Exploring the future of fuel loads in Tasmania, Australia: shifts in vegetation in response to changing fire weather, productivity, and fire frequency

Changes to the frequency of fire due to management decisions and climate change have the potential to affect the flammability of vegetation, with long-term effects on the vegetation structure and composition. Frequent fire in some vegetation types can lead to transformational change beyond which the vegetation type is radically altered. Such feedbacks limit our ability to project fuel loads under future climatic conditions or to consider the ecological tradeoffs associated with management burns. We present a “pathway modelling” approach to consider multiple transitional pathways that may occur under different fire frequencies. The model combines spatial layers representing current and future fire danger, biomass, flammability, and sensitivity to fire to assess potential future fire activity. The layers are derived from a dynamically downscaled regional climate model, attributes from a regional vegetation map, and information about fuel characteristics. Fire frequency is demonstrated to be an important factor influencing flammability and availability to burn and therefore an important determinant of future fire activity. Regional shifts in vegetation type occur in response to frequent fire, as the rate of change differs across vegetation type. Fire-sensitive vegetation types move towards drier, more fire-adapted vegetation quickly, as they may be irreversibly impacted by even a single fire, and require very long recovery times. Understanding the interaction between climate change and fire is important to identify appropriate management regimes to sustain fire-sensitive communities and maintain the distribution of broad vegetation types across the landscape

Characterizing spatial and temporal variability of lightning activity associated with wildfire over Tasmania, Australia

Lightning strikes are pervasive, however, their distributions vary both spatially and in time, resulting in a complex pattern of lightning-ignited wildfires. Over the last decades, lightning-ignited wildfires have become an increasing threat in south-east Australia. Lightning in combination with drought conditions preceding the fire season can increase probability of sustained ignitions. In this study, we investigate spatial and seasonal patterns in cloud-to-ground lightning strikes in the island state of Tasmania using data from the Global Position and Tracking System (GPATS) for the period January 2011 to June 2019. The annual number of lightning strikes and the ratio of negative to positive lightning (78:22 overall) were considerably different from one year to the next. There was an average of 80 lightning days per year, however, 50% of lightning strikes were concentrated over just four days. Most lightning strikes were observed in the west and north of the state consistent with topography and wind patterns. We searched the whole population of lightning strikes for those most likely to cause wildfires up to 72 h before fire detection and within 10 km of the ignition point derived from in situ fire ignition records. Only 70% of lightning ignitions were matched up with lightning records. The lightning ignition efficiency per stroke/flash was also estimated, showing an annual average efficiency of 0.24% ignition per lightning stroke with a seasonal maximum during summer. The lightning ignition efficiency as a function of different fuel types also highlighted the role of buttongrass moorland (0.39%) in wildfire incidents across Tasmania. Understanding lightning climatology provides vital information about lightning characteristics that influence the probability that an individual stroke causes ignition over a particular landscape. This research provides fire agencies with valuable information to minimize the potential impacts of lightning-induced wildfires through early detection and effective response

Impact of vertical atmospheric structure on an atypical fire in a mountain valley

Wildfires are not only a natural part of many ecosystems, but they can also have disastrous consequences for humans, including in Australia. Rugged terrain adds to the difficulty of predicting fire behavior and fire spread, as fires often propagate contrary to expectations. Even though fire models generally incorporate weather, fuels, and topography, which are important factors affecting fire behavior, they usually only consider the surface wind; however, the more elevated winds should also be accounted for, in addition to surface winds, when predicting fire spread in rugged terrain because valley winds are often dynamically altered by the interaction of a layered atmosphere and the topography. Here, fire spread in rugged terrain was examined in a case study of the Riveaux Road Fire, which was ignited by multiple lightning strikes in January 2019 in southern Tasmania, Australia and burnt approximately 637.19 km2. Firstly, the number of conducive wind structures, which are defined as the combination of wind and temperature layers likely to result in enhanced surface wind, were counted by examining the vertical wind structure of the atmosphere, and the potential for above-surface winds to affect fire propagation was identified. Then, the multiple fire propagations were simulated using a new fire simulator (Prototype 2) motivated by the draft specification of the forthcoming new fire danger rating system, the Australian Fire Danger Rating System (AFDRS). Simulations were performed with one experiment group utilizing wind fields that included upper-air interactions, and two control groups that utilized downscaled wind from a model that only incorporated surface winds, to identify the impact of upper air interactions. Consequently, a detailed analysis showed that more conducive structures were commonly observed in the rugged terrain than in the other topography. In addition, the simulation of the experiment group performed better in predicting fire spread than those of the control groups in rugged terrain. In contrast, the control groups based on the downscaled surface wind model performed well in less rugged terrain. These results suggest that not only surface winds but also the higher altitude winds above the surface are required to be considered, especially in rugged terrain