Abstract/Summary

Accurately predicting flowering phenology in fruit tree orchards is crucial for timely pest and pathogen treatments and for the introduction of managed pollinators. Making predictions requires large datasets of flowering dates, which are often limited to single locations. Consequently, resulting phenology predictions are not representative across larger geographic areas. Citizen science may offer a solution to this data gap, with millions of biological records across a wide range of taxa recorded annually. Here, a new citizen science platform called “FruitWatch” is introduced, monitoring flowering dates of fruit trees in Great Britain. The objectives of this study are to assess the suitability of FruitWatch submissions to 1) detect latitudinal variation in flowering onset dates, 2) parameterize existing phenology modelling frameworks, and 3) make predictions of flowering onset dates across Great Britain for a single year. Using data for four cultivars from 2022, linear models reveal significant latitudinal delays in flowering onset of as much as 1.49±0.63 days per degree latitude further north (Pear ‘Conference’), with significant delays also seen in Cherry ‘Stella’ (1.39±0.48 days) and Plum ‘Victoria’ (1.22±0.18 days). FruitWatch informed phenology modelling frameworks performed well for predicting flowering onset, with root-mean-square Error values of predictions from validation datasets ranging between 4.6 (‘Victoria’) and 8.0 (‘Conference’) days. The parameterized models also provided realistic flowering onset predictions across Great Britain in 2022, with earlier flowering dates predicted in warmer areas. These findings demonstrate the potential of citizen science data to offer growers cultivar- and location-specific phenology predictions to help inform orchard management.