Designing a large-scale track-based monitoring program to detect changes in species distributions in arid Australia.

Monitoring trends in animal populations in arid regions is challenging due to remoteness and low population densities. However, detecting species' tracks or signs is an effective survey technique for monitoring population trends across large spatial and temporal scales. In this study, we developed a simulation framework to evaluate the performance of alternative track-based monitoring designs at detecting change in species distributions in arid Australia.

Long-Distance Movements of Feral Cats in Semi-Arid South Australia and Implications for Conservation Management.

Movements that extend beyond the usual space use of an animal have been documented in a range of species and are particularly prevalent in arid areas. We present long-distance movement data on five feral cats () GPS/VHF-collared during two different research projects in arid and semi-arid Australia. We compare these movements with data from other feral cat studies.

Rabbit biocontrol and landscape-scale recovery of threatened desert mammals.

Funding for species conservation is insufficient to meet the current challenges facing global biodiversity, yet many programs use expensive single-species recovery actions and neglect broader management that addresses threatening processes. Arid Australia has the world's worst modern mammalian extinction record, largely attributable to competition from introduced herbivores, particularly European rabbits (Oryctolagus cuniculus) and predation by feral cats (Felis catus) and foxes (Vulpes vulpes). The biological control agent rabbit hemorrhagic disease virus (RHDV) was introduced to Australia in 1995 and resulted in dramatic, widespread rabbit suppression.

Non-detection errors in a survey of persistent, highly-detectable vegetation species.

Rare, small or annual vegetation species are widely known to be imperfectly detected with single site surveys by most conventional vegetation survey methods. However, the detectability of common, persistent vegetation species is assumed to be high, but without supporting research. In this study, we evaluate the extent of false-negative errors of perennial vegetation species in a systematic vegetation survey in arid South Australia.