Open AccessTaxonomic sufficiency and indicator taxa reduce sampling costs and increase monitoring effectiveness for ants
Author(s) -
Souza Jorge Luiz Pereira,
Baccaro Fabricio Beggiato,
Landeiro Victor Lemes,
Franklin Elizabeth,
Magnusson William Ernest,
Pequeno Pedro Aurélio Costa Lima,
Fernandes Itanna Oliveira
Publication year - 2016
Publication title -
diversity and distributions
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.918
H-Index - 118
eISSN - 1472-4642
pISSN - 1366-9516
DOI - 10.1111/ddi.12371
Subject(s) - species richness , taxon , ecology , biodiversity , global biodiversity , sampling (signal processing) , indicator species , taxonomic rank , biology , habitat , filter (signal processing) , computer science , computer vision
Aim Despite the accelerating loss of biodiversity and the increased number of methods for conservation planning, the availability of information about the spatial distribution of biodiversity remains limited. One way to overcome this problem is to focus on surrogate resolutions that are able to represent species‐level data and can be efficiently measured. Surrogates are only useful if the ecological patterns detected at the species‐level still hold when based on coarser taxonomic identification, and if these responses are consistent across regions. We present a comprehensive analysis using data from a large‐scale evaluation of ground‐dwelling ants, to evaluate the use of surrogates. Location Amazon basin. Methods The sampling design covered 13 sites in eight phytophysiognomies, which in conjunction with other environmental characteristics (altitude, soil granulometry and slope) were used to validate the ecological patterns (ability of the surrogates to reproduce the ecological responses identified for species) of coarser surrogate taxa (indicator taxa, mixed‐level approach, genus and subfamily). The surrogates were evaluated for their capacity to predict variation in total species richness and composition. We also estimated the monetary and time costs, in order to evaluate the cost‐effectiveness of using different surrogate levels. Results Genus was the most cost‐effective surrogate: it predicted 81% of site variation in species richness, was highly correlated ( r 2 = 0.76) with species composition, very highly correlated ( r 2 = 0.97) with ecological patterns detected at species level and saved ~40% of total project costs. The mixed‐level approach, indicator taxa and subfamily were not effective in representing the species‐level data. Main conclusions Genus can be used as a surrogate for species, due to its high predictive value, independent of environmental heterogeneity. Genus may be useful as a surrogate for species in other megadiverse regions, especially where savings in project costs can be applied to increase sampling effort.