Extreme fire weather is the major driver of severe bushfires in southeast Australia

In Australia, the proportion of forest area that burns in a typical fire season is less than for other vegetation types. However, the 2019-2020 austral spring-summer was an exception, with over four times the previous maximum area burnt in southeast Australian temperate forests. Temperate forest fires have extensive socio-economic, human health, greenhouse gas emissions, and biodiversity impacts due to high fire intensities. A robust model that identifies driving factors of forest fires and relates impact thresholds to fire activity at regional scales would help land managers and fire-fighting agencies prepare for potentially hazardous fire in Australia. Here, we developed a machine-learning diagnostic model to quantify nonlinear relationships between monthly burnt area and biophysical factors in southeast Australian forests for 2001-2020 on a 0.25° grid based on several biophysical parameters, notably fire weather and vegetation productivity. Our model explained over 80% of the variation in the burnt area. We identified that burnt area dynamics in southeast Australian forest were primarily controlled by extreme fire weather, which mainly linked to fluctuations in the Southern Annular Mode (SAM) and Indian Ocean Dipole (IOD), with a relatively smaller contribution from the central Pacific El Niño Southern Oscillation (ENSO). Our fire diagnostic model and the non-linear relationships between burnt area and environmental covariates can provide useful guidance to decision-makers who manage preparations for an upcoming fire season, and model developers working on improved early warning systems for forest fires.

Long-term patterns in estuarine fish growth across two climatically divergent regions

Long-term ecological datasets are vital for investigating how species respond to changes in their environment, yet there is a critical lack of such datasets from aquatic systems. We developed otolith growth 'chronologies' to reconstruct the growth history of a temperate estuarine fish species, black bream (Acanthopagrus butcheri). Chronologies represented two regions in south-east Australia: South Australia, characterised by a relatively warm, dry climate, and Tasmania, characterised by a relatively cool, wet climate. Using a mixed modelling approach, we related inter-annual growth variation to air temperature, rainfall, freshwater inflow (South Australia only), and El Niño-Southern Oscillation events. Otolith chronologies provided a continuous record of growth over a 13- and 21-year period for fish from South Australia and Tasmania, respectively. Even though fish from Tasmania were sourced across multiple estuaries, they showed higher levels of growth synchronicity across years, and greater year-to-year growth variation, than fish from South Australia, which were sourced from a single, large estuary. Growth in Tasmanian fish declined markedly over the time period studied and was negatively correlated to temperature. In contrast, growth in South Australian fish was positively correlated to both temperature and rainfall. The stark contrast between the two regions suggests that Tasmanian black bream populations are more responsive to regional scale environmental variation and may be more vulnerable to global warming. This study highlights the importance of examining species response to climate change at the intra-specific level and further validates the emerging use of growth chronologies for generating long-term ecological data in aquatic systems.