Pupping and yearling survival in Galápagos Sea Lions: impact of maternal investment, environmental fluctuations and population decline
Data files
Jun 04, 2026 version files 10.89 MB
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Births_Analysis_Exact.html
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Births_Analysis_Exact.Rmd
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Births_Analysis.html
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Births_Analysis.Rmd
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BirthsREADME.rtf
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census_avg.RData
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data.RData
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README.md
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Jul 13, 2026 version files 11.70 MB
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Births_Analysis_Exact.html
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Births_Analysis_Exact.Rmd
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Births_Analysis.html
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Births_Analysis.Rmd
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BirthsREADME.rtf
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census_avg.csv
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census_avg.RData
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census_raw.csv
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data.csv
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data.RData
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README.md
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smi_raw.csv
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Jul 21, 2026 version files 11.70 MB
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Births_Analysis_Exact.html
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Births_Analysis_Exact.Rmd
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Births_Analysis.html
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Births_Analysis.Rmd
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BirthsREADME.txt
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census_avg.csv
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census_avg.RData
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census_raw.csv
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data.csv
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data.RData
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README.md
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smi_raw.csv
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Jul 21, 2026 version files 12.10 MB
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Births_Analysis_Exact.html
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Births_Analysis_Exact.Rmd
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Births_Analysis.html
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Births_Analysis.Rmd
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BirthsREADME.txt
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census_avg.csv
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census_avg.RData
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census_raw.csv
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data.csv
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data.RData
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README.md
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smi_raw.csv
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Abstract
The Galápagos sea lion (GSL) is an endangered marine apex predator that has experienced a 50-75% population decline over the last 50 years. Using 21 years of data, we present the first long-term analysis of pupping trends and pup survival in this species, revealing how extreme climate oscillations may shape population dynamics and future trends. We found that the Caamaño colony has been in decline since monitoring began in 2003 (-3%), with the rate accelerating significantly after the 2010 reproductive period (-8.4%). This pattern cannot be explained by climate effects or reduced female fecundity but is more likely the result of decreasing recruitment due to lowered juvenile survival. Whilst there has been no overall change in median pupping point, there has been a significant shortening of the duration of the pupping period (» 6 days / year) since the acceleration of the population decline. We found that pelagic foraging females give birth significantly earlier and appear to adapt the timing of parturition to variations in resource availability. Male pups are born significantly earlier suggesting sex differences in gestational length or implantation. Although climate does effect pup survival to yearling age, there has been no temporal change in survival over the study period. Body condition at birth and juvenile presence within the colony have a positive impact on pup survival. Our results confirm that GSL are highly adapted to deal with the extreme variability of their environment and that their continued decline is likely driven by factors not related to climate.
Dataset DOI: 10.5061/dryad.zs7h44jr0
Description of the data and file structure
Data were collected between September 2003 and April 2023 on Isla Caamaño during 2 annual field seasons from October-December and February-April that cover the main reproductive period. The islet is located off the southern coast of Santa Cruz in the centre of the Galápagos archipelago and is home to a breeding colony of GSL that has been intensively studied since 2003. All individuals that are born on, or regularly use the islet, are marked and assigned a unique identification ("ID"). Date of birth (DoB) is recorded for every individual born in the colony and assigned a category according to how exact the DoB information is ("exact": the day is known precisely, "weak": +-2 weeks, "unknown": less exact or completely unknown). During the marking morphometric measurements are taken, some individuals have been captured multiple times over their life span either to replace missing markers or as part of another contained study. The islet is sub-divided into artificial sites to record movement within the colony. Identification rounds ("resight rounds") were conducted at least twice daily. During each round the ID, and location of every individual present on the islet is recorded.
B. Originators
Alexandra K. Childs; Department of Animal Behaviour, Faculty of Biology, Bielefeld University, Konsequenz 45, 33501, Germany.
