Species diversity
Species diversity is the number of different
Calculation of diversity
Species diversity in a dataset can be calculated by first taking the
The
The value of q determines which mean is used. q = 0 corresponds to the weighted harmonic mean, which is 1/S because the values cancel out, with the result that 0D is equal to the number of species or species richness, S. q = 1 is undefined, except that the limit as q approaches 1 is well defined:[4]
which is the exponential of the Shannon entropy.
q = 2 corresponds to the arithmetic mean. As q approaches infinity, the generalized mean approaches the maximum value. In practice, q modifies species weighting, such that increasing q increases the weight given to the most abundant species, and fewer equally abundant species are hence needed to reach mean proportional abundance. Consequently, large values of q lead to smaller species diversity than small values of q for the same dataset. If all species are equally abundant in the dataset, changing the value of q has no effect, but species diversity at any value of q equals species richness.
Negative values of q are not used, because then the effective number of species (diversity) would exceed the actual number of species (richness). As q approaches negative infinity, the generalized mean approaches the minimum value. In many real datasets, the least abundant species is represented by a single individual, and then the effective number of species would equal the number of individuals in the dataset.[2][3]
The same equation can be used to calculate the diversity in relation to any classification, not only species. If the individuals are classified into genera or functional types, represents the proportional abundance of the ith genus or functional type, and qD equals genus diversity or functional type diversity, respectively.
Diversity indices
Often researchers have used the values given by one or more
When interpreted in ecological terms, each one of these indices corresponds to a different thing, and their values are therefore not directly comparable. Species richness quantifies the actual rather than effective number of species. The Shannon index equals log(1D), that is, q approaching 1, and in practice quantifies the uncertainty in the species identity of an individual that is taken at random from the dataset. The Simpson index equals 1/2D, q = 2, and quantifies the probability that two individuals taken at random from the dataset (with replacement of the first individual before taking the second) represent the same species. The Gini-Simpson index equals 1 - 1/2D and quantifies the probability that the two randomly taken individuals represent different species.[1][2][3][7][8]
Sampling considerations
Depending on the purposes of quantifying species diversity, the data set used for the calculations can be obtained in different ways. Although species diversity can be calculated for any data-set where individuals have been identified to species, meaningful ecological interpretations require that the dataset is appropriate for the questions at hand. In practice, the interest is usually in the species diversity of areas so large that not all individuals in them can be observed and identified to species, but a sample of the relevant individuals has to be obtained. Extrapolation from the sample to the underlying population of interest is not straightforward, because the species diversity of the available sample generally gives an underestimation of the species diversity in the entire population. Applying different
In general, sets with many individuals can be expected to have higher species diversity than sets with fewer individuals. When species diversity values are compared among sets, sampling efforts need to be standardised in an appropriate way for the comparisons to yield ecologically meaningful results. Resampling methods can be used to bring samples of different sizes to a common footing.[10][11] Species discovery curves and the number of species only represented by one or a few individuals can be used to help in estimating how representative the available sample is of the population from which it was drawn.[12][13]
Trends
The observed species diversity is affected not only by the number of individuals but also by the heterogeneity of the sample. If individuals are drawn from different environmental conditions (or different habitats), the species diversity of the resulting set can be expected to be higher than if all individuals are drawn from a similar environment. Increasing the area sampled increases observed species diversity both because more individuals get included in the sample and because large areas are environmentally more heterogeneous than small areas.
See also
Notes
- ^ a b c Hill, M. O. (1973) Diversity and evenness: a unifying notation and its consequences. Ecology, 54, 427–432
- ^
- ^
- ^ Krebs, C. J. (1999) Ecological Methodology. Second edition. Addison-Wesley, California.
- ^ Magurran, A. E. (2004) Measuring biological diversity. Blackwell Publishing, Oxford.
- ^ a b Jost, L. (2006) Entropy and diversity. Oikos, 113, 363–375
- ^ Jost, L. (2007) Partitioning diversity into independent alpha and beta components. Ecology, 88, 2427–2439.
- ^ Colwell, R. K. and Coddington, J. A. (1994) Estimating terrestrial biodiversity through extrapolation. Philosophical Transactions: Biological Sciences, 345, 101-118.
- JSTOR 2257891
- ^ Good, I. J. and Toulmin, G. H. (1956) The number of new species, and the increase in population coverage, when a sample is increased. Biometrika, 43, 45-63.
- ^ Chao, A. (2005) Species richness estimation. Pages 7909-7916 in N. Balakrishnan, C. B. Read, and B. Vidakovic, eds. Encyclopedia of Statistical Sciences. New York, Wiley.
External links
- Harrison, Ian; Laverty, Melina; Sterling, Eleanor. "Species Diversity". Connexions (cnx.org). William and Flora Hewlett Foundation, the Maxfield Foundation, and the Connexions Consortium. Retrieved 1 February 2011. (Licensed under Creative Commons 1.0 Attribution Generic).