 2.5 acres of flat grassland with a few trees along one edge and neighbors and a road on the others. The treed edge is the edge of a cliff leading down to a riparian area along a creek in the valley below. There is a beaver dam built in the creek below the house. Across the road is a mountain slope up to a plateau. The area is agricultural with most of the surrounding properties having various types of livestock.

The entire yard is covered in snow. No fresh snow for the past few days and snow on the ground has a hard crust. Minimal vegetation visible. Front yard has one large willow tree and a small lilac bush. The back yard has a large Blue Spruce, a small stand of Aspen on the cliff edge, and a small maple tree. Dormant Saskatoon bushes between the road and property edge. No dead grasses visible due to depth of snow. A few cones visible under the Blue Spruce in the back yard. No animals were observed during this observation session. No tracks, scat or evidence of any animals seen.

When examining the willow tree, many rows of fairly uniformly sized and spaced holes were discovered in the bark. Three small mushrooms were also observed to be growing on the willow but I was unable to tell if they were currently alive. An old bird’s nest was also seen in the branches of the willow. Bark damage to one of the aspen trees on the cliff edge was noted and photographed. The bark of the aspen trees was also noted to be green on some sides of some trees.

Holes in willow tree

Three questions that could be investigated further:

1) Holes in the willow tree: What made them? How can they make them so uniform? Why?

2) Green aspen bark: Why is it green? Why isn’t every tree green? Why only on some sides of the tree?

3) Mushrooms on the willow: Are they alive in the winter? If so, how can they stay alive in winter conditions?

Blog Post 2: Sources of Scientific Information

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The source of ecological information I have chosen to evaluate is “A note on the observable bark coloration of quaking aspen (Populus tremuloides)” from the Western North American Naturalist.

Using the course information on how to evaluate sources of scientific information I would classify this article as academic, peer-reviewed research material.

This article is academic because both authors are associated with the University of Colorado. The article also contains in-text citations and a list of all cited literature. It is peer-reviewed because it specifically mentions anonymous editors in the acknowledgment section of the article. This article is research material because it contains methods and results sections.

Article link:

Rabinowitz, Oren and Tripp, Erin A. (2015) “A note on the observable bark coloration of quaking aspen (Populus tremuloides),” Western North American Naturalist: Vol. 75 : No. 3 , Article 12. Available at: https://scholarsarchive.byu.edu/wnan/vol75/iss3/12

Post #4: Sampling Strategies

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The Virtual Forests Tutorial revealed results that were surprising in varying degrees. I did the area based tutorial, and I think the most surprising aspect was that there wasn’t a single technique that produced the highest accuracy 100% of the time. While performing the tutorial, I thought that the random sampling method would produce the most accurate results because of the unbiased nature of the design: quadrats were scattered randomly throughout the entire study area as opposed to the single transect line of the systematic design. I assumed the haphazard design would produce the least accurate results (which it generally did), though I attempted to place the haphazard quadrats in spots that seemed “representative” or at least kind of random.

The systematic design had the fastest estimated time at 12 hours 4 minutes, which makes sense as it requires quadrats to be placed along a single line, or bearing. However it wasn’t faster by that much – all three sample designs were estimated to take between 12 and 13 hours.

As far as accuracy was concerned, the most common species encountered had the highest degree of accuracy in abundance estimates, and the accuracy of the estimates was relatively high in both systematic and random sampling placement strategies with random placement marginally the most accurate (except that it did not capture any data on the rarest species); the haphazard placements did not produce accurate abundance estimates for the common species. As a species abundance became scarcer, accuracy went down, except for the capturing of the rarest species (white pine) by the systematic placement of the quadrats, which (out of luck I presume) managed to pick up virtually all of the actual individuals in the sampling area.

Overall, it seemed like the number of samples was adequate to accurately quantify the most common species and would likely be sufficient in a relatively homogenous stand with uniform characteristics, but I would probably want more plots/quadrats if I was striving to capture rare species or a distribution pattern that was more clumped. If I could, I would attempt to use either random or systematic as my sampling placement strategy.

Blog Post 4: Sampling Strategies

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After completing the virtual survey of the Snyder-Middleswarth Natural area, there were some interesting observations in regards to the time and accuracy for each sampling method in relation to the population density.

Survey Stats

Fig 1.0 – Survey Stats

 

OBSERVATIONS REGARDING DATA:

The technique which had the fastest estimated sampling time turned out to be the systemic transects at 12 hours and 35 minutes.

The percentage of error was lowest with the haphazard selection. This was surprising because it allows for inherent bias. When I conducted the virtual selection of survey quadrats, 5 locations were selected in the medial aspect of each topographical section, and spaced equally from west to east. This way a similar sample location was chosen along each topographical feature.
The fact that this was the lowest percentage of error is surprising as I was worried my bias would affect the outcome, but apparently because I applied a system it actually negated an increase in error.

