DOI: 10.5061/dryad.31zcrjdrv
title: Data from: Multiple effects of weather on common waxbill group foraging and social behavior

description: The weather poses challenges for wildlife. Environmental challenges can be
 responded to at the group level by social animals, but the influence of
 weather on group behavior is poorly understood. We investigated how the
 weather affects behavior in a gregarious species by monitoring common
 waxbills (Estrilda astrild) in a large mesocosm during five years. We
 found seasonal patterns on collective foraging, aggressiveness, and the
 structure of the social network, usually showing two cycles per year: one
 peaking in Spring and a smaller one in late Summer. Controlling for
 seasonality, we found behavioral changes related to increased energy
 demands on colder and/or cloudier days, such as more frequent and larger
 foraging groups that resulted in less structured social networks. Rain and
 wind disturb movement, and we found that on rainy days foraging group
 journeys became briefer and more synchronous, resulting in stronger
 associations between individuals and less structured networks, and that on
 windy days foraging groups were less frequent, larger, and with more
 within-group aggression. The results show that the weather has more varied
 effects than anticipated on ecologically-relevant group behavior. We
 discuss how such weather-related effects can improve predictions of how
 social animals will react to environmental changes.
description: # Data from 'Multiple effects of weather on common waxbill group
 foraging and social behavior' (Beltrão et al. 2024, Behavioral
 Ecology). Created in June 2023 by Patrícia Beltrão
 ([pbsantospt@cibio.up.pt](mailto:pbsantospt@cibio.up.pt)). ## GENERAL
 INFORMATION 1. Title: Data from: Multiple effects of weather on common
 waxbill group foraging and social behavior 2. Authors: Patrícia Beltrão
 (1,2), Ana Cristina R. Gomes (1,2,3), Beatriz C. Saldanha (1,2), Fernando
 P. Lima (1,2) & Gonçalo C. Cardoso (1,2) (1) CIBIO, Centro de
 Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório
 Associado, Campus de Vairão, Universidade do Porto, 4485-661 Vairão,
 Portugal (2) BIOPOLIS Program in Genomics, Biodiversity and Land Planning,
 CIBIO, Campus de Vairão, 4485-661 Vairão, Portugal (3) Department of
 Zoology, Stockholm University, Stockholm, Sweden 3. Data collection: 2018
 - 2022 4. Funding sources: Fundação para a Ciência e a Tecnologia
 (PTDC/BIAECO/32210/2017, DL57/2016/CP1440/CT0011, SFRH/BD/129002/2017,
 SFRH/BD/148392/2019). 5. Citation for this dataset: Beltrão, Gomes,
 Saldanha, Lima & Cardoso (2023), Data from: Multiple effects of
 weather on common waxbill group foraging and social behavior, Dryad,
 Dataset ## FILE OVERVIEW 1. Description of datasets Datasets for the
 behavioral and weather metrics used in the research article. 2. File List:
 File: ‘data.RData’ Description: Contains 3 data frames with behavioral and
 weather data. ### METHODOLOGICAL INFORMATION Behavioral data was collected
 through a radio-frequency identification (RFID) system (Dorset ID, The
 Netherlands) that monitored the attendance of common waxbills in feeders
 and perches with RFID antennae. All birds had a passive integrated
 transponder (PIT) tag. Aggressive displacements were computed with the
 function available in Beltrão et al. 2021 (doi:
 10.1016/j.anbehav.2021.09.011) ### INFORMATION FOR: ‘data.RData’ The file
 has three data frames: (1) daily_response_var, (2) weekly_response_var,
 and (3) climatic_predictors. `daily_response_var` Description: Date and
 response variables computed per day * Total time all birds spent at the
 feeders, in seconds, divided by the number of individuals recorded in the
 RFID system; * Number of foraging groups; * Mean duration of foraging
 groups, in minutes; * Mean size of foraging groups; * Aggressiveness -
 number of aggressive displacements by each individual, divided by the
 total time it spent at the feeders, in minutes, averaged across the
 population ). `weekly_response_var` Description: Week of the year and
 response variables computed per week * Mean strength of associations; *
 Coefficient of variation of the strengths of associations; * Network
 entropy; * Steepness of dominance hierarchy (repeatability of the
 randomized Elo-ratings). `weather_predictors` Description: Date and
 weather predictors * Temperature (ºC); * Cloud Cover (%); * Precipitation
 (kg/m2); * Wind speed (m/s); * Relative Humidity (%).