Claire Stainfield; Scotland’s Rural College (SRUC) Aberdeen Campus, Craibstone Estate Craibstone Drive, Aberdeen AB21 9TR, UK.
Svenja Stoehr; Department of Animal Behaviour, Faculty of Biology, Bielefeld University, Konsequenz 45, 33501, Germany; Galápagos Sea Lion Project, Bielefeld 33501, Germany.
Sean D. Twiss; Department of Biosciences, Durham University, Durham DH1 3LE, UK.
Oliver Krüger; Department of Animal Behaviour, Faculty of Biology, Bielefeld University, Konsequenz 45, 33501, Germany;Joint Institute for Individualisation in a Changing Environment (JICE), Bielefeld University and University of Münster, Konsequenz 45, Bielefeld 33615, Germany.
C. Contact information
Alexandra K. Childs; ORCID 0009-0003-4150-6745
Department of Animal Behaviour, Faculty of Biology, Bielefeld University, Konsequenz 45, 33501 Bielefeld, Germany;
D. Dates of data collection
September 2003 and April 2023
E. Geographic Location(s) of data collection
Isla Caamaño, Galápagos, Ecuador
F. Funding Sources
This work was supported by the German Research Foundation (DFG) via the collaborative research centre CRC TRR 212, project number 316099922, project B07 and D06, and Bielefeld University.
Licenses/restrictions placed on the data or code
- CC0 1.0 Universal
Recommended citation for this data/code archive
Childs, A.K.; Stainfield, C.; Stoehr, S.; Twiss, S. D.; Krüger, O.; (2025). Data from: Flexible maternal strategies in Galápagos Sea Lions mitigate climate impacts but fail to halt population decline [Dataset]. Dryad. https://doi.org/10.5061/dryad.zs7h44jr0
All coding was performed in RStudio 2024.9.0.375
Files and variables
This data repository consists of 6 data files, 2 code scripts and their HTML output, and this README document, with the following data and code filenames and variables.
File: Births_Analysis_Exact.html
Description: output of Births_Analysis_Exact.Rmd
File: Births_Analysis.html
Description: output of Births_Analysis.Rmd
File: Births_Analysis_Exact.Rmd
Description: code to perform all analysis for the associated study with only pups whose births were directly observed
File: Births_Analysis.Rmd
Description: code to perform all analysis for the associated study
File: census_avg.RData
Description: includes data the average number of individuals observed in the colony according to age category where: adult = 5+ years, juvenile = 6 months - 4 years, pup = 0 - 6 months
37 obs. of 25 variables
Variables
- SeasonOfRound: identifier of the reproductive season when the round was conducted, where 1 represents the first year of data collection. The Galapagos Sea Lion reproductive year runs from July 1st - June 30th
- Males_avg: mean number of adult males observed during the reproductive season
- Females_avg: mean number of adult females observed during the reproductive season
- Females_max: maximum number of adult females observed during a single census round during the reproductive year
- Adults_avg: mean number of adults with no positive ID and/or who could not be sexed observed during the reproductive season
- All_Adults_avg: mean number of all adults observed during the reproductive season, this includes males, females and adults with no positive ID and/or who could not be sexed
- Juveniles_avg: mean number of juveniles observed during the reproductive season
- Pups_avg: mean number of pups observed during the reproductive season
- Total_avg: mean number of sea lions (all age categories) observed during the reproductive season
- Total_avg_wo_pups: mean number of adults and juveniles observed during the reproductive season, excluding pups
- Total_avg_wo_fem_pups: mean number of adult males, unidentifiable adults and juveniles observed during the reproductive season, excluding pups
- Total_avg_male_juv: mean number of unidentifiable adult males and juveniles observed during the reproductive season
- n_counts: total number of births during the reproductive season
- SeasonOfRound_YearStart: the year of the reproductive season (according to the Galapagos Sea Lion, July 1st - June 30th) where the year is identified according to the Gregorian calendar year in which it started
