DOI: 10.5061/dryad.stqjq2cbm
title: Data from: Stress-coping styles are associated with energy budgets and variability in energy management strategies in a capital breeder

description: Individuals vary in their stress-coping styles, characterized by specific
 behavioural and physiological traits that influence their response to
 stressors. Theory suggests that these traits are linked to underlying
 metabolic mechanisms that affect energy management strategies. Despite the
 potential of this powerful comparative approach, few studies have explored
 how stress-coping styles relate to energy management strategies. Using
 heart rate telemetry data from a large, capital-breeding pinniped, the
 grey seal (Halichoerus grypus), we sought to investigate the relationship
 that stress-coping styles may have on energy management strategies.
  Background energy expenditures, a proxy for metabolic rate and
 other background processes, and daily energy expenditures were found to be
 individually repeatable in grey seal mothers across successive breeding
 seasons. Proactive individuals, associated with more bold and aggressive
 phenotypes, exhibited consistently higher background and daily energy
 expenditures than reactive females. However, reactive phenotypes were more
 variable overall in energy management strategy, highlighting greater
 flexibility in their energy management strategy. Our results highlight key
 energetic trade-offs associated with stress-coping styles in grey seal
 mothers during this short but critical life-history stage; proactive
 individuals tended to exhibit a single pattern of energy management,
 expending greater energy while incurring greater risk of overspending,
 than those with a more reactive phenotype.
description: # Data from: Stress-coping styles are associated with energy budgets and
 variability in energy management strategies in a capital breeder Dataset
 DOI: [10.5061/dryad.stqjq2cbm](10.5061/dryad.stqjq2cbm) ## Description of
 the data and file structure Using heart rate telemetry data from a large,
 capital-breeding pinniped, we sought to investigate the influence that
 stress-coping styles have on energy management strategies. To do this, we
 first evaluated the repeatability of energy usage (energy management
 strategy) in grey seal mothers over multiple consecutive breeding seasons
 (file: Daily_grey_seal_msDat.txt).  We then investigated the associations
 that stress-coping styles (resting heart rate variability) may have with
 energy use and management strategies among grey seals (file:
 Seasonal_grey_seal_msDat.txt). All code used in the analysis and figures
 presented in text is included in the RMarkdown html document. ### Files
 and variables #### File: Daily\_grey\_seal\_msDat.txt
 **Description:** Data file for assessing individual repeatability of
 energy management parameter estimates (from Shuert et al. 2020) for each
 day of study (daily values).  ##### Variables * ID: Unique grey seal
 mother id * Year: Breeding year of study * DDate: Date that heart rate
 variables were collected * min_fH: Daily minimum of mean heart rate
 (minimum daily mean heart rate value), a proxy for background energy
 expenditure (beats/min) * mean_fH: Daily mean heart rate, a proxy for
 daily energy expenditure (beats/min) * d.aux_fH: Auxiliary heart rate
 (min_fH subtracted from mean_fH), a proxy for activity-specific energy
 expenditure (beats/min) * n_seg: Number of sampled heart rate segments
 used to estimate energy management heart rate proxies *
 Z_rMSSD.adj.RPCALL: Standardized estimate of resting heart rate
 variability (rHRV) derived using the root mean square of successive
 differences (rMSSD) of inter-beat intervals. * rMSSD.adj.RPCALL:
 Unstandardized estimate of resting heart rate variability (rHRV) derived
 using the root mean square of successive differences (rMSSD) of inter-beat
 intervals. * MS.MDML.NEW: Estimated maternal daily mass loss rate (kg/day)
 #### File: Seasonal\_grey\_seal\_msDat.txt **Description:** Seasonal data
 of resting heart rate variability (rHRV) used to assess against estimates
 of energy management strategy proxies.  ##### Variables * ID: Unique grey
 seal mother id * Year: Breeding year of study * min_fH: Daily minimum of
 mean heart rate (minimum mean heart rate value), a proxy for background
 energy expenditure (beats/minute) * mean_fH: Daily mean heart rate, a
 proxy for daily energy expenditure (beats/minute) * c_min_fH: Energy
 management strategy slope * z.year_rMSSD: Standardized yearly estimate of
 resting heart rate variability (rHRV) derived using the root mean square
 of successive differences (rMSSD) of inter-beat intervals. *
 Z_MS.MDML.NEW: Standardized estimated maternal daily mass loss rate
 (standardized, kg/day) * sf_01: Binomial indicating whether female
 abandoned lactation early or not #### File: EM\_HRV\_ManuscriptCode.html
 **Description:** Code used to analyse all data presented in the
 manuscript. This includes in-depth descriptions of the data, analysis
 approaches, and figure generation which are described in the main text. 
 ## Code/software Below is a list of the packages and versions used to
 complete this analysis. Data and analysis were prepared R Version 4.3.2
 (2023-10-31 ucrt). ``` # Not Run #
 install.packages("tidyverse",dependencies = T, lib =
 .libPaths()[1]) # Packages library(tidyr) # Data manipulation - v1.3.0
 library(readr) # File reader - v2.1.4 library(purrr) # Data manipulation -
 v1.0.2 library(dplyr) # Data manipulation - v1.1.3 library(nlme) #
 Mixed-effects modelling - v3.1-163 library(viridis) # Colour-blind
 friendly palettes - v0.6.4 library(ggplot2) # Plotting and figure
 preparations - v3.4.4 library(rptR) # Repeatability analysis - v0.9.22
 library(Matrix) # Support package - v1.6-4 library(lme4) library(terra)
 ```