The species abundance also affected accuracy. As the abundance decreased, we saw a decrease in accuracy. The accuracy could likely be improved with an increased sampling size. With any sampling, the lower sample size runs a higher percentage of error.

Overall the haphazard selection appeared to be more accurate than others, but likely due to the systematic bias I introduced by surveying plots equally distanced from one another in an almost grid shaped pattern.

 

 

 

 

 

Post #3 Ongoing Field Observations

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I initially went out to my field site with the hopes of finding patterns in the way shrub species such as Amelanchier alnifolia and Salix were responding to browse pressure by moose. Looking at percent cover of biomass, horizontal growth patterns, or length of new shoots, I wasn’t able to imagine a study design that could answer specific questions, or maybe I just couldn’t formulate questions that lended themselves to good scientific study.

Thoughts on browse patterns

So I moved on to several places around my lake where Aspen stands have sent out suckers following beaver disturbance that ended some time ago, observing the gradient between the older stand and the younger individuals that have come up.

I also noticed other places where aspen were encroaching on fields or human-cleared sites, and some of these had distinctive successional gradients, too. And now to come up with a study design:

Aspen succession observations

1.) Identify the organism or biological attribute that you plan to study.

I plan to study Aspen trees in the process of succession.

2.) Use your field journal to document observations of your organism or biological attribute along an environmental gradient. Choose at least three locations along the gradient and observe and record any changes in the distribution, abundance, or character of your object of study.

One location is inside the parent clone of the aspen organism, where the individuals are mature with similar ages (presumably) and similar sizes (heights and diameters). Also noteworthy may be variables such as density, basal area, and incidence of health or pathological indicators such as conk.

Transition between aspen parent and offspring

A second location along the gradient is where there is an obvious shift in the clone’s attributes such as size, age, and density; i.e. where the aspen clone initially sent out suckers in response to the disturbance from years ago, and there is a higher abundance of individuals.

The third location along the gradient is the point at which there are no longer any suckers coming up, or where the suckers are obviously young or new clones, and maybe more abundant. In some places, shrub species are present in varying numbers/densities at this point on the gradient with varying levels of browse, and some of the aspen suckers are also being affected by browse pressure. Could the aspen be responding to browse pressure by continually putting out new suckers?

3.)Think about underlying processes that may cause any patterns that you have observed. Postulate one hypothesis and make one formal prediction based on that hypothesis. Your hypothesis may include the environmental gradient; however, if you come up with a hypothesis that you want to pursue within one part of the gradient or one site, that is acceptable as well.

Several processes are likely acting on the aspen trees to cause differences in the way they expand and fill the spaces they occupy following disturbances. Aspect, slope, and time are definite variables influencing the rate of aspen expansion I would think. I’m also curious about how the age and density of the parent stand at the time of clonal expansion influences how the younger clone individuals proliferate/spread. Many potential hypotheses to pursue…this project may incorporate the Hypothetico-Deductive Method approach.

I think I’ll start with age of the parent stand influencing how the younger clones develop. I hypothesize that the older the parent stand, the less its offspring will spread, or the less biomass will be produced by offspring. Framed another way, I hypothesize that the younger and “more vigourous” the parent stand is, the denser (or taller or further-travelled) the offspring will be.

4.) Based on your hypothesis and prediction, list one potential response variable and one potential explanatory variable and whether they would be categorical or continuous. Use the experimental design tutorial to help you with this.

Response variable: Density of the younger aspen. Or height to age ratio of younger aspen. This is continuous.

Predictor variable: Age of the parent stand. Though ascertaining the age of multiple trees would provide a continuous dataset, in this case (because aspen are clones) the parent stand’s age may be categorical, e.g. “veteran, mature, older immature” etc.

If I were to predict that offspring density or site index (a continuous variable) would be affected by the parent’s age as categorical, the statistical design would be ANOVA.

If I were to predict that offspring density or site index (a continuous variable) would be affected by the parent’s age in years (or density, basal area, site index – continuous variables), the design would be a regression analysis.

Blog Post 4: Sampling Strategies

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For the virtual sampling tutorial, I chose to use area-based sampling for the Snyder-Middleswarth Natural Area. Results are shown in figure 1.

