Abiotic Factors, Interspecific Interactions and Quadrat Sampling Revision Notes | A Level AQA Biology

1. Why Do Organisms Live Where They Do?

Walk from a shaded woodland floor into an open meadow and the plant species change almost immediately. That shift is not random — it is driven by measurable physical conditions called abiotic factors. Understanding these factors is the first step to explaining why any organism lives where it does.

Abiotic factors are the non-living components of an environment. They include light intensity, temperature, water availability, pH, mineral ion concentration, and oxygen availability. Each factor can act as a limiting resource, meaning that if it falls outside a species' tolerance range, that species cannot survive there.

Consider light intensity as a concrete example. In a dense woodland, the canopy intercepts most incoming light. Only shade-tolerant species — those with broad, thin leaves and high chlorophyll concentrations — can photosynthesise effectively at low irradiance. Species requiring high light intensity are absent, not because of predation or competition, but because a single abiotic variable falls below their threshold.

Abiotic factors rarely act in isolation. A coastal rock pool, for instance, experiences simultaneous variation in salinity, temperature, oxygen concentration, and pH across a single tidal cycle. Organisms present must tolerate the combined range of all these variables — which is why rock pool communities are relatively species-poor compared with stable subtidal habitats.

2. Interactions Between Organisms: Competition and Predation

Abiotic factors set the stage, but organisms also shape each other's populations through biotic interactions. The two most important categories for AQA are competition (interspecific and intraspecific) and predation. Getting these definitions precise is essential — examiners distinguish between them carefully.

Intraspecific competition is the engine behind logistic population growth. When a population is small, resources are plentiful and individuals reproduce rapidly. As numbers rise, individuals compete more intensely for food, territory, and mates. Birth rate falls and death rate rises until the population stabilises at the carrying capacity of the environment.

Interspecific competition occurs between different species that share a resource. The outcome depends on which species is the stronger competitor for that particular resource. In the classic case of the grey squirrel (Sciurus carolinensis) and the red squirrel (Sciurus vulgaris) in Britain, the grey squirrel outcompetes the red for food and can carry the squirrelpox virus without symptoms — driving the red squirrel towards local extinction in most of England.

Predation introduces a different dynamic. A predator–prey relationship creates cyclical fluctuations in both populations. When prey numbers are high, predators have abundant food, reproduce successfully, and their numbers rise. Increased predation then reduces prey numbers, which in turn reduces food availability for predators — so predator numbers fall. The prey population then recovers, and the cycle repeats.

Notice in the chart that the predator peak follows the prey peak with a time lag. This lag exists because predator reproduction takes time to respond to increased food availability. Examiners frequently ask students to explain this lag — make sure you can articulate the cause-and-effect chain clearly.

Together, abiotic factors and biotic interactions (competition and predation) determine the size and distribution of every population in an ecosystem. The next challenge is measuring those populations accurately — which requires careful sampling methodology.

3. Sampling Populations: Quadrats and Transects

You cannot count every individual in a habitat — it would take too long and disturb the very organisms you are studying. Instead, ecologists use quadrats to sample a representative subset of the population and then extrapolate to estimate total abundance. The key word here is representative: the sampling method must avoid bias.

For quadrats to give valid data, they must be placed randomly. Random placement means every point in the habitat has an equal probability of being sampled, removing the unconscious bias that occurs when a researcher chooses where to place a quadrat by eye. The standard method is to generate two random numbers (one for the x-axis and one for the y-axis) using a random number generator or random number table, which together give a coordinate pair on a grid laid over the study area.

Worked example: How to Place Quadrats Randomly in a Field

A student wants to estimate the abundance of daisy plants in a 10 m × 10 m grassland plot using randomly placed 0.5 m × 0.5 m quadrats.

