Number of Samples Required for Estimating Herbaceous Biomass

Abstract

Although the precision of herbaceous biomass estimation depends on the sample number, the spatial heterogeneity of the biomass, and sampling procedures, the magnitudes of the influences on the precision have not been clarified. We simulated virtual plant communities based on the gamma distribution to clarify the relationships between the precision of estimating herbaceous biomass and the number of samples, sampling density, spatial heterogeneity of the biomass, and sampling procedures. Using only two parameters, the gamma distribution can approximate the frequency distribution of herbage mass with varying heterogeneity. Our simulations demonstrated that the number of samples is a more influential factor than sampling density on the precision of the herbaceous biomass estimation. Moreover, our simulations confirmed that biomass heterogeneity strongly affected the precision and quantified the magnitude of the influence. When we estimated biomass with random sampling and a 50 X 50 cm quadrat and accepted estimation error of +/- 10% of the mean for a confidence interval of 95%, the numbers of samples needed were 200, 77, and 9 for very, intermediate, and less heterogeneous grasslands, respectively. Similarly, when we estimated biomass with a ranked set sampling (RSS), then 24, 15, and 4 samples were needed in very, intermediate and less heterogeneous grasslands, respectively. We came to two conclusions: 1) In less heterogeneous grasslands, good precision of estimation can be obtained with a small number of samples, and it is useful to employ RSS. The cutting method, as well as nondestructive methods, will be practical; and 2) estimation for heterogeneous grassland requires a large number of samples, and it is not so useful to employ RSS. For that reason, more research is needed on nondestructive methods.