Static occupancy model

The quintessential package for fauna abundance and analysis.

• Model occupation, abundance and density of unmarked animals.
• Analogous to Presence program
• Contrast with the Mark program

• Single-season site occupancy model (MacKenzie et al., 2002)
• Royle-Nichols model (Royle and Nichols, 2003)
• Binomial N-mixture models (Royle, 2004b)
• Multinomial N-mixture models (Royle, 2004a)
• Distance sampling models (Royle et al., 2004)
• “Open population” versions of the above: (MacKenzie et al., 2003; Chandler et al., 2011; Dail and Madsen, 2011)

• The sampling units are the sites
• Ideally there should be at least 3 visits per site
• The covariates ideally in another table.

- Site covariates and observation covariates (several tables).

Data structure

The three tables are linked in a special object called unmarkedFrame.

umf <- unmarkedFrame (y = detections,
                      siteCovs = sitedata,
                      obsCovs = list(wind=viento, date=fecha))

Example of the static model (Mackenzie 2002), a single season.

Start a new project in Rstudio

Download the code

Download the data and install in the data folder

vignette by unmarkedFrameOccu

# Fake data
R <- 4 # number of sites
J <- 3 # number of visits
y <- matrix(c(1,1,0,0,0,0,1,1,1,1,0,1), nrow=R, ncol=J, byrow=TRUE)
site.covs <- data.frame(x1=1:4, x2=factor(c('A','B','A','B')))
obs.covs <- list(
   x3 = matrix(c(-1,0,1,-2,0,0,-3,1,0,0,0,0), nrow=R, ncol=J, byrow=TRUE),
   x4 = matrix(c(
      'a','b','c',
      'd','b','a',
      'a','a','c',
      'a','b','a'), nrow=R, ncol=J, byrow=TRUE))
umf <- unmarkedFrameOccu(y=y, siteCovs=site.covs, obsCovs=obs.covs) # organize data
umf                     # look at data
summary(umf)            # summarize      
fm <- occu(~1 ~1, umf)  # fit a model

Packages: R2jags, spatstat, raster, rgeos, sp

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