2012
DOI: 10.1016/j.ecolind.2012.04.023
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How far can we go in simplifying biomonitoring assessments? An integrated analysis of taxonomic surrogacy, taxonomic sufficiency and numerical resolution in a megadiverse region

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Cited by 85 publications
(60 citation statements)
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References 65 publications
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“…Successional changes in the liana community in this landscape were highly correlated with those of the non-liana community (Mantel test, = 0.61, P = 0.0019). A similar pattern of floristic congruence between trees and lianas has been found in the south-western and north central Amazon (Macía et al 2007;Landeiro et al 2012). Lianas in the Bignoniaceae had one of the highest levels of floristic congruence with other taxa, suggesting a possible role for lianas in biomonitoring and rapid vegetation inventories (Landeiro et al 2012).…”
Section: Species Composition Patternsmentioning
confidence: 62%
“…Successional changes in the liana community in this landscape were highly correlated with those of the non-liana community (Mantel test, = 0.61, P = 0.0019). A similar pattern of floristic congruence between trees and lianas has been found in the south-western and north central Amazon (Macía et al 2007;Landeiro et al 2012). Lianas in the Bignoniaceae had one of the highest levels of floristic congruence with other taxa, suggesting a possible role for lianas in biomonitoring and rapid vegetation inventories (Landeiro et al 2012).…”
Section: Species Composition Patternsmentioning
confidence: 62%
“…Compared with abundance data, presence–absence data have several advantages: (1) Presence–absence data can increase efficiency in ecological and conservation research because they are easier to collect than abundance data and are much less costly in terms of time, price, and human resources, especially at large spatial or temporal scales (Badenhausser, Amouroux, & Bretagnolle, 2007; Casner, Forister, Ram, & Shapiro, 2014; Fukuda, Mouton, & De Baets, 2012; Furnas, 2013; Gu & Swihart, 2004; Gutiérrez, Harcourt, Díez, Gutiérrez Illán, & Wilson, 2013; Joseph, Field, Wilcox, & Possingham, 2006; MacKenzie & Nichols, 2004; Ribas & Padial, 2015). (2) In many cases, when differences among groups are large, presence–absence data can provide adequate indicators to describe ecological patterns, which are often in agreement with those obtained from abundance data (Carneiro, Bini, & Rodrigues, 2010; Landeiro et al., 2012; Melo, 2005; Ribas & Padial, 2015; Tweedley, Warwick, & Potter, 2015). (3) Presence–absence data can remove much of the noise induced by sampling biases or errors, whereas large sampling errors can lead to unreliable abundance data (Hirst & Jackson, 2007; Jackson & Harvey, 1997).…”
Section: Methodsmentioning
confidence: 99%
“…Thus, if the community variation patterns are consistent between at least two groups, is possible to simplify monitoring programs by sampling only one group (Johnson & Hering 2010;Landeiro et al, 2012). Furthemore, higher taxonomic levels can be used, as information on family level or genus replacing species (taxonomic resolution) or species occurrence família?…”
Section: Introductionmentioning
confidence: 99%
“…The environmental impacts have been occurring faster than we can monitor and maintain biodiversity (Bini et al, 2007;Landeiro et al, 2012;Martinelli et al, 2010). The increase of impacted areas affects directly and indirectly the functioning of terrestrial and aquatic ecosystems, highly contributing to the extinction of species (Ceballos et al, 2015).…”
Section: Introductionmentioning
confidence: 99%