Statistical performance of a multicomparison method for generalized species diversity indices under realistic empirical scenarios

Butturi-Gomes, Davi; Petrere, Miguel; Giacomini, Henrique C.; Zocchi, Silvio Sandoval

doi:10.1016/j.ecolind.2016.08.054

Cited by 7 publications

(3 citation statements)

References 38 publications

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“…For the purpose of this discussion, we assume that we have a sample of n individuals from the community in question. Most estimators of diversity assume that this sample is random, namely that its observations are independent and identically distributed [94]. But this requires either an infinite population, or sampling with replacement.…”

Section: Introductionmentioning

confidence: 99%

Ecological Diversity: Measuring the Unmeasurable

2018

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Diversity is a concept central to ecology, and its measurement is essential for any study of ecosystem health. But summarizing this complex and multidimensional concept in a single measure is problematic. Dozens of mathematical indices have been proposed for this purpose, but these can provide contradictory results leading to misleading or incorrect conclusions about a community's diversity. In this review, we summarize the key conceptual issues underlying the measurement of ecological diversity, survey the indices most commonly used in ecology, and discuss their relative suitability. We advocate for indices that: (i) satisfy key mathematical axioms; (ii) can be expressed as so-called effective numbers; (iii) can be extended to account for disparity between types; (iv) can be parameterized to obtain diversity profiles; and (v) for which an estimator (preferably unbiased) can be found so that the index is useful for practical applications.

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Section: Introductionmentioning

confidence: 99%

Ecological Diversity: Measuring the Unmeasurable

2018

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“…See Daly, Baetens, and Baets (2018) for an excellent overview and Sherwin and Prat I Fornells (2019) for a discussion of the history. Within ecology it is well-known that undersampling can result in inaccurate and biased estimates of diversity measures (Beck and Schwanghart 2010;Beck, Holloway, and Schwanghart 2013) and the performance of different statistical methods has been studied for realistic scenarios (Butturi-Gomes et al 2017;Brocklehurst, Day, and Fr€ obisch 2018). In response, better estimators have been proposed that are based on the discovery rate of new species (Chao, Wang, and Jost 2013;Chao and Jost 2015;Haegeman et al 2013), measures such as pairwise dissimilarities (Marion 2016) have been used as alternatives, and Bayesian estimators have been developed (Marion, Fordyce, and Fitzpatrick 2018).…”

Section: Introductionmentioning

confidence: 99%

Quantifying errors in the aerosol mixing-state index based on limited particle sample size

Gasparik

Curtis

et al. 2020

Aerosol Science and Technology

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This study evaluates the error that is introduced in quantifying observed aerosol mixing states due to a limited particle sample size. We used the particle-resolved model PartMC-MOSAIC to generate a scenario library that encompasses a large number of reference particle populations with a wide range of mixing states quantified by the mixing-state index v. We stochastically sub-sampled these particle populations using sample sizes of 10 to 10,000 particles and recalculated v based on the sub-samples. The finite sample size led to a consistent overestimation of v, with the 95% confidence intervals ranging from À70 to 30 percentage points for sample sizes of 10 particles, and decreasing to ±10 percentage points for sample sizes of 10,000 particles. These findings were experimentally confirmed with singleparticle measurements from the Pittsburgh area using a soot-particle aerosol mass spectrometer.

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“…Measures of biological or species diversity are central to ecology and conservation biology (e.g., MacArthur, 1965, Magurran, 2004, Pielou, 1975, Whittaker, 1960, Williams, 1964. If appropriate conservation policies are to be implemented, then appropriate measures of community structure must continue to be developed (Butturi-Gomes et al, 2017). Buckland et al (2005) assert that no single index can capture all aspects related to the dynamics of biodiversity.…”

Section: Introductionmentioning

confidence: 99%

A supplementary tool to existing approaches for assessing ecosystem community structure

Hopton

Karunanithi

Garmestani

et al. 2017

Ecological Modelling

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Measures of biological or species diversity are central to ecology and conservation biology. Although there are several commonly used indices, each has shortcomings and all vary in the relative emphasis they place on the number of species and their relative abundance. We propose utilizing Fisher Information, not as a replacement for existing indices, but as a supplement to other indices because it is sensitive to community structure. We demonstrate how Shannon's and Simpson's diversity indices quantify the diversity of two different systems and how Fisher Information can enhance the analyses by comparing, as example, body size, and phylogenetic diversity of the different communities. Fisher Information is sensitive to the order in which species are entered into the analysis, and therefore, it can detect differences in community structure. Thus, the Fisher Information index can be useful in helping understand and analyze biodiversity of ecosystems and in comparing ecological communities.

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Statistical performance of a multicomparison method for generalized species diversity indices under realistic empirical scenarios

Cited by 7 publications

References 38 publications

Ecological Diversity: Measuring the Unmeasurable

Ecological Diversity: Measuring the Unmeasurable

Quantifying errors in the aerosol mixing-state index based on limited particle sample size

A supplementary tool to existing approaches for assessing ecosystem community structure

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