We want to compare the dominance of species altitudinally and adopting the method of stratified random sampling.
Pravin -
Not my area of application, but I think you are not exactly using stratified random sampling because you apparently want to compare subpopulations at different altitudes , not get a better idea of just one 'community.' I don't know what kind of data you collect in your discipline, but if you look for numerical results, especially continuous number data, then for each question/variable, you would want to compare different, I suppose, altitude levels, not get better overall/'average' estimates.
So, I'm guessing that each stratum you have planned is really a different subpopulation, and you want to compare them, possibly comparing numbers estimated for certain variables. I think that you could think of each subpopulation as one from which you want to collect data on a number of randomly selected plots. This could actually be considered to be a type of cluster sampling, where the size of each plot may have an optimum value (I think, though not my area of expertise), all things considered. I think that there are papers on ResearchGate by people in forestry and agriculture, perhaps soil science, that might help you if you search on publications at the top of your screen.
There is a book, Sampling Techniques, by William Cochran, 3rd ed, 1977, Wiley, where on pages 243 and 244 they discuss variance and how that relates to plot (or cluster) size. (This also relates to heteroscedasticity, an area for me, but that is not exactly your interest here.) I think it might help if you looked at Chapters 9 and 9A in Cochran on single-stage cluster sampling, or perhaps any one of a number of other books on survey sampling. (I notice that in my copy of Steven K. Thompson's 3rd ed, 2012, of Sampling, also a Wiley book, the subject index has an entry for "Plots in conventional systematic vs cluster sampling," page 349, but at a quick glance, without looking at preceding pages, I could not tell if that was the right topic, but there are plenty of survey sampling books you could check, and I suppose the papers you find on ResearchGate could give you better references for your discipline/subject matter.)
Here are two possible leads for you:
https://www.researchgate.net/project/Textbook-Use-of-models-in-forest-sciences?_esc=profileInterest&_iepl%5BviewId%5D=wNg0gG87PzoU0cdYvGQrh3z1&_iepl%5Bcontexts%5D%5B0%5D=prfipri&_iepl%5BinteractionType%5D=projectView
https://www.researchgate.net/publication/321979278_Optimal_sample_size_and_plot_size_or_point_sampling_factor_based_on_cost-plus-loss_using_the_Fairfield_Smith_relationship_for_plot_size?_esc=Profile%3A%3AInterests&_iepl%5BviewId%5D=wNg0gG87PzoU0cdYvGQrh3z1&_iepl%5BprofilePublicationItemVariant%5D=default&_iepl%5Bcontexts%5D%5B0%5D=prfipi&_iepl%5BtargetEntityId%5D=PB%3A321979278&_iepl%5BinteractionType%5D=publicationTitle
Cheers - Jim
@ Pravin Rawat,
Since you have adopted the method of stratified random sampling, you will have to cover the entire area (2200 sq km).
You will have to divide the entire area into a number of strata which are homogeneous within but heterogeneous between. Then you will have to draw samples from each stratum of suitable size by simple random sampling method. Then you will have to combine the samples collected from the strata to obtain the sample you need.
Pravin -
To be clear, in stratified random sampling, one is trying to get the best overall measures. That is not what you are doing. You are comparing subpopulations. The key word is that you say you want to "compare" these subpopulations. Thus the notion of "optimal allocation," an important consideration in stratified random sampling, does not apply to you. (Even if you were doing a qualitative analysis, you have to have enough information from each subpopulation to make comparisons. In stratified random sampling, you don't care if you can do that or not.)
You can draw a simple random sample from each subpopulation, or you can select with unequal probabilities. See chapters 9 and 9A in Cochran, as I noted earlier, or another survey statistics book, or perhaps better, check the forestry, soil science, and agriculture resource papers on or referenced on ResearchGate. The question then becomes, What size plot (cluster) do you choose? You could base that on variance calculations, as found in Cochran, and I suspect elsewhere, if you have the required kind of quantitative data.
I urge you to first look at the forestry and related papers available on ResearchGate (hopefully legally), or referenced on ResearchGate, and perhaps textbooks referenced by such resources.
Best wishes - Jim
Dear Friend the sampling size depends upon the man power and money as well as time period at least 6% to 10% should take the sampling area for you studies.
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