Data files associated with the paper titled: "Citizen science data reveals climate warming is leading to earlier and shorter flight periods of the Dark Edged Bee-fly"

The two data files available here are associated with the paper titled: "Citizen science data reveals climate warming is leading to earlier and shorter flight periods of the Dark Edged Bee-fly" published in the Royal Entomological Society (RES) journal 'Insect Conservation and Diversity'. Understanding impacts of climate change on insects is hindered by a lack of long-term monitoring data for most species. Citizen science occurrence records provide opportunities to examine changes in timing of life cycle events (phenology), even for relatively poorly sampled taxon groups. Here we developed a workflow to examine the effects of climate change on insect phenology using occurrence records and tested it for the Dark Edged Bee-fly, Bombylius major Linnaeus 1758, in Britain. We extracted citizen science observations (dates, locations and associated metadata) from iRecord https://irecord.org.uk/ and iNaturalist https://www.inaturalist.org/ of the Dark-edged Bee-fly Bombylius major. Quantile regression was used to investigate changes in the phenology (emergence and senescence dates) and flight period of the fly in Britain. Phenology changes were characterised by changes in quantiles of calendar day of observation over the study period 1984 to 2024. Two datasets were prepared, as follows: A .csv file ('bm_phen_clim_dat3.csv') consisting of 30,423 rows (column titles are in the first row) where each row contains information about a unique observation of B. major, and 47 columns of metadata (variables) associated with each observation (details of the variables are given in the README file). This file contains the data that was analysed. A .csv file ('mod_v_ob1.csv') consisting of 40 rows (column titles are in the first row) of model results for visualisation with five columns as variables (details of the variables are given in the README file). This file contains model results that were visualised.