**-r**- Renyi enthropy index
**-s**- Richness index
**-h**- Shannon index
**-p**- Reversed Simpson index
**-g**- Gini-Simpson index
**-e**- Pielou's evenness index
**-n**- Shannon effective number of species
**-t**- Total counts
**--overwrite**- Allow output files to overwrite existing files
**--help**- Print usage summary
**--verbose**- Verbose module output
**--quiet**- Quiet module output
**--ui**- Force launching GUI dialog

**input**=*name[,**name*,...]**[required]**- input layers
- input layers
**output**=*name***[required]**- prefix name output layer
**alpha**=*number(s)[,**number(s)*,...]- Order of generalized entropy
- Options:
*0.0-**

Currently when working with very large raster layers and many input layers, computations can take a long time. On the todo list: find a way to reduce this.

r.mapcalc "spec1 = 60" r.mapcalc "spec2 = 10" r.mapcalc "spec3 = 25" r.mapcalc "spec4 = 1" r.mapcalc "spec5 = 4"

Now we can calculate the renyi index for alpha is 0, 1 and 2 (this should be 1.61, 1.06 and 0.83 respectively)

r.series.diversity -r in=spec1,spec2,spec3,spec4,spec5 out=renyi alpha=0,1,2 r.info -r map=renyi_Renyi_0_0 min=1.6094379124341 max=1.6094379124341 r.info -r map=renyi_Renyi_1_0 min=1.05813420869358 max=1.05813420869358 r.info -r map=renyi_Renyi_2_0 min=0.834250021537946 max=0.834250021537946

You can also compute the species richness, shannon, inverse simpson and gini-simpson indices

r.series.diversity -s -h -p -g in=spec1,spec2,spec3,spec4,spec5 out=biodiversity

The species richness you get should of course be 5. The shannon index is the same as the renyi index with alpha=1 (1.06). The inverse simpson and gini-simpson should be 2.3 and 0.57 respectively. Let's check:

r.info -r map=biodiversity_richness min=5 max=5 r.info -r map=biodiversity_shannon min=1.05813420869358 max=1.05813420869358 r.info -r map=biodiversity_invsimpson min=2.30308613542147 max=2.30308613542147 r.info -r map=biodiversity_ginisimpson min=0.5658 max=0.5658

- Chase and Knight (2013). "Scale-dependent effect sizes of ecological drivers on biodiversity: why standardised sampling is not enough". Ecology Letters, Volume 16, Issue Supplement s1, pgs 17-26.
- Gini, C. 1912. Variabilità e mutabilità. Reprinted in Memorie di metodologica statistica (Ed. Pizetti E, Salvemini, T). Rome: Libreria Eredi Virgilio Veschi 1.
- Jost L. 2006. Entropy and diversity. Oikos 113:363-75
- Legendre P, Legendre L. 1998. Numerical Ecology. Second English edition. Elsevier, Amsterdam
- Simpson, E. H. 1949. Measurement of Diversity Nature 163

Available at: r.series.diversity source code (history)

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