DOI: 10.5061/dryad.t76hdr8cg
title: Phenological turnover matters when making trait-based predictions of plant-pollinator interactions

description: Understanding the processes determining species’ interactions is key to
 predicting and safeguarding ecological networks under rapid environmental
 change. One approach to estimating interactions is to use morphologies of
 taxa interacting across trophic levels to reveal suites of traits they are
 more likely to interact with (i.e. a morphological trait
 niche). Previous work studying these morphological trait niches
 has typically used interactions between species that are pooled in space
 and time. However, species assemblages, and the traits of individuals
 within species, can change across even small landscapes over a season,
 leading to morphological trait space being dynamically reshaped.
 Therefore, it is unclear how morphological trait turnover affects our
 inferences of trait niches, and our ability to answer this is in part
 limited by a lack of individual-level trait data. Here, we
 directly address this by studying a montane Arctic plant-pollinator
 community over five growing seasons (&gt;1,300 hours of fieldwork).
 Specifically, we linked every recorded plant-bumblebee interaction with
 the traits of the bee individual involved (n = 1,150), to investigate 1)
 whether plant taxa (n = 10) exhibited bee trait niches by interacting with
 specific regions of multidimensional trait space of visiting bumblebees,
 and 2) how our inference of these trait niches was affected by considering
 bumblebee trait turnover and plant taxon turnover over space and
 time. When we did not consider turnover (i.e., interactions in
 space and time were pooled), plant taxa demonstrated bee trait niches.
 However, we next considered how bee trait space was reshaped over the
 elevational and seasonal gradient (for example, with the emergence of
 different castes), and how this reshaping co-occurred with different
 spatiotemporal ranges of the plant taxa. From this, we found plant taxa no
 longer interacted with a smaller area of bee community trait space than
 expected by chance (i.e. no longer showed a bee trait niche), and that
 seasonal reshaping of bee trait space was the primary driver of this
 trend. Overall, in highly dynamic systems, like the Arctic, overlooking
 community turnover could mask and even overestimate the ability of
 morphology to explain interactions. Hence, determining how morphological
 traits of individual interaction partners are in phenological synchrony at
 localised scales will be fundamental to understanding the role morphology
 plays in underpinning plant-pollinator interactions.
description: # Phenological turnover matters when making trait-based predictions of
 plant-pollinator interactions Dataset DOI:
 [10.5061/dryad.t76hdr8cg](10.5061/dryad.t76hdr8cg) ## Description of the
 data and file structure The data are composed of three files:
 - Working_spreadsheet_ITV_1819212223_v2.xlsx – These data were collected
 from observations of plant-bumblebee interactions on Mt. Nuolja in Sweden
 in 2018, 2019, 2021, 2022, and 2023. Each bee that was caught was
 photographed in the field, and from these photos, trait measurements were
 made. These measurements are also present in the dataset, in both raw and
 scaled forms, and then when summarized into PCA axes.
 - Different_phenology_ranges_using_phenology_data.csv – These were
 collected by the Nuolja phenology project, in which phenophases of the
 plant community are recorded along a 3.4 km transect. The data in this
 file represent the onset and end of flowering (in day of year) each year.
 - Different_elevation_ranges_using_phenology_data.csv – These were
 collected by the Nuolja phenology project, in which phenophases of the
 plant community are recorded along a 3.4 km transect. The data in this
 file represent the ranges that each species was detected along the
 transect. The values represent the sub-transects present (spaced 45 m
 apart). ### Files and variables #### File:
 Different_elevation_ranges_using_phenology_data.csv ##### Variables *
 Year: The year the data were collected. - Species: The plant taxon for
 which the data were collected. * Yr_sp: This is a combination of the year
 the data were collected, and the plant taxon that the data corresponds to.
 - Min_elevation_all: This is the lowest pole (corresponding to lowest
 elevation) on the transect for which this taxon was observed flowering
 that year. - Max_elevation_all: This is the highest pole (corresponding to
 highest elevation) on the transect for which this taxon was observed
 flowering that year. - Min_elevation_595: This is the lowest pole
 (corresponding to lowest elevation) on the transect for which this taxon
 was observed flowering that year. However, this value was attained after
 removing the first and last 5% of data points (to avoid outliers affecting
 the elevational range of each plant taxon). - Max_elevation_595: This is
 the highest pole (corresponding to highest elevation) on the transect for
 which this taxon was observed flowering that year. However, this value was
 attained after removing the first and last 5% of data points (to avoid
 outliers affecting the elevational range of each plant taxon). #### File:
 Different_phenology_ranges_using_phenology_data.csv ##### Variables *
 Year: The year the data were collected. - Species: The plant taxon for
 which the data were collected. * Yr_sp: This is a combination of the year
 the data were collected and the plant taxon that the data corresponds to.
