Weather correlates of temporal activity patterns in a desert lizard: insights for designing more effective surveys

Imperfect detection of individuals within an animal population can bias estimates of abundance and other population metrics. However, detectability may be improved by timing surveys with conditions that increase detection among individuals of the population. We explored the weather conditions that promote surface activity in a burrowing desert lizard, Slater's skink Liopholis slateri, with the aim of increasing detectability in observational surveys for this endangered species. We matched repeated count data (n = 126) of individuals within a population of Slater's skink sampled across four survey years with corresponding weather observations. We used classification and regression tree (CART) models to determine the environmental conditions that promoted high skink counts, and by inference high levels of surface activity. We also investigated how individual activity patterns varied over a day–night cycle through the course of a survey year using remote infrared cameras at burrow entrances set to capture images every 30 min. We found that two weather variables, air temperature and humidity, influenced activity levels, but there was no consistent single covariate, or set of covariates that explained surface activity. Variation in results of analysis between morning and evening datasets suggests that lizards respond to different weather conditions at different times of the day. We also found evidence of previously unreported nocturnal activity during the hottest months of the year. The issue of detectability is particularly pertinent to arid environments where extremes of temperature and aridity constrain surface activity of many animals (and researchers) over extended periods of time, limiting opportunities for behavioural observation. This study is one of the first to explore the environmental conditions that correlate with surface activity of a desert ectotherm, and could be useful for surveys of other species with low detection probabilities.