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IB DP ESS — Topic 2: Ecology | SL & HL | Paper 1 & Paper 2A
🎯 Learning Intentions By the end of this note, you will be able to:
- Define population, sample, and sampling frame using IB-aligned ESS terminology.
- Explain why random, systematic, and stratified sampling methods are used in ecological fieldwork and the conditions under which each is most appropriate.
- Describe how quadrat and transect methods are used to estimate population size and distribution in different habitat types.
- Outline the mark-release-recapture (Lincoln-Petersen) method and the assumptions on which it depends.
- Calculate population size estimates using the Lincoln-Petersen equation and interpret the reliability of those estimates.
- Analyse sources of error and bias in ecological sampling, including the assumptions underlying each method.
- Evaluate the suitability of different sampling strategies for specific ecological contexts, considering scale, reliability, and ethical constraints.
- Discuss how sampling data informs conservation decision-making and the limitations of using sample estimates to represent whole populations.
Real-World Context & Relevance
In 2022, the IPBES Global Assessment estimated that approximately one million species face extinction, many within decades. Yet for the vast majority of those species, no one has ever counted every individual. When the WWF published its Living Planet Report in 2022, reporting a 69% average decline in monitored vertebrate populations since 1970, that figure was not derived from a complete census of every animal on Earth. It was derived from carefully designed sampling programmes — statistical windows into populations too large, too mobile, or too cryptic to count directly (WWF, "Living Planet Report 2022").
The same challenge faces a student conducting fieldwork in a local meadow: you cannot count every grass blade, every beetle, or every clover plant. Instead, you design a sampling strategy that gives you a reliable, unbiased estimate. The methods you choose — quadrats, transects, mark-release-recapture — determine whether your conclusions are valid. A poorly designed sampling protocol can produce data that systematically overestimates or underestimates a population, leading to flawed conservation policy. Understanding sampling is therefore not merely a practical fieldwork skill; it is the epistemological foundation of ecology itself.
🌍 Why This Matters Decisions about which species receive legal protection, which habitats are designated as reserves, and which fisheries are declared sustainable all depend on population estimates derived from sampling. If those estimates are biased or unreliable, conservation resources may be misallocated — protecting species that are thriving while overlooking those in genuine crisis.
Core Concepts & Definitions
Before any sampling can begin, ecologists must be precise about what they are trying to measure. A population is not simply "all the animals in a forest" — it is a defined group of individuals of the same species occupying a defined area at a defined time. This precision matters because the boundaries you draw around your study population determine which individuals could theoretically be sampled, and therefore whether your estimate is meaningful.
📖 Key Definition —