Enter abundance data
Add one taxon per line as “Name, count” or enter comma-separated counts.
Example data table
| Taxon | Observed count | Comment |
|---|---|---|
| Taxon A | 18 | Dominant sequence group |
| Taxon B | 12 | Common member |
| Taxon C | 9 | Stable contribution |
| Taxon D | 7 | Intermediate abundance |
| Taxon E | 4 | Minor contributor |
| Taxon F | 2 | Rare member |
| Taxon G | 1 | Singleton taxon |
How to use this calculator
- Enter a sample name and optional study label.
- Paste abundance counts as taxon-count pairs or numeric values.
- Choose the Shannon log base and decimal precision.
- Select whether zero-count taxa should be ignored.
- Press the calculate button to generate diversity metrics.
- Download the current results as CSV or PDF.
Formula used
- Relative abundance: pi = ni / N
- Observed richness: S = number of taxa with positive abundance.
- Shannon index: H′ = −Σ pi log(pi)
- Simpson dominance: D = Σ pi2
- Simpson diversity: 1 − D
- Inverse Simpson: 1 / D
- Pielou evenness: J = H′ / log(S)
- Margalef richness: (S − 1) / ln(N)
- Menhinick richness: S / √N
- Berger-Parker dominance: max(ni) / N
- Chao1 estimator: S + F12 / (2F2), with a fallback when F2 = 0
- Good's coverage: 1 − F1 / N
- Fisher's alpha: solve S = α ln(1 + N/α) numerically.
Interpretation notes
Higher richness means more observed taxa, while higher evenness means abundances are distributed more uniformly. Shannon and Simpson respond differently to rare and dominant taxa, so reviewing both helps create a more balanced ecological interpretation.
Chao1 and Good's coverage are especially useful when rare taxa matter, such as microbiome studies, biodiversity surveys, and sequencing-based habitat comparisons.
Frequently asked questions
1. What does alpha diversity measure?
Alpha diversity measures diversity within one sample. It combines richness and abundance balance to describe how many taxa are present and how evenly they are distributed.
2. Can I use sequencing read counts here?
Yes. You can use read counts, organism counts, colony counts, or any abundance values representing taxa within one sample. Keep the measurement approach consistent across comparisons.
3. Why are Shannon and Simpson both included?
They emphasize different features. Shannon is sensitive to richness and moderate rarity, while Simpson gives more weight to dominant taxa. Using both improves interpretation.
4. What is the difference between richness and evenness?
Richness counts how many taxa are observed. Evenness describes how similarly the abundances are spread across those taxa. Two samples can share richness but differ strongly in evenness.
5. When is Chao1 useful?
Chao1 is useful when rare taxa matter. It estimates unseen richness by using singleton and doubleton counts, helping adjust for undersampling in ecological or microbial datasets.
6. Why would Fisher's alpha show N/A?
It may show N/A when the sample structure makes the numerical solution unstable, especially when richness approaches total count or the data are too limited.
7. Should I include zero-count taxa?
Usually no. Zero-count taxa are often ignored because they were not observed in that sample. Keep them only when your workflow explicitly tracks unobserved expected taxa.
8. Can this compare multiple samples directly?
This page calculates one sample at a time. To compare samples, run each sample separately and then place the exported metrics side by side.