4.6 Article

Climate effects on the onset of flowering in the United Kingdom

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ENVIRONMENTAL SCIENCES EUROPE
卷 31, 期 1, 页码 -

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SPRINGEROPEN
DOI: 10.1186/s12302-019-0271-4

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Bluebell; Citizen science; Climate change; Coltsfoot; Cuckooflower; Garlic mustard; Plant phenology; Wood anemone

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Background A warmer climate has consequences for the timing of phenological events, as temperature is a key factor controlling plant development and flowering. In this study, we analyse the effects of the long-term climate change and an extreme weather event on the first flowering day (FFD) of five spring-flowering wild plant species in the United Kingdom. Citizen science data from the UK Woodland Trust were obtained for five species: Tussilago farfara (coltsfoot), Anemone nemorosa (wood anemone), Hyacinthoides non-scripta (bluebell), Cardamine pratensis (cuckooflower) and Alliaria petiolate (garlic mustard). Results Out of the 351 site-specific time series (>= 15-years of FFD records), 74.6% showed significant negative response rates, i.e. earlier flowering in warmer years, ranging from - 5.6 to - 7.7 days degrees C-1. 23.7% of the series had non-significant negative response rates, and 1.7% had non-significant positive response rates. For cuckooflower, the response rate was increasingly more negative with decreasing latitudes. The winter of 2007 reflects an extreme weather event, about 2 degrees C warmer compared to 2006, where the 2006 winter temperatures were similar to the 1961-1990 baseline average. The FFD of each species was compared between 2006 and 2007. The results showed that the mean FFD of all species significantly advanced between 13 and 18 days during the extreme warmer winter of 2007, confirming that FFD is affected by temperature. Conclusion Given that all species in the study significantly respond to ambient near-surface temperatures, they are suitable as climate-change indicators. However, the responses to a + 2 degrees C warmer winter were both more and less pronounced than expected from an analysis of >= 15-year time series. This may reflect non-linear responses, species-specific thresholds and cumulative temperature effects. It also indicates that knowledge on extreme weather events is needed for detailed projections of potential climate change effects.

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