Shifting Seasons: Long-Term Insights Into Climate Change Effects on Bird Phenology From Ringing Data.

Understanding how animal communities respond to environmental change is crucial for predicting biodiversity trends. Birds, particularly migratory species and those experiencing large-scale declines, are sensitive to shifting climatic conditions. Environmental stressors have been linked to earlier migration timing, which can alter species abundance and disrupt ecological interactions. Long-term population monitoring provides essential insights into species' capacity to adapt to climate change, offering a predictive framework for assessing their future viability. We analyse a 25-year bird ringing dataset from Spurn Bird Observatory located at a notable migratory bird hotspot in the UK. We show that climate factors, especially temperature, are significantly changing and consequently impact migrant bird arrival times. We also show that different species' abundances are changing over time and make a weak but notable association between these trends with climate change. When species are analysed in isolation, it is clear there are other potential contributing factors which may explain variation in abundance at Spurn over the years-to fully understand these changes, species must be studied in an ecological context, including multi-species analyses. We take care to control for catching effort in our analyses, as we find that this directly correlates with both abundance and diversity of species caught, which demonstrates the importance of year-round standardised ringing coverage at UK biodiversity hotspots. As such, we suggest caution when using ringing data to make ecological interpretations. While citizen science ringing data has limitations that restrict its use for elucidating mechanisms of species-level patterns, it remains a vital tool for informing conservation. Our study highlights the value of sustained ecological datasets in tracking these dynamics and informing conservation strategies across taxa for habitat and landscape-level management.