DOI: 10.5061/dryad.31zcrjdzn
title: Emergence and return times in a colonial, cave-dwelling bat: age and sex differences driven by reproductive cycle

description: The time that bats emerge, and subsequently return, from a colonial roost
 determines their maximum foraging period and influences their exposure to
 mortality risks. The order in which different age and sex cohorts emerge
 and return reflects variation in these cohorts’ resource requirements. The
 critically endangered Southern Bent-wing Bat (Miniopterus orianae
 bassanii) is an Australian insectivorous cave-roosting colonial bat.
 Resource limitation is hypothesised to have contributed to its decline,
 but may not affect all cohorts equally. We tagged and monitored 3,462 wild
 Southern Bent-wing Bats over seven years with Passive Integrated
 Transponder technology. To infer resource requirements of different
 cohorts over the reproductive cycle, we estimated cohort-specific peak
 emergence and return times and the frequency of nocturnal returns to the
 roost. The emergence and return behaviour varied with age, sex, and
 throughout the annual reproductive cycle. Although adult females and males
 behaved similarly during the non-breeding period (winter), females emerged
 significantly (12-21 minutes) earlier and returned (27-62 minutes) later
 than males during pregnancy, lactation, and weaning. Adult females were
 less likely than males to be detected overnight in the maternity roost
 while dependent young were present, suggesting that females prioritised
 maximising foraging over nocturnal nursing. When juveniles commenced
 flying, they delayed emergence until several hours after sunset (well
 after adults had departed the roost). During the 40-day weaning period,
 they progressively emerged earlier, such that by the end of this period
 they emerged with the adults, then subsequently foraged for longer than
 adults over winter. Passive monitoring of emergence and return behaviour
 in colonial bats can provide valuable data to infer cohort-specific
 resource requirements. Regular monitoring of a population’s emergence and
 return times potentially allows for the early detection of changes in
 resource requirements, and the use of PIT technology allows for the most
 vulnerable cohort(s) to be identified.
description: <strong>Study sites</strong>
 Southern Bent-wing Bats were monitored at a maternity roost and
 an associated non-maternity roost from 2016 to 2022. The maternity roost
 is located in Bat Cave, a multi-chambered cave within the Naracoorte Caves
 National Park World Heritage Area in south-east South Australia. Southern
 Bent-wing Bats congregate here in the austral spring to form a maternity
 colony. Occupancy peaks in summer, when the site is occupied by
 approximately 28,000 adult bats, comprising both females and males of all
 ages (Hamilton-Smith, 1972). The cave entrance is a collapsed window
 measuring approximately 8 × 4 m, surrounded by vegetation of varying
 heights.  The non-maternity roost is approximately 70
 km from the maternity roost. Here, the cave entrance is in a large doline
 (a funnel-like depression in the ground), and measures approximately 6 × 2
 m. The cave is situated on a dairy farm and is surrounded by cleared
 pastures. Southern Bent-wing Bats are known to move regularly between this
 site and the maternity roost (van Harten et al., 2022b).
 <strong>Automated fly-out and fly-in counts at the
 maternity roost</strong> A monitoring program was
 established at the maternity roost in late 2021 to estimate the Southern
 Bent-wing Bat population size each night. An infra-red camera and
 illuminators are installed outside the cave, which film emergence and
 return from dusk until dawn. The Southern Bent-wing Bat is the only bat
 that roosts in this cave. Population estimates are derived using the
 bespoke N2 software package specifically created to tally emerging and
 returning bats within each minute of every sampled night at this site.
