Data and code from: Photoperiod modulates courtship behavior and plasma testosterone in a short-day passerine
Data files
Sep 07, 2026 version files 120.44 KB
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courtship_time_only_1000s_from_start_gap_leq15.csv
886 B
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courtship_time_only_1000s_from_start_gap_leq15.tsv
886 B
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Ethograms_analysis_script.rtf
10.86 KB
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ethograms_R.tsv
103.09 KB
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README.md
4.71 KB
Abstract
Seasonal reproduction in birds is commonly regulated by photoperiod, and passerines are generally considered long-day breeders. The Java sparrow (Padda oryzivora) has been proposed as a possible exception, but experimental evidence for short-day photoperiodicity has remained limited. Here, we tested the effects of day-length manipulation on courtship behavior and plasma testosterone levels in male Java sparrows. Birds were exposed sequentially to long-day, short-day, and long-day conditions, and behavioral and hormonal responses were quantified at defined stages across the experiment. Courtship increased after the transition from long to short days and decreased after the return to long days. Plasma testosterone showed a related but more heterogeneous pattern: it did not increase significantly at the group level after transfer to short days, but declined markedly after re-exposure to long days. In addition, variation in plasma testosterone did not consistently predict variation in courtship across treatment stages. Together, these results provide experimental support for a short-day reproductive response in Java sparrows, particularly at the behavioral level, and identify increasing day length as a potent inhibitory cue for both courtship and circulating testosterone. More broadly, our findings refine current views of photoperiodic regulation in passerines and highlight the complexity of the relationship between environmental cues, endocrine responses, and reproductive behavior in birds.
Dataset DOI: 10.5061/dryad.2rbnzs85s
Description of the data and file structure
Behavioral and hormonal data were collected from adult male Java sparrows (Padda oryzivora) exposed sequentially to long-day and short-day photoperiods. Courtship behavior toward a female and plasma testosterone concentrations were measured at four experimental stages: an initial long-day condition, two time points during short-day exposure, and a final stage after return to long-day conditions. The experiment was designed to assess how changes in photoperiod influence male courtship behavior and circulating testosterone.
Files and variables
File: ethograms_R.tsv
Description: Anonymized behavioral ethogram data from male Java sparrows. Each row represents a behavioral event recorded during a female-exposure trial.
Variables:
- Animal: anonymized numerical identifier of the male
- Day_length: photoperiod condition. L = long-day photoperiod (14L:10D); C = short-day photoperiod (10L:14D)
- Stage: experimental sampling stage
- Stage 1 = initial long-day condition (L1)
- Stage 2 = first sampling under short-day conditions (S2)
- Stage 3 = later sampling under short-day conditions (S3)
- Stage 4 = sampling after return to long-day conditions (L4)
- Behavior: behavioral event recorded in the ethogram, including start, end, singing, bill wiping, hopping, and mix of bill wiping and hopping
- Behavior_type: type of behavioral record. “point” indicates an instantaneous event and “state” indicates a behavior with measurable duration
- Start_s: start time of the event, in seconds
- Stop_s: stop time of the event, in seconds
- Duration_s: duration of state events, in seconds. NA indicates that duration is not applicable, as for point events.
File: courtship_time_only_1000s_from_start_gap_leq15.csv
Description: Derived dataset containing total courtship time for each male at each experimental stage.
Variables:
- Animal: anonymized numerical identifier of the male
- Day_length: photoperiod condition
- L = long-day photoperiod (14L:10D)
- C = short-day photoperiod (10L:14D)
- Stage: experimental sampling stage, as defined above
- Courtship_time_s: total courtship duration during the first 1000 s of the observation period, in seconds. A value of 0 indicates that the observation was completed but no courtship behavior meeting the defined criteria was detected; it is not a missing value.
File: courtship_time_only_1000s_from_start_gap_leq15.tsv
Description: Tab-separated version of courtship_time_only_1000s_from_start_gap_leq15.csv. It contains the same variables and data as the CSV file.
File: Ethograms_analysis_script.rtf
Description: R code used to derive total courtship time from the anonymized ethograms. Behavioral events were aligned to the original start of each observation, and the first 1000 s were analyzed. Singing, bill wiping, hopping, and mixed bill-wiping/hopping displays were considered courtship-related behaviors. Consecutive courtship-related events separated by 15 s or less were grouped into the same bout. Single isolated bill-wiping or hopping events were not classified as courtship. Total courtship time was calculated as the summed duration of retained courtship bouts for each Animal × Day_length × Stage combination.
Code/software
R was used to process the behavioral data and calculate courtship time. The analysis script is provided as Ethograms_analysis_script.rtf.
The script uses the following R packages:
dplyr: data manipulation and summarization
readr: import and export of CSV and TSV files
readxl: optional import of Excel files
tools: identification of input file extensions
The workflow was as follows: ethograms_R.tsv was used as the input behavioral dataset. The script aligned each ethogram to its original start time, retained behavioral events occurring within the first 1000 s of the observation, identified and grouped courtship-related events into bouts using a maximum inter-event gap of 15 s, and calculated total courtship time for each Animal × Day_length × Stage combination. The resulting data were exported as courtship_time_only_1000s_from_start_gap_leq15.csv and courtship_time_only_1000s_from_start_gap_leq15.tsv.
The tabular data files can be viewed with any spreadsheet or text-editing software and do not require proprietary software.
Access information
Other publicly accessible locations of the data:
- N/A
Data was derived from the following sources:
- N/A