Use Jaccard Index when you need to compute the Jaccard similarity index between two species counts. Enter Species in community A, Species in community B, and Shared species using the definitions and units below so the result can be reproduced.

Species in community A

An integer count or setting greater than or equal to 0.

Species in community B

An integer count or setting greater than or equal to 0.

Shared species

An integer count or setting greater than or equal to 0.

The published tool contract uses this rule: Compute the Jaccard similarity index between two species counts.

Jaccard index

The calculated jaccard index.

The calculation does not propagate measurement uncertainty, sampling error, or biological and chemical variability.

Retain the original Species in community A, Species in community B, and Shared species values and their units alongside the result. Sorensen Index is useful when you instead need to compute the Sorensen-Dice coefficient of community similarity as 2 times the number of shared species divided by the sum of species counts in both communities. Morisita-Horn Counts provides another view by helping you quantify overlap between two communities over two species from raw abundance counts with the Morisita-Horn index.

• Sorensen Index

  Compute the Sorensen-Dice coefficient of community similarity as 2 times the number of shared species divided by the sum of species counts in both communities.

• Morisita-Horn Counts

  Quantify overlap between two communities over two species from raw abundance counts with the Morisita-Horn index.

• Brillouin Index

  Compute the Brillouin diversity index HB = (ln(N!) - sum(ln(ni!))) / N from three species counts using loop-based log factorials for communities up to 10000 individuals.