DOI: 10.5061/dryad.x69p8czgr
title: Social partners and temperature jointly affect morning foraging activity of small birds in winter

description: Daily foraging activity of small wintering birds is classically thought to
 be driven by the need to gather enough energy reserves to survive each
 night. A separate line of research has shown that sociality is a major
 driver in winter foraging activities in many species. Here, we use
 wintering birds as a study system to move towards an integrative
 understanding of the influence of energy requirements and sociality on
 foraging ecology. We used RFID-enabled feeders in Lincoln, Nebraska, USA
 in January-March 2019 to measure foraging activity in two species (downy
 woodpecker, Picoides pubescens, and white-breasted nuthatches, Sitta
 carolinensis). We analyzed the relationship between overnight temperature
 and morning foraging activity and found that lowest overnight temperature
 was negatively correlated with morning visitation at feeders. We then used
 a network approach to ask if flock associations explain similarity in
 birds’ foraging activity. In both species, individuals with stronger
 associations in a social network were more likely to share similar feeder
 activity, and an index of social partners’ activity explained foraging
 activity better than overnight temperature. This brings forth new
 questions about the interplay between individual response to temperature
 and social factors in shaping how small animals cope with harsh winter
 conditions.
description: The dataset was collected
 in three parts: 1) measurements and band numbers recorded during banding
 efforts, 2) a time series of visits detected at bird feeders and 3)
 weather measurements collected by a nearby weather station. The following
 is a revised, condensed version of the data collection methods reported in
 the manuscript.  We caught songbirds using mist
 nets near bird feeders in Lincoln, Nebraska, USA. We banded all captured
 birds with aluminum leg bands distributed by the United States Fish and
 Wildlife Services (USFWS) and we placed RFID leg bands (Eccel Technology,
 Leicester UK) on downy woodpeckers (n=18) and white-breasted nuthatches
 (n=13). Birds were sexed by plumage and other morphological measurements
 were taken, including weight, culmen length, tarsus length, and wing
 length. Next, we
 distributed 8 RFID feeders of uniform design over an area of approximately
 150,866 m<sup>2</sup>, with a mean distance of approximately
 287 m between feeders. Feeders were hung from trees and spaced as evenly
 as possible (i.e., given availability of suitable trees) to maximize
 coverage of the field site. Each feeder (New Generation(R) 23 inch feeder:
 Droll Yankee, Plainfield, CT) was equipped with an IBT EM4102 data logger
 board (Eccel Technology, Leicester, UK) to record RFID tag, date, and time
 when a bird visited the feeder. Data loggers were programmed to scan for
 RFID tags every ¼ second from 6:30 am-8:00 pm. We observed that the
 feeders could detect birds more than once during a single visit, therefore
 we condensed these data into discrete visits using an empirical cumulative
 distribution function. After 2 seconds, the density distribution of time
 delays exponentially decreased and we found it reasonable to accept that
 any detection of the same bird within 2 seconds was likely to be part of
 the same feeder visit. For a given bird, we collapsed consecutive
 detections ≤ 2 seconds apart into a single visit at the time of the first
 detection. These data are included as a master data file
 ("all_visits.dat") and were further transformed into the
 included data subsets for various analyses, as explained in the ReadMe
 text file.  Last,
 we collected weather data from the Lincoln Municipal Airport
 (approximately 8.4 km from the study site) weather station through the
 Weather Underground website (https://www.wunderground.com/history,
 accessed 11 April 2019). We selected the lowest overnight temperature from
 this dataset to include in temperature response analyses. 
description: There are 16 files in all, including code scripts, data files,
 spreadsheet files, and a ReadMe file. We have included descriptions of
 the data files in the ReadMe file, and code scripts are annotated to allow
 navigation to re-create our analyses. The code scripts were written either
 for program R or Matlab, as explained in the ReadMe file.