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Abstract. Smoke from wildfires poses a significant threat to affected communities. Prescribed burning is conducted to reduce the extent and potential damage of wildfires, but produces its own smoke threat. Planners of prescribed fires model the likely dispersion of smoke to help manage the impacts on local communities. Significant uncertainty remains about the actual smoke impact from prescribed fires, especially near the fire, and the accuracy of smoke dispersal models.To address this uncertainty, a detailed study of smoke dispersal was conducted for one small (52 ha) and one large (700 ha) prescribed fire near Appin in New South Wales, Australia, through the use of stationary and handheld pollution monitors, visual observations and rain radar data, and by comparing observations to predictions from an atmospheric dispersion model. The 52 ha fire produced a smoke plume about 800 m high and 9 km long. Particle concentrations (PM 2.5 ) reached very high peak values (> 400 µg m −3 ) and high 24 h average values (> 100 µg m −3 ) at several locations next to or within ∼ 500 m downwind from the fire, but low levels elsewhere. The 700 ha fire produced a much larger plume, peaking at ∼ 2000 m altitude and affecting downwind areas up to 14 km away. Both peak and 24 h average PM 2.5 values near the fire were lower than for the 52 ha fire, but this may be because the monitoring locations were further away from the fire. Some lofted smoke spread north against the ground-level wind direction. Smoke from this fire collapsed to the ground during the night at different times in different locations. Although it is hard to attribute particle concentrations definitively to smoke, it seems that the collapsed plume affected a huge area including the towns of Wollongong, Bargo, Oakdale, Camden and Campbelltown (∼ 1200 km 2 ). PM 2.5 concentrations up to 169 µg m −3 were recorded on the morning following the fire. The atmospheric dispersion model accurately predicted the general behaviour of both plumes in the early phases of the fires, but was poor at predicting fine-scale variation in particulate concentrations (e.g. places 500 m from the fire). The correlation between predicted and observed varied between 0 and 0.87 depending on location. The model also completely failed to predict the night-time collapse of the plume from the 700 ha fire.This study provides a preliminary insight into the potential for large impacts from prescribed fire smoke to NSW communities and the need for increased accuracy in smoke dispersion modelling. More research is needed to better understand when and why such impacts might occur and provide better predictions of pollution risk.

Sequestration of carbon in forest ecosystems has been identified as an effective strategy to help mitigate the effects of global climate change. Prescribed burning and timber harvesting are two common, co‐occurring, forest management practices that may alter forest carbon pools. Prescribed burning for forest management, such as wildfire risk reduction, may shorten inter‐fire intervals and potentially reduce carbon stocks. Timber harvesting may further increase the susceptibility of forest carbon to losses in response to frequent burning regimes by redistributing carbon stocks from the live pools into the dead pools, causing mechanical damage to retained trees and shifting the demography of tree communities. We used a 27‐yr experiment in a temperate eucalypt forest to examine the effect of prescribed burning frequency and timber harvesting on aboveground carbon (AGC). Total AGC was reduced by ~23% on harvested plots when fire frequency increased from zero to seven fires, but was not affected by fire frequency on unharvested plots. The reduction in total AGC associated with increasing fire frequency on harvested plots was driven by declines in large coarse woody debris (≥10 cm diameter) and large trees (≥20 cm diameter). Small tree (<20 cm DBH) AGC increased with fire frequency on harvested plots, but decreased on unharvested plots. Carbon in dead standing trees decreased with increasing fire frequency on unharvested plots, but was unaffected on harvested plots. Small coarse woody debris (<10 cm diameter) was largely unaffected by fire frequency and harvesting. Total AGC on harvested plots was between 67% and 82% of that on unharvested plots, depending on burning treatment. Our results suggest that AGC in historically harvested forests may be susceptible to declines in response to increases in prescribed burning frequency. Consideration of historic harvesting will be important in understanding the effect of prescribed burning programs on forest carbon budgets.

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Bushfire survival plans are a valuable tool for residents living in fire-prone landscapes. Plans include assigning trigger points for action, roles for all household members, and alternate approaches should the original plan fail. Fire agencies advocate that residents write, practise and discuss these plans before the fire season. In this study we use a multiple-methods approach to examine the theoretical and actual application of bushfire survival plans in south-east Australia. First, we review agency advice regarding survival plans to determine the consistency, clarity and specificity of the advice. Second, an online survey of residents examines the relationships between types of plans, with the planned action during a wildfire, gender and past experience with fire. Finally, semi-structured interviews with residents who have experienced wildfire examine the reality of decision-making, triggers used for actions and the role of survival plans. The study concludes that: a) fire agencies provide clear and concise information around survival plans despite some variation between states; b) preparation of survival plans is limited by the same range of factors that limit the extent of overall wildfire preparedness; and c) without a written, discussed and practised plan, decision-making during a wildfire may be impaired with potentially fatal consequences. Wildfire survival plans are a valuable tool for residents living in fire-prone landscapes. Plans include 15 assigning trigger points for action, roles for all household members, and alternate approaches should 16 the original plan fail. Fire agencies advocate that residents write, practice and discuss these plans 17 before the fire season. In this study we use a multiple-methods approach to examine the theoretical 18 and actual application of wildfire survival plans in southeast Australia. First, we review agency advice 19 regarding survival plans to determine the consistency, clarity and specificity of the advice. Secondly, 20 an online survey of residents examines the relationships between types of plans, with the planned 21 action during a bushfire, gender and past experience with fire. Finally, semi-structured interviews 22 with residents who have experienced wildfire examine the reality of decision-making, triggers used 23 for actions and the role of survival plans. The study concludes that: a) fire agencies provide clear and 24 concise information around survival plans despite some variation between states; b) preparation of 25 survival plans is limited by the same range of factors that limit the extent of overall wildfire 26 preparedness; and c) without a written, discussed and practiced plan, decision-making during a 27 bushfire may be impaired with potentially fatal consequences. 28

