The capacity to predict fire dynamics in fuel beds comprised of live and dead fuel components is constrained by our limited understanding of the effects of live fuels on fire propagation. A field-based experimental burning program was conducted to specifically address the effect of the degree of curing, the proportion of dead fuels in the fuel bed, on fire propagation in grasslands. Experimental fires were conducted at two sites characterised by structurally distinct fuels with curing levels varying between 20% and 100%. Fire sustainability experiments showed that fire propagation can occur down to curing levels as low as 20%. Rate of fire spread varied between 41.7 and 102 m min–1 in fully cured fuels and between 2.8 and 43.5 m min–1 in partially cured grasslands. The degree of curing was found to be the best variable describing the damping effect of live fuels in a natural, senescing grassland. Live fuel moisture content by itself was not found to be related to the damping effect of live fuels on the rate of fire spread. Existing models for the effect of grass curing on fire behaviour presently used in Australia were found to under-predict the rate of forward fire spread in partially cured grasslands. A new curing relationship for southern Australian grasslands derived from the study results is proposed.

In Australia, the Grassland Fire Danger Index is determined by several inputs including an essential component, the degree of grassland curing, defined as the proportion of senescent material. In the state of Victoria (south-eastern Australia), techniques used for curing assessment have included the use of ground-based observations and the use of satellite imagery. Both techniques alone have inherent limitations. An improved technique has been developed for estimating the degree of curing that entails the use of satellite observations adjusted by observations from the ground. First, a satellite model was developed, named MapVictoria, based on historical satellite and ground-based observations. Second, with use of the new (MapVictoria) satellite model, an integrated model was developed, named the Victorian Improved Satellite Curing Algorithm, combining near-real-time satellite data with weekly observations of curing from the ground. This integrated model was deployed in operations supporting accurate fire danger calculations for grasslands in Victoria in 2013.

Grass senescence, or grassland curing, is a dynamic process in which grass fuels transition from a live to dead state and, in turn, influence fire dynamics. In the present study we examined the process of curing with specific consideration of changes in fuel structure that will affect potential fire behaviour. Our sampling protocol expanded the fuel component groups from two (live and dead) to four (green, senescing, new dead and old dead fuel). We found that all these components had significant fuel moisture content differences, thereby justifying our sampling protocol. Visual curing assessment predominantly resulted in an over-prediction bias of curing level and failed to capture the effect of the senescing process on fuel availability to combust due to misclassification of fuel components (e.g. senescing fuels with high fuel moisture content were classified as dead fuels because of their colouration). Models were developed to estimate the: (1) proportion of senescing and green fuels from knowledge of the current year’s dead fuel proportion; and (2) actual curing level from fuel moisture content and soil dryness level.

A field-based experimental study was conducted in 50×50m square plots to investigate the behaviour of free-spreading fires in wheat to quantify the effect of crop condition (i.e. harvested, unharvested and harvested and baled) on the propagation rate of fires and their associated flame characteristics, and to evaluate the adequacy of existing operational prediction models used in these fuel types. The dataset of 45 fires ranged from 2.4 to 10.2kmh−1 in their forward rate of fire spread and 3860 and 28000 kWm−1 in fireline intensity. Rate of fire spread and flame heights differed significantly between crop conditions, with the unharvested condition yielding the fastest spreading fires and tallest flames and the baled condition having the slowest moving fires and lowest flames. Rate of fire spread in the three crop conditions corresponded directly with the outputs from the models of Cheney et al. (1998) for grass fires: unharvested wheat → natural grass; harvested wheat (~0.3m tall stubble) → grazed or cut grass; and baled wheat (<0.1m tall stubble) → eaten-out grass. These models produced mean absolute percent errors between 21% and 25% with reduced bias, a result on par with the most accurate published fire spread model evaluations.

Oocytes are postulated to repress the proton pumps (e.g., complex IV) and ATP synthase to safeguard mitochondrial DNA homoplasmy by curtailing superoxide production. Whether the ATP synthase is inhibited is, however, unknown. Here we show that: oligomycin sensitive ATP synthase activity is significantly greater (~170 vs. 20 nmol/min−1/mg−1) in testes compared to oocytes in Xenopus laevis (X. laevis). Since ATP synthase activity is redox regulated, we explored a regulatory role for reversible thiol oxidation. If a protein thiol inhibits the ATP synthase, then constituent subunits must be reversibly oxidised. Catalyst-free trans-cyclooctene 6-methyltetrazine (TCO-Tz) immunocapture coupled to redox affinity blotting reveals several subunits in F1 (e.g., ATP-α-F1) and Fo (e.g., subunit c) are reversibly oxidised. Catalyst-free TCO-Tz Click PEGylation reveals significant (~60%) reversible ATP-α-F1 oxidation at two evolutionary conserved cysteine residues (C244 and C294) in oocytes. TCO-Tz Click PEGylation reveals ~20% of the total thiols in the ATP synthase are substantially oxidised. Chemically reversing thiol oxidation significantly increased oligomycin sensitive ATP synthase activity from ~12 to 100 nmol/min−1/mg−1 in oocytes. We conclude that reversible thiol oxidation inhibits the mitochondrial ATP synthase in X. laevis oocytes.