- SeasonOfRound_extra: identifier of the reproductive half-season when the round was conducted (i.e. 6-month intervals: Jul-Dec; Jan-Jun) where .5 represents the first half of the season (Jun-Dec) and whole numbers (.0) the second half (Jan-Jun)
- Males_avg_ex: mean number of adult males observed during the reproductive half-season
- Females_avg_ex: mean number of adult females observed during the reproductive half-season
- Adults_avg_ex: mean number of adults with no positive ID and/or who could not be sexed observed during the reproductive half-season
- All_Adults_avg_ex: mean number of all adults observed during the reproductive season, this includes males, females and adults with no positive ID and/or who
- Juveniles_avg_ex: mean number of juveniles observed during the reproductive half-season
- Pups_avg_ex: mean number of pups observed during the reproductive half-season
- Total_avg_ex: mean number of sea lions (all age categories) observed during the reproductive half-season
- n_counts_ex: total number of births during the reproductive half-season
- Total_avg_wo_pups_ex: mean number of all adults and juveniles observed during the reproductive half-season, excluding pups
- Total_avg_wo_fem_pups_ex: mean number of adult males, unidentifiable adults and juveniles observed during the reproductive half-season, excluding pups
File: data.RData
Description: includes data on all individuals born in the colony during the data collection period and the associated variables used during analysis
2214 obs. of 44 variables
Variables
- ID: identifier of the offspring
- Sex: sex of the suckling individual (empty or 'NA' cells are where no positive sex was recorded (n = 16))
- Birth: date of birth (DoB) of the offspring (yyyy-mm-dd)
- ExactBirth: how exact the birth information is ("exact": the day is known precisely, "weak": +-2 weeks, "rough": +-1 half-season or the equivalent of 6 months, only assigned to individuals handled for the first time when under 6 months of age, "unknown": less exact or completely unknown)
- SiteBorn: identifier of the site the offspring was born in (empty or 'NA' cells are associated with no location of the birth being recorded (n = 677))
- SiteBornName: common name of the site the offspring was born in (corresponds with the published map) (empty or 'NA' cells are associated with 1. missing information in SiteBorn 2. site identifiers that were used prior to 2007 and so no longer correspond to the current sub-division of the islet (n = 1104))
- SeasonOfBirth: the reproductive season of birth of the offspring where 1 represents the first year of data collection. The Galapagos Sea Lion reproductive year runs from July 1st - June 30th
- SeasonOfBirth_extra: the reproductive half-season (i.e. 6-month intervals: Jul-Dec; Jan-Jun) of birth of the offspring where .5 represents the first half of the season (Jun-Dec) and whole numbers (.0) the second half (Jan-Jun)
- Season_BirthYearStart: the year of the reproductive season of birth where the year is identified according to the Gregorian calendar year in which it started
- scaled_mass_index: scale mass index (SMI) of the offspring at birth (<= 10 days old) calculated according to Peig & Green (2009) using mass (M) and length (L). Formula: M_i = M_i \times (L_0 / L_i) \textasciicircum {b_{SMA}} (empty or 'NA' cells are associated with missing morphological measurements during this age window so no SMI could be calculated (n = 682))
- SST_Daily: the mean daily sea surface temperature (in Celsius) recorded on the offspring's DoB (empty or 'NA' cells are associated with no available data from the original source (n = 1))
- SST_monthly_avg: the mean sea surface temperature (in Celsius) of the month of birth
- ANOM_Month: the anomaly (in Celsius) of the month of birth
- ONI_Cat_Month: the ONI category of the month of birth
- mean_ANOM_extra: the mean ONI anomaly (in Celsius) of the reproductive half-year during which the offspring was born (Jul-Dec or Jan-Jun)
- ONI_Category_Extra: the ONI category (as defined by NOAA) according to the mean anomaly of the reproductive half-year during which the offspring was born (Jul-Dec or Jan-Jun)
