I have six ecosystems in two substrate categories (Triplicates essentially). I have determined shannon wiener index values for each ecosystem and also for the two categories separately. I have done this for two separate sets of data that were sampled in two separate years. Is it possible to statistically compare the development of the biodiversity between each of the categories i.e., the development of biodiveristy in ecosystem 1 between the two years, using the shannon wiener values somehow? Are there any other tests that could work? I am aware of the hutcheson t test however, some of my data is not normally distributed.
I would really appreciate some help!
Download the free software PAST 4 and read the manual, there are many ways to compare species diversity in different samples.
http://www.ievbras.ru/ecostat/Kiril/Library/Book1/Content243/Content243.htm
To statistically compare Shannon index values (a measure of diversity) between two years, you can use several methods depending on the data's nature and distribution. Here's a step-by-step guide:
1. Prepare Your Data
Ensure you have the Shannon index values for the two years. Your data might look something like this:
Year Shannon_Index
2022 2.3
2022 2.5
2022 2.1
2023 2.7
2023 2.8
2023 2.6
2. Check Normality
Determine if the Shannon index values follow a normal distribution. This can be done using tests such as the Shapiro-Wilk test.
3. Choose a Statistical Test
Based on the normality of the data, choose an appropriate test:
If data is normally distributed:
Use an independent t-test if the variances between the groups are equal (you can check for this using Levene's test).
Use Welch's t-test if the variances are not equal.
If data is not normally distributed:
Use a non-parametric test such as the Mann-Whitney U test (also known as the Wilcoxon rank-sum test).
4. Perform the Test
Good time
at first I must have some information.
yes if we have enough data we can compare.
I did it in one of y work.
with best regards
You can compare your values by t-test or non-parametric F test depending on normality test of your data set.
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