Kate Brandis

Classifying landform at broad spatial scales: the distribution and conservation of wetlands in New South Wales, Australia

Relatively few large-scale inventories of the worlds wetlands exist because of the difficulties of spatial scale, associated cost and multiple objectives, often temporally confounded, that drive classification. The extent of wetlands across a large part of Australia (New South Wales, 80.6 million ha) was determined using satellite image analyses. These data allowed analyses of the distribution of wetlands, their conservation status and potential threats at different spatial scales; that is, State, coastal and inland, and catchment. Approximately 5.6% of New South Wales is wetland (4.5 million ha), mostly (96%) in inland river catchments. Broad classification allowed identification of the extent of wetland types: (i) floodplains (89%); (ii) freshwater lakes (6.6%); (iii) saline lakes (< 1%); (iv) estuarine wetlands (2.5%); and (v) coastal lagoons and lakes (1.5%). Conservation reserves protect only 3% of wetland area. The analyses identified the north-west as the key area for wetland conservation as most other catchments have lower wetland extent and more potential threatening processes. The first stage of a large-scale inventory is to determine the extent and location of wetlands, with immediate benefits for strategic conservation and management. Other objectives (e.g. classification, biotic composition, hydrology and threats) seldom have sufficient data available for large-scale inventories but can be completed later with resources.

Estimation of vegetative fuel loads using Landsat TM imagery in New South Wales, Australia

Fuel loads in forest areas are dependent on vegetation type and the time since the last fire. This paper reports a study on the feasibility of using remotely sensed data to estimate vegetative fuel loads. It describes two methods for estimating fuel loads using Landsat TM data based on equations describing litter accumulation and decomposition. The first method uses classification techniques to predict vegetation types coupled with fire history data to derive current fuel loads. The second method applies a canopy turnover rate to estimate litterfall and subsequently accumulated litter from biomass, thus utilising the dominant influence of canopy on remotely sensed data. Both methods are compared with data collected from Popran National Park in coastal New South Wales. The amounts of litter calculated with the biomass method were similar to field results, but the classification method was found to overestimate fuel loads. A sensitivity analysis investigated the impact of varying the vegetation constants and rates used in the fuel estimates to simulate uncertainty or error in their values. The biomass method was less subject to uncertainties and has potential for estimating fuel quantities to provide useful spatial information for fire managers.

Australia's wetlands – learning from the past to manage for the future

Australia has diverse wetlands with multiple threats. We reviewed knowledge about the extent of wetlands, representativeness, impacts and threats to integrity and options for effective conservation. Natural Australian wetlands cover an estimated 33 266 245 ha (4.4%), with 55% palustrine (floodplains and swamps), followed by 31% lakes, 10% estuarine systems, and 5% rivers and creeks. The Lake Eyre (1.1%), Murray–Darling (0.73%), Tanami–Timor Sea Coast (0.71%) and the Carpentaria Coast (0.55%) drainage divisions have more wetlands, also reflected in the distributions among states and territories. Ramsar sites and wetlands in protected areas were generally biased towards the southern continent. Overall representation of mapped wetlands was good for lacustrine (40.6%) and estuarine (34.4%), fair for riverine (16.8%), but inadequate for palustrine (10.8%) wetlands. Within drainage divisions, representation varied considerably, with shortfalls from the Aichi target of 17%. Agriculture, urbanisation, pollution and invasive species have degraded or destroyed wetlands, particularly in the developed south-east, south-west and north-east of the continent. Water resource developments, primarily the building of dams, diversion of water and development of floodplains, seriously threaten Australian wetlands, with all threats exacerbated by climate change impacts of rising sea levels and high temperatures. Management and policy for wetlands is dependent on data on distribution, type and extent of wetlands, a key national constraint. Some States are well advanced (e.g. Queensland) and others lack any comprehensive data on the distribution of wetlands. Mitigation of increasing development (e.g. northern Australia) will be critical for conservation, along with increased representativeness in protected areas and restoration, particularly with environmental flows.

Novel detection of provenance in the illegal wildlife trade using elemental data

Despite being the fourth largest criminal market in the world, no forensic tools have been sufficiently developed to accurately determine the legal status of seized animals and their parts. Although legal trading is permissible for farmed or captive-bred animals, many animals are illegally removed from the wild and laundered by masquerading them as captive bred. Here we present high-resolution x-ray fluorescence (XRF) as a non-invasive and cost-effective tool for forensic classification. We tested the efficacy of this technique by using machine learning on a training set of zoo specimens and wild-caught individuals of short-beaked echidnas (Tachyglossus aculeatus), a small insectivorous monotreme in Australia. XRF outperformed stable isotope analysis (δ13C, δ15N), reducing overall classification error below 4%. XRF has the added advantage of providing samples every 200 μm on a single quill, enabling 100% classification accuracy by taking the consensus of votes per quill. This accurate and cost-effective forensic technique could provide a much needed in situ solution for combating the illegal laundering of wildlife, and conversely, assist with certification of legally bred animals.