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- W852094073 abstract "Community ecology is often studied by the use of diversity indices. Historically, the most important indices are derived from Shannon and from Simpson’s formulas. Presently, there is a family of diversity indices, derived from Tsallis entropy, which include the above ones. The species/abundance models are also important to describe the observed patterns in nature. It is well known that, when sampling in natural communities, quadrats are used and that species populations usually exhibit an aggregated pattern of spatial distribution, instead of a random one. The main objective of this dissertation is to evaluate the possible effects that the community structure imposed by the classic species/abundance models, such as the logarithmic and geometric series and the lognormal distribution, the level of aggregation and the sampling method (by quadrats or individual sampling) would interfere with the estimation of the Tsallis diversity indices family. Simulations based on the modified Thomas method were performed (following other studies on the field), in which different scenarios were computationally created, representing the biological communities, with three treatments: (i) the species/abundance model, (ii) the aggregation level and, (iii) the sampling method. Then the performances of the maximum likelihood (MLE), jackknife and boostrap estimators were evaluated. The performances are measured by the relative bias around the population parameter, the length of the confidence intervals and also by the relative number of cases in which the confidence intervals covered the population parameter. It is observed that the MLE, in every scenario, generated more biased estimations than the two evaluated resampling methods. Also it is observed that the geometric series is the species/abundance distribution which caused less bias among the tested models, especially for species richness estimation. Concerning the aggregation patterns, it is observed that the medium levels of aggregation were those which produced lesser biased estimators. Thus, the sampling method analyses have shown a low intensity effect of the quadrat size over the bias in the diversity estimations, although such sampling method goes strongly against the principle of random sampling of individuals. Generally, the jackknife method is most precise than the bootstrap and, for indices that approach the species richness, the jackknife is also more accurate. Nevertheless, for those diversity indices which are more influenced by dominant species, it is strongly recommended the use of the bootstrap method of estimation." @default.
- W852094073 created "2016-06-24" @default.
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- W852094073 date "2011-02-25" @default.
- W852094073 modified "2023-09-26" @default.
- W852094073 title "AGREGAÇÃO E VIÉS EM MEDIDAS DE DIVERSIDADE: UMA ABORDAGEM COMPUTACIONAL INTENSIVA" @default.
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