Distribution and Abundance of Species Revision Notes for OCR A-Level Biology A

Distribution and Abundance of Species

Understanding biodiversity measurements

Measuring biodiversity involves more than simply creating a species list. While species richness (the total number of different species in an area) provides important information, it does not reveal the full picture of an ecosystem's biodiversity.

A species list is qualitative — it identifies which species are present but provides no information about how common or rare each species is. For example, one species might dominate an area while all others are rare, or the species might be evenly distributed. These two scenarios represent very different levels of biodiversity despite having identical species richness.

infoNote

The distinction between qualitative and quantitative data is crucial in ecology. A qualitative species list tells you "what is there" but not "how much" — limiting its usefulness for comparing different habitats or monitoring changes over time.

Species evenness measures the relative abundance of different species in an area. High species evenness, where all species are present in similar numbers, indicates high biodiversity. Low species evenness, where one or a few species dominate, indicates lower biodiversity even if species richness is high.

Quadrat sampling methods

The quadrat is the standard apparatus for assessing the abundance of species in an area. Quadrats create defined sampling areas of known size, allowing researchers to make comparable measurements across a habitat.

Types of quadrats

Three main types of quadrat are used in ecological surveys:

Open frame quadrats: Simple squares of known area, typically $0.25\,\text{m}^2$ or $1\,\text{m}^2$ , used for counting individual organisms
Gridded quadrats: Divided by wires or string into smaller sections (commonly $5 \times 5$ or $10 \times 10$ grids), making percentage cover estimation easier
Large-scale quadrats: Marked out using tape or GPS coordinates, used for surveying large areas or trees

Measuring abundance with quadrats

Quadrats enable three different methods of measuring species abundance, each suited to different situations and species types.

Species frequency is the percentage of quadrats that contain a particular species. Calculate this by dividing the number of quadrats containing the species by the total number of quadrats sampled, then multiply by $100$ .

$\text{Species frequency} = \frac{\text{number of quadrats containing species}}{\text{total quadrats}} \times 100\%$

Species density counts individual organisms within quadrats and expresses the result as numbers per unit area (usually per $\text{m}^2$ ). This method works well for discrete individual plants or slow-moving animals but becomes impractical for very abundant or difficult-to-separate species.

$\text{Species density} = \frac{\text{total number of organisms}}{\text{total area sampled}}$

Percentage cover estimates the proportion of the quadrat area occupied by each species. This is the most practical method for abundant species like grasses where counting individuals is impossible. Each grid square in a $10 \times 10$ gridded quadrat represents $1\%$ of the total area, simplifying estimation.

chatImportant

Choosing the Right Measurement Method:

Use frequency when presence/absence is more practical than counting
Use density for discrete, countable organisms (individual plants, slow-moving animals)
Use percentage cover for abundant or mat-forming species where individual counting is impossible (grasses, mosses, algae)

lightbulbExample

Worked Example: Calculating Frequency and Density

Table

Using the dandelion data shown:

Dandelions appeared in quadrats $1$ , $2$ , $4$ , $5$ , $6$ , $9$ , and $10$ — a total of $7$ out of $10$ quadrats
Species frequency = $\frac{7}{10} \times 100 = 70\%$

For density calculation:

Total dandelions counted = $2 + 6 + 0 + 3 + 7 + 3 + 0 + 0 + 8 + 4 = 33$ plants
Total area sampled = $10 \times 0.25\,\text{m}^2 = 2.5\,\text{m}^2$
Species density = $\frac{33}{2.5} = 13.2$ plants per $\text{m}^2$

Selecting appropriate quadrat size

The quadrat must be large enough to include a reasonable number of species but small enough to be practical. Too small, and many quadrats will be empty; too large, and sampling becomes time-consuming.

Researchers test different quadrat sizes and plot species number against area. When the graph levels off (species number becomes relatively constant), the quadrat size is appropriate. In the example shown, species number continues increasing up to $64\,\text{m}^2$ , but the rate of increase slows considerably after $8\,\text{m}^2$ . Practical considerations often mean using smaller quadrats ( $1\,\text{m}^2$ ) with more samples rather than fewer very large quadrats.

