Data and code from: Staying sheltered: geographical variation in nestbox use by a nocturnal raptor outside the breeding season
Data files
Jun 15, 2026 version files 13.45 MB
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Breeding_season_correlation.csv
2.18 KB
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Dataset_revision.csv
69.41 KB
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Onelinepicture.csv
13.34 MB
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Rcode_Revision2.R
28.99 KB
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README.md
6.80 KB
Abstract
Datasets supporting the manuscript “Staying sheltered: geographical variation in nestbox use by a nocturnal raptor outside the breeding season”. These datasets contain observations of nestbox use by a nocturnal raptor outside the breeding season, together with environmental, habitat, and breeding-season variables collected from monitored nestboxes. The data are organized into three complementary files.
The first file, “Dataset_revision”, contains aggregated observations by nestbox, year, and season (autumn and winter), including information on monitoring effort, nestbox occupancy, playback surveys, environmental conditions (temperature, wind speed, day length, rainfall, and snow depth), bird community census data, and surrounding habitat composition.
The second file, “Onelinepicture”, contains data at the individual image level, where each row corresponds to a single camera-trap photograph with associated nestbox ID, date-time information, and recorded owl presence/absence inside the nestbox.
The third file, “Breeding_season_correlation”, contains nestbox occupancy information during the breeding season across multiple years, allowing comparisons between breeding and non-breeding season use patterns. For the analyses presented in the associated manuscript, information from these datasets was combined using R.
Dataset DOI: 10.5061/dryad.f7m0cfzbs
Description of the data and file structure
This repository contains three datasets supporting the manuscript “Staying sheltered: geographical variation in nestbox use by a nocturnal raptor outside the breeding season”. Each dataset is described below. Missing values are coded as NA. NA indicates that a value was not available or was not applicable for a given observation.
In Dataset_revision, NA values mainly occur when a variable was not collected or could not be calculated for a specific nestbox, year, or season. For example, autumn observations may contain NA values for variables related to owl presence or bird census counts when no camera recording or census was available for that period. Environmental variables may also contain NA values when corresponding measurements were unavailable.
In Breeding_season_correlation, NA values may occur when breeding-season occupancy information was not available for a nestbox in a given year.
NA values should not be interpreted as zero. They indicate missing information or that the variable was not applicable for that observation.
Data processing
For the analyses presented in the associated manuscript, information from the three datasets was combined using R. The original datasets are provided separately to preserve the different levels of data resolution (seasonal summaries, individual images, and breeding-season occupancy).
Files and variables
File: Rcode_Revision2.R
Description: See Code/Software section below.
File: Dataset_revision.csv
Description: This dataset contains observations aggregated by nestbox, year, and season. Each row represents one nestbox monitored during one season (autumn or winter) of a given year.
Variables
- Country: Country where the nestbox is located (Finland, Sweden, Slovenia, Italy)
- BoxID: Unique identifier of the nestbox
- Year: Year of observation
- Season: Season of monitoring Aut = autumn; Win = winter
- N.nights.recorded: Number of nights recorded by the camera
- Owl.in.box: Presence of owl inside the nestbox 1 = owl present; 0 = owl absent
- Playback: Whether playback survey was conducted 1 = yes; 0 = no
- Box.active: Whether the nestbox territory was active 1 = active; 0 = inactive
- Temp.ave: Mean temperature during monitoring period (°C)
- Wind.speed.ave: Mean wind speed during monitoring period (m/s)
- Daylenght.ave: Mean daylight duration (hours)
- rain.ave: Mean rainfall (mm)
- Snow.depth.ave: Mean snow depth (cm)
- Census: Whether bird community census was performed 1 = yes; 0 = no
- N_pass: Number of passerines detected during census
- N_corv: Number of corvids detected during census
- N_thr: Number of thrushes detected during census
- N_wood: Number of woodpeckers detected during census
- N_drap: Number of diurnal raptors detected during census
- Perc_con: Percentage of surrounding coniferous forest
- Perc_dec: Percentage of surrounding deciduous forest
- Perc_mixed: Percentage of surrounding mixed forest
File: Breeding_season_correlation.csv
Description: This dataset contains nestbox occupancy information during the breeding season across different years. Each row represents one nestbox.
Variables
- Country: Country where the nestbox is located (Finland, Sweden, Slovenia, Italy)
- BoxID: Unique identifier of the nestbox
- Breeding_season 2022: Nestbox occupied during breeding season 2022 1 = occupied; 0 = not occupied
- Breeding_season 2023: Nestbox occupied during breeding season 2023 1 = occupied; 0 = not occupied
- Breeding_season 2024: Nestbox occupied during breeding season 2024 1 = occupied; 0 = not occupied
File: Onelinepicture.csv
Description: This dataset contains data at the individual camera-image level. Each row corresponds to one photograph taken by the camera trap.
Variables
- Country: Country where the nestbox is located (Finland, Sweden, Slovenia, Italy)
- BoxID: Unique identifier of the nestbox
- Date_time: Date and time when the image was recorded
- Owl.in.box: Presence of owl inside the nestbox in the image 1 = owl present; 0 = owl absent
Code/Software
All data processing, statistical analyses, and visualisation were conducted in R version 4.4.2 (R Core Team, 2024).
The following R packages were used in the workflow:
lme4, glmmTMB, glmm, car, carData, performance, FactoMineR, factoextra, dplyr, tidyr, ggplot2, ggeffects, gridExtra, patchwork, suncalc, lubridate, emmeans, nnet.
The code includes three main analytical workflows:
- Data processing and integration
Scripts were used to clean and merge the three datasets (Dataset_revision, Onelinepicture, and Breeding_season_correlation), including alignment of seasonal and yearly information, creation of derived variables (e.g., rainfall standardisation and light-period classification), and preparation of camera-trap image data for analysis. - Statistical analyses
- Principal Component Analysis (PCA) using FactoMineR to summarise variation in climate, habitat, and bird community variables among populations
- Generalised Linear Mixed Models (GLMMs) using glmmTMB to analyse nestbox use patterns and breeding-season occupancy relationships
- Binomial and multinomial models to assess temporal (seasonal and light-period) variation in nestbox use
- Model diagnostics and inference
Model assumptions and multicollinearity were assessed using the performance and car packages. Post-hoc comparisons were conducted using emmeans, and predicted values were extracted using ggeffects. Visualisations were produced with ggplot2 and patchwork.
The full R script used for analyses is included in the submission and documents the complete workflow from raw data processing to final figures and statistical models.
Access information
Other publicly accessible locations of the data:
- Forest cover variables (percentage of coniferous, deciduous, and mixed forest) were derived from the CORINE Land Cover dataset (European Environment Agency). Climate variables were obtained from publicly available meteorological sources and national/regional weather databases for each study country.
Data were derived from the following sources:
- CORINE Land Cover (European Environment Agency) – used to extract habitat composition (forest type percentages) around nestbox sites.
- National and regional meteorological data providers (Finland, Sweden, Slovenia, and Italy) – used to obtain temperature, precipitation, wind speed, snow depth, and daylight-related variables.