I want to do a sample inventory of a 700 ha forest to have the amount of biomass and apply i-Tree Eco to determine carbon storage and sequestration. I would like to know the minimum number of plots for the results to be significant.
For example, 200 plots are needed for a standard error of 10% in the case of an i-Tree Eco analysis.
The ratio of research should be sufficient, the characteristics of each region should be studied and analyzed, and there should be no omission. The percentage is determined according to the characteristics of your area. If the research conclusion is sufficient, the more abundant the data collected, the better.
The higher the sample size, the lower the SE, which is desirable. But one measure of ideal sample size for an unknown population = (zˆ2 x p(1-p))/eˆ2, where z is the z score, e is chosen margin of error, and p is an acceptable standard deviation. A Z-score is a numerical measurement that describes a value's relationship to the mean of a group of values. Z-score is measured in terms of standard deviations from the mean. If a Z-score is 0, it indicates that the data point's score is identical to the mean score.
I think the plot size will to some extent determine the minimum number of plots to use. The smaller the plot size, the more the number of plots required to get a representative sample size and vice versa.
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