Random sampling

Random sampling prevents bias in data collection. If researchers only sampled easy-to-reach areas or visually interesting patches, results would not represent the whole habitat accurately.

infoNote

Why Random Sampling Matters: Human observers naturally gravitate toward interesting or accessible areas. Random sampling ensures every part of the habitat has an equal chance of selection, producing data that truly represents the entire study area rather than just the convenient or unusual parts.

The random sampling procedure involves:

Lay two tape measures at right angles along two edges of the study area
Generate random number pairs using a calculator or mobile app
Use these as coordinates to position each quadrat
Sample at each randomly selected location

Random sampling ensures that every part of the habitat has an equal chance of being sampled. If the habitat is uniform, sampling $5-10\%$ of the total area provides representative data.

Sampling mobile animals

Quadrats work well for plants and slow-moving animals but are ineffective for mobile species. Several alternative methods exist for sampling animals that move quickly or avoid detection:

Pitfall traps: Jars buried in the ground with sheltering material (paper/cardboard) and a rain cover, collecting ground-dwelling invertebrates
Beating trays: White sheets placed under trees which are then shaken, dislodging invertebrates for collection
Sweep nets: For catching flying insects or those in long grass
Pond nets: Strong nets for collecting aquatic organisms
Pooters: Small devices for collecting tiny invertebrates by suction

Estimating population size using mark-release-recapture

The Lincoln index estimates population sizes of mobile animals through a mark-release-recapture process, providing quantitative data when direct counting is impossible.

The mark-release-recapture procedure:

Capture a sample of animals ( $S_1$ ) and mark them harmlessly (e.g., non-toxic paint on snail shells, fur clipping on small mammals)
Release the marked animals back into the habitat
Allow time for marked individuals to mix thoroughly with the unmarked population
Recapture a second sample ( $S_2$ ) and count how many are marked
Calculate population size using the Lincoln index formula

$\text{Population size} = \frac{S_1 \times S_2}{\text{number marked in } S_2}$

The logic behind this method: if many marked individuals appear in the second sample, the total population must be small. If few marked individuals are recaptured, the total population is large.

lightbulbExample

Worked Example: Pond Snail Populations

Table

For pond snails:

$\text{Population} = \frac{31 \times 69}{6} = \frac{2139}{6} \approx 357 \text{ snails}$

For ramshorn snails:

$\text{Population} = \frac{19 \times 5}{2} = \frac{95}{2} \approx 48 \text{ snails}$

chatImportant

Critical Assumptions for Mark-Release-Recapture:

Marks must not harm animals or make them more visible to predators
Sufficient time must elapse for mixing (typically $24$ hours)
The population must be closed (no births, deaths, immigration, or emigration between samples)
Marked and unmarked individuals must have equal chances of recapture
Marks must remain visible throughout the study period

Simpson's index of diversity

Simpson's index of diversity ( $D$ ) combines species richness and evenness into a single value, making biodiversity comparison between sites straightforward. This index is more informative than species richness alone because it accounts for both the number of species and how evenly distributed they are.

The formula is:

$D = 1 - \sum\left(\frac{n}{N}\right)^2$

Where:

$n$ = number of individuals of each species
$N$ = total number of all individuals
$\sum$ means "sum of"

lightbulbExample

Worked Example: Calculating Simpson's Index

Species	Number ( $n$ )	$n/N$	$(n/N)^2$
dandelion	$40$	$0.154$	$0.0237$
daisy	$150$	$0.579$	$0.3352$
buddleia seedlings	$3$	$0.012$	$0.00014$
ragwort	$5$	$0.019$	$0.00036$
plantain	$18$	$0.069$	$0.0048$
groundsel	$15$	$0.058$	$0.0034$
willowherb	$11$	$0.043$	$0.0018$
spurge	$17$	$0.066$	$0.0044$
Totals	$259$		$0.3738$

Step 1: Calculate $n/N$ for each species (divide each species count by total $259$ )

Step 2: Square each $n/N$ value to get $(n/N)^2$

Step 3: Sum all $(n/N)^2$ values: $\sum(n/N)^2 = 0.3738$

Step 4: Subtract from $1$ :

$D = 1 - 0.3738 = 0.63$

Interpreting Simpson's index

The value ranges from $0$ to $1$ :

$D$ near $0$ indicates low diversity (one or few species dominate)
$D$ near $1$ indicates high diversity (many species with similar abundances)

infoNote

The calculated value ( $0.63$ or $63\%$ ) represents the probability that two randomly selected individuals belong to different species. Higher values indicate more stable, resilient communities better able to withstand environmental pressures or pollution.