- delayed_ONI_Category_extra: the ONI category (as defined by NOAA) according to the mean anomaly of the reproductive half-year immediately prior to the one in which the offspring was born (Jul-Dec or Jan-Jun)
- delayed_mean_ANOM_extra: the mean ONI anomaly (in Celsius) of the reproductive half-year immediately prior to the one in which the offspring was born (Jul-Dec or Jan-Jun)
- mean_SST_extra: the mean sea surface temperature (in Celsius) of the reproductive half-year during which the offspring was born (Jul-Dec or Jan-Jun)
- delayed_mean_SST_extra: the mean sea surface temperature (in Celsius) of the reproductive half-year immediately prior to the one in which the offspring was born (Jul-Dec or Jan-Jun)
- mean_ANOM: the mean ONI anomaly (in Celsius) of the reproductive year (i.e. season) during which the offspring was born (Jul-Jun)
- ONI_Category: the ONI category (as defined by NOAA) of the reproductive year (i.e. season) during which the offspring was born (Jul-Jun)
- delayed_ONI_Category: the ONI category (as defined by NOAA) of the reproductive year (i.e. season) immediately prior to the one in which the offspring was born (Jul-Jun)
- delayed_mean_ANOM: the mean ONI anomaly (in Celsius) of the reproductive year (i.e. season) immediately prior to the one in which the offspring was born (Jul-Jun)
- mean_SST: the mean sea surface temperature (in Celsius) of the reproductive year (i.e. season) during which the offspring was born (Jul-Jun)
- delayed_mean_SST: the mean sea surface temperature (in Celsius) of the reproductive year (i.e. season) immediately prior to the one in which the offspring was born (Jul-Jun)
- rounds_per_day: the number of rounds made on the offspring's DoB where all individual's ID and location were recorded (empty or 'NA' cells are associated with DoB where no rounds were made due to 1. DoB falling outside of field season dates 2. researcher illness preventing rounds from being made (n = 632))
- effort_days_half: the number of days during the reproductive half-year where rounds were made recording all individuals' ID and location (Jul-Dec or Jan-Jun) (empty or 'NA' cells are associated with reproductive year 2020 where there was only 2 weeks of field work due to COVID-19 (n = 38))
- effort_rounds_half: the number of rounds made during the reproductive half-year recording all individuals' IDs and location (Jul-Dec or Jan-Jun) (empty or 'NA' cells are associated with reproductive year 2020 where there was only 2 weeks of field work due to COVID-19 (n = 38))
- effort_duration_half: the number of days during each field season where rounds were made recording all individuals' IDs and location (cold/hot) (empty or 'NA' cells are associated with reproductive year 2020 where there was only 2 weeks of field work due to COVID-19 (n = 38))
- effort_days_season: the number of days during the reproductive year where rounds were made recording all individuals' IDs and location (Jul-Jun) (empty or 'NA' cells are associated with reproductive year 2020 where there was only 2 weeks of field work due to COVID-19 (n = 38))
- effort_rounds_season: the number of rounds made during the reproductive half (i.e. season) recording all individuals' IDs and location (Jul-Jun) (empty or 'NA' cells are associated with reproductive year 2020 where there was only 2 weeks of field work due to COVID-19 (n = 38))
- effort_duration_season: the number of days between the first observation day of the reproductive year (cold season) and the last observation day (of the hot season - where there was one, otherwise the cold season) where rounds were made recording all individual's ID and location (empty or 'NA' cells are associated with reproductive year 2020 where there was only 2 weeks of field work due to COVID-19 (n = 38))
- Observed_1y: logical variable telling us if the offspring was observed as a 1-year-old (age-specific), where TRUE = yes (empty or 'NA' cells are associated with offspring born in the 2023 reproductive year (i.e. season) and were therefore not old enough to have been observed as one-year-olds (n = 29))
