Growth Rate Variation in Brown Treesnakes (Boiga irregularis): An Invasive Species of Conservation Concern - Björn Lardner; Brian S. Cade; Julie A. Savidge; Gordon H. Rodda; Robert N. Reed; Amy A. Yackel Adams (Ecology and Evolution, 2025)
ABSTRACT Somatic growth rate is a fundamental trait that influences metabolism, lifespan and reproductive maturity and is critical for understanding population dynamics and informing management actions. Brown Treesnakes (Boiga irregularis) introduced to Guam are highly invasive and can reproduce year‐round without discrete cohorts. We compared snake size trajectories described by the conventionally used von Bertalanffy growth function versus the Gompertz model. Using quantile regression with a regularized effect for individual snakes we modeled growth rates of 270 marked, wild snakes as a function of size. The Gompertz model explained more of the variation in growth and rendered more realistic predictions of asymptotic sizes than did the von Bertalanffy model. With the Gompertz model, growth rates were 1.05–1.16× faster in males than in females. Females reached asymptotic sizes at shorter snout‐vent lengths than males. Growth rate was positively correlated with amount of precipitation, and modeling wet‐dry seasonality on Guam as a sinusoidal function identified a growth peak in September—October. Effects of seasonality and precipitation, however, were minor compared to individual and sex related differences in size‐adjusted growth rates. We estimated that the 50th (and 5th, 95th) growth‐rate percentile males in our study population become sexually mature at an age of 33 (∞, 15) months, while females mature at 41 (∞, 18) months, where ∞ indicates that the slowest growing snakes never reach maturity. However, 50% of the snakes mature at a size below the median, and age at maturity may be as low as 10.4 (males) and 13.7 (females) months for average‐sized hatchlings that grow fast. Our results have implications for the timing of management options for this species and our approach can be broadly applied to animals where repeated growth data are obtained and age is unknown.