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Spec Mapping — OCR H420 Module 4.2.1 — Biodiversity, content statements covering practical investigations of biodiversity using random and non-random sampling, quadrats, transects, sweep nets, pitfall traps, kick sampling, and the mark-release-recapture method for estimating animal populations (refer to the official OCR H420 specification document for exact wording). This lesson is the practical core of Module 4.2 and the direct theoretical backbone of PAG 3 (Sampling techniques).
Measuring biodiversity requires us to estimate the abundance and distribution of organisms across a habitat, but it is usually impossible to count every individual. Instead, ecologists take samples — small, representative portions of the habitat — and extrapolate from them to describe the whole. OCR A-Level Biology A Module 4.2.1 requires you to know the main sampling techniques for plants and animals, explain the difference between random and non-random sampling, and use the mark-release-recapture method (the Lincoln-Petersen estimator, frequently called the Lincoln index) to estimate animal populations.
The mathematical and methodological framework here is the work of several twentieth-century ecologists rather than a single figure. The mark-release-recapture estimator was developed independently by Frederic Lincoln (1930, waterfowl) and C. G. J. Petersen (1896, fish) and is now a staple of population ecology. The principle that scientific data must be unbiased and representative — and therefore must be sampled, not gathered opportunistically — is older still, formalised in the early twentieth century when statisticians like Ronald Fisher placed experimental design on a rigorous footing.
Key Definitions:
- Sample — a small subset of a population used to estimate the properties of the whole.
- Random sampling — sampling in which every individual or location has an equal chance of being selected.
- Systematic sampling — sampling at regular intervals, often along a transect.
- Stratified sampling — sampling each sub-habitat in proportion to its size or importance.
- Bias — systematic error that makes a sample unrepresentative.
Sampling is necessary because:
A good sample is representative: it accurately reflects the composition of the whole population. Two properties make a sample representative: adequate size (large enough to reduce chance effects) and lack of bias.
flowchart TD
A[Sampling] --> B[Random]
A --> C[Non-Random]
B --> B1[Every point has equal chance]
B --> B2[Avoids bias]
B --> B3[Uses random number generator]
C --> C1[Systematic: regular intervals]
C --> C2[Stratified: proportional to sub-habitat]
C --> C3[Opportunistic: easiest to sample]
In random sampling, a random number generator produces coordinates within the study area and quadrats are placed at those coordinates. This avoids conscious or unconscious bias — such as placing quadrats where the flowers look prettiest. It is ideal when a habitat is relatively uniform.
Procedure:
In systematic sampling, samples are taken at regular intervals — for example, a quadrat every 2 m along a transect. This is used when you want to investigate how communities change along an environmental gradient (e.g. distance from a path, altitude on a mountain, shore height on a beach).
In stratified sampling, the area is divided into sub-habitats, and the number of samples from each sub-habitat is proportional to its size. For example, if a nature reserve is 70% grassland and 30% woodland, you might take 70 grassland quadrats and 30 woodland quadrats. This gives better coverage than simple random sampling when habitats are uneven.
Opportunistic sampling just records what is easiest to find. It is quick but very prone to bias, and is generally avoided in scientific work.
Exam Tip: OCR often asks you to "suggest why a scientist would choose random sampling". The standard answer is: to avoid bias and to allow statistical analysis. If the question specifies a non-uniform habitat, the answer shifts to stratified or systematic sampling.
A quadrat is a square frame of known area (commonly 0.25 m² or 1 m²) used to delimit the sample. Inside each quadrat you can record:
Point quadrats use a horizontal bar with vertical pins; each plant the pin touches is recorded. This gives an accurate measure of percentage cover without subjective estimation.
A transect is a line across the habitat along which samples are taken.
Transects are ideal for studying how communities change along an environmental gradient — for example, zonation on a rocky shore from high tide to low tide.
Animals are harder to sample because they move. Different groups require different methods:
| Technique | Targets | Principle |
|---|---|---|
| Pitfall trap | Ground-dwelling invertebrates (beetles, spiders) | Sunken container; animals fall in |
| Sweep net | Long-grass insects | Net swept through vegetation |
| Pooter | Small insects | Suction into a collection tube |
| Kick sampling | Freshwater invertebrates | Kicking substrate dislodges animals into a downstream net |
| Tullgren funnel | Soil invertebrates | Heat and light drive animals down into a collection jar |
| Light trap | Moths and nocturnal insects | UV light attracts insects into trap |
| Longworth trap | Small mammals | Live trap with bait |
All methods have limitations. Pitfall traps only catch actively moving ground animals; sweep nets miss species in the canopy; Longworth traps miss shy or trap-averse individuals. Combining several techniques gives the most representative picture.
Live traps must be checked regularly (at least twice daily); bedding and food must be provided in Longworth traps; captured animals should be released at the point of capture. Ethical considerations are a valid exam topic.
For mobile animals where a census is impossible, ecologists use mark-release-recapture (MRR), also called the Lincoln index. The principle: if you capture, mark and release a known number of animals, then capture a second sample, the proportion of marked individuals in the second sample tells you what fraction of the population was originally marked.
N=m2n1×n2
Where:
A student studying woodlice in a garden collects n₁ = 60 woodlice, marks them with a tiny spot of non-toxic paint, and releases them. A week later she collects n₂ = 75 woodlice, of which m₂ = 15 are marked.
N=1560×75=300
The estimated population is 300 woodlice.
The Lincoln index is only valid if:
If any of these assumptions fail, the estimate is unreliable. For example, if the paint attracts predators, marked individuals will be under-represented in the second sample, inflating the population estimate.
Exam Tip: Examiners love the assumptions of the Lincoln index. If you are asked to "evaluate the validity" of an MRR study, run through each assumption and identify which might be violated by the specific scenario.
Sampling error is reduced by:
A rule of thumb is that sampling should continue until adding more samples no longer increases the cumulative species count (the "species-area curve" flattens out).
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