 This system provides information about the emergence and return times of
 the whole aggregation, complementing PIT-tag data, which provides
 additional information on the behaviour of age and sex cohorts. We
 primarily used these data to evaluate the accuracy of emergence and return
 estimates from the PIT antenna positioned inside the cave (see
 below). <strong>PIT-tagging and
 detection</strong> A total of 2,966 Southern
 Bent-wing Bats were trapped and PIT tagged at the maternity cave from
 2016-2018, as described in van Harten et al. (2019, 2020). We PIT tagged
 an additional 496 bats in January and February 2022, following the same
 method. Bats were trapped throughout the night, from dusk until just
 before dawn, with two-bank Austbat harp traps (Faunatech/Austbat, Mount
 Taylor). Bats were sexed based on external genitalia and aged, with
 juveniles (&lt; 3 months old) classified based on the shape of
 metacarpal phalangeal joints and presence of cartilage in these joints
 (Brunet-Rossinni & Wilkinson, 2009). Prior to tagging, bats were
 scanned for existing PIT tags, then the forearm length and mass of each
 bat were recorded. Sample sizes were similar for males and females, with
 marginally more juveniles than adults tagged in later years (795 AF, 671
 AM, 969 JF, 1027 JM; Table S1).<br>In 2022, the PIT tags used were
 Biomark APT12, with Biomark HPT12 PIT tags used from 2016 to 2018 (van
 Harten et al., 2019). Both tags are 12 mm glass-encapsulated microchips
 with a high read range on stationary PIT readers (Karltek 2021, pers.
 comm.). Tags were inserted subcutaneously to rest between the scapulae,
 with the insertion site sealed with tissue glue to minimise tag loss (van
 Harten et al. 2020, 2021). PIT-tag placement was checked before releasing
 the bats. This technique is associated with high tag retention, with
 PIT-tag loss of 2.7% in a similar-sized bat, Chalinolobus gouldii, all
 recorded within 2 months of tagging (van Harten et al., 2021).
 A Biomark IS1001 PIT reader system was installed in the maternity
 cave in January 2016. This system consists of a tag reader, data logger,
 and a 15 m flexible cord antenna, as described in van Harten et al.
 (2019). The system was installed in the closest suitably-sized cave
 passage, which is c. 100 m from the entrance (van Harten et al., 2019) and
 c. 30 m from the maternity chamber (Dwyer & Hamilton-Smith, 1965).
 An identical system was installed at the entrance of the non-maternity
 roost in April 2017 (van Harten et al., 2019). PIT-tag detections are
 recorded in real-time by these readers, although power outages and high
 electromagnetic interference have caused temporary loss of data for short
 periods (van Harten et al., 2019). All data processing
 and statistical analyses were performed in R (v. 4.2.2) software for
 statistical and graphic computing (R Core Team, 2022).
 <strong>Classification of age-sex cohorts and reproductive
 periods</strong>   PIT-tagged individuals
 (detected from 2016 to 2022) were classified into cohorts based on their
 sex and age at capture. The assumed birth date of first-year individuals
 was November 24th, the mean date of mass birthing at the maternity roost
 during the study period (T. Shortt 2023, pers. comm; van Harten et al.,
 2022b). Juveniles were classified as first-year males or females from
 their initial capture date until 24/11/[capture year], then reclassified
 as second-year males or females for the next 12 months. Second-year male
 and female cohorts were separated from the adult cohorts to examine the
 effects of age and reproductive maturity separately. After the second year
 of life, bats were then reclassified as adult males or females on
 24/11/[capture year + 1]. Adults and second-year individuals without tags
 could not be distinguished on capture, so all non-juveniles were excluded
 from analysis in their capture year and classified as adults on November
 24th of the following year. Based on current and past observations of
 birthing behaviour (Crichton et al., 1989; van Harten et al., 2022b), we
 defined four key stages of the annual reproductive cycle of Southern
 Bent-wing Bats: the non-breeding, pregnancy, lactation, and weaning
 periods (Table 1).  <strong>Emergence and return
 times</strong> We derived sunrise and sunset
 times for each monitoring night at each roost using the bioRad package
 (Dokter et al., 2019). Daytime observations between one hour after sunrise
 and one hour before sunset were excluded from analysis, as bats detected
 in this period were presumed to be moving within the cave. 
