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A variety of objective means exist to empirically measure biodiversity. Each measure relates to a particular use of the data, and is likely to be associated with the variety of genes. Biodiversity is commonly measured in terms of taxonomic richness of a geographic area over a time interval. In order to calculate biodiversity, species evenness ...
Consequently, some macroecological and community patterns cannot be fully expressed by alpha and beta diversity. Due to these two reasons, a new way of measuring species turnover, coined Zeta diversity (ζ-diversity), [ 12 ] has been proposed and used to connect all existing incidence-based biodiversity patterns.
The observed species richness 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 richness of the resulting set can be expected to be higher than if all individuals are drawn from similar environments.
Species richness, or biodiversity, increases from the poles to the tropics for a wide variety of terrestrial and marine organisms, often referred to as the latitudinal diversity gradient. [1] The latitudinal diversity gradient is one of the most widely recognized patterns in ecology. [1] It has been observed to varying degrees in Earth's past. [2]
Species abundance patterns can be best visualized in the form of relative abundance distribution plots. The consistency of relative species abundance patterns suggests that some common macroecological "rule" or process determines the distribution of individuals among species within a trophic level.
The technique of rarefaction was developed in 1968 by Howard Sanders in a biodiversity assay of marine benthic ecosystems, as he sought a model for diversity that would allow him to compare species richness data among sets with different sample sizes; he developed rarefaction curves as a method to compare the shape of a curve rather than absolute numbers of species.
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The concept is partly based on the earlier Essential Climate Variables. [ 3 ] [ 4 ] It can be generalised as the minimum set of variables for describing and predicting a system's state and dynamics. Areas with more developed EV lists include climate, ocean, and biodiversity.