Use Sorensen Index when you 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. Enter Species A, Species B, and Shared species using the definitions and units below so the result can be reproduced.

Species A

Species count in community A; must not be negative.

Species B

Species count in community B; must not be negative.

Shared species

Number of species shared by both communities; must not exceed either count.

The published tool contract uses this rule: 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.

Sorensen index

Sorensen index between 0 and 1.

A ratio or percentage can conceal the scale of its numerator and denominator and becomes sensitive to measurement error when the denominator is small.

Retain the original Species A, Species B, and Shared species values and their units alongside the result. Jaccard Index is useful when you instead need to compute the Jaccard similarity index between two species counts. Morisita-Horn Overlap provides another view by helping you compare two communities with the Morisita-Horn similarity coefficient for two categories. Each pair of proportions must sum to one; zero means no shared composition and one means identical composition.

• Jaccard Index

  Compute the Jaccard similarity index between two species counts.

• Morisita-Horn Overlap

  Compare two communities with the Morisita-Horn similarity coefficient for two categories. Each pair of proportions must sum to one; zero means no shared composition and one means identical composition.

• 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.