DOI: 10.5061/dryad.pc866t1rq
title: Active season body mass patterns of Little Brown Bats and Northern Myotis: Raw and fitted mass values, environmental conditions and inflection point estimates

description: Animals are expected to adjust their behavioural patterns to improve
 fitness outcomes, such as fecundity or offspring survival. For long-lived
 hibernators, decisions made in each annual cycle may reflect
 considerations not just for concurrent survival and reproduction, but also
 the pressure to maximize overwinter survival and future reproductive
 success. We examined how these elements manifest themselves in the body
 mass variation patterns of North American northern latitude temperate
 bats, whose size and roosting habits present considerable monitoring
 challenges. We characterized and compared the summer and fall mass
 variation patterns of little brown myotis (Myotis lucifugus) and northern
 myotis (M. septentrionalis) from a historic dataset. In summer, the
 estimated date of parturition was strongly associated with spring foraging
 conditions (low wind, low precipitation, warm temperatures), and mass gain
 associated with female reproduction conferred considerable differentiation
 between the mass variation patterns of females and males. In fall,
 differences were most apparent among species, although adults exhibited a
 greater capacity for rapid mass gain than juveniles. These results
 demonstrate how reproductive constraints and interannual survival have
 important influences on the behaviour of temperate bats. Future work
 should seek to quantify the fitness benefits of patterns identified in
 this study, such as the rate of prehibernation mass gain.
description: These data include bat capture records spanning capture surveys
 between 2000 and 2019 and weather data provided by Environment and Climate
 Change Canada. The capture data used in this project are the body mass
 values of bats captured by independent research teams in the Canadian
 provinces of New Brunswick, Nova Scotia, Prince Edward Island, Ontario,
 and the island of Newfoundland. In
 these projects, bats were captured with mist nets (Avinet, Dryden, New
 York, USA) and harp traps (Austbat Research Equipment, Lower Plenty,
 Victoria, Australia) by different research groups and assessed for
 standard morphometric and diagnostic criteria, including sex, age class
 (adult or juvenile per Kunz and Anthony 1982), and mass (g) to two decimal places. Upon
 initial screening of the dataset, we chose to proceed with little brown
 myotis and northern myotis because they were the two species with
 sufficient data for an informative comparison. The capture dates were
 recorded as Julian Date (1-365), and individual observations were grouped
 for analysis according to year, province, age-class (adult/juvenile), sex,
 and species. We categorized the initial full historical dataset according
 to capture record timing, location, individual sex, and individual age. We
 further screened records for suitability in our time series analysis, and
 the data presented here include those sets that met our critieria for
 summer and fall analysis: at least nine unique sampling nights and no
 sampling gaps longer than 20 days. We have
 included both the raw mass values and the LOESS nonparametric fitted
 values (span = 0.75, quadratic fit). We fitted the mass value records to
 the widest possible range available for the summer and fall groups, which
 were Julian Dates 158-207 (approximately June 7 - July 26) for summer and
 227-262 (approximately August 15 - September 19) for fall. We chose not to
 fit exclusively between these dates because doing so would lose accuracy
 provided by captures outside that range for groups with more
 sampling. The environmental data here are raw hourly
 weather conditions at Canadian federal weather stations near bat capture
 sites. We considered temperature, wind, and precipitation when creating
 our foraging condition index, and weighed the data from a particular
 station according to the proportion of bats caught near it.
description: All data are accessible through spreadsheet software such as
 Microsoft Excel and are best processed in R.