The sensitivity of early plant regeneration to environmental change makes regeneration a critical stage for understanding species response to climate change. We investigated the spatial and temporal response of eucalypt trees in the Central Highland region of south eastern Australia to high and low climate change scenarios. We developed a novel mechanistic model incorporating germination processes, TACA-GEM, to evaluate establishment probabilities of five key eucalypt species, Eucalyptus pauciflora, Eucalyptus delegatensis, Eucalyptus regnans, Eucalyptus nitens and Eucalyptus obliqua. Changes to regeneration potential at landscape and site levels were calculated to determine climate thresholds. Model results demonstrated that climate change is likely to impact plant regeneration. We observed increases and decreases in regeneration potential depending on the ecosystem, indicating that some species will increase in abundance in some forest types, whilst other forest types will become inhabitable. In general, the dry forest ecosystems were most impacted, whilst the wet forests were least impacted. We also observed that species with seed dormancy mechanisms, like E. pauciflora and E. delegatensis, are likely to be at higher risk than those without. Landscape- and site-level analysis revealed heterogeneity in species response at different scales. On a landscape scale, a 4.3 °C mean temperature increase and 22% decline in precipitation (predicted for 2080) is predicted to be a threshold for large spatial shifts in species regeneration niches across the study region, while a 2.6 °C increase and 15% decline in precipitation (predicted for 2050) will likely result in local site-level shifts. Site-level analysis showed that considerable declines in regeneration potential for E. delegatensis,E. pauciflora and E. nitens were modelled to occur in some ecosystems by 2050. While overall model performance and accuracy was good, better understanding of effects from extreme events and other underlying processes on regeneration will improve modelling and development of species conservation strategies.