 The emergence and return time of each cohort was estimated
 separately for each night of PIT-tag monitoring (n=1807 nights at
 maternity roost, 1256 at non-maternity roost). We defined each cohort’s
 emergence (and return) time as the peak detection period of individuals in
 a cohort before midnight, in units of decimal hours since sunset, and
 return as decimal hours until sunrise. <br>To calculate emergence
 and return times, we tallied the number of unique tagged individuals from
 each cohort that were detected within each 5-minute interval over the
 course of each night. To smooth out short-term fluctuations, we then used
 a moving-average smoother to calculate the mean detection count over every
 three consecutive (5-minute) intervals. The 5-minute interval
 corresponding to the maximum moving-average value was deemed the emergence
 (peak detections before midnight) or return (peak detections after
 midnight) time for that cohort on that night.  We
 analysed emergence and return times at each roost separately, with
 generalised additive models (GAMs) using the package ‘mgcv’ (Wood, 2011).
 To compare differences in emergence and return times between cohorts and
 reproductive periods, we included these fixed factors and their
 interaction as explanatory variables (Table 2). We also accounted for
 changes in these times due to the annual progression with a cyclic
 penalized cubic regression spline on the day of the year and included a
 random effect of year to consider unexplained variation between years. To
 account for improved accuracy of nightly peak emergence and return times
 when more bats were detected, we weighted the GAM model likelihoods for
 each estimate by the associated moving-average peak count of bats detected
 (as derived above). Tukey’s tests were used to compare the estimated mean
 emergence and return times in each period between cohorts at each roost,
 and between periods for each cohort. To explore changes
 in first-year bats’ emergence and return times throughout the weaning
 period, relative to other cohorts, emergence and return times were also
 separately estimated for all first-year bats (regardless of sex) and older
 cohorts throughout the 40-day weaning period at the maternity roost. The
 emergence and return times of first-year bats and all other cohorts over
 this period were analysed with separate GAM models that included day of
 the weaning period and a random effect of year (Table S2). These models
 were only fitted to data from the maternity roost, as all first-year bats
 are at this location during the weaning period. <br>Emergence times
 are measured in minutes since sunset, return times are measured in minutes
 until sunrise.  <strong>Population-level
 emergence and return times from the PIT and N2
 datasets</strong> Peak emergence and return times
 were also estimated for all tagged bats, regardless of cohort, to estimate
 the colony-level emergence and return times at the maternity roost on a
 sample of nights when PIT monitoring and N2 monitoring were both being
 conducted (199 nights compared for emergence times, 147 nights compared
 for return times). Peak emergence and return times were then derived from
 the N2 monitoring data based on detections of all exiting and entering,
 using the method detailed above. We used paired t-tests to compare in-cave
 (PIT monitoring) and outside-cave (N2 monitoring) estimates for emergence
 and return time over this period, and within key reproductive periods
 (Table 1).   <strong>Overnight activity
 patterns</strong> To investigate how often bats
 return to their roosts throughout the night in each reproductive period,
 we modelled the probability of recording PIT-tagged individuals from each
 cohort over the course of each night, for each reproductive period (Table
 1). First, we calculated the total number of bats recorded on the reader
 from each cohort on each night (i.e., from an hour before sunset until an
 hour after sunrise). Second, we tallied the number of bats of each cohort
 recorded in each five-minute interval over the course of each night. Using
 the number of individuals of a cohort recorded within each 5-minute
 interval relative to the number of bats from that cohort recorded that
 night, we modelled the probability of a bat being detected within each
 interval over the course of the night using a binomial generalised
 additive model (GAM) and package mgcv (Wood, 2011). Cohort and
 reproductive period were included as explanatory fixed factors, along with
 a random effect of year. To investigate changes in nightly activity
 patterns between groups over the course of a night, we also included time
 since sunset as an explanatory variable within this model, using a
 thin-plate regression spline fitted within each cohort and period
 combination (Table 2).
description: # Emergence and return times in a colonial, cave-dwelling bat: age and sex
 differences driven by reproductive cycle Dataset DOI:
 [10.5061/dryad.31zcrjdzn](10.5061/dryad.31zcrjdzn) ## Description of the
 data and file structure Detection data were collected from 3,462 wild
 Southern Bent-wing Bats via in-cave PIT-tag readers from 2016-2022.
