%0 Journal Article %1 DeCaceres20101674 %A De Caceres, M. %A Legendre, P. %A Moretti, M. %D 2010 %J Oikos %K analysis bioindicator breadth correlation habitat niche quantitative type %N 10 %P 1674-1684 %R 10.1111/j.1600-0706.2010.18334.x %T Improving indicator species analysis by combining groups of sites %U http://www.scopus.com/inward/record.url?eid=2-s2.0-77956631921&partnerID=40&md5=358bb3c0464ca8b2d0507aab7b684981 %V 119 %X Indicator species are species that are used as ecological indicators of community or habitat types, environmental conditions, or environmental changes. In order to determine indicator species, the characteristic to be predicted is represented in the form of a classification of the sites, which is compared to the patterns of distribution of the species found at the sites. Indicator species analysis should take into account the fact that species have different niche breadths: if a species is related to the conditions prevailing in two or more groups of sites, an indicator species analysis undertaken on individual groups of sites may fail to reveal this association. In this paper, we suggest improving indicator species analysis by considering all possible combinations of groups of sites and selecting the combination for which the species can be best used as indicator. When using a correlation index, such as the point-biserial correlation, the method yields the combination where the difference between the observed and expected abundance/frequency of the species is the largest. When an indicator value index (IndVal) is used, the method provides the set of site-groups that best matches the observed distribution pattern of the species. We illustrate the advantages of the method in three different examples. Consideration of combinations of groups of sites provides an extra flexibility to qualitatively model the habitat preferences of the species of interest. The method also allows users to cross multiple classifications of the same sites, increasing the amount of information resulting from the analysis. When applied to community types, it allows one to distinguish those species that characterize individual types from those that characterize the relationships between them. This distinction is useful to determine the number of types that maximizes the number of indicator species. © 2010 The Authors.

@article{DeCaceres20101674, abbrev_source_title = {Oikos}, abstract = {Indicator species are species that are used as ecological indicators of community or habitat types, environmental conditions, or environmental changes. In order to determine indicator species, the characteristic to be predicted is represented in the form of a classification of the sites, which is compared to the patterns of distribution of the species found at the sites. Indicator species analysis should take into account the fact that species have different niche breadths: if a species is related to the conditions prevailing in two or more groups of sites, an indicator species analysis undertaken on individual groups of sites may fail to reveal this association. In this paper, we suggest improving indicator species analysis by considering all possible combinations of groups of sites and selecting the combination for which the species can be best used as indicator. When using a correlation index, such as the point-biserial correlation, the method yields the combination where the difference between the observed and expected abundance/frequency of the species is the largest. When an indicator value index (IndVal) is used, the method provides the set of site-groups that best matches the observed distribution pattern of the species. We illustrate the advantages of the method in three different examples. Consideration of combinations of groups of sites provides an extra flexibility to qualitatively model the habitat preferences of the species of interest. The method also allows users to cross multiple classifications of the same sites, increasing the amount of information resulting from the analysis. When applied to community types, it allows one to distinguish those species that characterize individual types from those that characterize the relationships between them. This distinction is useful to determine the number of types that maximizes the number of indicator species. © 2010 The Authors.}, added-at = {2012-04-06T18:59:48.000+0200}, affiliation = {Dépt de Sciences Biologiques, Univ. de Montréal, C.P. 6128, succursale Centre-ville, Montréal, QC, H3C 3J7, Canada; Centre Tecnològic Forestal de Catalunya, Ctra. St. Llorenç de Morunys km 2, ES-25280 Solsona, Catalonia, Spain; Swiss Federal Research Inst., WSL, Ecosystem Boundaries, Via Belsoggiorno 22, CH-6500 Bellinzona, Switzerland}, author = {De Caceres, M. and Legendre, P. and Moretti, M.}, biburl = {https://www.bibsonomy.org/bibtex/2934589419fb464c1a12c116168d4d037/s-boutry}, coden = {OIKSA}, correspondence_address = {De Cáceres, M.; Dépt de Sciences Biologiques, Univ. de Montréal, C.P. 6128, succursale Centre-ville, Montréal, QC, H3C 3J7, Canada; email: miquelcaceres@gmail.com}, document_type = {Article}, doi = {10.1111/j.1600-0706.2010.18334.x}, file = {:\\\\filer1.bordeaux.cemagref.fr\\stagiaires$\\Sebastien.Boutry\\Bureau\\Docs\\De-Caceres-M._Improving-indicator-species-analysis-by-combining-groups-of-sites_2010.pdf:PDF}, groups = {private}, interhash = {b56a3e1168eb87c9893d980954820dc0}, intrahash = {934589419fb464c1a12c116168d4d037}, issn = {00301299}, journal = {Oikos}, keywords = {analysis bioindicator breadth correlation habitat niche quantitative type}, language = {English}, note = {cited By (since 1996) 0}, number = 10, pages = {1674-1684}, references = {Aho, K., Using geometric and non-geometric internal evaluators to compare eight vegetation classification methods (2008) J. 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ADAI/CEIF Univ. of Coimbra; Willner, W., Effects of different fidelity measures and contexts on the determination of diagnostic species (2009) J. Veg. Sci., 20, pp. 130-137}, source = {Scopus}, timestamp = {2012-04-06T19:08:59.000+0200}, title = {Improving indicator species analysis by combining groups of sites}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-77956631921&partnerID=40&md5=358bb3c0464ca8b2d0507aab7b684981}, username = {s-boutry}, volume = 119, year = 2010 }