There are several reasons why the tools that have

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distributions and physiological characteristics (Purvis and Hector, 2000). There are several reasons why the tools that have been developed for assessing biodiversity in plant and animal communities are not appropriate for measuring microbial diversity. Ecologists have tradi- tionally relied on integrating multiple biotic and abiotic indexes to explain past trends in environmental parameters and to account for trajectories of change. The simplest measures of species diversity rely only on the number of species ( s ) and the total number of individ- Community species diversity Measurable characteristics: richness, evenness, composition, interaction Ecosystem functions Ecosystem resilience Alpha diversity (local ecosystems) Beta diversity (ecosystems across landscapes) Gamma diversity (regional and global ecosystems) Fig. 11.1 Indexes of species diversity and ecosystem function are based on some quantitatively measurable characteristics such as species richness, evenness of distribution, and composition. Some measures are more difficult to quantify, such as interactions among different species. Indexes of species diversity and parameters of environmental change are linked through the roles performed by species in sustaining ecosystem functions and ecosystem resilience. These roles are integrated into measures of biodiversity at differ- ent geographical scales, namely alpha, beta, and gamma diversities, which are sensitive to perturbations at the habitat, ecosystem, and global scales, respectively. OGU11 8/14/04 11:52 AM Page 227
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228 PART II Principles and applications uals representing all the species ( N ). For example, the Margalef index ( D m ) computes the species diversity according to the following equation (Margalef, 1958 and 1963): The Margalef index and similar indexes do not support the differentiation of com- munities that have identical s and N values because the evenness of the distribution of individuals within the communities is not considered. To correct this shortcoming, some investigators have introduced the concept of species dominance into measures of diversity. For example, Simpson (1949) demonstrated that if two individuals are selected randomly from a community, the probability ( P d ) that the two individuals belong to the same species is a measure of dominance ( d s ), and it is given by the following equation: where n i is the abundance of individual members belonging to species i . Simpson’s measure of dominance has been modified to compute species diversity as follows: Simpson’s diversity index has been referred to as the probability of an interspecific encounter, which expresses the number of times required to select two independent individuals at random from the community before both are found to belong to the same species (Hurlburt, 1971; Brower et al ., 1998). Estimates of D s are based on the assumption that the data on the number of species and abundance of individual members are derived from randomly collected environmental samples. However, in cases where it is possible to conduct an exhaustive sampling of a community (e.g. microcosm experiments), where
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