1. Lay two tape measures at right angles along two edges of the plot, creating x-axis (0–10 m) and y-axis (0–10 m). — The grid gives every point in the habitat a unique coordinate pair, making random selection possible.
2. Use a random number generator (or random number table) to produce pairs of numbers between 0 and 10. Example: (3.2, 7.8), (6.1, 1.4), (8.9, 5.0). — Random coordinates ensure no point is more likely to be sampled than any other — this removes investigator bias.
3. Position the bottom-left corner of the 0.5 m × 0.5 m frame at each coordinate in turn. — Using a consistent corner as the reference point ensures the quadrat area is always the same and placement is reproducible.
4. Count the number of daisy plants (or estimate percentage cover) within the frame. Record in a results table. — Consistent recording criteria — for example, whether to include plants touching the frame boundary — must be agreed before sampling begins to ensure reliability.
5. Repeat for at least 10 quadrats (more gives greater reliability). Calculate the mean number of daisies per quadrat. — A larger sample size reduces the effect of anomalous quadrats and improves the reliability of the estimate.
6. Each quadrat covers 0.5 × 0.5 = 0.25 m². The total plot area = 10 × 10 = 100 m². Number of quadrat-sized units in plot = 100 ÷ 0.25 = 400. Estimated total daisies = mean per quadrat × 400. — This extrapolation assumes the sampled quadrats are representative of the whole plot — which is only valid if placement was truly random.

Answer: Estimated total population = mean daisy count per quadrat × 400 (for a 100 m² plot sampled with 0.25 m² quadrats).

Random quadrat placement works well when the habitat is relatively uniform. However, many habitats show a clear gradient — for example, moving from a stream bank up a hillside, or from the low-tide mark to the high-tide mark on a rocky shore. In these situations, a belt transect is more appropriate.

In a belt transect, a tape measure is laid from one end of the gradient to the other. Quadrats are placed at regular intervals — say, every 2 m — along the tape. This reveals how species composition changes across the gradient, which is called zonation. A line transect records only the species touching the tape itself; a belt transect records all species within the strip, giving richer abundance data.

4. Measuring Abundance: Percentage Cover and Frequency

Once a quadrat is placed, you need a consistent way to record how abundant a species is within it. For sessile (non-moving) organisms such as plants, lichens, and barnacles, AQA specifies two measures: percentage cover and frequency. Each has strengths and limitations that examiners expect you to evaluate.

Percentage cover estimates the proportion of the quadrat's area that is occupied by a given species, expressed as a percentage. A quadrat divided into a 10 × 10 grid of 100 smaller squares makes this practical: count the number of small squares in which the species is present, and that number is the percentage cover directly. Values can exceed 100% in total across all species if plants overlap vertically — which is itself ecologically informative.

Frequency is a different measure. It records the proportion of quadrats in which a species is present, regardless of how many individuals are in each quadrat. If a species appears in 7 out of 10 quadrats, its frequency is 70%. Frequency is quick to record and requires no subjective judgement about cover, but it gives no information about how densely a species grows where it does occur.

5. Required Practical 12: Investigating Environmental Factors and Species Distribution

Required Practical 12 brings together everything covered so far. You are asked to investigate the effect of a named environmental (abiotic) factor on the distribution of a given species. A common example is investigating how light intensity affects the distribution of a ground-cover plant such as clover or plantain across a woodland-to-open-grassland gradient.

When evaluating this practical in an exam, you need to go beyond listing variables. Examiners award marks for identifying specific sources of error and suggesting concrete improvements. The most common sources of error are subjective percentage cover estimation and natural variation in light intensity caused by cloud cover during measurements.

6. Exam Technique: Getting Full Marks on Ecology Questions

Ecology questions are among the most mark-rich in AQA Biology Paper 2, yet students consistently lose marks through imprecise language and incomplete reasoning chains. The guidance below targets the most common errors seen in mark schemes.

For six-mark extended response questions on ecology, structure your answer as follows: open with a direct statement that addresses the question, then develop two or three linked scientific points each supported by a mechanism, acknowledge a counter-argument or limitation where relevant, and close with a justified conclusion. Avoid bullet points in extended responses — continuous prose signals higher-order reasoning to the examiner.