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The principal method for estimating the abundance of bats in roosts is to count the number of bats exiting the roost at dusk ('flyout counts'). We hypothesised that the accuracy and precision of flyout counts decrease non-linearly as the number of bats moving per unit of time increases, and that accuracy increases with observer experience. To test these hypotheses, we filmed grey-headed flying-foxes (Pteropus poliocephalus) exiting a roost in Melbourne on three consecutive evenings. The film was slowed and the number of flying-foxes flying-out in 30-s intervals was counted and assumed to be the true abundance. Thirteen other observers independently counted the number of flying-foxes flying-out in real time. We formulated our hypotheses into candidate models and compared support for these models using information-theoretic methods. Non-linear models had much greater support than linear models for all three flyouts. There was undercounting in two flyouts and overcounting in the third. There was good support for an effect of observer experience in one of the flyouts, but less support in the others. Precision declined as the true abundance increased in all three flyout counts. Our results indicate that accuracy, precision and observer effects vary with the dynamics of each flyout, and suggest that under some conditions flyout counts will often provide both inaccurate and imprecise estimates of abundance.

Context Invasive mammalian predators are a primary cause of extinctions, especially on islands. Baseline data on the impact of invasive mammalian predators are critical for deciding whether their eradication or control should be attempted, and for monitoring ecosystem changes over time if control does occur. Christmas Island is a tropical island with multiple invasive species, including two mammalian predators (black rats, Rattus rattus and feral cats, Felis catus). Black rats are known to prey upon island bird species (including their nests) elsewhere, but the severity of their impacts on Christmas Island birds is unclear. Describing these impacts would help managers decide whether rat control is warranted, especially as a cat eradication program underway on the island could conceivably result in increased rat density. Aims In this study, we quantify the impacts of rats on Christmas Island bird abundance and nesting success. Methods The abundance of four endemic forest bird species/subspecies (Christmas Island imperial pigeon, Ducula whartoni, emerald dove, Chalcophaps indica natalis, thrush, Turdus poliocephalus erythropleurus and white-eye, Zosterops natalis) was measured using transect surveys. Nest success was measured using remote sensing camera surveillance for one forest bird species (thrush) and one seabird species (red-tailed tropicbird, Phaethon rubicaudra westralis). We explored whether these measures were related to spatial variation in rat density and activity (measured by trapping and inkcards), the presence of other invasive species, habitat and seasonal variables. Key results Neither rat density nor activity explained the abundance of any forest bird species. Instead, seasonal and habitat features were more consistent predictors of bird abundance. White-eyes were more abundant near yellow crazy ant (Anoplolepis gracilipes) supercolonies. Nest success for thrushes and red-tailed tropicbirds was either not, or only very weakly, influenced by rats. Conclusions Black rats currently have little effect on the population sizes and nesting success of Christmas Island birds. Implications This study suggests that rat control is not currently a management priority, but ongoing monitoring of rat density, activity, and impacts is needed to ensure management can respond promptly if rat density or impacts change as cat control progresses towards eradication.

Foxes, wild dogs, feral cats, rabbits, feral pigs and feral goats are believed to have deleterious impacts on native biodiversity in Australia. However, although considerable resources have been expended controlling these six species, little is known about national patterns and costs of control and monitoring. We therefore conducted a survey of pest-control operations undertaken by conservation-focused organisations in Australia. A total of 1306 control operations were reported, with most conducted during 1998–2003: there was little information prior to 1990. Foxes and rabbits were the most, and feral cats the least, frequently controlled pest species. The total area on which control was undertaken in 2003, the year for which most information was available, ranged from ~0.4 × 104 km2 for feral cats to ~10.7 × 104 km2 for foxes. A wide range of techniques and intensities were used to control each of the six species. The estimated cost of labour expended on control in 2003 ranged from $0.4 × 106 for feral cats to $5.3 × 106 for foxes. Monitoring of the pest or biodiversity occurred in 50–56% of control actions in which foxes, wild dogs and feral cats were targeted, but only 22–26% of control actions in which rabbits, feral pigs and feral goats were targeted. Our results are discussed in relation to previous studies of pest animal control and monitoring in Australia.

Species distribution models (SDMs) are increasingly proposed to support conservation decision making. However, evidence of SDMs supporting solutions for on‐ground conservation problems is still scarce in the scientific literature. Here, we show that successful examples exist but are still largely hidden in the grey literature, and thus less accessible for analysis and learning. Furthermore, the decision framework within which SDMs are used is rarely made explicit. Using case studies from biological invasions, identification of critical habitats, reserve selection and translocation of endangered species, we propose that SDMs may be tailored to suit a range of decision‐making contexts when used within a structured and transparent decision‐making process. To construct appropriate SDMs to more effectively guide conservation actions, modellers need to better understand the decision process, and decision makers need to provide feedback to modellers regarding the actual use of SDMs to support conservation decisions. This could be facilitated by individuals or institutions playing the role of 'translators' between modellers and decision makers. We encourage species distribution modellers to get involved in real decision‐making processes that will benefit from their technical input; this strategy has the potential to better bridge theory and practice, and contribute to improve both scientific knowledge and conservation outcomes. ; AG's stay in Brisbane, Australia, was supported by the CSIRO McMaster Foundation. The three workshops (held on December 2011, April and May 2012) that led to this publication were organised with financial support and within the framework of the Australian Research Council Centre of Excellence for Environmental Decisions (CEED; http://www.ceed.edu.au) led by HPP. AG benefitted from insights from a project on applying SDMs to invasive management in Switzerland granted by the Swiss Federal Office of the Environment (FOEN) and the National Centre for Competence in Research (NCCR) 'Plant Survival' in Neuchâtel. LB benefitted from support from the Catalan Government (CARTOBIO and 2010‐BE‐272 projects) and the EU‐FP7 SCALES (#226852) to attend the workshops.