In a systematic sampling design, sample units are selected according to a predetermined methodical pattern, which ensures that each unit of the sample represents an equal portion of the whole population. For example, running transects off a baseline at regular 10m intervals represents a systematic sampling design. Systematic sampling is also commonly used in research situations, when quadrats are located on a grid arrangement throughout the small study area.
Methodical selection within the site permits sample units to be located more rapidly and more evenly distributed than is the case with random sampling. Sample units are also selected without personal bias, as long as the systematic arrangement is determined without intent to include or exclude certain portions of the population.
The main drawback of systematic sampling is that typical methods of statistical inference cannot be applied, because the assumption of random selection is not met. Even though the observer may be certain that the sampling units were selected free from personal bias, it is possible that the accuracy of the data is compromised by a regular spatial pattern within the vegetation community. For example, sampling according to a 30m grid in a pecan orchard where trees were planted on a 30m spacing could result in estimated cover values of either 0% or 100%, depending on whether the sampling grid coincided with the trees or with the interspaces!
Various interpretations and modifications have been suggested so that data collected under systematic sampling designs represent an unbiased selection of the population, to ensure valid applications of typical statistical analysis methods. For example, a degree of randomization may be incorporated into the sampling design by tossing a coin to decide whether each regularly spaced transect should be run in a left or right perpendicular direction away from the baseline. In other situations, the scale of spatial patterns within the vegetation community may have been previously investigated (particularly for key species), so a contrasting scale could be adopted when planning the systematic sampling design.
However, the purist's approach to rangeland inventory and monitoring will insist that only true randomization ensures valid statistical analysis using typical methods. In practice, it remains the responsibility of individual to objectively guarantee the accuracy of the data.
References and Further Reading
Cook, C.W., and J. Stubbendieck. (eds). 1986. Range research: Basic problems and techniques. Society for Range Management, Denver, CO. pp 249-250.
Daubenmire, R. 1968. Plant communities: A textbook on plant synecology. Harper Row, New York, NY. pp 81-86.
Osborne, J.G. 1942. Sampling errors of systematic and random surveys of cover-type areas. Journal of American Statistics Association 37:257-264.
Salmon, S.C. 1953. Random versus systematic arrangement of field plots. Agronomy Journal 45:459-462.