 * Earliest_flowering_all: This is the earliest day of the year that the
 taxon was observed flowering on the transect that year. *
 Latest_flowering_all: The latest day of the year that the taxon was
 observed flowering on the transect that year. * Earliest_flowering_595:
 This is the earliest day of the year that the taxon was observed flowering
 on the transect that year. However, this value was attained after removing
 the first and last 5% of data points (to avoid outliers affecting the
 phenological range of each plant taxon). * Latest_flowering_595: The
 latest day of the year that the taxon was observed flowering on the
 transect that year. However, this value was attained after removing the
 first and last 5% of data points (to avoid outliers affecting the
 phenological range of each plant taxon). #### File:
 Working_spreadsheet_ITV_1819212223_v2.xlsx ##### Variables * Sample_No: A
 unique identifier for each bee in the dataset. * Year: The year the data
 was collected. * Date: The date on which the survey of bee-plant
 interactions occurred. * DOY: The day of year (derived from the date) on
 which the survey of bee-plant interactions occurred. * Month: The month
 during which the survey of bee-plant interactions occurred. *
 Sub_Transect: The survey plot along Mt. Nuolja in Sweden, in which we
 conducted bumblebee observations. The values are (from lowest to highest
 elevation plots): 04-05, 09-10, 21-22, 25-26, 29-30, 32-33, 35-36, 41-42,
 45-46, 47-48, 60-61, 65-66, and 73-74. * Sub_Transect_numbered: This
 numbers the "Sub-Transect" in order from lowest to highest
 elevation, i.e., 04-05 is 1, and 73-74 is 13. * Vegetation_Zone: This
 identifies the vegetation zone on Mt. Nuolja in which the survey plot is
 situated. Vegetation zone A corresponds to old birch forest and contains
 survey plots 04-05, 09-10, and 21-22. Zone B is a young, newly established
 birch forest, containing survey plots 25-26 and 29-30. Zone C is shrub
 willow, containing plots 32-33, 35-36, and 41-42. Zone D is an herbaceous
 meadow, containing plots 45-46 and 47-48. Finally, zone E is Arctic dwarf
 shrub and heath, containing plots 60-61, 65-66, and 73-74. * Altitude: The
 elevation of the survey plots in meters above sea level. *
 Activity_Flying_Foraging: During a survey, if we saw a bumblebee, we noted
 if it was flying or foraging. N.B. This dataset has been filtered to only
 include foraging bees. * Catch_Y_N: During a survey, if we say a
 bumblebee, we would try to catch it, to photograph for trait measurements.
 We would note down if the bee was successfully caught (Y = yes, N = no).
 N.B. This dataset has been filtered to only include bees that we caught. *
 Bombus_Species: The species identity of the bumblebee, based on
 morphological identification. * Bombus_Species_Certainty: Bumblebee
 species identifications were given a confidence score (1 = not confident,
 3 = confident). N.B. This dataset has been filtered to only include bees
 that we identified with a confidence score of 2 or greater. *
 Caste_Assigned_CT: The caste of the bumblebee. * Head_width_mm: The head
 width (i.e., the largest distance between distal surfaces of the eyes
 measured dorsally) of the bumblebee, measured from a photograph (in mm). *
 ITD_mm: The intertegular distance of the bumblebee, measured from a
 photograph (in mm). * Wing_length_mm: The wing length (i.e., the maximal
 distance between one forewing attachment point and the most distal point
 on that corresponding wing’s marginal cell) of the bumblebee, measured
 from a photograph (in mm). * Corrected_Flower_Species_ID2: The plant taxon
 that we observed the bumblebee interacting with. * Social_parasitic:
 Whether the bumblebee species is known to be parasitic (e.g. *Bombus
 flavidus*). * Estimated_prementum_length_mm: The predicted prementum
 length of the bumblebee, estimated using a mixed-effects model, with their
 intertegular distance, species identity and caste as predictor variables.
 * Species_caste: A variable combining bee species identity and caste. *
 Tongue_scaled: Bumblebee prementum length after it has been centred and
 scaled (mean = 0, sd = 1). * Head_scaled: Bumblebee head width after it
 has been centred and scaled (mean = 0, sd = 1). * Wing_scaled: Bumblebee
 wing length after it has been centred and scaled (mean = 0, sd = 1). *
 ITD_scaled: Bumblebee intertegular distance after it has been centred and
 scaled (mean = 0, sd = 1). * Species_Caste: A variable combining bee
 species identity and caste. * pca_axis1: The first PC axis after
 performing a PCA on the scaled bee trait measurements (i.e., columns:
 Tongue_scaled, Head_scaled, Wing_scaled, and ITD_scaled). * pca_axis2: The
 second PC axis after performing a PCA on the scaled bee trait measurements
 (i.e., columns: Tongue_scaled, Head_scaled, Wing_scaled, and ITD_scaled).
 * pca_axis3: The third PC axis after performing a PCA on the scaled bee
 trait measurements (i.e., columns: Tongue_scaled, Head_scaled,
 Wing_scaled, and ITD_scaled). * pca_axis4: The fourth PC axis after
 performing a PCA on the scaled bee trait measurements (i.e., columns:
 Tongue_scaled, Head_scaled, Wing_scaled, and ITD_scaled). * SD2_outliers:
 This column indicates whether any of the trait measurements for that bee
 were greater than two standard deviations away from the mean of the trait
 for the species & caste of that bee. Y = bee has traits greater than
 two standard deviations from the mean. * SD3_outliers: This column
 indicates whether any of the trait measurements for that bee were greater
 than three standard deviations away from the mean of the trait for the
 species & caste of that bee. N.B. Bees with traits greater than three
 standard deviations have been filtered out from this dataset. ##
 Code/software These files can be opened with MS Excel.