Data collection
We collected data on roosting structure of three species (black flying-fox: P. alecto , grey-headed flying-fox: P. poliocephalus and little red flying-fox:P. scapulatus ) from eight roost sites in south-east Queensland and north-east New South Wales, Australia (Fig. 1).P. alecto are believed to be the primary reservoir for Hendra virus in this study region (Goldspink et al. 2015), however a newly-identified Hendra virus variant has been detected in P. poliocephalus and P. scapulatus tissues (Veterinary Practitioners Board of New South Wales 2021). All sites were previously documented as having continuous occupation by at least one species of flying-fox (National Flying-Fox Monitoring Program 2017). Roosting surveys were repeated once a month for 13 months (August 2018 - August 2019).
Methodological details are described in Lunn et al. (2021). Briefly, we mapped the spatial arrangement of all overstory, canopy and midstory trees in a grid network of 10 stratified random subplots (20 x 20 meters each) using an ultrasound distance instrument (Vertex Hypsometer, Haglöf Sweden). Trees were mapped and tagged using tree survey methods described in the “Ausplots Forest Monitoring Network, Large Tree Survey Protocol” (Wood et al. 2015). This approach allowed for precise spatial mapping of trees, with locations of trees within subplots accurate to 10-30 cm. Tagged trees were revisited monthly, and the number of bats per tree was visually estimated and recorded per species using a quasi-logarithmic index: 0: no bats, 1: 1-5 bats, 2: 6-10 bats, 3: 11-20 bats, 4: 21-50 bats, 5: 51-100 bats, 6:101-199 bats and 7: 200+ bats. In total 2,522 trees were mapped across the eight sites. For a subset of trees (60 per site, consistent through time) absolute counts, minimum roosting height, and maximum roosting height of each species were recorded. The roost perimeter boundary (defined as the outermost perimeter delimitating occupied space, as per Clancy and Einoder (2004)) was mapped with GPS (accurate to 10 meters) immediately after the tree survey by walking directly underneath roosting flying-foxes. This track was used to calculate perimeter length and occupied roost area (QGIS 3.1). Total abundance at each roost was estimated with a census count of bats where feasible (i.e. where total abundance was predicted to be <5,000 individuals), or by counting bats as they emerge in the evening from their roosts (“fly-out”), as per Westcott et al.(2011). If these counts could not be conducted, population counts from local councils (conducted within ~a week of the bat surveys) were used, as total abundance of roosts are generally stable over short timeframes (Nelson 1965). Because roost estimates become more unreliable with increasing abundance, we converted the total estimated abundance into an index estimate, as per values used by the National Flying-Fox Monitoring Program (2017). Index categories were as follows: 1: 1-499 bats; 2: 500-2,499 bats; 3: 2,500-4,999 bats; 4: 5,000-9,999 bats; 5: 10,000-15,999 bats; 6: 16,000-49,999 bats; and 7: 50,000+ bats.
All observations were made from a distance to minimise potential disturbance to bats during the survey. In general, bats showed minimal response to the observers during the surveys, providing observers remained quiet, did not move quickly, and kept an appropriate distance, consistent with other studies on flying-foxes (Markus & Blackshaw 2002; Klose et al. 2009).