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Background: Fire management is a crucial part of managing ecosystems. The years since last burn (YSLB) metric is commonly used in fire planning to predict when an area might be suitable to burn; however, this metric fails to account for variable recovery due to climate variability. Aim: The aim of this study was to develop a predictor of when an area may be able to 'carry' fire based on observed patterns of vegetation recovery and fire occurrence that is responsive to climate variability. Methods: Fire history maps and Landsat satellite imagery within the Great Victoria Desert of Australia were used to map vegetation recovery following fire. Burn potential models were then created by calculating the distributions of YSLB and vegetation recovery values for areas that subsequently burnt. Key result: A burn potential model based on vegetation recovery is a better predictor of when an area is likely to burn than a model based on YSLB. Conclusions: A burn potential model based on vegetation recovery provides an evidence-based and dynamic assessment of whether an area is likely to burn. Implications: This approach provides a model that is responsive to climate variability that can assist fire managers in burn planning and assessing fire risk. Fire management is a crucial part of managing many environments. We present a burn potential model developed using satellite imagery that predicts when an area may be able to 'carry' fire. The model accounts for rapid or delayed vegetation cover response since the last burn due to climate variability. [ABSTRACT FROM AUTHOR]

Conservation practitioners require cost-effective and repeatable remotely sensed data for assistive monitoring. This paper tests the ability of standard remotely piloted aircraft (DJI Phantom 4 Pro) imagery to discriminate between plant species in a rangeland environment. Flights were performed over two 0.3–0.4 ha exclusion plot sites, established as controls to protect vegetation from translocated animal disturbance on Dirk Hartog Island, Western Australia. Comparisons of discriminatory variables, classification potential, and optimal flight height were made between plot sites with different plant species diversity. We found reflectance bands and height variables to have high differentiation potential, whilst measures of texture were less useful for multisegmented plant canopies. Discrimination between species varied with omission errors ranging from 13 to 93%. Purposely resampling c. 5 mm imagery as captured at 20–25 m above terrain identified that a flight height of 120 m would improve capture efficiency in future surveys without hindering accuracy. Overall accuracy at a site with low species diversity (n = 4) was 70%, which is an encouraging result given the imagery is limited to visible spectral bands. With higher species diversity (n = 10), the accuracy reduced to 53%, although it is expected to improve with additional bands or grouping like species. Findings suggest that in rangeland environments with low species diversity, monitoring using a standard RPA is viable. [ABSTRACT FROM AUTHOR]

Fire management is increasingly acknowledged as a necessary tool to maintain diversity in desert environments such as the Great Victoria Desert of Australia, but it needs to be informed by accurate fire history data. We compared and assessed the utility of Landsat-derived and Moderate Resolution Imaging Spectroradiometer (MODIS)-derived burnt area mapping (30 m and 250 m resolution, respectively) for sub-regional, landscape and habitat scale management. We did so by using Sentinel-2-derived, 10 m resolution, burnt area mapping as a reference, to determine the most appropriate product to support land management planning. At the landscape scale, Landsat had significantly lower average omission and commission errors (3.4% and 8.0%, respectively) compared with that of MODIS (42.2% and 19.9%, respectively). At the habitat scale, Landsat burnt area percentage was more accurate, in plots of 500 m × 500 m (root mean square error (RMSE) 0.6% to 8.6%), but offered lower accuracy when estimating partially burnt habitat plots of 120 m × 120 m (RMSE 14.1% to 23.9%). Only Landsat-derived fire scar mapping provided enough detail to produce reliable fire history maps to inform fire management and biodiversity conservation operations at a sub-regional scale, landscape scale and a habitat scale of 500 m by 500 m. In the context of fire management in a desert of Western Australia, we compared fire scars generated with data from three different satellites. Our results indicate that Landsat-derived fire scars are the most appropriate product to generate reliable fire history maps to inform fire management and biodiversity conservation operations. [ABSTRACT FROM AUTHOR]

Claims that literacy and literature become interrelated in classrooms where there are many opportunities to engage in the narrative mode of thought. Discusses how the potential of literacy/literature experiences is enriched when students draw from the narrative reservoirs of the community and school. (JD)

High quality children's literature should be used to facilitate language-learning-disabled children's narrative abilities in the areas of structure, content, values, and aesthetic appreciation. Using the macrostructure of the story can lead to the exploration of feelings and values in real or imagined situations. (DB)

Feral cats are one of the most damaging predators on Earth. They can be found throughout most of Australia's mainland and many of its larger islands, where they are adaptable predators responsible for the decline and extinction of many species of native fauna. Managing feral cat populations to mitigate their impacts is a conservation priority. Control strategies can be better informed by knowledge of the locations that cats frequent the most. However, this information is rarely captured at the population level and therefore requires modelling based on observations of a sample of individuals. Here, we use movement data from collared feral cats to estimate home range sizes by gender and create species distribution models in the Pilbara bioregion of Western Australia. Home ranges were estimated using dynamic Brownian bridge movement models and split into 50% and 95% utilisation distribution contours. Species distribution models used points intersecting with the 50% utilisation contours and thinned by spacing points 500 m apart to remove sampling bias. Male cat home ranges were between 5 km2 (50% utilisation) and 34 km2 (95% utilisation), which were approximately twice the size of the female cats studied (2–17 km2). Species distribution modelling revealed a preference for low-lying riparian habitats with highly productive vegetation cover and a tendency to avoid newly burnt areas and topographically complex, rocky landscapes. Conservation management can benefit by targeting control effort in preferential habitat. [ABSTRACT FROM AUTHOR]