ContextAerial surveys provide valuable information about the population status and distribution of many native and pest vertebrate species. They are vital for evidence-based monitoring, budget planning and setting management targets. Despite aircraft running costs, they remain one of the most cost-effective ways to capture distribution and abundance data over a broad area. In Australia, annual surveys of large macropods are undertaken in several states to inform management, and in some jurisdictions, to help set commercial kangaroo harvest quotas. Improvements in the cost efficiencies of these surveys are continually sought. Aerial thermal imaging techniques are increasingly being tested for wildlife surveys, but to date no studies have directly compared population data derived from thermal imaging with data collected by human observers during the same flight. AimsDuring an aerial survey of western grey kangaroos (Macropus fuliginosus), eastern grey kangaroos (M. giganteus) and red kangaroos (Osphranter rufus) across the state of Victoria, Australia, the objective was to conduct a direct comparison of the effectiveness of thermal camera technology and human observers for estimating kangaroo populations from aerial surveys. MethodsA thermal camera was mounted alongside an aerial observer on one side of the aircraft for a total of 1360km of transect lines. All thermal footage was reviewed manually. Population density estimates and distance sampling models were compared with human observer counts. Key resultsOverall, the kangaroo density estimates obtained from the thermal camera data were around 30% higher than estimates derived from aerial observer counts. This difference was greater in wooded habitats. Conversely, human-derived counts were greater in open habitats, possibly due to interference from sunlight and flushing. It was not possible to distinguish between species of macropod in the thermal imagery. ConclusionsThermal survey techniques require refining, but the results of the present study suggest that with careful selection of time of day for surveys, more accurate population estimates may be possible than with conventional aerial surveys. ImplicationsConventional aerial surveys may be underestimating animal populations in some habitats. Further studies that directly compare the performance of aerial observers and thermal imaging are required across a range of species and habitats.

A better understanding of the movement of feral dromedary camels (Camelus dromedarius) in Australia would be useful for planning removal operations (harvest or culling), because the pattern and scale of camel movement relates to the period they reside in a given area, and thus the search effort, timing and frequency of removal operations. From our results, we suspect that the dune direction influences how camels move across central Australia; particularly effects like the north–south longitudinal dune systems in the Simpson Desert, which appeared to elongate camel movement in the same direction as the dunes. We called this movement anisotropy. Research suggests camel movement in Australia is not migratory but partially cyclic, with two distinctive movement patterns. Our study investigated this further by using satellite tracking data from 54 camels in central Australia, recorded between 2007 and 2016. The mean tracking period for each animal was 363.9 days (s.e.m.=44.1 days). We used a method labelled multi-scale partitioning to test for changes in movement behaviour and partitioned more localised intensive movements within utilisation areas, from larger-scale movement, called ranging. This involved analysing the proximity of movement trajectories to other nearby trajectories of the same animal over time. We also used Dynamic Brownian Bridges Movement Models, which consider the relationship of consecutive locations to determine the areas of utilisation. The mean utilisation area and duration of a camel (n=658 areas) was found to be 342.6km2 (s.e.m.=33.2km2) over 23.5 days (s.e.m.=1.6 days), and the mean ranging distance (n=611 ranging paths) was a 45.1km (s.e.m.=2.0km) path over 3.1 days (s.e.m.=0.1 days).