epp: Building data-set for realized and unrealized EPP-pairs

In valcu/expp: Spatial Analysis of Extra-Pair Paternity

Description

epp combines a SpatialPointsBreeding, a SpatialPolygons* as obtained from DirichletPolygons and a eppMatrix to create the spatial context for every potential and realized extra-pair male-female combination.

Usage

epp(breedingDat, polygonsDat, eppDat, maxlag = 3)

## S4 method for signature 'epp,missing'
plot(x, zoom, maxlag = 3, zoom.col = "grey", ...)

## S4 method for signature 'epp'
barplot(height, relativeValues = FALSE, ...)

## S4 method for signature 'epp'
as.data.frame(x)

Arguments

breedingDat	A SpatialPointsBreeding object, created by the SpatialPointsBreeding function
polygonsDat	A SpatialPolygons* object as obtained by calling DirichletPolygons function
eppDat	An object of class eppMatrix
maxlag	A numeric value indicating the maximum breeding distance for which male-female combinations should be calculated. When plotting it defines the outermost row of neighbors plotted around a focal id set by zoom
x, height	an epp object
zoom	a SpatialPointsBreeding id which is used for subsetting prior to plot
zoom.col	background color of the id (and hence the polygon) set by zoom
...	further arguments to pass to plot.SpatialPointsBreeding and plot.SpatialPolygons*
relativeValues	Defines the unit of the y-axis. TRUE plots proportions, FALSE absolute numbers.

Details

'plot' plots the territories, the identity of males ('m...') and females ('f...') at breeding sites (numbers), and the extra-pair events (dashed red arrows). Individuals that had extra-pair offspring are marked red. The parameter 'zoom' can be used to make a detailed visual check of a specific location (nestbox) and its surroundings.

'barplot' displays the distribution of extra-pair events over different breeding distances between the partners (in the number of territories) as vertical bars. Note that the distribution of all potential extra-pair partners is displayed as a dashed line only if the argument 'relativeValues' is TRUE.

Value

Returns an S4-class epp-object with 5 slots:

breedingDat	Input breeding data-set.
polygonsDat	Either polygons are estimated automatically using Thiessen Polygons, or input breeding polygons.
eppDat	Input data.frame with all male-female combinations that had EPP together.
maxlag	Input rank. Defaults to 3.
EPP	data.frame containing columns for the focal male and female ("male", "female"), their breeding distance ("rank"), and the parameters associated either with the male (column with prefix "_MALE") or the female (column with prefix "_FEMALE") territory.

See Also

vignette(expp)

Examples

  ### Simple example with three breeding pairs
  require(expp)
  # create raw data
  set.seed(1310)
  b = data.frame(id = as.integer(10:12), x = rnorm(3), y = rnorm(3), 
  male = paste0("m",1:3), female =  paste0("f",1:3), xx = rnorm(3), stringsAsFactors=FALSE  )  
  eppPairs = data.frame(male = c("m1", "m2", "m1"), female=c("f3", "f1", "f2") )
  
  # prepare data
  breedingDat = SpatialPointsBreeding(b, id = 'id', coords = ~ x + y, breeding = ~ male + female)
  polygonsDat = DirichletPolygons(breedingDat)
  eppDat   = eppMatrix(eppPairs, pairs = ~ male + female)

  plot(breedingDat, eppDat)
  
  # convert to epp class     
  x = epp(breedingDat, polygonsDat, eppDat, maxlag = 3)
  as.data.frame(x)
  
  
  #plot 
  plot(x) 
  
  ### Example on a random data set with n breeding pairs and  n/2 extra-pair paternity rate
  # create raw data
  set.seed(123)
  n = 20
  b = data.frame(id = 1:n, x = rnorm(n), y = rnorm(n), 
  male = paste0("m",1:n), female =  paste0("f",1:n), xx = rnorm(n), stringsAsFactors=FALSE  )  
  eppPairs = data.frame(male = sample(b$male, round(n/2) ), female = sample(b$female, round(n/2) ) )
  
  # prepare data
  breedingDat = SpatialPointsBreeding(b, id = 'id', coords = ~ x + y, breeding = ~ male + female)
  polygonsDat = DirichletPolygons(breedingDat)
  eppDat   = eppMatrix(eppPairs, pairs = ~ male + female)
  
  # convert to epp class
  x = epp(breedingDat, polygonsDat, eppDat, maxlag = 10)
  
  # plot 
  plot(x)
  barplot(x) 
  barplot(x, relativeValues = TRUE) 
  

   
  ### Real data example
  # Raw datasets 
  data(bluetit_breeding)
  data(bluetit_epp)
  # select one year 
  year = 2010
  b = bluetit_breeding[bluetit_breeding$year_ == year, ]
  eppPairs = bluetit_epp[bluetit_epp$year_ == year, ]
  
  # prepare data
  breedingDat  = SpatialPointsBreeding(b, id = 'id', coords = ~ x + y, breeding = ~ male + female)
  polygonsDat = DirichletPolygons(breedingDat)
  eppDat = eppMatrix(eppPairs, pairs = ~ male + female)
  
  # convert to epp class
  x = epp(breedingDat, polygonsDat, eppDat, maxlag = 2)
  
  # plot
  plot(x)
  barplot(x) 
  # plot zoom
  plot(x, zoom = 120, maxlag = 3) 
  
  # run model on epp probability     
  dat = as.data.frame(x)
  nrow(dat[dat$epp == 1, c('male', 'female')] )
  nrow(unique(eppPairs))
  
  if(require(lme4))
   (summary(glmer(epp ~ rank + male_age_MALE + (1|male) + (1|female), 
    data = dat, family = binomial)))


  

valcu/expp documentation built on June 20, 2021, 7:52 a.m.