Sampling in ecology is the act of quantifying or measuring populations of organisms. Sampling is often used to measure the biological diversity of plants and animals, and can help us estimate their density, distribution or migratory patterns. Generally, the easier a species is to catch or detect (partly determined by its size and abundance), the more likely the chances of detecting that species. For this reason, it is important to note that not all species are equally detectable.
Taking samples requires objectives. Objectives are specific questions that the sampling survey aims to answer. In other words, objectives provide the reason behind quantifying a population in the first place. Objectives also inform the structure of the survey. Without objectives, the survey data could become unfocused or useless altogether. The objectives of a sampling survey dictate what will be measured, what strategies may be optimal in taking those measurements or how much ground should be covered in the study.
What Is A Sampling Bias?
The sampling frame is the a list of the organisms (plant, animals, bacteria or insects) of a population from which a sample survey is taken. Sampling frames vary between study studies because different are structured to answer different questions about a target population. Target populations are the ecological resource, the species or organism, of interest. When studying a target population, ecologists have to consider bias involved in their study.
A sample is biased if it does not represent the population from the sampling frame. Bias may be grouped into two distinct categories measurement bias and sampling bias. Measurement bias describe measurements which have been taken inaccurately. An example of measurement bias can be measuring only a fraction of the sampling frame or the region of concern. This sort of measuring error would give ecologists values which do not completely cover the scope of the sampling surveys objective, and therefore could leave out crucial data points.
What Causes Sampling Bias?
Sampling biases are the result of taking a sample that fails to include all groups of the target population. Every sampling method, and ipso facto, every sampling survey inherently contains some sampling bias. Meaning, not all target populations and organisms will be measured with equal accuracy. Sampling biases might occur due to the fact that some species are easier to detect that others, or because there is a particular set of limitations to consider when sampling a given species. Understanding biases is crucial for assessing the trustworthiness of a sample.
To rectify sampling biases, ecologist may double sample. Double sampling involves randomly choosing certain species from the total survey and measuring them a second time. Double sampling tests inconsistencies and potential defects in survey analysis.