OCR A Level Biology A: Measuring biodiversity (H420)

This guide covers section 4.2.1(a) to (e) of the OCR A Level Biology A (H420) specification, Version 4.1 (April 2026), for first assessment in 2025. It sits in Module 4, Biodiversity, evolution and disease. It teaches the levels of biodiversity, sampling in the field, species richness and evenness, Simpson’s Index of Diversity and the measurement of genetic diversity. Sections 4.2.1(f) to (h), on the factors affecting biodiversity and conservation, are outside this unit.

Use it with the revision notes and the practice questions. The OCR A Level Biology hub and the printable checklist list the rest of the course, and the free diagnostics show where to start. Statistics and practical ideas from Development of Practical Skills also apply here.

What this unit covers

Spec reference	What you must be able to do
4.2.1(a)	Consider biodiversity at different levels: habitat, species (richness and evenness) and genetic
4.2.1(b)(i)	Explain how sampling is used to measure the biodiversity of a habitat, and why it matters
4.2.1(b)(ii)	Carry out random and non-random sampling in the field (practical activity group 3, PAG3)
4.2.1(c)	Measure species richness and species evenness in a habitat
4.2.1(d)	Use and interpret Simpson’s Index of Diversity (D), including high and low values
4.2.1(e)	Assess genetic biodiversity, including calculations of genetic diversity

The specification says that Simpson’s formula will be provided where needed in assessments and does not need to be recalled. You still need to substitute into it accurately and say what the answer means.

4.2.1(a) Levels of biodiversity

Biodiversity is the variety and complexity of life. It is an important indicator in the study of habitats. The specification names three levels.

• Habitat biodiversity. The number and range of different habitats in an area, for example sand dunes, woodland, meadows and streams. Each habitat has its own set of conditions and its own community.
• Species biodiversity. The variety of species in a habitat. It has two parts: species richness and species evenness.
• Genetic biodiversity. The variety of alleles and genes within a species, for example the different breeds within a species.

Species richness is the count of distinct species found in a habitat. Species evenness is how close in number the populations of the different species are. A community where every species has a similar number of individuals is more even than one where a single species makes up most of the individuals.

4.2.1(b) Sampling

Why sample?

You cannot count every organism in a woodland or a stream. A sample is a small part of the habitat that you study in detail, then use to draw conclusions about the whole. A sample is only useful if it represents the habitat. Sampling saves time, avoids damaging the habitat and allows repeat measurements. Chance can still make a sample unrepresentative, so take enough samples and calculate a mean.

The specification also stresses the importance of sampling the range of organisms in a habitat. One technique finds only some groups. Plants are missed by a sweep net and flying insects are missed by a pitfall trap, so a measure of biodiversity based on one method alone under-records the habitat.

Types of sampling

Type	How samples are placed	Notes
Random	Positions chosen by chance, for example random numbers used as coordinates on a grid laid over the area	Avoids bias. Best where the area is fairly uniform.
Systematic (non-random)	Samples at regular intervals, for example along a line transect	Shows change along a gradient, such as up a dune.
Stratified (non-random)	The habitat is divided into distinct areas and each is sampled in proportion to its size	Ensures each area is represented.
Opportunistic (non-random)	Whatever is convenient or easy to reach	Quick, but biased, so weak for comparing habitats.

Random sampling method. Lay two tape measures along adjacent edges of the area, at right angles. Generate pairs of coordinates from a table of random digits or a random number generator. Place a quadrat at each coordinate. Random numbers are better than throwing a quadrat over your shoulder, which is not truly random and favours accessible spots.

Systematic sampling method. Run a tape from one edge of a gradient, for example from the strandline up a dune, and record at regular intervals (every 5 m, say). A belt transect uses a continuous strip of quadrats. Because the positions are not chosen at random, systematic sampling suits a change in conditions rather than a uniform area.

Stratified example. A field is 70% flat grass and 30% damp hollow. With 20 quadrats in total, use 14 in the grass and 6 in the hollow. A purely random sample could place nearly all quadrats in one zone by chance.

Techniques

• Quadrats estimate the abundance of plants and slow-moving or fixed animals. Record counts, frequency (the fraction of quadrats containing a species) or percentage cover. Use a quadrat of suitable size for the plants.
• Sweep nets catch flying and leaf-dwelling insects in tall vegetation. Use a fixed number of sweeps in each sample.
• Pitfall traps are containers sunk into the ground with the rim level with the surface, for catching ground-living invertebrates. Cover them to keep out rain, check them regularly and release the animals.
• Pooters suck small insects from leaves, bark or a beating tray into a container, with a filter in the mouthpiece tube so you do not inhale them.

Good practice in the field: keep the effort the same in each sample, repeat on more than one day if possible, identify with a key, handle animals gently and return them to where they were caught, and leave the habitat as you found it.

Worked example: estimating a population from quadrats

Thirty random quadrats, each 0.25 m², were placed in a rectangular field of 4000 m². A total of 156 daisy plants were counted.

1. Mean per quadrat = 156 ÷ 30 = 5.2 plants.
2. Density per m² = 5.2 ÷ 0.25 = 20.8 plants per m².
3. Estimated population = 20.8 × 4000 = 83 200 plants.