Abstract. The revegetation of cleared landscapes with woody plants (termed "environmental planting") has the potential to sequester carbon (C), provide habitat, and increase biodiversity and connectivity. These environmental values are potentially offset by an increased fire hazard posed by revegetation. There is a need to understand the influence environmental planting has on landscape fire behavior and to determine how this changes as plantings age. This study examined how environmental values, regenerative capacity, fuel metrics, and potential fire behavior change with time since planting. We assessed 57 sites across the Albury-Wodonga region (New South Wales, Australia). This included a range of environmental planting ages (4-40 yr time since planting), remnants, and pastures. Carbon storage increased with age of planting, with largest C stores found in remnants (105 tC/ha), while habitat complexity plateaued around 20 yr, with no significant difference between moderately aged plantings (14-20 yr), old plantings (>20 yr), and remnants. Modeled rate of fire spread was faster in pastures compared to environmental plantings and remnants. Flame height was slightly higher (0.5-1 m) in pastures than environmental plantings and remnants under a Very High Forest Fire Danger Index (FFDI), but this trend reversed under Extreme and Catastrophic conditions with flame heights greatest in environmental plantings and remnants albeit with slower rates of spread. This research highlights the importance of environmental plantings in the landscape in terms of C storage and environmental values and indicates the perceived hazard associated with rate of spread and flame height may not be justified at or less than Very High FFDI. However, at FFDI greater than Very High fire behavior may be significantly enhanced in environmental plantings and remnants. Further consideration needs to be given to the size and design of plantings and the type of species planted to fully develop an understanding of the complexities of fire risk. This study allows land managers to make informed decisions regarding the values and risks associated with revegetation of cleared landscapes with woody plants.

Abstract. Smoke from wildfires poses a significant threat to affected communities. Prescribed burning is conducted to reduce the extent and potential damage of wildfires, but produces its own smoke threat. Planners of prescribed fires model the likely dispersion of smoke to help manage the impacts on local communities. Significant uncertainty remains about the actual smoke impact from prescribed fires, especially near the fire, and the accuracy of smoke dispersal models. To address this uncertainty, a detailed study of smoke dispersal was conducted for one small (52 ha) and one large (700 ha) prescribed fire near Appin in New South Wales, Australia through the use of stationary and handheld pollution monitors, visual observations and rain radar data, and by comparing observations to predictions from an atmospheric dispersion model. The 52 ha fire produced a smoke plume about 800 m high and 9 km long. Particle concentrations (PM2.5) reached very high peak values (> 400 μg/m3) and high 24 hour average values (> 100 μg/m3) at several locations next to or within ~ 500 m downwind from the fire, but low levels elsewhere. The 700 ha fire produced a much larger plume, peaking at ~ 2000 m altitude and affecting downwind areas up to 14 km away. Both peak and 24 hour average PM2.5 values near the fire were lower than for the 52 ha fire, but this may be because the monitoring locations were further away from the fire. Some lofted smoke spread north against the ground-level wind direction. Smoke from this fire collapsed to the ground during the night at different times in different locations. Although it is hard to attribute particle concentrations definitively to smoke, it seems that the collapsed plume affected a huge area including the towns of Wollongong, Bargo, Oakdale, Camden and Campbelltown (~ 120,000 ha). PM2.5 concentrations up to 169 μg/m3 were recorded on the morning following the fire. The atmospheric dispersion model accurately predicted the general behaviour of both plumes in the early phases of the fires, but was poor at predicting fine-scale variation in particulate concentrations (e.g. places 500 m from the fire). The correlation between predicted and observed varied between 0 and 0.87 depending on location. The model also completely failed to predict the night time collapse of the plume from the 700 ha fire. This study provides a preliminary insight into the potential for large impacts from prescribed fire smoke to NSW communities and the need for increased accuracy in smoke dispersion modelling. More research is needed to better understand when and why such impacts might occur and provide better predictions of pollution risk.