Many researchers want to study plants and animals in their natural habitats without disturbing them. However, ranges are often too large for a team of researchers to adequately study. Quadrats are defined plots, randomly distributed throughout the study area. Researchers collect data from them and use it to make assumptions about either the entire study area or the species being studied.
Quadrats allow researchers to study plant and animal populations spread out over large areas. They are inexpensive, relatively easy to design and can be adapted to study unevenly distributed populations. Quadrats work well for studying changes to whole populations over time, including distribution patterns, nesting and overall health. However, capture-recapture techniques that allow researchers to study individual animals often do not work with quadrats because even slow-moving animals can move out of the study boundaries between sample periods.
Plants, slow-moving animals, and faster moving animals with a small range, such as insects, are ideally suited for quadrat studies. For example, ants move fairly quickly but they are always organised around a stationary ant hill. Quadrats can be used to study both the distribution of ant hills within a larger area and ant behaviour within the sample area. Very fast-moving animals will not stay within the quadrat boundaries and must be studied using different techniques. Quadrat sampling is less harmful to most species than other methods, although some animals can be harmed if the population within the quadrat is collected instead of being studied in the field.
Ease of Use
Compared to other sampling methods, quadrats are relatively simple to use. Quadrat plots are uniform in size and shape and are distributed randomly throughout your sample area, which makes the study design fairly straightforward. They are also one of the most affordable techniques because very few materials are required. However, quadrat sampling can be very physically demanding since all of the individuals within each plot are usually counted out in the field.
Despite the relative ease of designing quadrat studies, you can easily introduce errors into your project. Quadrats that are too large, too small or spaced inappropriately will result in errors. For example, larger species require larger plots. Randomly-spaced quadrats that are too small might miss too many individuals, resulting in under-representative estimates of population size. Errors are also introduced when researchers are not consistent either counting or omitting species that lie partially within the boundaries.