- yearling_survival: logical variable telling us if the offspring was observed as a one-year-old or older at any point during the data collection period, where TRUE = yes (empty or 'NA' cells are associated with offspring born in the 2023 reproductive year (i.e. season) and were therefore not old enough to have been observed as one-year-olds (n = 29))
- Mother_ID: identifier of the offspring's mother (empty or 'NA' cells are associated with no positive ID recorded for the mother, most likely because she was unmarked and/or had lost her markings (n = 1281))
- MotherSOB: the reproductive season (i.e. year: Jul-Jun) of the mother's DoB (empty or 'NA' cells are associated with no positive ID recorded for the mother and/or an "unknown" DoB (n = 1850))
- Mother_BirthYearStart: the year of the reproductive season of the mother's DoB (empty or 'NA' cells are associated with missing information in MotherSOB (n = 1850))
- Mother_age_at_Parity: age in years (i.e. seasons) of the mother at the time of the offspring's birth (empty or 'NA' cells are where either 1. no positive ID was recorded, 2. date of birth of mother was "unknown" and so no accurate age could be calculated (n = 1928))
- strategy: foraging strategy of the offspring's mother (according to Stoehr et al. 2025, Schwarz et al. 2021) (empty or 'NA' cells are associated with no available information on maternal foraging strategy (n = 2173))
- adjusted_SiteBorn: identifier of the site in which the offspring was most commonly observed during the first 30 days of life (empty or 'NA' cells are associated with offspring who were born a month or more outside of the field seasons and so no observations of them during their first 30 days of life are available (n = 1132))
- adjusted_SiteBornName: common name of the adjusted_SiteBorn that corresponds with the map of the islet (empty or 'NA' cells are associated with missing information in adjusted_SiteBorn (n = 1132))
- adj_inclusive_births: the total number of births in an offspring's adjusted_SiteBorn and all sites boarding their adjusted_SiteBorn during the reproductive year (i.e. season) of their birth (empty or 'NA' cells are associated with missing information in adjusted_SiteBorn (n = 1132))
- n_births: the total number of births in the colony during the offspring's reproductive year (i.e. season) of birth
File: census_avg.csv
Description: .csv version of census_avg.RData, to use this version the source must be changed in Births_Analysis.Rmd and Births_Analysis_Exact.Rmd
File: data.csv
Description: .csv version of data.RData, to use this version the source must be changed in Births_Analysis.Rmd and Births_Analysis_Exact.Rmd
File: smi_raw.csv
Description: includes the raw data (length and mass measurements according to Mueller et al. [2011]) used to calculate pup Scaled Mass Index (SMI) at birth according to Peig & Green (2009)
1532 obs. of 4 variables
Variables
- ID: identifier of the offspring
- Age_at_Capture_Days: age in days of the focal offspring at the time of handling, used to identify measurements that are appropriate for calculating SMI at birth (≤ 10 days)
- Acctual_Mass_Kg: mass in kilograms of the focal offspring recorded during handling using an electronic scale
- Body_Length_cm: length (tip of the nose to tip of the tail) in centimetres of the focal offspring recorded during handling using a standardised measuring stick
File: census_raw.csv
Description: includes the raw data used to calculate the means found in census_avg.RData/census_avg.csv individuals observed in the colony according to age category where: adult = 5+ years, immature = 6 months - 4 years (equivalent to “juvenile” in other data files), pup = 0 - 6 months
census rounds count the total number of individuals observed in the colony, including those without unique identifiers (tags/shaves) and those individuals whose identifiers could not be clearly read due to distance/movement/obstruction
516 obs. of 8 variables
Variables
