DOI: 10.5061/dryad.0rxwdbsc2
title: Arctic seabirds show individual variation in foraging responses to glacial conditions without consequences for reproductive output

description: Behavioural plasticity is predicted to be the primary mechanism by which
 long-lived species continue to access resources under rapid climate
 change. Plasticity will be particularly important at highly dynamic,
 prey-rich foraging areas such as upwelling fronts of marine-terminating
 glacier in the high Arctic, where profitability varies significantly
 across space and time. Understanding individual variation in plasticity is
 crucial to understand populations adaptability to future climate
 scenarios. By analysing GPS data from 186 black-legged kittiwakes (Rissa
 tridactyla) breeding in the high Arctic over six years, we quantified
 individual variation in behavioural plasticity in use of glacial fronts
 and its relationship with the number of chicks produced. Variation in the
 relationship between glacial use and levels of discharged meltwater was
 primarily explained by differences in food availability between years.
 Whereas individuals spent more time at glaciers with increasing discharge
 when zooplankton biomass was low in the fjord, the probability of glacial
 front use decreased in years when food was more abundant despite high
 discharge and likely good conditions at the front. Interestingly, neither
 glacial use nor plasticity in foraging during the breeding season
 correlated with the number of surviving chicks, suggesting that all
 individuals still obtained enough food for reproduction. With increasing
 rate of glacier retreat and shifts in food availability, less plastic
 individuals or those reliant on glacial fronts may face pressure in
 finding food and may thereby experience long-term declines in reproductive
 success. Understanding and quantifying the complex nature of individual
 variation in plasticity will provide more detailed insights into how
 species will survive in rapidly changing environments.
description: # Arctic seabirds show individual variation in foraging responses to
 glacial conditions without consequences for reproductive output Dataset
 DOI: [10.5061/dryad.0rxwdbsc2](10.5061/dryad.0rxwdbsc2) ## Description of
 the data and file structure All Datasets provided can be used to recreate
 the analysis described in the associated article.  ### Files and variables
 Any NA values included within the datasets refer to non available data
 points. This could be for a variety of reasons such as it not being
 possible to gather environmental data on a given day or there not being a
 confirmed sex for an individual. #### File:
 Kongsfjorden_Zooplankton_2014_2021_Station_Averages.csv
 **Description:** This dataset contains information from zooplankton
 samples, including the location, date, and depth when the sample was
 created. It contains the total biomass of zooplankton that kittiwakes feed
 on from those samples. ##### Variables * Station: Location of zooplankton
 sampling station * Sampling.date: Date of sampling * Max.depth: Max depth
 the zooplankton sampling reached in metres * Min.depth: Minimum depth of
 zooplankton sampler in metres * Station.biomass.depth.cat.KI: Biomass of
 zooplankton fed on by kittiwakes in mg m^−3 ^ *
 depth.ave.sum.station.zoop: Depth-averaged sum of zooplankton biomass by
 station in mg m^-3^ #### File: Kongsfjorden_Sex_Database.csv
 **Description:** Contains the identified sex of all individuals included
 in the analysis. ##### Variables * BirdID: Individual ID * Sex: Sex of
 Individual #### File: Kongsfjorden_Reproductive_outcomes.csv
 **Description:** Contains data on breeding success from all of the
 monitored nests within Kongsfjorden during the study period. It also
 contains information on environmental conditions during the sampling
 years. ##### Variables * Nest.ID: Nest identifier * ACRNNID: Colony
 specific nest identifier * Breed.year: Year of breeding attempt *
 Hatch..Success: Binary hatching success * Breeding.Success: Binary
 breeding success * N.of.Chicks: Number of chicks in nest * Day.Criteria:
 Date of final check * Colony: Which colony * Comments: * zoop.annual.mean:
 DA zooplankton mean in mg m^-3^ * scaled.zoop: DA zooplankton mean scaled
 * zoop.annual.mean.inner: DA zooplankton mean of inner stations in mg
 m^-3^ * scaled.zoop.inner: DA zooplankton mean of inner stations scaled *
 BirdID: Individual ID * n.year: Year * bird.years: how many years of data
 we have per bird * BirdID.year: Individual ID and year * breed.ave.diff:
 Difference in breeding success to the average * chick.1.0: Binary, did
 they produce one or more chicks #### File:
 Kongsfjorden_GPS_Trips_Time_to_reach_glacier.csv **Description:** This
 dataset contains information on how long it took an individual to reach a
 glacier within a given trip. ##### Variables * birdTrip: Trip within each
 deployment * time.to.visit.glacier: Time spent at the glacier in minutes
 #### File: Glacier_Visits_per_bird_per_trip_GPS_600m.csv
 **Description:** This dataset contains information on how many different
 glaciers an individual visited during a trip and which one they visited
 most. ##### Variables * birdTrip: Trip within each deployment *
