Leadbeater’s possum (Gymnobelideus leadbeateri) body weight, environmental and sex variables
We sought to determine if body weight in Leadbeater’s possum (Gymnobelideus leadbeateri) is related to environmental variables and/or sex. Using linear regression modelling, we quantified the influence on body weight of broadscale geographic variables such as latitude and elevation, site-level indicators of forest productivity (forest type, slope, aspect and topographic wetness) and an individual-level variable (sex). We found that body weight was significantly associated with elevation and sex, with individuals being heavier at higher elevations and males (on average) being heavier than females.
Steps to reproduce
We constructed linear regression models of the factors influencing body weight using the lm function in R (R Core Team 2021). We modelled latitude, elevation, slope, aspect, topographical wetness index, and sex as predictor variables in our global model (Table S1). We assessed the model residuals by plotting a histogram, scatter plot, and qq-plot. We reduced the number of covariates in the model using the stepAIC function from the MASS package (Venables and Ripley 2002), so that only the significant predictor variables were included in the best-fit model (Table S2). We completed post hoc analysis on the relationship between body weight and our best-fit predictor variables using the emmeans package (Lenth 2020).