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ResightRound_ID: identifier of the census round, numbers are not consecutive as other forms of observation rounds are conducted in-between
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ResightRound_Date: date of the census round
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MalesTotal: total number of adult males
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FemalesTotal: total number of adult females
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AdultsTotal: total number of adults who could not be identified or sexed
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ImmaturesTotal: total number of immatures/juveniles
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PupsTotal: total number of pups - please note that the number of observed pups varies greatly according to how far into the reproductive season the census was conducted and is therefore not an accurate representation of the colonies annual reproductive success
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Total: total number of individuals observed in the colony for each unique census (ResightRound_ID) calculated by adding all values in each age category
File: BirthsREADME.txt
Description: ReadMe file that contains additional information about this data such as software packages, additional public data sources and references
REFERENCES
Mueller, B., Pörschmann, U., Wolf, J. B. W., & Trillmich, F. (2011). Growth under uncertainty: The influence of marine variability on early development of Galapagos sea lions. Marine Mammal Science, 27(2), 350–365. https://doi.org/10.1111/j.1748-7692.2010.00404.x
Peig, J., & Green, A. J. (2009). New perspectives for estimating body condition from mass/length data: the scaled mass index as an alternative method. Oikos, 118(12), 1883–1891. https://doi.org/10.1111/j.1600-0706.2009.17643.x
Schwarz, J. F. L., Mews, S., DeRango, E. J., Langrock, R., Piedrahita, P., Páez-Rosas, D., & Krüger, O. (2021). Individuality counts: A new comprehensive approach to foraging strategies of a tropical marine predator. Oecologia, 195(2), 313–325. https://doi.org/10.1007/s00442-021-04850-w
Stoehr, S., Childs, A., Krüger, O., Piedrahita, P., & Schwarz, J. (2025). Vibrissae length as a morphological proxy for foraging behaviour in pinnipeds. EcoEvoRxiv. https://doi.org/10.32942/X2BW6ZAccess information
Code/software
All analyses were conducted in R version 4.5.1 (2025-06-13).
Auguie B (2017). gridExtra: Miscellaneous Functions for "Grid" Graphics doi:10.32614/CRAN.package.gridExtra https://doi.org/10.32614/CRAN.package.gridExtra, R package version 2.3, https://CRAN.R-project.org/package=gridExtra.
Bartoń K (2025). MuMIn: Multi-Model Inference doi:10.32614/CRAN.package.MuMIn https://doi.org/10.32614/CRAN.package.MuMIn, R package version 1.48.11, https://CRAN.R-project.org/package=MuMIn.
Bates D, Mächler M, Bolker B, Walker S (2015). "Fitting Linear Mixed-Effects Models Using lme4." Journal of Statistical Software 67(1), 1-48. doi:10.18637/jss.v067.i01 https://doi.org/10.18637/jss.v067.i01.
Bates D, Maechler M, Jagan M (2025). Matrix: Sparse and Dense Matrix Classes and Methods doi:10.32614/CRAN.package.Matrix https://doi.org/10.32614/CRAN.package.Matrix, R package version 1.7-3, https://CRAN.R-project.org/package=Matrix.
Grolemund G, Wickham H (2011). "Dates and Times Made Easy with lubridate." Journal of Statistical Software 40(3), 1-25. https://www.jstatsoft.org/v40/i03/.
Kuhn, Max (2008). "Building Predictive Models in R Using the caret Package." Journal of Statistical Software 28(5), 1–26. doi:10.18637/jss.v028.i05 https://doi.org/10.18637/jss.v028.i05, https://www.jstatsoft.org/index.php/jss/article/view/v028i05.
Kuznetsova A, Brockhoff PB, Christensen RHB (2017). "lmerTest Package: Tests in Linear Mixed Effects Models." Journal of Statistical Software 82(13), 1-26. doi:10.18637/jss.v082.i13 https://doi.org/10.18637/jss.v082.i13.
Lenth R, Piaskowski J (2025). emmeans: Estimated Marginal Means, aka Least-Squares Means doi:10.32614/CRAN.package.emmeans https://doi.org/10.32614/CRAN.package.emmeans, R package version 2.0.1, https://CRAN.R-project.org/package=emmeans.