Figure 1: Virtual Sampling Results for 

As shown in the results table, all three sampling methods took over 12 hours to complete, with the random method being the longest at 13 hours and 13 minutes. The two most common species encountered were Eastern Hemlock and Sweet Birch, while the two least encountered (rare) species were Striped Maple and White Pine. Random sampling had the lowest percent error for the Eastern Hemlock, while systematic had the lowest for Sweet Birch. Systematic had a 100% percent error for the two rarest species, Striped Maple and White Pine. Haphazard had the lowest percent error for Striped Maple, while random had the lowest for White Pine, with haphazard only being slightly higher. Systemic generally improved greatly in percent error as species abundance increased. This was also generally true for random sampling as well. Haphazard did not show a consistent trend either way in terms of percent error with a change in species abundance as it greatly improved for the second rarest species but got much worse for the rarest species. For abundant species, I would say that systematic is likely to be the most accurate while haphazard would be the least accurate. For the rare species, systematic is likely to be the least accurate. With 24 sample points, haphazard was able to be quite accurate for Striped Maple but much less accurate for White Pine. This is likely a chance event and I would expect if this was repeated the percent error would be higher for Striped Maple. Likewise, systematic was not very accurate in sampling both rare species in which case increasing the number of sample points would likely improve the degree of accuracy.

Blog Post 3: Ongoing Field Observations

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For my ongoing field observations, I visited Pipers Lagoon on Sunday, January 17th at 9:43 am.  The weather was overcast, 6 degrees in temperature, and no wind.

 

1. Identify the organism or biological attribute that you plan to study.

The organism I plan to study is the Broad-Leaved Stonecrop, sedum Spathurifolium.

 

Figure 1: Broad-Leaved Stonecrop

2. Use your field journal to document observations of your organism or biological attribute along an environmental gradient. Choose at least three locations along the gradient and observe and record any changes in the distribution, abundance, or character of your object of study.

 

 

During my first field observation, I had noted that the Broad-Leaved Stonecrop was generally only found along the ocean-facing rocky outcrops and not present on the lagoon facing ones. The plant is able to grow within various cracks and crevasses in the rocky outcrops. During this field observation, I decided to use the elevation from sea level as my gradient as well as exposure to the sun and the ocean. I also decided to focus on just the headland island portion of the park. 

I chose three different locations along the headland island, all with similar topography (open, exposed cliffs, primarily moss/lichen/stonecrop dominant). These were the northeast rocky outcrop, northwest rocky outcrop, and the south/southwest portion of the headland island. 

Figure 2: Observation Locations

Along the rocky outcrop of the northeast side of the headland island, the stonecrop generally grew from mid to high elevation from sea level, with no growth at all below the high watermark. It was typically most abundant mid to high elevation, with less abundance along the plateau. As the amount of sun exposure throughout the day differed (i.e morning vs afternoon) it was noted that the abundance and distribution of the stonecrop increased (i.e more abundant and more area covered along the west side of the rocky outcrop than the east). Again, the growth was most pronounced at mid to high elevation and tapered off along the plateau. It was also noted that the stonecrop more exposed to the sun throughout the day had a more reddish color to its leaves than those that were in less sun-exposed areas.

The northwest rocky outcrop of the headland island had a similar growth regime (i.e mid to high elevation, tapering off at the plateau). It was noted that the stonecrop distribution spread beyond strictly the rocky outcrop on this portion of the headland island. A large abundance was observed along a steep slope farther inland than the rocky outcrop.

The Southwest portion of the headland island had virtually no presence of stonecrop, despite being a similarly rocky, sun-exposed area. However, there was certainly more soil and much less hard rock here than the more sea cliff type rocky outcrops in the other areas. This area also has no exposure to the open ocean while elevation gain from sea level was much more gradual and smaller than the much sharper increase in northeast and northwest portions of the headland island.

 

3. Think about underlying processes that may cause any patterns that you have observed. 

 

Some underlying processes that may cause the patterns observed include the moisture and drainage of the substrate that the stonecrop grows in, the type of substrate, and the amount of sunlight exposure.

Postulate one hypothesis and make one formal prediction based on that hypothesis. Your hypothesis may include the environmental gradient; however, if you come up with a hypothesis that you want to pursue within one part of the gradient or one site, that is acceptable as well.

Based on my observations of where the stonecrop was found to be thriving I hypothesize that stonecrop abundance is negatively impacted by increased substrate moisture. Therefore I predict that the stonecrop will be most abundant in areas with at least half-day sun exposure and bare, exposed rock.

 

4. Based on your hypothesis and prediction, list one potential response variable and one potential explanatory variable and whether they would be categorical or continuous. Use the experimental design tutorial to help you with this.

 

One potential response variable would be the abundance of stonecrop while one potential explanatory variable is substrate type. Substrate type would give an indication of the amount of moisture the stonecrop is exposed to as well as the drainability of water in the area. The response variable would be considered continuous (i.e abundance in terms of percent cover) while the predictor variable would be considered categorical (i.e type of substrate). This would classify the experimental design as being ANOVA.

