Sampling

The aim of sampling is to select a sample that accurately reflects the wider population.

In ecology, this means choosing a set of measurements or observations that capture the true range of species, densities and conditions found across the habitat.

A representative sample avoids bias and allows reliable conclusions to be drawn about the population without surveying every individual or every square metre. One QCAA markscheme mentions trying to ensure a minimum of 10% of the site is sampled.

What can we find out from sampling?

Option 1: We can estimate population means of organisms, including their density and distribution. Or consider the diversity between different areas.

Option 2. We can also consider environmental gradients and profiles, including zonation and stratification, showing the impact of an abiotic factor on a biotic one.

Random Sampling

Random sampling is a method used to collect data from an ecosystem without introducing personal bias.

Ecologists use it to estimate the abundance or distribution of organisms across a habitat in a fair and representative way. The idea is that every location within the study area has an equal chance of being selected.

To carry it out, researchers usually lay out a grid across the site, then use random number generators to choose coordinates. Because sites are chosen randomly, the final data better reflect the true variation across the habitat.

Systematic Sampling

Systematic sampling involves collecting data at fixed, regular intervals. Instead of choosing points at random, a structured layout is used to ensure even coverage.

One approach is to overlay a grid across the study site. Every square in the grid is then sampled, or samples are taken at consistent points within each square. This removes selection bias and ensures that the whole area is surveyed in a uniform way.

Another common method is a transect. A tape measure is stretched across the habitat and quadrats or point counts are taken at set distances along the line.

Systematic sampling is particularly useful for studying gradients such as shore zonation or changes in vegetation across slopes because it shows how species and abiotic factors shift in a predictable pattern.

Stratified Sampling

Stratified sampling involves dividing a habitat into distinct sections that differ in important ways, such as vegetation type, moisture level or light exposure. Each section is treated as a separate stratum and is sampled independently to ensure that all key habitat types are represented in the data.

This approach is useful when the study area is varied, because sampling each stratum separately provides a more accurate picture of overall species distribution. If the habitat is largely uniform, stratification is not required.

Non-stratified Sampling

Non-stratified sampling treats the entire habitat as one continuous area without dividing it into separate sections. Ecologists use this approach when the site is fairly uniform, meaning there are no clear differences in environmental conditions or vegetation that would justify separating the area into strata.

Samples are taken using a single method, such as random or systematic sampling, and all data are pooled to give an overall estimate for the habitat. This provides an efficient and straightforward way to gather reliable information when variation across the site is minimal.

Give one limitation of using a line transect to collect data. Show Answer