1. ABOUT THE DATASET ------------ Title: Datasets and R Code supporting results from 'New Citizen Science initiative reveals impact of climate on fruit tree blossom patterns in Great Britain' Creators: Chris Wyver (https://orcid.org/0000-0002-8661-0859) Organisation(s): Centre for Agri-Environmental Research, School of Agriculture, Policy and Development, University of Reading RG6 6AR Rights-holder(s): University of Reading Publication Year: 2023 Description: This dataset contains gridded temperature data for Great Britain and phenological recordings for the onset of blossom for four cultivars of fruit tree (Apple 'Bramley', Cherry 'Stella', Pear 'Conference', Plum 'Victoria'). Gridded temperature data was derived from the E-Obs database (https://cds.climate.copernicus.eu/cdsapp#!/dataset/insitu-gridded-observations-europe?tab=overview) and Phenology recordings were submitted to the FruitWatch project (www.fruitwatch.org) - Contact Chris Wyver (c.w.wyver@pgr.reading.ac.uk) for access to the full dataset, containing more cultivars and data for other years. Cite as: Wyver, C.(2023). Dataset and R Code supporting results from 'New Citizen Science initiative reveals impact of climate on fruit tree blossom patterns in Great Britain'. DOI: 10.17864/1947.000524 Related publication: Wyver, C., Potts, S.G., Pitts, R., Riley, M., Janetzko, G. and Senapathi, D. (2023). New Citizen Science initiative reveals impact of climate on fruit tree blossom patterns in Great Britain. Horticulture Research, In Prep. Contact: Chris Wyver, c.w.wyver@pgr.reading.ac.uk, 07887298390 2. TERMS OF USE ------------ Copyright 2023 University of Reading. This dataset is licensed under a Creative Commons Attribution 4.0 International Licence: https://creativecommons.org/licenses/by/4.0/. 3. PROJECT AND FUNDING INFORMATION ------------ Title: Mitigating risks to pollination services caused by climate change - PhD Project Dates: Sept 19 - Jan 24 Funding organisation: BBSRC via Waitrose Collaborative Training Partnership Grant no.: BB/T508895/1 WorldWide Fruit Ltd contributed to the funding and development of this project. 4. CONTENTS ------------ FruitWatch.csv - A .csv file containing blossom onset recordings submitted to the FruitWatch website (www.fruitwatch.org) in 2022. - 9 variables, 449 rows Variables: - Id: Unique identification number for each record. Numeric - Date: Date of phenological recording. Date. Format: DD/MM/YYYY - Latitude: Latitude of phenological recording. Numeric - Longitude: Longitude of phenological recording. Numeric - Month: Month of phenological recording. Numeric - Day: Day of the month of phenological recording. Numeric - Year: Year of phenological recording. Numeric - DoY: Day of Year (Jan 1st = 1, Jan 2nd = 2...) of phenological recording. Numeric - Variety: Variety of phenological recording. Numeric TempData.csv - A .csv file containing gridded daily maximum and minimum temperature values for Great Britain, from 01/01/2021 - 30/06/2023 - 11 variables, 2,836,854 rows Variables: - Id: Unique identification number for each record. Numeric - Date: Date of temperature recording. Date. Format: YYYY.MM.DD - x: Longitude of phenological recording. Numeric - y: Latitude of phenological recording. Numeric - Tmin: Daily minimum temperature. Degrees celsius - Tmax: Daily maximum temperature. Degrees celsius - Year: Grid Square & Year of phenological recording (e.g. grid square 1, in the year 2021 = 12021). Numeric - DoY: Day of Year (Jan 1st = 1, Jan 2nd = 2...) of phenological recording. Numeric - Month: Month of temperature recording. Numeric - Day: Day of the month of temperature recording. Numeric - ID: Grid square ID number of temperature recording. Numeric - Trange: Daily temperature range (Tmax - Tmin). Numeric 3. orchard_ids.csv - A .csv file containing Grid Square IDs containing orchards, extracted from raw data obtainable from the OS MasterMap (https://www.ordnancesurvey.co.uk/products) - 1 variable, 1930 rows - ID: ID of unique year and grid square combinations containing orchards in 2022 (e.g. grid square 1 = 12022, grid square 2 = 22022...) 4.PhenoFlexCode.R - R script used to produce the spatial analysis in the manuscript "New Citizen Science initiative reveals impact of climate on fruit tree blossom patterns in Great Britain". It contains details of data manipulation, Linear models to assess change in blossom date in relation to latitude, PhenoFlex modelling to parameterize blossom onset models, and blossom onset predictions for orchard locations in Great Britain for 2022. 5. METHODS ----------- Raw phenology submissions for four cultivars of fruit tree were used to parameterize blossom onset models, with performance of these models assessed using root-mean-square-Error and Mean Absolute Error. These models were then used to generate predictions of blossom dates for the four cultivars, for known orchard locations within 2022. 6. REFERENCES ------------ Wyver, C., Potts, S.G., Pitts, R., Riley, M., Janetzko, G. and Senapathi, D. (2023). New Citizen Science initiative reveals impact of climate on fruit tree blossom patterns in Great Britain. Horticulture Research, In Prep.