Field Notes:

 

Blog Post 3: Ongoing Field Observations

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For the course project I have been gathering data on the ecology and communities of a 1km x 1km area in western Ukraine.  The following information contains both my ongoing field observations and my considerations regarding a possible hypothesis.

Organism or Biological Attribute:
For the course project I have chosen to study the Eastern European Mole, and how it interacts with local predators such as dogs and cats.

Documentation:

I have been observing and documenting mole colonies, dog sightings, cat sightings, weather conditions, and mole hill activity over the last month in the observation areas. Specifically Zone 9, Zone 15, Zone 12, and zone 7.  Contrasting to this, there is a single Zone I have been documenting called ‘Control zone’ east of the observation area which has no Canine or Cat activity observed.

Example of Zone observations
Example of Zone observations

Gradients Observed:

TOPOGRAPHY: In the control area, there is a gradient of topography with approximately a linear grade from the southern aspect dropping approximately 12 feet to the northern most aspect. Of note there is approximately an 8 foot gully near creek on western aspect of observation area.

VEGITATION: The general area which the moles are observed is the grassed areas which sit on a sandy aggregate soil.

PREDATORY CONCENTRATION: There appears to be a higher concentration of predators in north western aspect of observation areas, but less in south eastern area either due to topography,  territorial behavior, access to food, or a combination there of.

GROUND: Keeping in mind soil types change throughout the area. Again, the mole hills appear in sandy soil but the depth gradient of tunnels is not able to be directly observed despite the research on moles that indicates that these can go as deep as 6 feet. There is a carpet of decomposing leaves and rich soil under the oak trees (often thick with acorns) but little to none under pine trees.

TEMPORAL: Over time the count of active mole hills, spoor, coil conditions, and weather changes which may affect activity levels of all organisms in observation area.

 

Three locations inside the Observation area are:
——————————–
North west aspect of Zone 9 – Medium to low dog activity in area/transit point no sleeping
Northwestern Aspect of Zone 15 – Low dog activity in area as they adhere to eastern aspect for midday sleeping.
South eastern aspect of Zone 7 – High Dog activity due to transit+sleeping area
Central area of Zone 12 – Low mole hill count, high dog activity during midday.
Control area: Zero dog/cat activity – Zone A (east of map)

Area of Observation
Area of Observation

Processes and Patterns

Anecdotally the mole hills appear more populus and active in zone 9 and 15, as well as the control area to the east. This seems to be inverse to the dog activity in those areas. The temperature changes over time seem to affect the mole activity to some extent.

Hypothesis

The number of predatory dogs and cats in the area directly effects the activity of the colonies in the observation area.

Response variable(continuous): Mole hills along the gradient of dog activity.
Explanatory/Predictor variable (continuous): Number of dogs in the area (based on sightings and new signs)

Initially this appears that a study for this hypothesis would be of a regression design

 

Blog Post 2: Sources of Scientific Information

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The source of scientific ecological information I have chosen to evaluate is “Linkage of Plant Trait Space to Successional Age and Species Richness in Boreal Forest Understorey Vegitation”, a journal article found in the Journal of Ecology Volume 103.

 

This article should be categorized as non peer-reviewed academic material for the following reasons:

The article is written by a number of experts, each with their own noted qualifications, working at prestigious schools. It has in-text citations throughout and contains a rich bibliography at the end. However, the article does not overtly identify a referee prior to publication as it does not contain any critique or evaluation.

 

Original Article Information:

Kumordzi, Bright B., et al. “Linkage of Plant Trait Space to Successional Age and Species Richness in Boreal Forest Understorey Vegetation.” Journal of Ecology, vol. 103, no. 6, 2015, pp. 1610–1620., www.jstor.org/stable/24542707. Accessed 13 Jan. 2021.

Blog Post 2: Sources of Scientific Information

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The source of scientific information I have chosen for this post is titled Spatial patterns and competition of tree species in a Douglas‐fir chronosequence on Vancouver Island. The article was found using google scholar and can be accessed here: https://onlinelibrary.wiley.com/doi/full/10.1111/j.2006.0906-7590.04675.x

Based on the module 1 tutorial on how to evaluate sources of scientific information I would classify this source as academic, peer-reviewed research material. My reasoning is as follows.

The authors are all affiliated with either universities or relevant scientific research centres as shown in Figure 1. This demonstrates relevant expertise on the subject matter.

Figure 1: Author Affiliation

The material also has both in-text citations and a bibliography listing all sources used as shown in Figure 2.

Figure 2: Bibliography

The material is published in the journal Ecography which has a double-blind peer review process for publishing content as described in their author guidelines shown in Figure 3.

Figure 3: Double Blind Peer Review

Lastly, the paper contains both a methods and results section demonstrating that it has undergone research as shown in figures 4 and 5.

Figure 4: Methods Section

Figure 5: Results Section