The answer is an estimate. It assumes the quadrats were random and the plants are spread evenly enough for the mean to represent the field. Data from several samples can also be compared using a statistical test, such as a Student’s t-test for the difference between two means, or Spearman’s rank correlation for change along a transect. Standard deviation shows how variable the counts were.

4.2.1(c) Species richness and species evenness

Measure species richness by sampling, identifying the organisms and counting how many different species you find. A bare count has limits. It treats a species with one individual the same as a species with a thousand, and it depends on how hard you looked.

Evenness needs the number of individuals of each species. Two sites can have the same richness but different evenness.

	Species 1	Species 2	Species 3	Species 4	Richness
Site X	25	25	25	25	4
Site Y	91	3	3	3	4

Both sites have four species and 100 individuals. Site X is perfectly even. Site Y is dominated by species 1, so it is much less even. Most people would call Site X the more diverse community, but richness alone cannot show this. This is why an index is used.

4.2.1(d) Simpson’s Index of Diversity (D)

Simpson’s Index of Diversity takes both richness and evenness into account:

D = 1 − Σ(n/N)²

• n is the number of individuals of one species.
• N is the total number of individuals of all species.
• Σ means add up the values for every species.

Method

1. Count the individuals of each species (n) and the total (N).
2. Work out n/N for each species.
3. Square each value.
4. Add the squares.
5. Subtract the total from 1.

Worked example: leaf-litter invertebrates

A woodland pitfall trap sample contained five species: 18, 11, 7, 3 and 1 individuals.

N = 18 + 11 + 7 + 3 + 1 = 40

n	n/N	(n/N)²
18	0.45	0.2025
11	0.275	0.0756
7	0.175	0.0306
3	0.075	0.0056
1	0.025	0.0006

Σ(n/N)² = 0.315 (exact working: 504 ÷ 1600)

D = 1 − 0.315 = 0.685

Comparing the two sites

For Site X, Σ(n/N)² = 4 × 0.25² = 0.25, so D = 0.75. For Site Y, Σ(n/N)² = 0.91² + 3 × 0.03² = 0.8308, so D = 0.169 (3 significant figures). The index separates the sites even though both have four species.

Interpreting D

D lies between 0 and 1.

• A high value, close to 1, means many species with individuals spread fairly evenly between them. The habitat is diverse. Such a community is generally more stable, because it has many species and is less likely to be badly damaged if one species declines.
• A low value, close to 0, means few species, or a community dominated by one species. The habitat is less diverse and more vulnerable to change, for example through disease, pollution or disturbance. A very low value may suggest harsh or disturbed conditions, or a managed habitat such as a monoculture.

Give the value to a sensible number of significant figures. Say what D shows about both richness and evenness, and relate it to the habitat in the question.

Limits to bear in mind: D depends on the quality of the sampling, a small sample gives an unreliable value, D describes the sampled habitat at one time, and it does not say which species matter most. To compare habitats fairly, sample them in the same way and with similar effort.

4.2.1(e) Genetic biodiversity

Genetic diversity is the variety of alleles present in a population or species. A gene locus is polymorphic if more than one allele of the gene is found in the population. One simple measure is the proportion of polymorphic gene loci:

proportion of polymorphic gene loci = number of polymorphic gene loci ÷ total number of loci

Multiply by 100 for a percentage. This gives the percentage of gene variants (alleles) in the genome that vary within the population, which is how the specification words the calculation. The specification links this to isolated populations such as zoos (captive breeding), rare breeds and pedigree animals.

Worked example: a captive herd

Researchers examined 60 gene loci in a captive herd of a rare sheep breed. Eighteen loci were polymorphic.

1. Proportion = 18 ÷ 60 = 0.30.
2. Percentage = 0.30 × 100 = 30%.

Several years later, with a smaller breeding group, only 12 of the same 60 loci were polymorphic. The proportion is now 12 ÷ 60 = 0.20, or 20%. The decrease is 10 percentage points. As a percentage of the original value, (0.30 − 0.20) ÷ 0.30 × 100 = 33.3%.

Interpreting genetic diversity

A small isolated population tends to lose alleles by chance, and mating between relatives (inbreeding) becomes more likely. This reduces the variety of alleles. A population with low genetic diversity has less variation for natural selection or breeders to work on, so it is less able to adapt to a change such as a new disease. In captive breeding, keeping pedigree records helps managers choose pairings that avoid mating between close relatives and keep as many alleles as possible.

Common errors

• Describing richness as “how many individuals”. It is the number of species.
• Using the total number of species instead of the total number of individuals as N.
• Forgetting to square n/N, or forgetting to subtract from 1.
• Saying that a high D means a large population. It means high diversity.
• Calling opportunistic sampling random. It is non-random and likely to be biased.
• Placing quadrats along a transect and calling it random.
• Dividing polymorphic loci by the number of alleles, not the number of loci.
• Writing a population estimate without a method or units.

Official syllabus

OCR, A Level Biology A (H420) specification, Version 4.1 (April 2026), for first assessment in 2025: section 4.2.1(a) to (e), Biodiversity, with the mathematical skills M0.2, M1.1 to M1.10, M2.3, M2.4 and M3.2 and PAG3 cited in the specification for these statements.