Makowski D, Lüdecke D, Patil I, Thériault R, Ben-Shachar M, Wiernik B (2023). "Automated Results Reporting as a Practical Tool to Improve Reproducibility and Methodological Best Practices Adoption." CRAN https://easystats.github.io/report/.
Pedersen T (2025). patchwork: The Composer of Plots doi:10.32614/CRAN.package.patchwork https://doi.org/10.32614/CRAN.package.patchwork, R package version 1.3.1, https://CRAN.R-project.org/package=patchwork.
Pinheiro J, Bates D, R Core Team (2025). nlme: Linear and Nonlinear Mixed Effects Models doi:10.32614/CRAN.package.nlme https://doi.org/10.32614/CRAN.package.nlme, R package version 3.1-168, https://CRAN.R-project.org/package=nlme.
Pinheiro JC, Bates DM (2000). Mixed-Effects Models in S and S-PLUS Springer, New York. doi:10.1007/b98882 https://doi.org/10.1007/b98882.
R Core Team (2025). R: A Language and Environment for Statistical Computing R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/.
Robin X, Turck N, Hainard A, Tiberti N, Lisacek F, Sanchez J, Müller M (2011). "pROC: an open-source package for R and S+ to analyze and compare ROC curves." BMC Bioinformatics 12, 77.
Robinson D, Hayes A, Couch S (2025). broom: Convert Statistical Objects into Tidy Tibbles doi:10.32614/CRAN.package.broom https://doi.org/10.32614/CRAN.package.broom, R package version 1.0.8, https://CRAN.R-project.org/package=broom.
Sarkar D (2008). Lattice: Multivariate Data Visualization with R Springer, New York. ISBN 978-0-387-75968-5, http://lmdvr.r-forge.r-project.org.
Vaughan D (2024). slider: Sliding Window Functions doi:10.32614/CRAN.package.slider https://doi.org/10.32614/CRAN.package.slider, R package version 0.3.2, https://CRAN.R-project.org/package=slider.
Venables WN, Ripley BD (2002). Modern Applied Statistics with S Fourth edition. Springer, New York. ISBN 0-387-95457-0, https://www.stats.ox.ac.uk/pub/MASS4/.
Wickham H (2016). ggplot2: Elegant Graphics for Data Analysis Springer-Verlag New York. ISBN 978-3-319-24277-4, https://ggplot2.tidyverse.org.
Wickham H, Bryan J (2025). readxl: Read Excel Files doi:10.32614/CRAN.package.readxl https://doi.org/10.32614/CRAN.package.readxl, R package version 1.4.5, https://CRAN.R-project.org/package=readxl.
Wickham H, François R, Henry L, Müller K, Vaughan D (2023). dplyr: A Grammar of Data Manipulation doi:10.32614/CRAN.package.dplyr https://doi.org/10.32614/CRAN.package.dplyr, R package version 1.1.4, https://CRAN.R-project.org/package=dplyr.
Wickham H, Henry L (2025). purrr: Functional Programming Tools doi:10.32614/CRAN.package.purrr https://doi.org/10.32614/CRAN.package.purrr, R package version 1.0.4, https://CRAN.R-project.org/package=purrr.
Wickham H, Hester J, Bryan J (2024). readr: Read Rectangular Text Data doi:10.32614/CRAN.package.readr https://doi.org/10.32614/CRAN.package.readr, R package version 2.1.5, https://CRAN.R-project.org/package=readr.
Wickham H, Pedersen T, Seidel D (2025). scales: Scale Functions for Visualization doi:10.32614/CRAN.package.scales https://doi.org/10.32614/CRAN.package.scales, R package version 1.4.0, https://CRAN.R-project.org/package=scales.
Wickham H, Vaughan D, Girlich M (2024). tidyr: Tidy Messy Data doi:10.32614/CRAN.package.tidyr https://doi.org/10.32614/CRAN.package.tidyr, R package version 1.3.1, https://CRAN.R-project.org/package=tidyr.