 Detection data were linked to capture data to identify the sex and age of
 bats. The year was split into 4 reproductive periods: pregnancy,
 lactation, weaning, and non-breeding. To calculate emergence and return
 times, detection data were filtered to exclude observations an hour after
 sunrise through to an hour before sunset. Data were binned into 5-minute
 intervals for each night of the study, and cohort detections were tallied.
 The moving average over 3 5-minute intervals with the highest number of
 detections was selected as emergence time (before midnight), measured in
 time since sunset, or return time (after midnight), measured in time to
 sunrise, for that particular night for that particular cohort. Data from
 population estimation software outside the cave (N2) were also binned into
 5-minute intervals and used to derive emergence and return times in the
 same manner as above, for all bats each night. PIT-tag data was used in
 the same way, with emergence and return times calculated nightly as above,
 but without considering cohort. This created 2 data frames for the series
 of nights both monitoring systems were operating, with peak emergence and
 return tie of the entire colony estimated outside the cave (with N2), and
 inside the cave (PIT reader data), allowing for the accuracy of in-cave
 emergence and return time estimated to be compared. These nightly
 emergence and return times were compared in the attached, with the
 difference in emergence and return times (in decimal hours) from PIT 
 monitoring subtracted from each corresponding night's N2 monitoring,
 forming the 'N2MinusPITDiff dataframe that was used to explore
 differences in overall and seasonal emergence and return times.  Similar
 data to that described in paragraph 2 were used to model the probability
 of detecting a bat (of each cohort) throughout each 5-minute interval of
 each night, using detection data from PIT-tag readers. The number of
 detections of a cohort each night in each 5-minute interval between an
 hour before sunset and an hour after sunrise was tallied, as was the total
 number of bats detected that night. These 2 variables informed a model
 exploring the likelihood of detection overnight for each cohort. The
 dataframes used to build these models are denoted
 'tag.dataGWFinal.RDS' for the non-maternity roost, and
 'tag.dataBCFinal.RDS' from the maternity roost. Separate models
 were for separate roosts.  ### Files and variables #### File:
 etdfBCFinal.RDS **Description:** This file is the data frame containing
 the emergence and return times (in time since sunset and time until
 sunrise), measured in decimal hours and denoted tss and ttsr, for each
 cohort at the maternity roost. M = male, F= female, A = adult, 1Y =
 first-year, 2Y = second-year. Data were binned into 5-minute intervals for
 each night of the study, and cohort detections were tallied. The moving
 average over 3 5-minute intervals with the highest number of detections
 was selected as emergence time (before midnight), measured in time since
 sunset, or return time (after midnight), measured in time to sunrise, for
 that particular night for that particular cohort. The resulting dataframe
 contains each individual night in the study which emergence and return
 times could be calculated, with the peak emergence and return times in
 decimal hours, for each cohort present each night of the study, and has
 reproductive periods classified based on the developmental or reproductive
 processes occurring in the population.  These data were used with the mgcv
 package in R to build generalised additive models for emergence and return
 time seperately, where the response variables for each model were
 Emergence time (time since sunset in decimal hours) and return time (time
 to sunrise in decimal hours), and explanatory variables were year (random
 effect), Reproductive Period (pregnant, lactating, weaning, non-breeding),
 Cohort (age-sex), the interaction of cohort and period, and day of year
 (with cyclic penalized cubic regression splines).  #### File:
 etdfGWFinal.RDS **Description:** This file is the data frame containing
 the emergence and return times (in time since sunset and time until
 sunrise), measured in decimal hours and denoted tss and ttsr, for each
 cohort at the non-maternity roost. M = male, F= female, A = adult, 1Y =
 first-year, 2Y = second-year Data were binned into 5-minute intervals for
 each night of the study, and cohort detections were tallied. The moving
 average over 3 5-minute intervals with the highest number of detections
 was selected as emergence time (before midnight), measured in time since
 sunset, or return time (after midnight), measured in time to sunrise, for
