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            <gco:CharacterString>To estimate the timing of activity and levels of activity in free-living birds, we used radio telemetry technology. Using mistnets, we caught, individually marked with a metal ring and radio tagged (details below) individuals of six passerine species (European robin, Eurasian blackbird, great tit, blue tit, dunnock, common chaffinch). They were caught during February-April (hereafter ‘pre-breeding phase’) and September-November (hereafter ‘post-breeding phase’) in 2020 and 2021 in two urban and two non-urban (forest) locations. The urban sites were located within the boundaries of Glasgow city (Kelvingrove Park and Garscube Campus). The non-urban forest sites were located in the surroundings of the Scottish Centre for Ecology and the Environment (‘SCENE’), approximately 45 kilometres north of Glasgow, on the eastern shore of Loch Lomond (SCENE and Sallochy forest). At the end of each year, the data collected during that year were checked and uploaded on a central database. In each site, we installed two to four automatic radio receivers which were set to scan each tag every 180 seconds. Whenever a tag was detected, the receiver recorded a date and time stamp, and the radio signal strength (dB). The raw data from the receivers was processed and analysed in R. The radio telemetry system generated a 3-min interval time series of radio detections per bird (i.e., tag) and per receiver. We calculated the absolute difference in radio signal strength between consecutive time intervals (hereafter termed ‘signal differential’) per receiver and per bird. We then averaged this value across the receivers per site. We estimated daily onset and end of activity assuming that variation in signal differentials is low during inactive phases and high during times of bird activity. We then seek to identify the point of clearest change between the active and inactive state. We applied several quality control steps and used the agreement in estimates of daily onset and end of activity between two employed methods to assess the quality of our dataset for downstream analysis. We used fixed time windows to quantify activity levels to avoid biases introduced by seasonal changes in day length and individual times of onset and end of activity.</gco:CharacterString>
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