ORCID Profile
0000-0002-2607-7183
Current Organisations
NSW Department of Planning, Industry and Environment
,
University of Sydney
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Publisher: Wiley
Date: 15-12-2010
Publisher: Wiley
Date: 09-06-2017
DOI: 10.1002/EAP.1555
Abstract: There is a public perception that large high-severity wildfires decrease bio ersity and increase fire hazard by homogenizing vegetation composition and increasing the cover of mid-story vegetation. But a growing literature suggests that vegetation responses are nuanced. LiDAR technology provides a promising remote sensing tool to test hypotheses about post-fire vegetation regrowth because vegetation cover can be quantified within different height strata at fine scales over large areas. We assess the usefulness of airborne LiDAR data for measuring post-fire mid-story vegetation regrowth over a range of spatial resolutions (10 × 10 m, 30 × 30 m, 50 × 50 m, 100 × 100 m cell size) and investigate the effect of fire severity on regrowth amount and spatial pattern following a mixed severity wildfire in Warrumbungle National Park, Australia. We predicted that recovery would be more vigorous in areas of high fire severity, because park managers observed dense post-fire regrowth in these areas. Moderate to strong positive associations were observed between LiDAR and field surveys of mid-story vegetation cover between 0.5-3.0 m. Thus our LiDAR survey was an apt representation of on-ground vegetation cover. LiDAR-derived mid-story vegetation cover was 22-40% lower in areas of low and moderate than high fire severity. Linear mixed-effects models showed that fire severity was among the strongest biophysical predictors of mid-story vegetation cover irrespective of spatial resolution. However much of the variance associated with these models was unexplained, presumably because soil seed banks varied at finer scales than our LiDAR maps. Dense patches of mid-story vegetation regrowth were small (median size 0.01 ha) and evenly distributed between areas of low, moderate and high fire severity, demonstrating that high-severity fires do not homogenize vegetation cover. Our results are relevant for ecosystem conservation and fire management because they: indicate that native vegetation are responsive and resilient to high-severity fire, and show the usefulness of remote sensing tools such as LiDAR to monitor post-fire vegetation recovery over large areas in situ.
Publisher: Elsevier BV
Date: 2017
DOI: 10.1016/J.SCITOTENV.2016.09.129
Abstract: High severity wildfires pose threats to human assets, but are also perceived to impact vegetation communities because a small number of species may become dominant immediately after fire. However there are considerable gaps in our knowledge about species-specific responses of plants to different fire severities, and how this influences fuel hazard in the short and long-term. Here we conduct a floristic survey at sites before and two years after a wildfire of unprecedented size and severity in the Warrumbungle National Park (Australia) to explore relationships between post-fire growth of a fire responsive shrub genera (Acacia), total mid-story vegetation cover, fire severity and fuel hazard. We then survey 129 plots surrounding the park to assess relationships between mid-story vegetation cover and time-since-fire. Acacia species richness and cover were 2.3 and 4.3 times greater at plots after than before the fire. However the same common dominant species were present throughout the study. Mid-story vegetation cover was 1.5 times greater after than before the wildfire, and Acacia species contribution to mid-story cover increased from 10 to 40%. Acacia species richness was not affected by fire severity, however strong positive associations were observed between Acacia and total mid-story vegetation cover and severity. Our analysis of mid-story vegetation recovery showed that cover was similarly high between 2 and 30years post-fire, then decreased until 52years. Collectively, our results suggest that Acacia species are extremely resilient to high severity wildfire and drive short to mid-term increases in fuel hazard. Our results are discussed in relation to fire regime management from the twin perspectives of conserving bio ersity and mitigating human losses due to wildfire.
Publisher: CSIRO Publishing
Date: 2001
DOI: 10.1071/AM01077
Abstract: Much of the knowledge of small mammal ecology in Australia has come from Elliott trapping, however the results of these studies are influenced by the way in which trapping is carried out. We review some of the major factors affecting the results of Elliott trapping: trap spacing, local placement, presence of odours on the trap (from conspecifics, similar species, predators, and humans), and duration of trapping. Most factors clearly influence trapping results and should be routinely considered, and preferably controlled, in future studies which use Elliott traps.
Publisher: CSIRO Publishing
Date: 2016
DOI: 10.1071/WF15171
Abstract: We analysed the influence of weather, time since fire (TSF) and topography on the occurrence of crown fire, as mapped from satellite imagery, in 23 of the largest wildfires in dry sclerophyll forests in eastern Australia from 2002 to 2013. Fires were analysed both in idually and as groups. Fire weather was the most important predictor of crown consumption. TSF (a surrogate for fuel accumulation) had complex nonlinear effects that varied among fires. Crown fire likelihood was low up to 4 years post-fire, peaked at ~10 years post-fire and then declined. There was no clear indication that recent burning became more or less effective as fire weather became more severe. Steeper slope reduced crown fire likelihood, contrary to the assumptions of common fire behaviour equations. More exposed areas (ridges and plains) had higher crown fire likelihood. Our results suggest prescribed burning to maintain an average of 10 years’ TSF may actually increase crown fire likelihood, but burning much more frequently can be effective for risk reduction. Our results also suggest the effects of weather, TSF and slope are not adequately represented in the underlying equations of most fire behaviour models, potentially leading to poor prediction of fire spread and risk.
Publisher: Wiley
Date: 14-03-2019
DOI: 10.1111/AEC.12713
Publisher: Wiley
Date: 02-04-2020
DOI: 10.1111/GCB.15038
Publisher: Wiley
Date: 06-2006
Publisher: Acoustical Society of America (ASA)
Date: 09-2017
DOI: 10.1121/1.4999318
Abstract: Ground parrot vocalisation can be considered as an audio event. Test-based erse density multiple instance learning (TB-DD-MIL) is proposed for detecting this event in audio files recorded in the field. The proposed method is motivated by the advantages of multiple instance learning from incomplete training data. Spectral features suitable for encoding the vocal source information of the ground parrot vocalization are also investigated. The proposed method was benchmarked against a dataset collected in various environmental conditions and an audio detection evaluation scheme is proposed. The evaluation includes a study on performance of the various vocal source features and comparison with other classification techniques. Experimental results indicated that the most appropriate feature to encode ground parrot calls is the spectral bandwidth and the proposed TB-DD-MIL method outperformed other existing classification methods.
Publisher: Elsevier BV
Date: 09-2012
Publisher: Elsevier BV
Date: 05-2012
Publisher: Informa UK Limited
Date: 07-02-2018
Location: Australia
Location: Australia
No related grants have been discovered for Elizabeth Tasker.