Fire models and methods to map fuel types: The role of remote sensing.

Understanding fire is essential to improving forest management strategies. More specifically, an accurate knowledge of the spatial distribution of fuels is critical when analyzing, modelling and predicting fire behaviour. First, we review the main concepts and terminology associated with forest fuels and a number of fuel type classifications. Second, we summarize the main techniques employed to map fuel types starting with the most traditional approaches, such as field work, aerial photo interpretation or ecological modelling. We pay special attention to more contemporary techniques, which involve the use of remote sensing systems. In general, remote sensing systems are low-priced, can be regularly updated and are less time-consuming than traditional methods, but they are still facing important limitations. Recent work has shown that the integration of different sources of information andmethods in a complementary way helps to overcome most of these limitations. Further research is encouraged to develop novel and enhanced remote sensing techniques

Time-dependent batch settling of flocculated suspensions

The equations governing the settling and consolidation of flocculated fully networked suspensions under the influence of gravity, based on the assumption that the network possesses a compressive yield stress P(oslash;) that is a function of local volume fraction (oslash;) only, are discussed. They are nonlinear partial differential equations with two moving boundaries, one at the top of the bed and the other marking the position of the consolidation region. A novel technique is used to solve these numerically. The time evolution of the volume fraction in the sedimenting column and the two moving boundaries are computed, and their dependence on the physical properties of the system are discussed. Analytic results for the steady state and the small time behavior are given

Fire weather risk differs across rain forest-savanna boundaries in the humid tropics of north-eastern Australia

Alternative stable state theory has been applied to understanding the control by landscape fire activity of pyrophobic tropical rain forest and pyrophytic eucalypt savanna boundaries, which are often separated by tall eucalypt forests. We evaluate the microclimate of three vegetation types across an elevational gradient and their relative fire risk as measured by McArthur's Forest Fire Danger Index (FFDI). Microclimatic data were collected from rain forest, tall eucalypt forest and savanna sites on eight vegetation boundaries throughout the humid tropics in north Queensland over a 3-year period and were compared with data from a nearby meteorological station. There was a clear annual pattern in daily FFDI with highest values in the austral winter dry season and lowest values in the austral summer wet season. There was a strong association of the meteorological station FFDI values with those from the three vegetation types, albeit they were substantially lower. The rank order of FFDI values among the vegetation types decreased from savanna, tall eucalypt forest, then rain forest, a pattern that was consistent across each transect. Only very rarely would rain forest be flammable, despite being adjacent to highly flammable savannas. These results demonstrate the very strong effect of vegetation type on microclimate and fire risk, compared with the weak effect of elevation, consistent with a fire–vegetation feedback. This study is the first demonstration of how vegetation type influences microclimate and fire risk across a topographically complex tropical forest–savanna gradient