In the example above, the moderate value ( $0.63$ ) reflects that while multiple species are present, daisies dominate the community ( $150$ out of $259$ individuals), reducing overall evenness.

Non-random sampling methods

While random sampling provides the most representative data, three non-random approaches are sometimes necessary when specific research questions or practical constraints make random sampling inappropriate.

Opportunistic sampling

Researchers sample locations based on convenience or accessibility rather than random selection. This method is quick but potentially biased — easily accessible areas may differ systematically from the whole habitat.

infoNote

Opportunistic sampling is useful for preliminary surveys or when time and resources are extremely limited. However, results should be interpreted cautiously and never used to make population estimates or strong ecological conclusions about the entire habitat.

Stratified sampling

When a habitat contains distinct zones occupying different proportions of the total area, stratified sampling ensures fair representation. The proportion of samples taken from each zone matches its proportion of the total area.

For example, if woodland occupies $80\%$ of a study area and grassland $20\%$ , then $80\%$ of quadrats should be placed in woodland and $20\%$ in grassland.

lightbulbExample

Worked Example: Stratified Sampling of Bluebells

The bluebell study demonstrates stratified sampling in practice:

Woodland area: $240\,\text{m}^2$ (sampled with $12$ quadrats)
Open grassland: $60\,\text{m}^2$ (sampled with $3$ quadrats)
This maintains the $4:1$ area ratio, ensuring each habitat type is fairly represented

Within each zone, quadrat placement should still be random to avoid bias.

Systematic sampling using transects

Systematic sampling works best when investigating how species distribution changes across environmental gradients (e.g., from shore to inland, up a mountain, or across a field boundary).

A transect is a line placed across the habitat. Two types exist:

Line transects record which species touch the line at regular intervals (e.g., every $0.5\,\text{m}$ ). This qualitative method quickly shows community changes but provides limited abundance data.

infoNote

The sand dune transect illustrates how plant communities change with distance from the sea and elevation, showing increasing species richness from beach ( $0$ species) to woodland ( $19$ species). This pattern reflects changing environmental conditions — from harsh, salt-exposed conditions near the sea to more sheltered, stable conditions inland.

Belt transects provide quantitative data by placing quadrats along the transect line. Two approaches exist:

Continuous belt transects: Quadrats placed end-to-end with no gaps (used for short distances)
Interrupted belt transects: Quadrats placed at intervals (more practical for long distances)

Results from belt transects are displayed as kite diagrams, which visually represent species abundance changes along the transect.

To construct a kite diagram:

Draw a vertical scale for abundance (percentage cover, density, or count)
Mark sampling stations along the horizontal axis
Plot abundance values above and below a central line
Connect the points to create a symmetrical "kite" shape for each species

The width of each kite at any station represents that species' abundance at that location, allowing quick visual comparison of distribution patterns.

ACFOR abundance scale

When species are too numerous to count accurately, the ACFOR scale provides semi-quantitative abundance data:

Abundant
Common
Frequent
Occasional
Rare

chatImportant

Clear definitions must be established before using the ACFOR scale (e.g., "abundant = covers more than $50\%$ of quadrat area"). Without standardized definitions, different observers may classify the same species differently, making data comparison impossible.

bookmarkSummary

Key Points to Remember:

Species richness counts different species; species evenness measures their relative abundances — both are needed to assess biodiversity fully
Quadrats enable three abundance measurements: frequency (percentage of quadrats containing species), density (individuals per unit area), and percentage cover (proportion of area occupied)
Random sampling uses random coordinates to prevent bias and ensure representative data — every part of the habitat must have equal chance of selection
The Lincoln index estimates mobile animal populations through mark-release-recapture: $\text{Population} = \frac{S_1 \times S_2}{\text{marked in } S_2}$
Simpson's index ( $D = 1 - \sum(n/N)^2$ ) combines richness and evenness; values near 1 indicate high diversity, values near 0 indicate low diversity
Transects (line or belt) sample systematically along environmental gradients, with results displayed as kite diagrams showing distribution patterns along the gradient

Distribution and Abundance of Species (OCR A-Level Biology A): Revision Notes