Quantifying long‐term phenological patterns of aerial insectivores roosting in the Great Lakes region using weather surveillance radar. Issue 5 (17th November 2022)

• Record Type: Journal Article
• Authors: Deng, Yuting; Belotti, Maria Carolina T. D.; Zhao, Wenlong; Cheng, Zezhou; Perez, Gustavo; Tielens, Elske; Simons, Victoria F.; Sheldon, Daniel R.; Maji, Subhransu; Kelly, Jeffrey F.; Horton, Kyle G.
• Is Part Of: Global change biology. Volume 29:Issue 5(2023)
• Page Start: 1407
• Page End: 1419
• Publication Date: 2022-11-17
• Subjects: aerial insectivore -- aeroecology -- birds -- machine learning -- migration -- NEXRAD -- phenology -- radar remote sensing -- roosts; Climatic changes -- Environmental aspects -- Periodicals; Troposphere -- Environmental aspects -- Periodicals; Biodiversity conservation -- Periodicals; Eutrophication -- Periodicals; 551.5
• DOI: 10.1111/gcb.16509
• Languages: English
• ISSNs: 1354-1013

Abstract

Abstract: Organisms have been shifting their timing of life history events (phenology) in response to changes in the emergence of resources induced by climate change. Yet understanding these patterns at large scales and across long time series is often challenging. Here we used the US weather surveillance radar network to collect data on the timing of communal swallow and martin roosts and evaluate the scale of phenological shifts and its potential association with temperature. The discrete morning departures of these aggregated aerial insectivores from ground‐based roosting locations are detected by radars around sunrise. For the first time, we applied a machine learning algorithm to automatically detect and track these large‐scale behaviors. We used 21 years of data from 12 weather surveillance radar stations in the Great Lakes region to quantify the phenology in roosting behavior of aerial insectivores at three spatial levels: local roost cluster, radar station, and across the Great Lakes region. We show that their peak roosting activity timing has advanced by 2.26 days per decade at the regional scale. Similar signals of advancement were found at the station scale, but not at the local roost cluster scale. Air temperature trends in the Great Lakes region during the active roosting period were predictive of later stages of roosting phenology trends (75% and 90% passage dates). Our study represents one of the longest‐term broad‐scale phenology examinations of avian aerial insectivore species responding to environmental change and provides a stepping stone for examining potential phenological mismatches across trophic levels at broad spatial scales. Abstract : Aerial insectivores are experiencing acute declines, making it critical to understand important phases of their annual cycle. The understudied pre‐migratory period, a phase where hundreds of thousands of individuals gather in roosts, offers a unique means to measure migration timing and changes therein under climate change. Using weather surveillance radar data from 12 stations around the Great Lakes region, we quantified the phenological patterns of roosting aerial insectivores over two decades. We found that peak and late roosting periods are shifting earlier and there is great within‐season synchrony among stations. Our study suggests that there is phenotypic flexibility in aerial insectivores responding to climate change.