 that particular night for that particular cohort. The resulting dataframe
 contains each individual night in the study which emergence and return
 times could be calculated, with the peak emergence and return times in
 decimal hours, for each cohort present each night of the study, and has
 reproductive periods classified based on the developmental or reproductive
 processes occurring in the population.  These data were used with the mgcv
 package in R to build generalised additive models for emergence and return
 time seperately, where the response variables for each model were
 Emergence time (time since sunset in decimal hours) and return time (time
 to sunrise in decimal hours), and explanatory variables were year (random
 effect), Reproductive Period (pregnant, lactating, weaning, non-breeding),
 Cohort (age-sex), the interaction of cohort and period, and day of year
 (with cyclic penalized cubic regression splines).  #### File:
 tag.dataGWFinal.RDS **Description:** This file contains the data used to
 model the probability of detection for each cohort at the non-maternity
 roost. These data were used to model the probability of detecting a bat
 (of each cohort) throughout each 5-minute interval of each night, using
 detection data from PIT-tag readers. The number of detections of a cohort
 each night in each 5-minute interval between an hour before sunset and an
 hour after sunrise was tallied, as was the total number of bats detected
 that night. These 2 variables informed a model exploring the likelihood of
 detection overnight for each cohort.  The attached dataframe was used to
 build generalised additive models following a binomial distribution, where
 the probability of detection was the response variable. This response
 variable was calculated by summing, for each cohort, each night: the total
 number of detections in a night, and the total number of detections in a
 5-minute interval. This allowed the model to allocate the probability of
 detection within each 5-minute interval of the night, for each cohort, in
 each reproductive period. Time of night was included in the model, fit
 with a thin-plate regression spline, and the interaction of period and
 cohort was also included as an explanatory variable. The year was included
 as a random effect. #### File: N2minusPITdiff.RDS **Description:** This
 file contains the nightly differences in emergence and return times as
 predicted by N2, a population estimation software filming bats outside the
 maternity roost, and the in-cave PIT-tag reader at the maternity roost.
 Estimates for emergence and return times, for each system, each night that
 both were operating, were formulated by calculating the number of unique
 detections of all bats detected in each 5-minute interval of the night,
 then taking the moving average over 3 5-minute intervals, then selecting
 the maximum moving average value as the peak emergence (before midnight)
 or return (after midnight) value. To inform paired t-tests, PIT-tag
 emergence and return time estimates were subtracted from the corresponding
 night's N2 emergence and return time estimates, resulting in the
 attached dataframe. Reproductive period was also included so that t-tests
 could be run separately to compare the overall emergence and return
 times' similarity between monitoring systems, as well as emergence
 and return times in each reproductive period.  These comparisons served to
 compare how monitoring bats outside the cave compared to monitoring bats
 within the cave. #### File: tag.dataBCFinal.RDS **Description:** This file
 contains the data used to model the probability of detection for each
 cohort at the maternity roost. The attached dataframe was used to build
 generalised additive models following a binomial distribution, where the
 probability of detection was the response variable. This response variable
 was calculated by summing, for each cohort, each night: the total number
 of detections in a night, and the total number of detections in a 5-minute
 interval. This allowed the model to allocate the probability of detection
 within each 5-minute interval of the night, for each cohort, in each
 reproductive period. Time of night was included in the model, fit with a
 thin-plate regression spline, and the interaction of period and cohort was
 also included as an explanatory variable. The year was included as a
 random effect. ## Code/software R and RStudio are needed to view the
 supplied RDS files. R version 4.2.2 was used for analyses.  Packages used:
 tidyverse, magrittr, mgcv, emmeans, bioRad, lubridate, dplyr, egg, kit,
 and reshape2 were used for data formulation and analyses. ## Access
 information NA