Sampling Techniques and Species Abundance

Step-by-Step: The Random Sampling Method

When describing this required practical in an exam, you must provide a logical sequence of steps.

1. Lay two long tape measures (e.g., $20\text{m}$) at right angles to create a grid across your survey area.
2. Use a random number generator (like a calculator or an app) to obtain random coordinates (e.g., $x = 4$, $y = 12$).
3. Place the quadrat exactly at the intersection of these coordinates.
4. Count and record the number of the target species inside the quadrat.
5. Repeat this process at least 10 times. A larger sample size (e.g., 30 quadrats or $5\%$ of the total area) increases the reliability and validity of your final estimate.

• When counting, you must apply a consistent "Edge Rule". For example, only count an organism if it is more than halfway inside the quadrat or touching the top or left edges, ignoring those on the bottom or right.
• If a species is too difficult to count individually (like grass or moss), ecologists estimate the percentage cover instead.

Measuring Distribution: Systematic Sampling

Now think about walking away from a large, shady oak tree into a sunny field. The types of plants change as the light level changes.

• To investigate how the distribution of a species changes across an environmental gradient (a gradual change in an abiotic factor like light, soil moisture, or altitude), we do NOT use random sampling.
• Instead, we use systematic sampling along a transect.
• A transect is simply a tape measure stretched in a straight line across the habitat.

Step-by-Step: The Transect Method

1. Stretch a tape measure (transect line) in a straight line across the environmental gradient.
2. Place a quadrat at the $0\text{m}$ mark (your initial sample).
3. Count the target species and measure the relevant abiotic factor (e.g., using a light meter or soil moisture probe) at that exact location.
4. Move the quadrat to the next fixed interval (e.g., every $2\text{m}$) along the tape and repeat the measurements. This specific technique is called a belt transect.
5. Repeat the entire process with at least two more parallel transect lines to calculate a mean abundance at each distance.

• Results from transect data are often plotted on a Kite Diagram, where the x-axis shows distance along the transect and the width of the "kite" shows the abundance of the species.

Processing Ecological Data: Central Tendency

Once you have collected your data, you must process the raw numbers to find the central tendency. This allows you to make estimates for the whole area.

• The mean is the sum of all values divided by the total number of values.
• The mode is the most frequently occurring value in the dataset. If the data is grouped into categories (e.g., 0-5 plants), this is called the modal class.
• The median is the middle value when the data is ordered numerically.
• The range is the difference between the highest and lowest values, indicating how spread out the data is.

When calculating a mean, you must look out for anomalous results. These are data points that do not fit the general pattern. In AQA exams, you must identify, circle, and exclude anomalies from your mean calculation.

Worked Example: Calculating Mode, Median, and Mean

A student counted dandelions in 10 quadrats. The results were: $4, 7, 2, 4, 1, 0, 4, 28, 3, 7$. Calculate the mode, median, and mean number of dandelions per quadrat.

Step 1: To find the mode, identify the most frequently occurring value in the dataset.

• The value $4$ appears three times, which is more often than any other number.
• Mode = $4$

Step 2: To find the median, order the raw data from lowest to highest.

• Ordered data: $0, 1, 2, 3, \mathbf{4, 4}, 4, 7, 7, 28$.
• There are 10 values, so the median is halfway between the 5th and 6th values.
• Both middle values are 4.
• Median = $4$

Step 3: To find the mean, first check for anomalies.

• The value $28$ is clearly an anomaly. Exclude it from the calculation.

Step 4: Calculate the mean with the remaining 9 values.

• $\text{Mean} = (4 + 7 + 2 + 4 + 1 + 0 + 4 + 3 + 7) \div 9$
• $\text{Mean} = 32 \div 9 = 3.56$

Worked Example: Estimating Population Size

Why does this matter? We can use our processed data to estimate the entire population of a habitat using a specific scaling-up formula:

$$\text{Estimated Population Size} = \frac{\text{Total Area}}{\text{Area Sampled}} \times \text{Total number of organisms found}$$

A field has a total area of $400\text{m}^2$. A student places ten $0.25\text{m}^2$ quadrats randomly across the field and counts a total of 30 dandelions. Estimate the total population of dandelions in the field.

Step 1: Calculate the total area sampled.

• $\text{Area Sampled} = 10 \text{ quadrats} \times 0.25\text{m}^2 = 2.5\text{m}^2$

Step 2: Substitute the known values into the formula.

• $\text{Total Area} = 400\text{m}^2$
• $\text{Area Sampled} = 2.5\text{m}^2$
• $\text{Total organisms found} = 30$

Step 3: Calculate the final estimate.

• $\text{Estimate} = \left(\frac{400}{2.5}\right) \times 30$
• $\text{Estimate} = 160 \times 30 = 4,800 \text{ dandelions}$