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).