DOI: 10.5061/dryad.x0k6djhtd
title: Data from: Early spring-flowering winter cover crop (<em>Camelina sativa</em>) increases insect flower visits in Wisconsin (USA)

description: The expansion and intensification of agriculture in the last century have
 reduced floral resources for wild insect pollinators, contributing to
 their decline and potentially lowering pollination services for crop
 production. Flowering cover crops that can overwinter in harsh climates,
 such as winter camelina (Camelina sativa [L.] Crantz), can provide key
 resources for spring-emerging insects and fit into forage cropping systems
 in the Upper Midwest region of the United States, where corn silage
 production is an important source of dairy forage. However, the amount of
 floral cover and length of time that cover is available, as well as the
 practicality of integrating camelina in annual forage cropping systems,
 depends on fall planting time and cover crop mix. We performed a
 plot-scale, randomized block experiment to measure spring floral cover and
 insect flower visitation of winter camelina and uncultivated flowers. This
 experiment occurred across 2 years in 3 cover crop mixes: 1) camelina
 monoculture, 2) camelina, triticale, hairy vetch mix, and 3) camelina,
 cereal rye, hairy vetch mix. In the second year, 3 camelina monocultures
 were planted at three different fall planting times, which constituted
 additional treatments: 4) early, 5) mid, and 6) late. We included an
 unseeded fallow treatment, i.e., no cover crop, for comparison. Cover crop
 mixes and camelina in monoculture planted simultaneously (all mid-fall
 plantings) provided equal amounts of floral cover and supported comparable
 insect visitation rates the following spring. For monocultures, camelina
 planted earlier in the fall had the highest spring floral cover, and the
 latest planting time provided virtually no flower cover. Despite the large
 proportion of total floral cover attributed to dandelion in many plots,
 flower visitation exclusively increased with increasing camelina floral
 cover. However, there is an upper asymptote at which adding more camelina
 does not further increase visitation. Our study demonstrates that winter
 camelina can provide abundant resources for insects in early spring when
 planted in a monoculture or mix the previous September as compared to
 winter fallow, though the period of flowering is short. We also show that
 although dandelion may provide floral cover early in the growing season,
 camelina may be more attractive to insects and provide an important spring
 floral resource.
description: See <em>"Flowering Cover Crops to Support Wild
 Pollinators in Annual Cropping Systems in Wisconsin"</em>
 University of Wisconsin – Madison, Minds @ UW (http://digital.library.wisc.edu/1793/85284) for detailed methods.
description: # Data from: Early spring-flowering winter cover crop (*Camelina sativa*)
 increases wild pollinator activity in Wisconsin (USA)
 [https://doi.org/10.5061/dryad.x0k6djhtd](https://doi.org/10.5061/dryad.x0k6djhtd) This dataset contains the number of flower visits per 5-minute survey and 3 measurements used to calculate floral cover for camelina (*Camelina sativa*) and uncultivated plants such as dandelion (*Taraxacum officianale*) from a randomized block experiment at the USDA ARS Dairy Forage Research Center farm in Wisconsin in 2022 and 2023. The objective of the experiment was to understand how different winter cover crop mixes and fall planting dates impact early spring floral cover of camelina and subsequent flower visitation from insect pollinators. ## Description of the data and file structure ### Floral_Count.csv: This file contains the number of open flowers per flowering plant and the % of open florets (reported as a number category) for 10 flowers per 0.5 m^2^ quadrat for 3 quadrats in each plot on each sampling date in 2022 and 2023. * *year*: year that the observation was recorded. * *date*: date in month/date/year format for when the observation was recorded. * *week*: unique data collection event for that year (there were 2 dates in 2022 and 5 in 2023) * *GDD.YTD*: growing degree day for that year to date. * *plot.num*: unique identifier for each plot within a year where observations were recorded. * *block*: the section that a given plot was in (the first number of the plot.num also correspponds to this, there were 4 blocks in 2022 and 5 in 2023) * *treatment*: the cover crop planting treatment for the given plot. * *treatment.type*: either "experiment" or "reference" to account for additional reference plots added in 2023 to compare with experimental data. * *quadrat*: the sub sample taken