Graphing Techniques

Sampling precision is improved by increasing sample size because data describing the vegetation attribute is collected for a greater proportion of the population. At some point, however, we begin to collect information that is repetitious and additional sampling becomes inefficient.

This point can be identified from a graph that illustrates changes to the sample mean with each additional sample unit. When there are few records comprising a sample, the sample mean will fluctuate widely between points because of the low likelihood that a small sample is representative of the population. However, these fluctuations will dampen as the sample size increases. The actual cut-off point for an adequate sample size is a subjective decision made by the sampler and is based on their perceived trade-off between costs and returns involved with the data collection.

Data for the graph can be obtained from a preliminary sample, or by examining data as it is collected in the field. In either case, the data should be randomized before graphing in order to scramble possible trends in the data that reflect underlying landscape patterns. A series of running means is calculated by initially calculating the average of two records, then three records, then four records, etc. The running means for each sample size are graphed on the vertical axis and the horizontal axis represents the sample size for each of the running means.

References and Further Reading

Daubenmire, R. 1968. Plant communities: A textbook on plant synecology. Harper Row, New York, NY. pp 89-91.

Greig-Smith, P. 1983. Quantitative plant ecology. Blackwell Scientific Publications, Oxford.3rd ed. p 31.

Kershaw, K.A. 1964. Quantitative and dynamic ecology. Edward Arnold Publishing Company, London. pp 68-72.

Mueller-Dombois, D., and H. Ellenburg. 1974. Aims and methods of vegetation ecology. John Wiley Sons, New York. pp 77-80.