Data from: Seeking temporal refugia to heat stress: Increasing nocturnal activity despite predation risk
Data files
Jan 11, 2024 version files 2.98 MB
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dataset_ibex.nocturnal.activity_FEMALES-KID.csv
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dataset_ibex.nocturnal.activity.csv
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ibex_nocturnal_activity_analysis.R
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README.md
Abstract
Flexibility in activity timing may enable organisms to quickly adapt to environmental changes. Under global warming, diurnally adapted endotherms may achieve a better energy balance by shifting their activity towards cooler nocturnal hours. However, this shift may expose animals to new or increased environmental challenges (e.g., increased predation risk, reduced foraging efficiency). We analysed a large dataset of activity data from 47 ibex (Capra ibex) in two protected areas, characterized by varying levels of predation risk (presence vs absence of the wolf – Canis lupus). We found that ibex increased nocturnal activity following warmer days and during brighter nights. Despite the considerable sexual dimorphism typical of this species and the consequent different predation-risk perception, males and females demonstrated consistent responses to heat in both predator-present and predator-absent areas. This supports the hypothesis that shifting activity towards nighttime may be a common strategy adopted by diurnal endotherms in response to global warming. As nowadays different pressures are pushing mammals towards nocturnality, our findings emphasize the urgent need to integrate knowledge of temporal behavioural modifications into management and conservation planning.
README: README_for_data_Brivio_etal_2023
Description:
This README file describes the data package accompanying the publication: Brivio F., Apollonio M., Anderwald P., Filli F., Bassano B., Bertolucci C., Grignolio S. Seeking temporal refugia to avoid heat stress: increasing nocturnal activity despite predation risk. Proc. R. Soc. B DOI: 10.1098/rspb.2023.1587
File list:
- “dataset_ibex.nocturnal.activity.csv”
- “dataset_ibex.nocturnal.activity_FEMALES-KID.csv”
- “ibex nocturnal activity analysis.R”
File description:
“dataset_ibex.nocturnal.activity.csv”: contains the data about the nocturnal activity of Alpine ibex monitored from 2006 to 2019 the critical period for ibex when they experience the highest environmental temperatures and must acquire energy prior to the rigours of winter, (i.e., from 1 May to 31 October) in the Gran Paradiso National Park (Italy and in the Swiss National Park (Switzerland). The dataset includes information on individual characteristics and weather conditions. The variables included in the dataset are the followings:
- animal.id: ibex identity code
- sex: sex of the monitored ibex (f=female, m=male)
- cohort: year of birth of the monitored ibex
- site: site where ibex was monitored (gpnp= Gran Paridiso National Park, snp= Swiss National Park)
- year: year of data collection
- j.date: day of data collection expressed as Julian date
- PNAT: proportion of nocturnal active time
- PDAT: proportion of active time during the previous diurnal hours
- night.brightness: night brightness (see the text for details)
- temp_PDH_min: minimum temperature of the previous diurnal hours (expressed in °C)
- temp_PDH_mean: mean temperature of the previous diurnal hours (expressed in °C)
- temp_PDH_max: maximum temperature of the previous diurnal hours (expressed in °C)
- temp_NH_min: minimum temperature of the nocturnal hours (expressed in °C)
- temp_NH_mean: mean temperature of the nocturnal hours (expressed in °C)
- temp_NH_max: maximum temperature of the nocturnal hours (expressed in °C)
- temp_FDH_min: minimum temperature of the following diurnal hours (expressed in °C)
- temp_FDH_mean: mean temperature of the following diurnal hours (expressed in °C)
- temp_FDH_max: maximum temperature of the following diurnal hours (expressed in °C)
- LN_prec_NH: mean of precipitation (i.e., the amount of rain expressed in millimeters of water) recorded during the nocturnal hours (log-transformed)
- LN_prec_PDH: mean of precipitation (i.e., the amount of rain expressed in millimeters of water) recorded during the previous diurnal hours (log-transformed)
“dataset_ibex.nocturnal.activity_FEMALES-KID.csv”: a subset of our data corresponding to the periods during which we had information about female productivity (i.e., we knew if females were with or without their kid). The dataset includes information on individual characteristics and weather conditions. The variables included in the dataset are the following:
- animal.id: ibex identity code
- sex: sex of the monitored ibex (f=female)
- repr.status: reproductive status of the monitored female ibex (2= without kid, 3= with kid)
- cohort: year of birth of the monitored ibex
- site: site where ibex was monitored (gpnp= Gran Paridiso National Park, snp= Swiss National Park)
- year: year of data collection
- j.date: day of data collection expressed as Julian date
- PNAT: proportion of nocturnal active time
- PDAT: proportion of active time during the previous diurnal hours
- night.brightness: night brightness (see the text for details)
- temp_PDH_min: minimum temperature of the previous diurnal hours (expressed in °C)
- temp_PDH_mean: mean temperature of the previous diurnal hours (expressed in °C)
- temp_PDH_max: maximum temperature of the previous diurnal hours (expressed in °C)
- temp_NH_min: minimum temperature of the nocturnal hours (expressed in °C)
- temp_NH_mean: mean temperature of the nocturnal hours (expressed in °C)
- temp_NH_max: maximum temperature of the nocturnal hours (expressed in °C)
- temp_FDH_min: minimum temperature of the following diurnal hours (expressed in °C)
- temp_FDH_mean: mean temperature of the following diurnal hours (expressed in °C)
- temp_FDH_max: maximum temperature of the following diurnal hours (expressed in °C)
- LN_prec_NH: mean of precipitation (i.e., the amount of rain expressed in millimeters of water) recorded during the nocturnal hours (log-transformed)
- LN_prec_PDH: mean of precipitation (i.e., the amount of rain expressed in millimeters of water) recorded during the previous diurnal hours (log-transformed)
“ibex nocturnal activity analysis.R”: This R script file reproduces the analyses of the paper cited above.
Methods
Activity data logging: The activity data of individual ibex (18 males and 9 females in PNGP, 12 males and 8 females in SNP, more details in the Supporting Information Table S1 and Table S2) were recorded by means of a dual-axis motion sensor (i.e., accelerometer) fitted on the collars. The accelerometer simultaneously measures along two orthogonal directions the changes in acceleration associated with the actual motion experienced by the collar. On the X-axis, the accelerometer was sensitive to acceleration events with forward/backward direction/axes, while on the Y-axis, it recorded acceleration events with a sideways and rotary direction. The accelerometer had a dynamic range of ±2g and measured activity as the change of static acceleration (gravity) and dynamic acceleration (collar) with a frequency of 4 Hz. The motion data from accelerometers, i.e., activity values, were calculated as the difference between consecutive measurements, averaged over a time interval of 4 or 5 minutes and given within a relative range between 0 (no difference between consecutive data) and 255 (difference of -2 g/+2 g), with the associated date and time. The activity data recorded were downloaded by means of a handheld terminal (Vectronic Aerospace GmbH, Berlin) and Yagi antenna.
Weather and Astronomical Data: Weather data such as hourly air temperature (°C) and hourly precipitation (i.e., the amount of rain expressed in millimetres of water) were provided by Meteorological Service of Regione Autonoma Valle d’Aosta (weather station of Pont, 45° 31′ N, 7° 12′ E; 1951 m a.s.l.) and by the Federal Office for Meteorology and Climatology (weather station of Samedan, 46° 31′ N; 9° 52′ E; 1710 m a.s.l.), for the GPNP and SNP study areas, respectively. We a priori chose to use temperature rather than radiation (which are highly correlated) because previous research suggested that air temperature was the main driver affecting ibex spatial choices (Brivio et al. 2019). Moon illumination was calculated using the suncalc package in R (Thieurmel and Elmarhraoui 2019) and was expressed as the illuminated fraction of the moon, which ranged from 0.0 (new moon) to 1.0 (full moon). Cloud cover estimates were downloaded from the NCEP/NCAR data set (Kalnay et al. 1996) by using the interpolation method “Inverse Distance Weighting” (Shepard 1968) by means of the NCEP.interp function in the RNCEP package in R (Kemp et al. 2012). Cloud cover data was expressed as the percentage of sky covered by clouds and had a spatial and temporal gridded resolution of 2.5° and 6 hours, respectively. In our analyses, only cloud cover data recorded at 00.00 AM were used.