Determination of diagnostic species with statistical fidelity measures

By Milan Chytrý, L. Tichý, Jason A. Holt, Z. Botta‐Dukát. 2002

825 citations recorded by the source corpus.

Subfields: Nature and Landscape Conservation, Plant Science

View Paper: https://www.semanticscholar.org/paper/4b551933af4a96fe0ffded68c675ac40aad5106f

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Citations in the corpus

Czech National Phytosociological Database: basic statistics ofthe available vegetation-plot data (2003, methodology): “…phytosociological data sets (Chytrý 2001), testing new formalized methods of vegetation classification and data analysis (Bruelheide & Chytrý 2000, Chytrý et al. 2002) and development of the computer program Juice (Tichý 2002), which includes several tools for numerical classification and…”
JUICE, software for vegetation classification (2002, methodology): “The program includes the following fidelity measures: binomial u value, hypergeometric u-value, f-coefficient, c2, G-statistic, Fisher’s exact test (Chytrý et al. 2002) and Indicator Value (Dufrêne & Legendre 1997).”
A methodological protocol for Annex i Habitats monitoring: The contribution of vegetation science (2016, background): “According to Dengler et al. (2008), the ‘diagnostic’ (characteristic or differential) species can be recognized in a vegetation type and their validity should be based on the concept of fidelity (see, e.g., Chytrý et al., 2002).”
Statistical determination of diagnostic species for site groups of unequal size (2006, methodology): “…(Dufrêne & Legendre 1997), to design procedures that would control for different size of basic sampling units (e.g. plot size of relevés) and for resulting differences in species richness (Dengler 2003), and to explore the effect of the context in which fidelity is measured (Chytrý et al. 2002b).”
Changes in vegetation types and Ellenberg indicator values after 65 years of fertilizer application in the Rengen Grassland Experiment, Germany. (2009, methodology): “In this table, species positively associated with individual treatments or groups of treatments were identified using the phi coefficient of association between species and treatments, based on presence/ absence data (Chytrý et al. 2002).”
Assessing species diagnostic value in large data sets: A comparison between phi-coefficient and Ochiai index (2008, methodology): “…relevé vegetation databases (Brisse et al. 1995; Ewald 2002; Font 2007; Hennekens & Schaminée 2001), diagnostic species and the objective measurement of fidelity have become a major research topic (Botta-Dukát & Borhidi 1999; Bruelheide 2000; Chytrý et al. 2002b; Tichý 2005; Tichý & Chytrý 2006).”
Diversity of Central European urban biota: effects of human‐made habitat types on plants and land snails (2011, background): “This coefficient is a statistical measure of the concentration of species occurrences in individual habitat types (Chytrý et al., 2002).”
The Variation of Testacean Assemblages (Rhizopoda) Along the Complete Base-Richness Gradient in Fens: A Case Study from the Western Carpathians (2006, background): “This coefficient shows the concentration of the species in the group of samples - a higher frequency of the species in the group as compared to the species frequency outside the group means a higher phi-coefficient (Chytrý et al. 2002).”
Identification of suitable unoccupied habitats in metapopulation studies using co-occurrence of species (2004, methodology): “The diagnostic species were selected as diagnostic species as defined by Chytrý (unpubl.) having the Phi /0.30 (Chytrý et al. 2002).”
History or abiotic filter: which is more important in determining the species composition of calcareous grasslands? (2009, result): “These methods offered similar results, therefore, only the results from the fidelity calculation expressed as a phi-coefficient (Sokal & Rohlf 2001, Chytrý et al. 2002) are presented in this paper (Table 4).”
Using species combinations in indicator value analyses (2012, methodology): “Several statistical alternatives already exist to address these questions (e.g. Dufrêne & Legendre 1997; Chytrý et al. 2002; De Cáceres & Legendre 2009; De Cáceres, Legendre & Moretti 2010b; Chazdon, Chao & Colwell 2011; Urban et al. 2012).”
New similarity indices for the assignment of relevés to the vegetation units of an existing phytosociological classification (2005, methodology): “FDi is a positive fidelity value (phi-coefficient) for species i to a selected vegetation unit present in analysed relevé (Chytrý et al. 2002).”
Habitat diversity of central European fens in relation to environmental gradients and an effort to standardise fen terminology in ecological studies (2006, methodology): “Fidelity was calculated as phi-coefficient (Chytrý et al., 2002a, b), the threshold value for inclusion to the table was arbitrarily set at 20. CF 1⁄4 calcareous fens; ERF 1⁄4 extremely rich fens; RF 1⁄4 rich fens; MRF 1⁄4 moderately rich fens; PF 1⁄4 poor fens. M. Hájek et al. / Perspectives in Pla”
Regeneration of sandy old-fields in the forest steppe region of Hungary (2011, methodology): “…were selected by the following procedure: in the database that contained relevés of agricultural habitats, forest plantations and semi-natural habitats, fidelity of species to the semi-natural habitats was determined by Fisher’s exact test (Chytrý et al. 2002) in the Juice program (Tichý 2002).”
EcoVeg: a new approach to vegetation description and classification (2014, methodology): “…and numerical analyses, such as two-way indicator species analysis (e.g., Roleček et al. 2009), indicator value index (Dufrêne and Legendre 1997), phi coefficient (e.g., Chytrý et al. 2002), and hybrid approaches that optimize clustering for diagnostic species values (e.g., Tichý et al. 2010).”