Wood SN (2011). "Fast stable restricted maximum likelihood and marginal likelihood estimation of semiparametric generalized linear models." Journal of the Royal Statistical Society (B), 73(1), 3-36. doi:10.1111/j.1467-9868.2010.00749.x https://doi.org/10.1111/j.1467-9868.2010.00749.x.
Wood SN, Pya N, Säfken B (2016). "Smoothing parameter and model selection for general smooth models (with discussion)." Journal of the American Statistical Association, 111, 1548-1575. doi:10.1080/01621459.2016.1180986 https://doi.org/10.1080/01621459.2016.1180986.
Wood SN (2004). "Stable and efficient multiple smoothing parameter estimation for generalized additive models." Journal of the American Statistical Association 99(467), 673-686. doi:10.1198/016214504000000980 https://doi.org/10.1198/016214504000000980.
Wood SN (2017). Generalized Additive Models: An Introduction with R 2nd edition. Chapman and Hall/CRC. Wood SN (2003). "Thin-plate regression splines." Journal of the Royal Statistical Society (B) 65(1), 95-114. doi:10.1111/1467-9868.00374 https://doi.org/10.1111/1467-9868.00374.
Xie Y (2025). knitr: A General-Purpose Package for Dynamic Report Generation in R. R package version 1.50, https://yihui.org/knitr/.
Xie Y (2015). Dynamic Documents with R and knitr 2nd edition. Chapman and Hall/CRC, Boca Raton, Florida. ISBN 978-1498716963, https://yihui.org/knitr/.
Xie Y (2014). "knitr: A Comprehensive Tool for Reproducible Research in R." In Stodden V, Leisch F, Peng RD (eds.), Implementing Reproducible Computational Research. Chapman and Hall/CRC. ISBN 978-1466561595.
Zeileis A, Grothendieck G (2005). "zoo: S3 Infrastructure for Regular and Irregular Time Series." Journal of Statistical Software 14(6), 1-27. doi:10.18637/jss.v014.i06 https://doi.org/10.18637/jss.v014.i06.
Zeileis A, Hothorn T (2002). "Diagnostic Checking in Regression Relationships." R News 2(3), 7-10. https://CRAN.R-project.org/doc/Rnews/.
Zhu H (2024). kableExtra: Construct Complex Table with 'kable' and Pipe Syntax. doi:10.32614/CRAN.package.kableExtra https://doi.org/10.32614/CRAN.package.kableExtra, R package version 1.4.0, https://CRAN.R-project.org/package=kableExtra.
Data derived from other sources
Climate data according to the ONI index obtained from NOAA (https://www.cpc.ncep.noaa.gov/products/analysis_monitoring/ensostuff/detrend.nino34.ascii.txt).
Sea surface temperature data obtained from "Galapagos Climatology Database", dataZone, Charles Darwin Foundation, https://datazone.darwinfoundation.org/en/climate/puerto-ayora. Accessed 18 September 2025.
Changes after Jun 4, 2026:
Additional data files added as requested by the publishing journal:
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.csv versions of the original data.RData and census_avg.RData for accessibility
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smi_raw.csv
includes the raw data (length and mass measurements according to Mueller et al. [2011]) used to calculate pup Scaled Mass Index (SMI) at birth according to Peig & Green (2009)
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census_raw.csv
includes the raw data used to calculate the means found in census_avg.RData/census_avg.csv individuals observed in the colony according to age category where: adult = 5+ years, immature = 6 months - 4 years (equivalent to “juvenile” in other data files), pup = 0 - 6 months
census rounds count the total number of individuals in the colony, including those without unique identifiers (tags/shaves) and those individuals whose identifiers could not be clearly read due to distance/movement/obstruction
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and updated version of BirthsREADME.rtf has been uploaded to reflect these changes
Changes after Jul 13, 2026:
converted BirthsREADME to .txt at the request of the journal
Changes after Jul 21, 2026: Edited README.md.
included R version number in .html and README
