Data and analytical code to model the growth rate of brown treesnakes (Boiga irregularis), Guam 2004-2013

The data set consists of three files pertaining to invasive Brown Treesnakes (Boiga irregularis) and temporally-associated weather covariates on Guam: 1) snout-vent length (SVL) and sex of brown treesnakes (bts_growth.csv), 2) precipitation (bts_rain.csv), and 3) seasonality (bts_season.csv). Snout-vent lengths in millimeters (mm) and sex of 270 individually marked and recaptured brown treesnakes were accessed at irregular intervals between 2004-2013 in a 5-hectare enclosure that is geographically-closed to the snakes. Snakes were located by visual searches at night, by trapping, after they took radio-transmittered bait, and by incidental encounters. PIT tags (passive integrated transponders) and ventral scale clips allowed individual identification. Individual identity was also genetically evaluated through related research for this population (Levine et al. 2019). Snakes were measured stretching their body along a measuring tape and were retained only if consecutive captures were ≥20 days apart to minimize impacts of measurement errors. Dataset includes growth in snakes from immature to mature stages with an initial SVL measurement ≤850 mm, below the size at which the average male and female snake on Guam matures and with at least 150 mm increase in SVL. We also only included snakes with ≥4 measurements. Growth rates were then evaluated considering the amount of precipitation (mm) and seasonality. Rainfall data from the weather station at Guam International Airport, ca 18 km from our study site, spanning from March 2003 to July 2013 were obtained from the National Oceanic and Atmospheric Administration’s “NOWdata – NOAA Online Weather Data” (www.weather.gov/wrh/Climate?wfo=gum; accessed on 04 January 2022). Starting >1 year prior to the first growth rate estimate, for each date we calculated the cumulative precipitation (mm rain) the previous 90 days. There is distinct wet-dry seasonality on Guam with July−November having a mean monthly precipitation of 295 mm and December−June a mean monthly precipitation of 120 mm. A sinusoidal season covariate with a phase of 365 days and values oscillating between -1 and +1, lagged between 0 and 51 weeks were calculated for each date (bts_season.csv). We also provide code written in the R programming language to model growth rates of Brown Treesnakes as a function our weather associated covariates. This code filters the brown treesnake data set to create the records necessary to conduct the Gompertz and von Bertalanffy growth analyses with quantile regression.