A new measure of fidelity and its application to defining species groups

By Helge Bruelheide. 2000

175 citations recorded by the source corpus.

Subfields: Nature and Landscape Conservation, Plant Science

View Paper: https://www.semanticscholar.org/paper/1312000e4bfecbba5b7bf06ec9f82261dad4a5a2

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In Nature and Landscape Conservation

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Citations in the corpus

Determination of diagnostic species with statistical fidelity measures (2002, unknown): “In addition, arbitrary weighting of species abundances is avoided by using categorical data (Bruelheide 2000).”
Statistical determination of diagnostic species for site groups of unequal size (2006, methodology): “(1) Bruelheide (1995, 2000) introduced an alternative notation for defining statistical measures of fidelity, which was also used by Chytrý et al. (2002a): N = number of sites in the data set, Np = number of sites in the target site group, n = number of occurrences of the species in the data set,…”
Testing a relict distributional pattern of fen plant and terrestrial snail species at the Holocene scale: a null model approach (2011, methodology): “The vascular plant and bryophyte species were identified as calcareous fen specialists with the help of the COCKTAIL method (Bruelheide, 2000) using juice software (Tichý, 2002).”
Associations between species and groups of sites: indices and statistical inference. (2009, background): “The determination of diagnostic species is still an active research topic in vegetation science (e.g., Bruel- heide 1995, 2000, Chytrý et al. 2002a, b, Tichý and Chytrý 2006, De Cáceres et al. 2008, Willner et al. 2009), where the most widely used index is the phi coefficient of association or…”
New similarity indices for the assignment of relevés to the vegetation units of an existing phytosociological classification (2005, background): “A statistical measures related to fidelity have already been developed by several authors (e.g. Dufrêne and Legendre 1997; Bruelheide 2000).”
A network approach for inferring species associations from co-occurrence data (2016, background): “The recent increase in availability of occurrence data has brought a renewed interest in using correlations and algorithms to infer species associations and the mechanisms behind them (Bruelheide 2000, Blick and Burns 2009, Blois et al. 2014).”
Using species combinations in indicator value analyses (2012, background): “Several alternatives exist for the statistical determination of indicator species (e.g., Hill 1979; Dufrêne & Legendre 1997; Bruelheide 2000; Chytrý et al. 2002; Chazdon, Chao&Colwell 2011; Urban et al. 2012).”
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).”
Habitat diversity of central European fens in relation to environmental gradients and an effort to standardise fen terminology in ecological studies (2006, methodology): “Several species groups were created by the Cocktail method (Bruelheide, 2000; see bottom of Table 1).”
JUICE, software for vegetation classification (2002, methodology): “The combination of different species groups using logical operators allows the user to re-define commonly known vegetation units in a formal way (Bruelheide 1997, 2000; Pflume 1999).”
EcoVeg: a new approach to vegetation description and classification (2014, background): “Differential species are distinctly more widespread or abundant in a pair or closely related sets of plant communities than in the other(s), though they may still be more abundant in other communities not under consideration (Curtis 1959, Bruelheide 2000).”