Tree ferns are slow-growing and long-lived components of temperate forests; however, these characteristics make determining size-age and population dynamics through mensuration approaches problematic while dendroecological approaches cannot be used. In this study, we use radiocarbon (14C) dating of Cyathea australis and Dicksonia antarctica to (1) determine their age-to-size relationships, (2) reconstruct the age distribution of tree fern species, and (3) test if predicted ages align with the ages of the co-occurring tree community and observed disturbance history. We used the best age-size models to reconstruct the population structure of tree ferns sampled in five paired rainforest and old-growth eucalypt stands and compared these to the age structure of co-occurring tree species. The species had similar growth allometry; however, C. australis grew four times faster than D. antarctica. The age class structures of tree ferns were congruent with the associated tree species and reflected known fire history and snowfall events in the region. Tree fern abundance increased with increasing time-since-fire and post canopy disturbance. The study demonstrates that 14C dating of tree ferns provides a means of investigating tree fern demographics and the role of disturbance in shaping their population structure in forests of southeast Australia.

Increasing impacts of climatic change and anthropogenic disturbances on natural ecosystems are leading to population declines or extinctions of many species worldwide. In Australia, recent climatic change has caused population declines in some native fauna. The projected increase in mean annual temperature by up to 4°C by the end of the 21st century is expected to exacerbate these trends. The greater glider (Petauroides volans), Australia's largest gliding marsupial, is widely distributed along the eastern coast, but has recently experienced drastic declines in population numbers. Its association with hollow-bearing trees, used for nesting, has made it an important species for the conservation of old-growth forest ecosystems. Fires and timber harvesting have been identified as threats to the species. Greater gliders have disappeared however from areas that have experienced neither raising questions about the role of other factors in their decline. A unique physiology and strict Eucalyptus diet make them vulnerable to high temperatures and low water availability. As such, climatic conditions may drive habitat selection and recent climatic trends may be contributing to observed population declines. Using presence:absence data from across its distribution in Victoria, coupled with high spatial and temporal resolution climatic data and machinelearning modeling, we tested the influence of climatic, topographic, edaphic, biotic, and disturbance variables on greater glider occupancy and habitat suitability. We found that climatic variables, particularly those related to aridity and extreme weather conditions, such as number of nights warmer than 20°C, were highly significant predictors of greater glider occurrence. Climatic conditions associated with habitat suitability have changed over time, with increasing aridity across much of its southeastern distribution. These changes in climate are closely aligned with observed population declines across this region. At higher elevation, some areas where the greater glider is observed at high densities, conditions have become wetter, which is improving habitat quality. These areas are of growing significance to greater glider conservation as they will become increasingly important as climatic refugia in the coming decades. Protecting these areas of habitat will be critical for facilitating the conservation of greater gliders as the broader landscape becomes less hospitable under future climatic change.

Available climate data for south east Australia is reliant upon elevational lapse rates, which do not account for mesoscale processes that can affect temperatures, such as cold air drainage. Additional predictor variables are available for generating new climate datasets such as topographic indices and Moderate Resolution Imaging Spectroradiometer land surface temperature (MODIS LST); however, these have not been thoroughly tested to date. In this study, the relative benefits of including a localized topographic index and standardized MODIS LST values for temperature interpolation were assessed using partial bivariate splines, full and partial trivariate splines, and regression kriging. Trivariate splines provided the best interpolation performance in most cases; however, the partial bivariate spline with a fixed dependence upon elevation performed marginally better than the full trivariate spline for minimum temperature. The local topographic index improved the RMSE of minimum temperature climate normals by 17% in comparison to the best performing elevation only model. A further improvement for minimum temperature performance was achieved by including standardized night time MODIS LST values as covariates (34–39% reduction in RMSE). Standardized day time MODIS LST values improved maximum temperature interpolation performance; however, the improvement was only marginal in comparison to the full trivariate spline (6% reduction in RMSE). Cross validation of daily maximum and minimum temperature anomalies reflected performance trends shown in the climate normal analysis. Results suggest that the use of alternative approaches to interpolating temperature data may have significant implications for the calculation of bioclimatic variables and provide new opportunities to study extremes at high spatial and temporal resolutions using existing weather station networks. Furthermore, improving minimum temperature surfaces by accounting for temperature inversions driven by cold air drainage regimes may improve our ability to incorporate mesoscale temperature variability into a variety of applications, such as deriving temperature dependent climatic variables, species distribution modelling and assessments of fire risk.

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