The impacts of escalating wildfire in many regions - the lives and homes lost, the expense of suppression and the damage to ecosystem services - necessitate a more sustainable coexistence with wildfire. Climate change and continued development on fire-prone landscapes will only compound current problems. Emerging strategies for managing ecosystems and mitigating risks to human communities provide some hope, although greater recognition of their inherent variation and links is crucial. Without a more integrated framework, fire will never operate as a natural ecosystem process, and the impact on society will continue to grow. A more coordinated approach to risk management and land-use planning in these coupled systems is needed.

Dry season fires are a feature of the tropical savannas of northern Australia. As part of a landscape‐scale fire experiment, we examined the effects of fire regimes on tree survival in a tropical savanna in Kakadu National Park, northern Australia. The fire regimes were annual early dry season (June) fires, annual late dry season (September) fires, and, no fire (control). Prescriptive, experimental fires were lit annually, between 1990 and 1994, in replicate compartments, each 15–20 km2. In addition to the prescribed fires, however, one of the control compartments, which had been unburnt for seven years, was burnt by an unplanned, high intensity fire (~ 20 000 kW m−1) in September 1994. This provided an opportunity to compare the impacts on the tree stratum of frequent, prescribed burning at various intensities, and a single unplanned fire. In all fire regimes, stem survival was substantially lower than whole‐plant survival, and decreased linearly with increasing fire intensity. Significantly, stem death following the single, high intensity 20 000 kWm−1 fire (75%) was comparable to that of a regime of annual late dry season burning for five years, at an average intensity of c. 8000 kWm−1. In the high intensity unplanned fire, stem survival showed a non‐linear response to stem size, being least in the small (< 10 cm DBH) and large (> 40 cm DBH) size classes, and highest in the intermediate size classes. Stem survival was also species‐dependent, being higher in the dominant Eucalyptus miniata than in the subdominant, broad‐leaf deciduous trees. In the absence of fire for 5–10 years, the structure and composition of the tree stratum of these savannas tends to become more complex than in sites burnt more frequently, especially by high intensity fire. Such a long‐term absence of fire may be a conservation objective for some areas of savanna. However, build‐up of fuel to near maximal levels can occur in 2–4 years without fire. This may predispose the savannas to high‐intensity, late dry season fires. Whatever the fire‐management goal within a given patch of savanna, whether it be the prescribed use of fire on a biennial basis, or the exclusion of fire at a semidecadal scale, careful attention still needs to be given to the consequences of fuel build‐up in fire‐excluded sites.

McArthur's fire-danger meters for grasslands (Mark 3) and forests (Mark 5) have been widely used in Australia for fire-danger forecasting and as a guide to fire behaviour. We present a set of equations to describe the data provided on these meters plus equations pertinent to the recentlyproduced Mark 5 grassland meter. The equations provide a simple method of describing the forecasting system and are particularly useful for machine processing, and modelling.

No abstract

In a landscape-scale experiment, fires were lit in replicate catchments 15-20 km2 in area, either early in the dry season (June) or late in the dry season (September) between 1990 and 1994. For each fire, Byram-intensity was determined in representative one ha areas of Eucalyptus miniata – E. tetrodonta open-forest, with a ground stratum dominated by annual grasses. Fuel weights were measured by harvest, fuel heat content was assumed to be constant, and the rate of spread was determined using electronic timers. Fuels consisted primarily of grass and leaf litter, and ranged from 1.5 to 13 t ha-1; in most years, average fuel loads were 2-4 t ha-1. Rates of spread were generally in the range of 0.2-0.8 ms-1. The mean intensity of early dry season fires (2100 kW m-1) was significantly less than that of the late dry season fires (7700 kW m-1), primarily because, in the late dry season, there was more leaf litter, fuels were drier, and fire weather was more extreme. Crown fires, a feature of forest fires of high intensity in southeastern Australia, were not observed in the Kapalga fires. Fire intensity was a very good predictor of both leaf-char height and leaf-scorch height for fires between 100 kW m-1 and 10,000 kW m-1, the range in which the majority of experimental fires fell.

The link between ‘fire mosaics’ and persistence of animal species is part of a prominent ecological/land management paradigm. This paradigm deals largely with the effects of fire on animals on the basis of individual events. The universality of the paradigm can be questioned on a variety of grounds, a major deficiency being the inability to deal with quantitative effects of recurrent fire (the fire regime). A conceptual model of fire-related habitat elements is proposed for exploration of a continuum of species/habitat/landscape/fire regime combinations. This approach predicts that the dependence of species on fire-mediated habitat heterogeneity will be highly variable and strongly context-dependent. A spatially explicit simulation model was used to examine the persistence of malleefowl (Leipoa ocellata) in a specific landscape/habitat context where dependence on fire-mosaics should be high. Results suggest that persistence of L. ocellata populations will be dependent on intervention using small patchy fires but that there is an optimum rate of intervention. Results were sensitive to spatial pattern of prescribed fire, landscape type (topography) and probability of wildfire. Underlying effects of the fire-interval distribution (the ‘invisible’ mosaic) on plant species and habitat account for these results. A management emphasis on species/landscape context and awareness of the ‘invisible’ mosaic is advocated.

Australia is among the most fire-prone of continents. While national fire management policy is focused on irregular and comparatively smaller fires in densely settled southern Australia, this comprehensive assessment of continental-scale fire patterning (1997–2005) derived from ~1 km2 Advanced Very High Resolution Radiometer (AVHRR) imagery shows that fire activity occurs predominantly in the savanna landscapes of monsoonal northern Australia. Statistical models that relate the distribution of large fires to a variety of biophysical variables show that, at the continental scale, rainfall seasonality substantially explains fire patterning. Modelling results, together with data concerning seasonal lightning incidence, implicate the importance of anthropogenic ignition sources, especially in the northern wet–dry tropics and arid Australia, for a substantial component of recurrent fire extent. Contemporary patterns differ markedly from those under Aboriginal occupancy, are causing significant impacts on biodiversity, and, under current patterns of human population distribution, land use, national policy and climate change scenarios, are likely to prevail, if not intensify, for decades to come. Implications of greenhouse gas emissions from savanna burning, especially seasonal emissions of CO2, are poorly understood and contribute to important underestimation of the significance of savanna emissions both in Australian and probably in international greenhouse gas inventories. A significant challenge for Australia is to address annual fire extent in fire-prone Australian savannas.

Environmental disturbance underpins the dynamics and diversity of many of the ecosystems of the world, yet its influence on the patterns and distribution of genetic diversity is poorly appreciated. We argue here that disturbance history may be the major driver that shapes patterns of genetic diversity in many natural populations. We outline how disturbance influences genetic diversity through changes in both selective processes and demographically driven, selectively neutral processes. Our review highlights the opportunities and challenges presented by genetic approaches, such as landscape genomics, for better understanding and predicting the demographic and evolutionary responses of natural populations to disturbance. Developing this understanding is now critical because disturbance regimes are changing rapidly in a human-modified world.