Progress towards the eradication of three melastome shrub species from northern Australian rainforests

To eradicate a weed incursion, its extent must be delimited and each infestation extirpated. Measures for delimitation and extirpation are utilized to assess the progress of eradication programs currently targeting three melastome shrub species (Clidemia hirta, Miconia nervosa and M. racemosa) in north-eastern Australia. The main infested area for each species was determined during the year after initial detection, but expanded surveys have led to the discovery of isolated, smaller outlying patches. Programs are refining survey methods (including search frequency) to prevent reproduction. Weed incursions that are limited to single infestations represent a prime opportunity for eradication. However, population and dispersal data indicate that eradication will require an ongoing investment for some time for all three species. Highly persistent seed and dispersal by frugivores suggest that eradication may prove extraordinarily difficult should any of these species spread or be discovered at more locations.

Estimation and evaluation of multi-decadal fire severity patterns using Landsat sensors

Retrospective identification of fire severity can improve our understanding of fire behaviour and ecological responses. However, burnt area records for many ecosystems are non-existent or incomplete, and those that are documented rarely include fire severity data. Retrospective analysis using satellite remote sensing data captured over extended periods can provide better estimates of fire history. This study aimed to assess the relationship between the Landsat differenced normalised burn ratio (dNBR) and field measured geometrically structured composite burn index (GeoCBI) for retrospective analysis of fire severity over a 23 year period in sclerophyll woodland and heath ecosystems. Further, we assessed for reduced dNBR fire severity classification accuracies associated with vegetation regrowth at increasing time between ignition and image capture. This was achieved by assessing four Landsat images captured at increasing time since ignition of the most recent burnt area. We found significant linear GeoCBI–dNBR relationships (R2 = 0.81 and 0.71) for data collected across ecosystems and for Eucalyptus racemosa ecosystems, respectively. Non-significant and weak linear relationships were observed for heath and Melaleuca quinquenervia ecosystems, suggesting that GeoCBI–dNBR was not appropriate for fire severity classification in specific ecosystems. Therefore, retrospective fire severity was classified across ecosystems. Landsat images captured within ~ 30 days after fire events were minimally affected by post burn vegetation regrowth.