All scientific investigations involve assumptions and have limitations. Identifying and critically evaluating these is a hallmark of rigorous scientific thinking and is explicitly assessed in VCE Environmental Science investigations.
Assumptions are conditions or beliefs taken to be true for the investigation to be valid, without being directly tested.
| Type | Example |
|---|---|
| Methodological assumption | ‘Species encountered in random quadrats are representative of the whole area’ |
| Statistical assumption | ‘The population is stable over the sampling period (for mark-recapture)’ |
| Ecological assumption | ‘Bird species richness is an appropriate indicator of overall biodiversity’ |
| Sampling assumption | ‘The sample size is sufficient to detect meaningful differences’ |
Limitations are factors that constrain the investigation’s scope, precision, accuracy or generalisability.
Limitations arise from:
- Available time, equipment and resources
- Practical constraints of fieldwork
- The inherent complexity and variability of natural systems
- The specific methodology chosen
| Limitation | Implication |
|---|---|
| Insufficient replication (e.g. only 2 quadrats per site) | Cannot reliably calculate averages or assess variability |
| Small spatial scale relative to the question | Findings may not generalise to the broader ecosystem |
| Single time point | Seasonal or year-to-year variation not captured |
| Method | Common Limitation |
|---|---|
| Quadrat sampling | Observer differences in species identification; difficulty with cryptic species |
| Mark-recapture | Assumption violations (population not closed; marks lost) |
| Point count (birds) | Detectability varies with weather, time of day; observer experience |
| Pitfall traps | Trap-happy behaviour; differential capture efficiency by species |
Variables not controlled may independently influence the dependent variable:
- Example: Comparing bird diversity between two sites — if one site is near a road (noise disturbance) while the other is not, the road effect confounds the effect of the intended independent variable (e.g. vegetation cover)
Violation of any assumption biases the population estimate
Violation: non-random placement over-represents open areas → overestimates species richness in those areas
A strong limitations section:
1. Names the specific limitation (not just ‘small sample size’ but ‘only 5 quadrats per site’)
2. Explains the mechanism by which it affects the data
3. States the direction of the likely bias (under- or over-estimate)
4. Proposes an improvement that would address the limitation
Example: ‘Only five quadrats were placed per site, which may be insufficient to capture the full species diversity of the 2 ha site. This likely underestimates species richness, particularly for rare or patchily distributed species. Using 20 randomly placed quadrats per site would improve the representativeness of the sample.’
EXAM TIP: VCAA assessment rewards explicit, specific identification of limitations with direction of bias and proposed improvement. The most common student error is identifying limitations without explaining how they affect the specific result obtained.
