Thirty-two human factors data forms used by six organizations participating in the definition of the NASA Apollo Applications Program were analyzed to develop a standard reporting technique compatible with computer data processing methods. The analysis provided a matrix of 17 data and document types by 43 content areas. Six user organizations indicated their information requirements by filling out the matrix sheet. High-frequency data items formed the basis for developing a single format that can be used initially in any manned space task equipment analysis, maintenance analysis, and training requirements analysis.
The purpose of this study was to determine whether reduced pressure (1.5 psi) versus ambient pressure (14.7 psi) had a differential effect on man's performance in a pressurized (3.7 psi) Apollo suit. Two subjects were tested on three different types of tasks: psychomotor, a lunar mission-specific task, and walking. The results of this study gave support to the hypothesis that it would require greater effort to complete the same tasks in the reduced pressure condition than in the ambient pressure condition. During the reduced pressure condition, an increase in total time, total errors, heart rate, and carbon dioxide production was consistently observed over the ambient condition. These findings are considered preliminary, and future research is required to substantiate the conclusion that reduced pressure associated with the space environment negatively affects human performance.
Context Seasonal migration and movements of bats have important implications for their conservation. The southern bent-winged bat (Miniopterus orianae bassanii), a critically endangered cave-dwelling taxon in Australia, has been described as undertaking regional-scale migration between maternity and non-breeding caves. Aims To describe the seasonal cycle of movements by the southern bent-winged bat, including migration and congregation events of different sex- and age-classes in the population. Methods We tagged a total of 2966 southern bent-winged bats with passive integrated transponder (PIT) tags. Antennas were used to detect bats in flight at a major maternity cave and a key non-breeding cave in south-east South Australia, from January 2016 to August 2019. We used capture–resight histories to visualise population patterns and model the daily encounter probability for each sex- and age-class at the respective roost sites. Key results Bats congregated at the maternity cave for most of the year, with different seasonal patterns among sex- and age-classes. Seasonal movements were associated with behaviour over winter months: most of the population dispersed from the maternity cave from May and a staged return occurred among population classes from July through September. A previously undescribed movement occurred in adult females and juveniles each year: these classes left the maternity cave in late summer, when juveniles became independent, and returned in early mid-autumn, later undertaking winter dispersal. Complex underlying movements of individuals occurred throughout the year, with individuals able to fly 72 km between roosting caves in just a few hours. Conclusions Seasonal movements are a key aspect of the life history of this taxon. The newly reported movement of adult females and juveniles conforms to the maternal guidance hypothesis, whereby mothers guide their young to suitable non-breeding caves and hibernation sites. In addition to seasonal movements, some individuals moved 72 km between caves multiple times over short time periods, including on successive nights. This 72-km overnight flight distance more than doubles the previous distance used to inform management buffer zones. Extended congregation of bats at the maternity cave highlights resource limitation in the surrounding area as a potential threat to this population. Implications The dynamic nature of the population has implications for the management of emerging risks, including mortality at windfarms and potential rapid spread of the exotic white-nose syndrome.
Context The ecology of cryptic animals is difficult to study without invasive tagging approaches or labour-intensive field surveys. Acoustic localisation provides an effective way to locate vocalising animals using acoustic recorders. Combining this with land cover classification gives new insight into wild animal behaviour using non-invasive tools. Aims This study aims to demonstrate how acoustic localisation – combined with high-resolution land cover classification – permits the study of the ecology of vocalising animals in the wild. We illustrate this technique by investigating the effect of land cover and distances to anthropogenic features on coyote and wolf vocal behaviour. Methods We collected recordings over 13 days in Wisconsin, USA, and triangulated vocalising animals' locations using acoustic localisation. We then mapped these locations onto land cover using a high-resolution land cover map we produced for the area. Key results Neither coyotes nor wolves vocalised more in one habitat type over another. Coyotes vocalised significantly closer to all human features than expected by chance, whereas wolves vocalised significantly further away. When vocalising closer to human features, coyotes selected forests but wolves showed no habitat preference. Conclusions This novel combination of two sophisticated, autonomous sensing-driven tools permits us to examine animal land use and behavioural ecology using passive sensors, with the aim of drawing ecologically important conclusions. Implications We envisage that this method can be used at larger scales to aid monitoring of vocally active animals across landscapes. Firstly, it permits us to characterise habitat use while vocalising, which is an essential behaviour for many species. Furthermore, if combined with additional knowledge of how a species' habitat selection while vocalising relates to its general habitat use, this method could permit the derivation of future conclusions on prevailing landscape use. In summary, this study demonstrates the potential of integrating acoustic localisation with land cover classification in ecological research.
