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Revisiting the Relation Between Species Diversity and Information Theory
Authors:Julio A Camargo
Institution:Departamento de Ecología, Facultad de Biología, Universidad de Alcalá, 28871, Alcala de Henares, Madrid, Spain. julio.camargo@uah.es
Abstract:The Shannon information function (H) has been extensively used in ecology as a statistic of species diversity. Yet, the use of Shannon diversity index has also been criticized, mainly because of its ambiguous ecological interpretation and because of its relatively great sensitivity to the relative abundances of species in the community. In my opinion, the major shortcoming of the traditional perspective (on the possible relation of species diversity with information theory) is that species need for an external receiver (the scientist or ecologist) to exist and transmit information. Because organisms are self-catalized replicating structures that can transmit genotypic information to offspring, it should be evident that any single species has two possible states or alternatives: to be or not to be. In other words, species have no need for an external receiver since they are their own receivers. Therefore, the amount of biological information (at the species scale) in a community with one only species would be log2 21 = 1 { \log }_{2} 2^{1} = 1 species, and not log2 1 = 0 { \log }_{2} 1 = 0 bits as in the traditional perspective. Moreover, species diversity appears to be a monotonic increasing function of log2 2\textS { \log }_{2} 2^{{\text{S}}} (or S) when all species are equally probable (S being species richness), and not a function of log2 \text S { \log }_{2} {\text{ S}} as in the traditional perspective. To avoid the noted shortcoming, we could use 2H (instead of H) for calculating species diversity and species evenness (= 2H/S). However, owing to the relatively great sensitivity of H to the relative abundances of species in the community, the value of species dominance (= 1 − 2H/S) is unreasonably high when differences between dominant and subordinate species are considerable, thereby lowering the value of species evenness and diversity. This unsatisfactory behaviour is even more evident for Simpson index and related algorithms. I propose the use of other statistics for a better analysis of community structure, their relationship being: species evenness + species dominance = 1; species diversity × species uniformity = 1; and species diversity = species richness × species evenness.
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