Ongoing Observation

Blog Post 3: Ongoing Field Observations

Study Subject: Dandelions (Taraxacum officinale)

For my ongoing field research project, I am focusing on the growth patterns of dandelions (Taraxacum officinale) in different environmental conditions. The study takes place across three locations near my home in Mississauga, Ontario, each with varying levels of human activity and soil conditions. The goal is to understand how these factors influence the distribution, abundance, and physical characteristics of dandelions.

Field Journal Observations

  • Date: July 30th, 2024
  • Time: 13:45 – 15:30 hours
  • Location: Forested park area in Mississauga, ON
  • Coordinates: 43.5890° N, 79.6441° W
  • Weather Conditions: 24˚C, partly cloudy, humidity 65%, pressure 1012 hPa, wind 8 km/h

During my observations, I noted the presence and condition of dandelions across three specific locations within the park. Each location represents a different point along an environmental gradient influenced by soil moisture and human activity.

Location 1: Low Elevation – Near Water Source (High Moisture, Low Human Activity)

  • Observations: This area is close to a small stream at the edge of the park. The soil here is moist and rich, with minimal human disturbance. Dandelions are scattered throughout this area but are not as dense as in other locations. The plants here are relatively small, with some signs of yellowing leaves, likely due to excessive moisture.
  • Plant Characteristics: Dandelions in this location are smaller, with slightly yellowed leaves. The plants appear healthy but less vigorous compared to those in drier conditions.

Location 2: Mid-Elevation – Open Lawn (Moderate Moisture, Moderate Human Activity)

  • Observations: This area is an open lawn within the park, receiving moderate sunlight and soil moisture. Human activity is more evident here, as the lawn is maintained and mowed regularly. Dandelions are more abundant, with larger and healthier plants compared to Location 1.
  • Plant Characteristics: Dandelions in this area are more robust, with greener leaves and a higher number of flowers. The plants are taller and appear to thrive in these moderately disturbed conditions.

Location 3: High Elevation – Park Periphery (Low Moisture, High Human Activity)

  • Observations: This location is on a slight slope at the edge of the park, where the soil is dry and compacted due to frequent foot traffic. Dandelions are sparse but tend to grow taller, with more flowers per plant. The plants in this area show signs of stress, with some leaves turning brown.
  • Plant Characteristics: Dandelions here are taller but with smaller leaves. The flowers are numerous, though smaller in size, possibly due to the challenging growing conditions.

Hypothesis and Prediction

Hypothesis: The size and abundance of dandelions are influenced by soil moisture and the level of human activity.

Prediction: Dandelions in areas with moderate moisture and human activity (such as Location 2) will show the healthiest growth, while those in areas with either too much or too little moisture (Locations 1 and 3) will exhibit signs of stress and reduced growth.

Experimental Design: Variables

  • Response Variable: Dandelion plant size (continuous) – Measured by plant height, leaf length, and flower count.
  • Explanatory Variable: Soil moisture and human activity (categorical) – Classified by proximity to water source and human disturbance level.

2 thoughts to “Ongoing Observation”

  1. I think your field study is really interesting! Your observations are clear, and the hypothesis is general, also linking soil moisture and human activity to dandelion growth patterns. Your observations are organized well and easy to follow. I know you mention it in you response variable, but I wonder stating exactly how you plan to quantify “healthiest growth” in your prediction would make it more specific. The predictor and response variables seem that they should be easy to measure in a field study. How are you categorizing human activity? I wonder if some potential confounding variables could include sunlight exposure, soil composition, or nutrient levels. Overall, I think you’ve done a great job connecting your observations to your hypothesis and creating a clear prediction!

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