## Statistical Analysis of Biomass Data

When the layout of quadrats for biomass sampling follows the principles of random sampling, each quadrat represents a sample unit, and values describing biomass in each quadrat form the data set used for statistical analysis. Although this approach is straightforward, it is often an inefficient design because the data usually has a large sample variance.

More often, quadrat layout follows the principles of systematic sampling, where biomass data is usually collected from multiple quadrats located along a transect. The averages calculated for each transect are the sample units contributing to the data set used for statistical analysis, and usually display a smaller sample variance.

Biomass data usually follows a normal distribution under either sampling design. Departures from this pattern generally indicate that sample unit size was too small. Significant differences between years or among sites are based on conventional inferential statistics, where two sample means are compared by considering the possibility that their respective confidence intervals overlap.

### References and Further Reading

Greig-Smith, P. 1983. *Quantitative plant ecology*. Blackwell Scientific Publications, Oxford. 3rd ed. pp 33-36.

Remington, K.K., Bonham, C.D., and R.M. Reich. 1992. Blue grama-buffalograss responses to grazing: A Weibull distribution. *Journal of Range Management* 45:272-276.