A paper out online in the August issue of Ecology Letters presents a new index for estimating biodiversity. John Harte of UC Berkeley and his colleagues have developed a method that they say yields more precise measures of biodiversity than classic indices, such as Simpson’s and Shannon’s diversity indices.
In an argument similar (but reversed) to that for quantum physics, Harte explains that fractal geometry helps to explain distributions at small scales, but not at large scales. Like most other indices, their new model uses an entropy index. Harte and his colleagues Adam Smith of UC Berkeley and David Storch of Charles University in Prague, Czech Republic, used insights from information theory, often used in thermodynamics and statistical mechanics. They say that maximizing the information entropy, or minimizing assumptions of the unknown based on small plot samples, led to a better prediction of species-area relationships.
Harte and his colleagues used their theory to estimate biodiversity the Western Ghats mountain range of India overlooking the Arabian Sea. Nearly 60,000 square kilometers, the Western Ghats are partially protected and have been studied extensively by Indian scientists in 48 quarter-hectare plots and through large-scale surveys. Earlier species-area theories predict between 400 and 500 species of trees throughout the range, but to date, Indian scientists have documented more than 900 tree species in the preserve. Harte’s theory estimates around 1,070. Said Harte in a press release:
“People have been finding different curves when looking at different organisms or in different habitats, but in fact, all these curves are the same. There really is a universal curve people are sampling, they are just sampling along different parts of the curve depending on the habitat or class of organisms.”
Harte , J., Smith, A., & Storch, D. (2009). Biodiversity scales from plots to biomes with a universal species-area curve Ecology Letters, 12 (8), 789-797 DOI: 10.1111/j.1461-0248.2009.01328.x