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Insectes Sociaux

, Volume 60, Issue 1, pp 103–110 | Cite as

Estimating density of ant nests using distance sampling

  • F. B. Baccaro
  • G. Ferraz
Research Article

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.

Keywords

Distance sampling Species density Formicidae Litter Tropical forest 

Notes

Acknowledgments

This paper was stimulated by conversations with J.D. Nichols, J.E. Hines and B.K. Williams during a 2007 workshop on Analysis and Management of Animal Populations at the Universidade Federal de Mato Grosso, Brazil. We are thankful to M. Kaspari for kindly providing site-specific data to the species density model, to Ricardo Braga-Neto for collecting and sharing litter depth measurements, and to Juliana Schietti for preparation of Fig. 1. Thiago Izzo, Alexander Christianini, Stephen Buckland and two anonymous reviewers offered valuable suggestions for improving the analysis and manuscript. F. Baccaro was supported by an Instituto Internacional de Educação do Brasil—IEB-Beca scholarship and fieldwork was supported by PPBio/MCT grants.

Supplementary material

40_2012_274_MOESM1_ESM.docx (43 kb)
Supplementary material 1 (DOCX 43 kb)

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Copyright information

© International Union for the Study of Social Insects (IUSSI) 2012

Authors and Affiliations

  1. 1.Programa de Pós-Graduação em Ecologia, Instituto Nacional de Pesquisas da Amazônia—INPAManausBrazil
  2. 2.Instituto Nacional de Pesquisas da Amazônia/Smithsonian Tropical Research InstituteBiological Dynamics of Forest Fragments ProjectManausBrazil
  3. 3.Smithsonian Tropical Research InstitutePanamaRepublic of Panama

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