from the plot for the given observation. * *flowering.plant*: common English and American name for the plant that was recorded in that observation. Category "none" signifies that there were no flowering plants in the quadrat during recording. * *flower.type*: categorical variable to describe if the plant observed was a weed or was intentionally planted (cover crop). Variable is NA if flowering.plant category was "none". * *number.inflor*: the number of inflorescences (flowers) counted for the given plant in te given quadrat. Variable is 0 if flowering.plant category was "none". * *inflor*: identifier for a unique inflorescence (up to 10). Variable is NA if flowering.plant category was "none". Variable is NA if flowering.plant category was "none". * *percent.openflorets.cat*: categorical variable to describe the percentage of florets on the florescence that were open at the time of observation. * *Recorder*: name of the individual(s) who recorded the observations. * *Notes*: notes to contextualize observations (not needed for analysis). ### Open_Floret_Cats.csv: This file contains the numbers given to categories used to record the % of open florets on a given flower, and the corresponding percentage ranges and average percentages for each category. * *percent.openflorets.cat*: categorical variable to describe the percentage of florets on the florescence that were open at the time of observation. * *percent.cat*: categorical variable describing the range of percentages in the open florets category. * *avg.open*: the average percentage for the range in each percentage category. ### Floral_Area.csv: This file contains the diameter (in cm) of 10 terminal flowers per flowering species per plot for all sampling dates. * *year*: year that the observation was recorded. * *date*: date in month/date/year format for when the observation was recorded. * *week*: unique data collection event for that year (there were 2 dates in 2022 and 5 in 2023) * *plot.num*: unique identifier for each plot within a year where observations were recorded. * *block*: the section that a given plot was in (the first number of the plot.num also correspponds to this, there were 4 blocks in 2022 and 5 in 2023). Value is NA for reference plots, which were not in a block. * *treatment*: the cover crop planting treatment for the given plot. * *treatment.type*: either "experiment" or "reference" to account for additional reference plots added in 2023 to compare with experimental data. * *flowering.plant*: common English and American name for the plant that was recorded in that observation. * *flower.type*: categorical variable to describe if the plant observed was a weed or was intentionally planted (cover crop). * *length.cm*: the diameter (in centimeters) of the given inflorescence. * *width.cm*: the perpendicular diameter (in centimeters) of the given inflorescence, if the florescence was not round (uncommon). Value is NA for observations where the width did not need to be measured based on the shape of the flower. * *recorder*: name of the individual(s) who recorded the observations. * *notes*: notes to contextualize observations (not needed for analysis). ### Avg_area_calculation.csv: * *treatment*: the cover crop planting treatment for the given plot. * *date*: date in month/date/year format for when the observation was recorded. * *avg_area*: the calculated area for the given flowering plant (in centimeters), calculated by taking a weighted average recorded on the previous and the subsequent recording dates (for dates that were next to each other, the same average area was used, see notes column). * *flowering.plant*: common English and American name for the plant that was recorded in that observation. * *notes*: notes to contextualize observations (not needed for analysis) ### Treatments.csv: This file contains the plot numbers and corresponding treatments for 2022 and 2023. * *year*: year that the observation was recorded. * *plot.num*: unique identifier for each plot within a year where observations were recorded. * *unique.plot*: unique identifier for all plots across both years. * *treatment*: the cover crop planting treatment for the given plot. Visitation_Raw.csv: This file contains the raw flower visitation data in units of visits per 5 minute survey. * *year*: year that the observation was recorded. * *date*: date in month/date/year format for when the observation was recorded. * *week*: unique data collection event for that year (there were 2 dates in 2022 and 5 in 2023) * *plot.num*: unique identifier for each plot within a year where observations were recorded. * *block*: the section that a given plot was in (the first number of the