 different.glaciers.600: How many glaciers did they visit *
 Predominant.glacier: What glacier did they spend the most time at? ####
 File: Glacier_visit_dates.csv **Description:** This dataset gives the date
 and time that an individual visited a glacier. ##### Variables *
 GlacierVisitID: Glacier visit for an individual in a trip * datetime: Date
 and time variable * g.visit.date: Date they visited the glacier #### File:
 Kongsfjorden_Glacier_Visits_10mins.csv **Description:** This dataset
 contains information on unique visits to a glacier front and how long each
 visit happened for. ##### Variables * ring: Individual Identifier *
 birdTrip: Individual trip within deployment * GlacierVisitID: Unique
 glacier visit identifier * TimeAtGlacier: Time spent at the glacier during
 that visit in minutes * Name: Name of glacier * year: Year #### File:
 Kongsfjorden_Foraging_Trips_2014_2022_FinalVersion.csv
 **Description:** This dataset gives summary information for each GPS trip
 throughout the study period, including basic metrics (i.e., trip length)
 as well as basic environmental conditions during the trip. ##### Variables
 * Year: Year * colony: Colony   * BirdID: Individual Identifier *
 birdTrip: Trip within deployment * TripLength: Length of foraging trip in
 minutes * maxDist: Maximum distance reached from colony in km *
 TripDistance: Maximum distance from colony in km * stage: Breeding stage *
 GlacierProp.trip: Proportion of the trip at the glacier *
 GlacierFeed.consec: How many visits to a glacier * minLong: Minimum
 longitude during trip * date: Date * number.trips: Number of trips during
 that deployment * TripType: Whether the trip was in the fjord, glacier, or
 pelagic * chlorophyll: Chlorophyll values for fjord on that day in mg
 m^-3^ * week.chloro.mean: Weekly average of chlorophyll in mg m^-3^ *
 Year.mean: Mean of chlorophyll for that season in mg m^-3^ * month: Month
 * daily.temp.ave: Average temperature in the fjord that day in degrees
 Celsius * daily.sal.ave: Average salinity in fjord that day in practical
 salinity units * roll.mean.temp.7: Rolling mean of temperature across last
 7 days in degrees Celsius * roll.mean.sal.7: Rolling mean of salinity
 across the last 7 days in practical salinity units * Time.at.glacier: Time
 spent at the glacier during the foraging trip #### File:
 Glacial_Discharge_Daily_2006_2022.csv **Description:** This dataset gives
 information on daily variation in discharge rates within the fjord. #####
 Variables * : The first column is an index column * Date: Date * Fjord:
 Which fjord within Svalbard * day: Day * month: Month * Year: Year *
 julianday: Day of the year * Ave.Daily.runoff: Average runoff in the fjord
 on that date in m^3^ s^-1^ #### File: ind_plasticity_estimates.csv
 **Description:** This dataset is the model estimates for individual
 plasticity in glacial front use. It contains each iteration produced by
 the model described in the manuscript. ##### Variables * chain: Chain of
 model * iteration: Iteration within chain * draw: Predicted draw within
 chain * b_Intercept: Model intercept * b_scaled.Daily.runoff: Value of
 runoff * BirdID.year: BirdID by year * BirdID.year_Intercept: BirdID ID
 Intercept * BirdID.year_slope: BirdID ID slope * BirdID: Individual ID *
 TAG: Predicted time spent at the glacier in minutes * conditional_slope:
 Plasticity estimate * meanslope: mean plasticity estimate *
 mean.ind.slope: mean plasticity estimate for the individual without
 effects * mean.TAG: mean predicted time spent at the glacier in minutes  *
 ave.GR: Average glacial run off during deployment in m^3^ s^-1^ *
 range.GR: Range of glacial run off experienced in m^3^ s^-1^ * colony:
 Breeding colony of an individual **File:
 MS_glacier_plasticity_data_preparation.Rmd** * A markdown document that
 contains the scripts to prepare the inputted data for running the models
 specified in the Analysis * This includes code for how the dataframes are
 merged together, how variables are standardised across datasets, and
 removes any NA values  **File: MS_glacier_plasticity_models.Rmd** * A
 Markdown document that contains the scripts for running the models
 specified in the analysis * Datasets produced by the previous markdown
 document are loaded in preparation for running the models. * Priors for
 the models are set * Models are run * Model diagnostics are conducted ##
 Code/software All analysis was run in R All packages are listed below: 
 "ggplot2", "dplyr", "tidyr",
 "lubridate", "magrittr", "brms",
 "lme4", "arm", "MuMIn", "plyr",
 "broom", "coda", "grid",
 "gridExtra", "broom.mixed", "merTools",
 "parallel", "tidybayes", "wesanderson",
 "rptR", "MCMCglmm", "performance",
 "see", "rstan", "StanHeaders",
 "zoo", "sjPlot", "bayestestR",
 "MASS", "reshape2", "reshape",
 "plotly", "ggmcmc", "mcmcplots",
 "climwin", "ggpubr", "cowplot",
 "stringr", "ggExtra" All models were run in the brms
 package.  ## Access information Other publicly accessible locations of the
 data: * [Glacier frontlines:
 https://doi.org/10.21334/npolar.2021.d60a919a](https://doi.org/10.21334/npolar.2021.d60a919a) * Zooplankton until 2016: [https://doi.org/10.21334/npolar.2019.94b29b16](https://doi.org/10.21334/npolar.2019.94b29b16)