FlexParamCurve (version 1.5-6)

tern.data: Field data on growth of common terns \(Sterna hirundo\)

Description

The tern.data data frame has 1164 rows and 12 columns of records of the measured masses for common tern chicks between 1 and 30 days of age collected at at Grays Beach, MA, in 1973 (Nisbet 1975) and Monomoy, MA, in 1975 (Nisbet et al. 1978)

Usage

tern.data

Format

This object of class c("nfnGroupedData", "nfGroupedData", "groupedData", "data.frame") containing the following columns:

site

Four character factor for the two sites (MYMA: Monomoy Island, MA; GBCT: Grays Beach, CT).

year

A factor specifying the year of measurement: 1973 or 1976.

bandid

an ordered factor indicating unique id of each individual: the union of the laying date of the nest relative to the colony and the band combination

siteyear

A factor specifying levels of year for different sites (different years at each site).

weight

a numeric vector of chick masses (g).

ckage

a numeric vector of chick ages (days).

Jdate

a numeric vector of first egg-laying date of the nest(days), relative to the mean laying date for all nests in that year.

nest

A factor of unique codes that identify each nest.

ck

A factor of hatching order for each chick (A = first hatched, B = second hatched C = third hatched).

outcome

A factor of codes for fate of each chick (F = fledged; only fledged chicks included).

eggmass

A numeric vector of the mass of the egg (from which the chick hatched) at laying.

clutch

A factor of size of clutch/brood that each chick comes from (either 1- or 2-chick brood).

Details

Data were collected as outlined in Nisbet (1975)[Grays Beach, MA, 1973] and Nisbet et al.(1978) [Monomoy, MA, 1975]. Please contact Ian Nisbet <[e-mail]> for use in collaborations.

Examples

require(stats); require(graphics)
#view data
tern.data
#create pnmodelparams for fixed parameters
modpar(tern.data$ckage, tern.data$weight, force4par = TRUE, pn.options = "myoptions")
plot(weight ~ ckage, data = tern.data, subset = bandid == tern.data$bandid[1],
     xlab = "Chick age (day)", las = 1,
     ylab = "Chick mass (g)",
     main = "tern.data and fitted curve (Chick #156 only)")
fm1 <- nls(weight ~ SSposnegRichards(ckage,Asym=Asym,K=K,Infl=Infl,modno=32,
           pn.options= "myoptions"),
           data = tern.data, subset = bandid == tern.data$bandid[1])
ckage <- seq(0, 30, length.out = 101)
lines(ckage, predict(fm1, list(ckage = ckage)))