DOI: 10.5061/dryad.2547d7wzn
title: Energetic trade-offs in migration decision-making, reproductive effort, and subsequent parental care in a long-distance migratory bird

description: Migratory species trade-off long-distance movement with survival and
 reproduction, but the spatiotemporal scales at which these decisions occur
 is relatively unknown. Technological and statistical advances allow
 fine-scale study of animal decision-making, improving our understanding of
 possible causes and therefore conservation management. We quantified
 effects of reproductive preparation during spring migration on subsequent
 breeding outcomes, breeding outcomes on autumn migration characteristics,
 and autumn migration characteristics on subsequent parental survival in
 Greenland white-fronted geese (Anser albifrons flavirostris). These are
 long-distance migratory birds with a ~50% population decline from 1999 to
 2022. We deployed GPS-acceleration devices on adult females to quantify up
 to five years of individual decision-making throughout the annual cycle.
 Weather and habitat-use affected time spent feeding and overall dynamic
 body acceleration (i.e., energy expenditure) during spring and autumn.
 Geese that expended less energy and fed longer during spring were more
 likely to successfully reproduce. Geese with offspring expended more
 energy and fed for less time during autumn, potentially representing
 adverse fitness consequences of breeding. These behavioural comparisons
 among Greenland white-fronted geese improve our understanding of fitness
 trade-offs underlying abundance. We provide a reproducible framework for
 full annual cycle modelling using location and behaviour data, applicable
 to similarly studied migratory animals.
description: # Energetic trade-offs in migration decision-making, reproductive effort,
 and subsequent parental care in a long-distance migratory bird This
 repository contains the data and code used in the following publication:
 Schindler, A. R., A. D. Fox, C. K. Wikle, B. M. Ballard, A. J. Walsh, S.
 B. A. Kelly, L. Cao, L. R. Griffin, M. D. Weegman. (2024). *Proceedings of
 the Royal Society B*, **291**:29120232016.
 [https://doi.org/10.1098/rspb.2023.2016](https://doi.org/10.1098/rspb.2023.2016). Data DOI: [https://doi.org/10.5061/dryad.2547d7wzn](https://doi.org/10.5061/dryad.2547d7wzn) Code DOI: [https://doi.org/10.5281/zenodo.10581609](https://doi.org/10.5281/zenodo.10581609) All analyses were completed using R. See manuscript for details about analyses and supplementary data for example code. Please contact the corresponding author with questions about this data package or to seek potential collaborations using these data. --- ### Description Model code and associated data files to quanitfy the effects of reproductive preparation during spring migration on subsequent breeding outcomes, breeding outcomes on autumn migration characteristics, and autumn migration characteristics on subsequent parental survival in Greenland white-fronted geese (*Anser albifrons flavirostris*). --- ### Authors Alexander R. Schindler\ Department of Biology, University of Saskatchewan, Saskatoon, SK, Canada Anthony D. Fox\ Department of Ecoscience, Aarhus University, Aarhus, Denmark Christopher K. Wikle\ Department of Statistics, University of Missouri, Columbia, MO, USA Bart M. Ballard\ Caesar Kleberg Wildlife Research Institute, Texas A&M University-Kingsville, Kingsville, TX, USA Alyn J. Walsh\ National Parks and Wildlife Service, Dublin, Ireland Seán B. A. Kelly\ National Parks and Wildlife Service, Dublin, Ireland Lei Cao\ State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, China University of Chinese Academy of Sciences, Beijing, China Larry R. Griffin\ Wildfowl & Wetlands Trust, Gloucester, UK ECO-LG Limited, Dumfries, UK Mitch D. Weegman\ Department of Biology, University of Saskatchewan, Saskatoon, SK, Canada --- ### Files * `full_annual_cycle_model_categorical.R` - Includes all code to read in data files and run the full annual cycle model with breeding outcome as a categorical variable (i.e., successful attempt, failed attempt, deferral). * `full_annual_cycle_model_bernoulli.R` - Includes all code to read in data files and run the full annual cycle model with breeding outcome as a Bernoulli variable (i.e., success, fail). * `spring_dat.csv` - All data for the spring sub-model (summarised to each bird/year/sub-season). * `autumn_dat.csv` - All data for the autumn sub-model (summarised to each bird/year/sub-season). ### Data file column names * `id` - numerical identifier for each bird marked in the study * `year` - numerical identifier for each year in the study (i.e., 1-5 corresponds with 2018-2022) * `sub_season` -numerical identifier for the sub-season in the corresponding season (spring_data.csv: 1 = late winter, 2 = first migration flight, 3 = first half of spring staging, 4 = second half of spring staging, 5 = second migration flight, 6 = early breeding; autumn_data.csv: 1 = late breeding, 2 = first migration flight, 3 = first half of autumn staging, 4 = second half of autumn staging, 5 = second migration flight, 6 = early winter) * `breeding_outcome` - 1 = successful breeding attempt, 2 = failed breeding attempt, 3 = breeding deferral * `breeding_success` - 1 = breeding success, 0 = breeding failure * `first_day` - day of year (i.e., days since 31 Dec the previous year) for the first day of the corresponding bird/year/sub-season * `log_ODBA` - log-transformed overall dynamic body acceleration (log(g)) * `num_feed_fixes` - number of ACC fixes classified as feeding * `num_ACC_fixes` - total number of ACC fixes * `mean_precip` - mean daily cumulative precipitation (mm) * `prop_days_below_freezing` - proportion of days below freezing * `prop_storm_days` - proportion of days with a severe storm * `prop_grass` - proportion of time spent in grasslands * `prop_ag` - proportion of time spent in (non-grassland) agricultural land * `prop_bog` - proportion of time spent in peat bogs * `survival` (autumn data only) - autumn survival (1 = survived, 0 = died)