Data from: Bumble bees are the most efficient pollinators of raspberry and strawberry in urban environments

This dataset contains data collected for a study of pollinator efficiency in the region of Paris (France), using strawberry (Fragaria x ananassa) and raspberry (Rubus ideus) as model plants. We made sure that each flower considered in the study was visited once by a pollinator which we assigned to a morphogroup category. We then measured fruit traits (mass, seed set and malformation) following these single visit trials and compared the performance among the different morphogroup categories. There are 6 datasets, each dedicated to a fruit trait for either strawberry or raspberry. Each row is an individual fruit. They all contain a variable specifying the individual fruit ID (Fruit_ID, factor variable), the experimental site at which the flower was visited (Site, factor variable, one of: IRD, CHEV, PHARMA, FONT, JDP, CEREEP), the habitat type (Habitat, factor variable, one of: Urban, Rural). In the datasets for strawberry, there is a variable specifying the year and season (Seasonality, factor variable, one of: spring.2023, autumn.2023, spring.2024, autumn.2024). In the data for raspberry, there is a variable specifying year (Year, factor variable, one of: 2023, 2024). The 6 datasets are presented below: Strawberry_mass (68 rows): In addition to the variables described above, this dataset has a variable giving the mass of individual strawberries, measured in g (Mass_g, continuous numerical variable). Strawberry_malformation (59 rows): In addition to the variables described above, this dataset has a variable describing whether each strawberry was well-formed (value of 0) or whether it showed severe malformations (value of 1) (Malformation, binary variable). Starwberry_seeds (68 rows): In addition to the variables described above, this dataset has a variable giving the seed set of each strawberry (Seed_set, discrete numerical variable). Raspberry_mass (97 rows): In addition to the variables described above, this dataset has a variable giving the mass of individual raspberries, measured in g (Mass_g, continuous numerical variable). Raspberry_malformation (64 rows): In addition to the variables described above, this dataset has a variable describing whether each raspberry was well-formed (value of 0) or whether it showed severe malformations (value of 1) (Malformation, binary variable). Raspberry_seeds (119 rows): In addition to the variables described above, this dataset has a variable giving the seed set of each raspberry (Seed_set, discrete numerical variable).