spatstat (version 1.23-1)

ants: Harkness-Isham ants' nests data

Description

These data give the spatial locations of nests of two species of ants, Messor wasmanni and Cataglyphis bicolor, recorded by Professor R.D. Harkness at a site in northern Greece, and described in Harkness & Isham (1983). The full dataset (supplied here) has an irregular polygonal boundary, while most analyses have been confined to two rectangular subsets of the pattern (also supplied here).

The harvester ant M. wasmanni collects seeds for food and builds a nest composed mainly of seed husks. C. bicolor is a heat-tolerant desert foraging ant which eats dead insects and other arthropods. Interest focuses on whether there is evidence in the data for intra-species competition between Messor nests (i.e. competition for resources) and for preferential placement of Cataglyphis nests in the vicinity of Messor nests.

The full dataset is displayed in Figure 1 of Harkness & Isham (1983). See Usage below to produce a comparable plot. It comprises 97 nests (68 Messor and 29 Cataglyphis) inside an irregular convex polygonal boundary, together with annotations showing a foot track through the region, the boundary between field and scrub areas inside the region, and indicating the two rectangular subregions A and B used in their analysis. Rectangular subsets of the data were analysed by Harkness & Isham (1983), Isham (1984), Takacs & Fiksel (1986), S"arkk"a (1993, section 5.3), H"ogmander and S"arkk"a (1999) and Baddeley & Turner (2000). The full dataset (inside its irregular boundary) was first analysed by Baddeley & Turner (2005b). The dataset ants is the full point pattern enclosed by the irregular polygonal boundary. The $x$ and $y$ coordinates are eastings (E-W) and northings (N-S) scaled so that 1 unit equals 0.5 feet. This is a multitype point pattern object, each point carrying a mark indicating the ant species (with levels Cataglyphis and Messor).

The dataset ants.extra is a list of auxiliary information: [object Object],[object Object],[object Object],[object Object],[object Object]

Usage

data(ants)

source

Harkness and Isham (1983). Nest coordinates kindly provided by Prof Valerie Isham. Polygon coordinates digitised by Adrian Baddeley from a reprint of Harkness & Isham (1983).

References

Baddeley, A. and Turner, R. (2000) Practical maximum pseudolikelihood for spatial point patterns. Australian and New Zealand Journal of Statistics 42, 283--322. Baddeley, A. and Turner, R. (2005a) Spatstat: an R package for analyzing spatial point patterns. Journal of Statistical Software 12:6, 1--42. URL: www.jstatsoft.org, ISSN: 1548-7660.

Baddeley, A. and Turner, R. (2005b) Modelling spatial point patterns in R. In: A. Baddeley, P. Gregori, J. Mateu, R. Stoica, and D. Stoyan, editors, Case Studies in Spatial Point Pattern Modelling, Lecture Notes in Statistics number 185. Pages 23--74. Springer-Verlag, New York, 2006. ISBN: 0-387-28311-0.

Harkness, R.D. and Isham, V. (1983) A bivariate spatial point pattern of ants' nests. Applied Statistics 32, 293--303.

H"ogmander, H. and S"arkk"a, A. (1999) Multitype spatial point patterns with hierarchical interactions. Biometrics 55, 1051--1058.

Isham, V.S. (1984) Multitype Markov point processes: some approximations. Proceedings of the Royal Society of London, Series A, 391, 39--53.

Takacs, R. and Fiksel, T. (1986) Interaction pair-potentials for a system of ants' nests. Biometrical Journal 28, 1007--1013.

S"arkk"a, A. (1993) Pseudo-likelihood approach for pair potential estimation of Gibbs processes. Number 22 in Jyv"askyl"a Studies in Computer Science, Economics and Statistics. University of Jyv"askyl"a, Finland.

Examples

# Equivalent to Figure 1 of Harkness and Isham (1983)

  data(ants)
  ants.extra$plot()

  # Data in subrectangle A, rotated 
  # Approximate data used by Sarkka (1993)

  angle <- atan(diff(ants.extra$fieldscrub$y)/diff(ants.extra$fieldscrub$x))
  plot(rotate(ants.extra$A, -angle))

  # Approximate window used by Takacs and Fiksel (1986)

  tfwindow <- bounding.box(ants$window)
  antsTF <- ppp(ants$x, ants$y, window=tfwindow)
  plot(antsTF)