School of Agriculture, Food and Ecosystem Sciences - Theses
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ItemQuantifying fire-severity patterns using optical remote sensing data in temperate eucalypt forests of south-eastern Australia( 2020)Wildfires have significant biophysical and ecological impacts on ecosystems worldwide from local to regional and national scales. The magnitude of such impacts is related to wildfire severity. Recent increases in wildfire occurrence have been associated with climate change, however whether there has also been a change in fire severity remains underexamined in many biomes. Better understanding of fire-severity patterns is required for effective wildfire management, particularly in the fire-prone landscapes of temperate south-eastern Australia, which support a diversity of forests varying in species composition, structure, and post-fire regeneration strategies. Thus, the overarching aims of my Thesis were to accurately quantify wildfire severity at landscape scales and to examine spatial and temporal variation in wildfire severity across a range of forest types in Victoria, south-eastern Australia. To meet the overarching aims, my Thesis involves: (1) identification of optimal optical spectral indices for mapping fire severity across the dominant and most fire-prone forest types in Victoria; (2) a comparison of the accuracy of two different fire-severity mapping approaches, namely single spectral indexing thresholding and machine learning; (3) using the acquired knowledge, the development of fire-severity maps for large (>1000 ha) wildfires occurring in Victoria between 1987 and 2017, and a retrospective analysis of changes in spatial patterns of high-severity fires over that period; and (4) an analysis of the relative importance of four groups of environmental variables (namely fire weather, fuel, topography and climate) as predictors of high-severity fire extent and landscape configuration. My evaluation of remote sensing based spectral indices indicated that the best-performing indices of fire severity varied with forest type and forest functional group, but that there is scope to group forests by structure and fire-regeneration strategy to simplify fire-severity classification in heterogeneous forest landscapes. Results from my comparative analysis confirmed that machine learning outperformed the spectral index thresholding approach for mapping fire severity in most cases, increasing overall accuracy by 11% on a forest-group basis, and 16% on an individual wildfire basis. My results also confirmed that the accuracy achieved with a reduced set of predictor variables that included the previously identified optimal indices of fire severity was not improved by adding more variables. Greater overall accuracies (by 12% on average) were achieved when in-situ data (rather than data from other fires) were used to train the machine-learning algorithm. As such, my study demonstrates the utility of machine-learning algorithms for streamlining a robust fire-severity mapping approach across heterogeneous forested landscapes. Analysis of spatial patterns highlighted that high-severity wildfires in temperate Australian forests have increased in extent and aggregation in recent decades. The total and proportional high-severity burned area increased through time from 1987 to 2017. While the number of high-severity patches per year remained unchanged in that period, the variability in high-severity patch size increased, and high-severity patches became more aggregated and more irregular in shape. Finally, key findings from my models on the relative importance of environmental drivers (climate, fire weather, fuel, and topography) were that fuel type and fire weather were the most important predictors of the extent and configuration of high-severity fires in Australian temperate forests. My Thesis presents one of the most comprehensive analyses of fire-severity patterns from remote sensing data in Australia. My research results support the reliable estimation of wildfire severity from optical images using machine-learning algorithms once optimal spectral indices are identified and when in-situ training data are available for individual fires. Importantly, the quantified shifts in fire regimes across Victoria’s forested landscapes may have critical consequences for ecosystem dynamics, as fire-adapted temperate forests are more likely to be burned at high severities relative to historical ranges, a trend that seems set to continue under projections of a hotter, drier climate in south-eastern Australia. It is therefore critical that forest scientists and land managers continue to acknowledge and quantify changing wildfire-severity patterns so that they are better informed to address the ecological consequences.
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ItemEffects of prescribed burning on surface runoff and erosion( 2012)Prescribed burning – the deliberate use of fire to achieve management objectives – is used extensively in fire-prone vegetation for reducing fuel hazards and enhancing ecological values. As governments set ambitious targets for more prescribed burning, it is important to understand and manage the potential negative impacts, such as increased erosion. While globally there are many studies that consider the effects of prescribed burning on surface runoff and erosion, there are critical knowledge gaps for particular forest types (e.g. dry eucalypt forests) and in relation to understanding the factors controlling particular post-fire hydrologic and erosion responses, the likelihood of large impacts, the effects of spatial scale on the magnitude of an impact and the long-term risks of repeated burning. Therefore, the aim of thesis was to quantify the effects of prescribed burning on soil hydrologic properties, surface runoff and erosion in dry eucalypt forests in Victoria, Australia. This aim was addressed by examining the effects of two potentially important aspects of fire regimes – fire severity and burn patchiness – on soil hydrologic properties, surface runoff and erosion. Measurements were conducted in unburnt, low fire severity (scorched understorey and intact canopy) and high fire severity (burnt understorey and scorched canopy) areas at three dry eucalypt forest sites. Soil water repellency (using the critical surface tension test) and infiltration capacity (using ponded and tension infiltrometers) were measured at the point-scale for all sites immediately post-burn and then at six-month intervals. Rainfall simulations were used to measure runoff and erosion at the plot-scale (3 m2) six-weeks and 11-months post-burn at one site. Additionally, at one site runoff samplers (116 unbounded plots, 10 cm wide and approximately 100 m from the catchment divide) were used to measure runoff and erosion downslope of six burn categories: (1) high severity, (2) low severity, (3) unburnt, and low severity above (4) 1 m, (5) 5 m, and (6) 10 m wide unburnt patches. Prescribed burning resulted in higher runoff and erosion rates. Cumulative hillslope runoff volumes (over16-months) were approximately two orders of magnitude higher on burnt hillslopes and cumulative sediment loads were approximately three orders of magnitude higher. Water repellency increased following burning at two sites, but loss of vegetation cover appeared to be the primary driver for increased runoff and erosion in burnt areas, as fire-induced water repellency did not affect point-scale infiltration capacities. Fire severity differences had relatively little effect on runoff and erosion, presumably because surface vegetation cover was similar in the high and low fire severities. Unburnt patches were highly effective at reducing the connectivity of runoff and erosion from upslope burnt areas, with reductions in overall sediment loads of 96.6% and 99.8% for the 5 m and 10 m wide patches, respectively. The effectiveness of the unburnt patches at reducing runoff and erosion connectivity varied with patch width and rainfall intensity. For example, the 1 m wide unburnt patch reduced the overall sediment load by 92% for rainfall events with average recurrence intervals of < 10 years but was ineffective during a 10-year storm. Overall, the results suggested that despite higher plot-scale runoff and erosion rates post-burn, prescribed burns are unlikely to substantially affect runoff and erosion at the catchment-scale for most rainfall events given their inherent patchiness. Only during particularly intense storms, when unburnt patches become less effective at intersecting runoff and erosion, might severe erosion occur. From a management perceptive, the results suggest that to minimise runoff and erosion connectivity and potential water quality impacts following prescribed burning, there should be a fine-grained mosaic of burnt and unburnt patches throughout a burn (e.g. > 50% unburnt and patches 5-10 m wide) and unburnt streamside buffers. Such burn patterns may be achieved by the ignition pattern, and burning under mild conditions when there are moisture differentials throughout the burn area. While fire severity was found to be a less significant factor in relation to post-burn runoff and erosion rates, it is likely that lower fire severities are associated with more patchy burns and therefore it would be reasonable to aim for low severity burn outcomes.