Please use this identifier to cite or link to this item: https://repositorio.inpa.gov.br/handle/1/17929
Title: Estimating density of ant nests using distance sampling
Authors: Baccaro, Fabricio Beggiato
Ferraz, Gonçalo
Keywords: Abundance
Ant
Bait
Estimation Method
Literature Review
Litter
Nest
Nest Site
Population Density
Quantitative Analysis
Sampling
Species Diversity
Tropical Forest
Amazonas
Manaus
Formicidae
Manihot Esculenta
Issue Date: 2013
metadata.dc.publisher.journal: Insectes Sociaux
metadata.dc.relation.ispartof: Volume 60, Número 1, Pags. 103-110
Abstract: The quantification of ant nest densities is a useful but challenging task given the group's high abundance and diversity of nesting sites. We present a new application of a distance-sampling method which follows standard distance analytical procedures, but introduces a sampling innovation that is particularly useful for ants; instead of having an observer look for ants we let ants find a bait station and measure the distances covered between nest and station. We test this method by estimating the density of epigaeic ant nests in an Amazon tropical forest site near Manaus, Brazil. We distributed 220 baits of canned sardine mixed with cassava flour among 10, 210-m long transects in old-growth upland forest. Forty-five minutes after baiting, we followed the ants' trails and measured the linear distance between the bait and each nest's entrance. We then used the freely available program DISTANCE to estimate the number of nests per unit area while accounting for the effect of distance on the probability that a colony will find a bait. There were found 38 species nesting in 287 different colonies, with an estimated 2. 66 nests/m2. This estimate fell within the 95 % confidence bounds of nest density predicted for a similar number of species based on a literature survey of ant species richness and nest density. Our sampling solution, however, takes less than 30 % of the time used by conventional sampling approaches for a similar area, with the advantage that it produces not only a point estimate but also a quantification of uncertainty about density. © 2012 International Union for the Study of Social Insects (IUSSI).
metadata.dc.identifier.doi: 10.1007/s00040-012-0274-2
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