Reactive scope model and emergency life history stage provide useful tools for evaluating the stress responses of native Australian lizards living in disturbed landscapes

Glucocorticoids (GCs) are used as biomarkers of physiological stress response in reptiles. Fundamental stress physiology tools including the emergency life history stage (ELHS) and the reactive scope model (RSM) can be useful to determine how individual variation of stress responses shape population ecology. In this perspective, we applied the RSM and ELHS into the context of two urban-dwelling small native Australian reptile species to compare the stress-response patterns in short- and long-breeding lizards. Firstly, by drawing inferences from the ELHS, we presented hypothetical scenarios using sample GC data for a short-breeding species (e.g. common blue-tongue lizard). We showed that activation of the physiological stress response would be non-adaptive due to the consequences of stress on reproduction. Therefore, blue-tongue lizards may become exposed to acute and chronic environmental stressors (e.g. human disturbance and habitat clearance) during the breeding season as they prefer not to activate their hypothalamo-pituitary interrenal (HPI) axis in support of their short-breeding season. On the contrary, long-breeding lizards (e.g. bearded dragons), which have multiple breeding opportunities and are accustomed to living around humans and altered urban environments, tended to operate above the critical adaptive value of the ELHS during their breeding period. This suggests that any future changes to the dynamics of habitat availability and breeding opportunities may favour the dragon differently over the blue-tongue lizard. To further capture the dynamics of stress responses along spatial and temporal scales, we suggested that researchers should collect field data (e.g. blood plasma or faecal GCs) and then use the ELHS and RSM to understand how the environment is shaping the animal’s stress physiology. The application of field stress monitoring and data visualization using the ELHS and RSM could guide environmental monitoring and conservation programs of native wildlife species.