Modelling the distribution of an oviparous skink, Oligosoma suteri

Predicting species distributions relies on understanding the fundamental constraints of climate conditions on organism’s physiological traits. Species distribution models (SDMs) provide predictions on species range limits and habitat suitability using spatial environmental data. Species distribution modelling is useful to estimate environmental conditions in time and space and how they may change in future climates. Predicting the distribution of terrestrial biodiversity requires an understanding of the mechanistic links between an organism’s traits and the environment. Implementation of mechanistic species distribution models requires knowledge of how environmental change influences physiological performance. Mechanistic modelling is considered more robust than correlative SDMs when extrapolating to novel environments predicted with climate change. I examined the spatial distribution and the impact of climate change on incubation duration of an endemic, nocturnal skink, Oligosoma suteri. My research focused on the ways a microclimate model with local weather data and degree-days can predict O. suteri’s distribution and affect incubation duration. Using a microclimate model (NicheMapR), I generated hourly soil temperatures for three depths in two substrate types (rock and sand) at a 15 km spatial resolution for the entire coastline of New Zealand and for seven depths for one substrate type (rock) for the coastline of Rangitoto/Motutapu Island at a 20 m spatial resolution. I estimated the minimum number of degree days required for successful embryonic development using a minimum temperature threshold for O. suteri eggs. I apply the incubation duration predicted by the model to map potential distribution for the two different spatial resolutions (15 km and 20 m) and I also include a climate change component to predict the potential effects on incubation duration and oviposition timing. My results from the New Zealand wide model indicate that embryonic development for O. suteri may be possible beyond their current distribution, and climate warming decreases incubation duration and lengthens the oviposition period for the New Zealand wide map. I generated maps of predicted incubation duration with depth for a coastal habitat at a higher resolution for Rangitoto/Motutapu Island. Incubation duration varied by depth with higher number of days to hatch predicted for greater depths. Temperature data loggers were installed at two different sites at three depths and were compared to the Rangitoto/Motutapu Island microclimate model. Modelled incubation durations were consistently shorter than data logger incubation durations across all three depths at both data logger sites. Species distribution model with coarse spatial and climate data can predict where soil temperatures would be suitable for successful development. A higher spatial resolution can reveal variation in incubation duration within sites indicated as suitable from the coarse resolution map. By using two different spatial extents initial starting points can be identified for which a higher resolution model can be applied to better inform management decisions relating to conservation actions and the effects of climate change for O. suteri and other species.