plot.num also correspponds to this, there were 4 blocks in 2022 and 5 in 2023) * *treatment*: the cover crop planting treatment for the given plot. * *treatment.type*: either "experiment" or "reference" to account for additional reference plots added in 2023 to compare with experimental data. * *flowering.plant*: common English and American name for the plant that was recorded in that observation. * *flower.type*: categorical variable to describe if the plant observed was a weed or was intentionally planted (cover crop). * *non.bees*: number of non bee insect visits to flowers during 5 minute survey. Value is NA when flowering.plant is "none" because there were no flowers to observe visits to. * *small.dark*: number of small dark bee visits to flowers during survey. Value is NA when flowering.plant is "none". * *large.dark*: number of large dark bee visits to flowers during survey. Value is NA when flowering.plant is "none". * *greenbees*: number of green bee visits to flowers during survey. Value is NA when flowering.plant is "none". * *honeybees*: number of honey bee visits to flowers during survey. Value is NA when flowering.plant is "none". * *bumblebees*: number of bumble bee visits to flowers during survey. Value is NA when flowering.plant is "none". * *recorder*: name of the individual(s) who recorded the observations. * *notes*: notes to contextualize observations (not needed for analysis). * *total_visits*: sum of all visit values from non.bees, small.dark, large.dark, honeybees, and bumblebees columns. Pollinator_Voucher.csv: This file contains identification to genus and morphospecies for all pollinators collected. Some cells are blank because we did not have the information for the given specimen or did not record it. * *year*: year that the observation was recorded. * *collection date*: date in month/date/year format for when the observation was recorded. * *collector*: name of the individual(s) who collected specimen. * *site*: section of research site where specimens were collected from. * *caught on*: English and American common name for flowering plant that the insect was collected from (if applicable). * *sexing character*: antatomical strucutre that was ued to determine the sex of the specimen. * *sex*: biological sex of the specimen. * *morphogroup*: insect morphogroup for the specimen (non bee, small dark bee, large dark bee, green bee, honey bee, bumble bee). * *number*: unique identifier for specimen. * *Order*: taxonomic Order of the specimen. * *identifying characters*: anatomical characters used to determine Family of the specimen. * *Family*: taxonomic Family of the specimen. * *Subfamily*: taxonomic Subfamily of the specimen (if applicable, when not applicable value is blank, NA, or N/A - all mean that this column was not applicable for this specimen). * *Tribe*: taxonomic Tribe of the specimen (if applicable, when not applicable value is blank, NA, or N/A - all mean that this column was not applicable for this specimen). * *Genus*: taxonomic Genus of the specimen. * *species*: taxonomic species OR grouping into distinct, unnamed species based on characteristics of the specimen. * *key*: dichotomous taxonomic key used to identify specimen. * *notes*: notes to contextualize observations (not needed for analysis). * *verified*: name of the scientist who verified the identification (if applicable). ## Code/Software This code was originally run in R Studio version 4.3.2. Packages used are linked in each file. Floral Cover Data Cleaning.R: This file should be used with Floral Count.csv, Open Floret Cats.csv, Floral Area.csv, Avg area calculation.csv, and Treatments.csv. Code in this file uses raw measurements of the number of flowers, area of a flower (cm^2^), and % of open florets to create the floral cover metric, which has units of cm^2/0.5m^. Visitation Data Cleaning.R: This file should be used with Visitation Raw.csv and Pollinator Voucher.csv. This file should be run after Floral Cover Data Cleaning.R, as it also pulls in the dataset created in that script. This code results in 2 datasets: one that includes both floral cover and pollinator visitation (in visits per minute) for each plot on each sampling date in 2022 and 2023, and the second that aggregates the number of pollinator species seen in each year. Analysis p1: This file uses the datasets created in Visitation Data Cleaning.R to model floral cover and pollinator visitation by camelina planting date and planting mix. Analysis p2: This file uses datasets created in Visitation Data Cleaning.R to model pollinator visitation by floral cover for 1) camelina, 2) dandelion, and 3) both camelina and dandelion combined (i.e. total).