Data and code from: Insecticides alter wild and managed pollination dynamics on oil crop yield
Data files
Jun 25, 2026 version files 510.40 KB
-
carinata_analysis.R
21.34 KB
-
carinata_observations.csv
359.62 KB
-
final_carinata_design.csv
1.17 KB
-
final_density.csv
16.07 KB
-
final_yield.csv
102.78 KB
-
pollinator_species_summary.csv
402 B
-
README.md
9.02 KB
Abstract
Background: There is increasing global production of Ethiopian rape (Brassica carinata), a crop used for biofuel production and animal feed. Its similarity to other mustard seed oil crops, such as canola and rapeseed, suggests that it may provide floral resources for pollinators within crop rotations. However, evidence on the benefits of mass-flowering crops for pollinators is mixed, and the provision of floral resources does not necessarily imply a dependence on pollination. Consequently, the role of pollination in B. carinata remains poorly understood.
Aim: This study investigates the pollination system of B. carinata experimentally at the farm scale. We aim to obtain a mechanistic understanding of how the availability of floral, regular insecticide applications, and the use of managed honey bee hives, affects crop pollination and crop yield.
Methods: Data were collected from 35 experimental field sites (0.404 ha = 1 acre each) across two consecutive years in the Prairie Coteau region of the Northern Great Plains, South Dakota, USA. Over 800 focal B. carinata individuals were monitored by collecting data on pollinator visitation, pollinator diversity, flower traits, and yield. We generated estimates of floral resource availability to quantify the relationship between pollinator visitation rate and yield at plant, square and site scale. We additionally quantified pollinator movement to assess the effects of insecticide treatment on pollinator behavior to provide a mechanistic explanation of the interaction of floral resource availability and insecticide treatment on pollinator visitation and yield.
Results: Pollinators increased seed set of B. carinata by 26.8%, with 28 species recorded visiting flowers. Wild pollinators were more efficient than honeybees, contributing on average 1.01 seeds per visit compared to 0.79 seeds per visit by honeybees, likely reflecting differences in pollen removal and deposition. In insecticide free fields, interactions between wild pollinators and honeybees led to non-additive effects on pollination, which may reflect underlying trade-offs between competition and facilitation. On fields with insecticides, wild pollinators were disproportionately suppressed, while honeybees partially compensated by maintaining visitation, buffering overall seed set losses. However, across spatial scales, wild pollinators consistently outperformed honeybees, though their advantage diminished under insecticide treatment. These results highlight scale and context-dependent interactions, with trade-offs in untreated fields and compensatory dynamics under chemical stress.
Synthesis and Application: Our findings emphasize that combining honeybee hives with pesticide use do not automatically optimize crop yield. Policy frameworks for pollinator conservation need to recognize scale-dependent pollination processes, as enhancing pollinator diversity and floral resources at the farm scale is key to maintaining resilient and productive agroecosystems Thus, we recommend a holistic strategy that integrates pesticide reduction, habitat enhancement and conservation of wild pollinators to optimize pollination services, promote biodiversity and support sustainable agricultural systems.
Dataset DOI: 10.5061/dryad.gxd254828
Dataset Description
This dataset contains field observations and experimental measurements collected from Brassica carinata (Ethiopian mustard) fields in South Dakota, USA. The study investigated how pollinator visitation, floral resource availability, honey bee hive additions, and agricultural management influence crop pollination and seed production.
Data were collected during the flowering period and include pollinator observations, nectar measurements, plant density estimates, vegetation characteristics, experimental treatments, and seed yield measurements.
The dataset consists of four primary data files and one analysis script.
File Inventory
carinata_observations.csv
Pollinator observation dataset containing flower visitation observations, floral resource measurements, and plant characteristics.
final_yield.csv
Seed production and yield measurements collected from focal plants after flowering.
final_density.csv
Plant density and vegetation height measurements collected within sampling quadrats.
final_carinata_design.csv
Experimental treatment assignments and site-level study design information.
pollinator_species_summary.csv
spec_id = species identifier
no_flo_v = count/frequency
carinata_analysis.R
Main R script used for data cleaning, calculation of derived variables, and statistical analyses presented in the manuscript.
Study Design
Field sites were established in commercial Brassica carinata fields.
Experimental treatments included:
- Honey bee hive addition treatment (
hb_treatment) - Seed treatment category (
seed_treatment) - Farming practice category (
farming_p)
Pollinator observations were conducted on focal plants during standardized observation periods. Floral resources were quantified using flower abundance, nectar volume, and nectar sugar concentration measurements.
Seed yield measurements were collected at the end of the flowering season.
Data File Descriptions
File: carinata_observations.csv
Each row represents a pollinator observation event conducted on a focal plant during a sampling session.
| Variable | Description | Units |
|---|---|---|
| site_id | Study site identifier | text |
| sq_id | Quadrat identifier within site | integer |
| fo_id | Focal plant identifier | integer |
| date | Original date code recorded in field sheets | numeric |
| time | Original time code recorded in field sheets | numeric |
| no_flo | Number of open flowers on focal plant | count |
| spec_id | Pollinator species or taxonomic identifier | text |
| dp | Heterospecific pollen deposition events observed | count |
| sp | Conspecific pollen deposition events observed | count |
| no_flo_v | Number of flower visits recorded during observation period | count |
| no_ind_po | Number of individual pollinators observed | count |
| nec_time | Time required for nectar collection | seconds |
| nec_conc | Nectar sugar concentration | % Brix |
| nec_vol | Nectar volume category (l = low, m = medium, h = high) | categorical |
| tot_flo | Total number of flowers within sampling quadrat | count |
| height (cm) | Height of focal plant | centimeters |
| comment | Field notes recorded during sampling | text |
| year | Sampling year | year |
| date_raw | Original raw date value | numeric |
| time_raw | Original raw time value | numeric |
| date_formatted | Reformatted calendar date | YYYY-MM-DD |
| time_formatted | Reformatted observation time | HH:MM |
Pollinator Species Codes
Species identifiers (spec_id) represent pollinator taxa observed during field surveys. Taxonomic assignments follow the field identification scheme used during data collection.
File: final_yield.csv
Each row represents yield measurements collected from a focal Brassica carinata plant.
Variables
| Variable | Description | Units |
|---|---|---|
| site_id | Study site identifier | text |
| sq_id | Quadrat identifier | integer |
| fo_id | Focal plant identifier | text |
| bag_w | Harvest bag weight | grams |
| no_fr | Number of fruits on focal plant | count |
| no_s_f_1 - no_s_f_5 | Number of fertile seeds in fruit 1–5 | count |
| no_s_a_1 - no_s_a_5 | Number of aborted seeds in fruit 1–5 | count |
| s_w_1 - s_w_5 | Seed mass from fruit 1–5 | grams |
| comments | Additional notes | text |
| year | Sampling year | year |
Derived Variables Used in Analyses
The analysis script calculates:
- seed_set_mean
- abort_mean
- seed_set_plant
- abort_plant
- mass_mean
- mass_per_seed
- plant_seed_mass
- fertile_sum
- non.fertile_sum
These variables are derived from the raw seed counts and seed mass measurements.
File: final_density.csv
Each row represents vegetation density measurements collected from a sampling quadrat.
| Variable | Description | Units |
|---|---|---|
| site_id | Study site identifier | text |
| sq_id | Quadrat identifier | integer |
| date | Sampling date | YYYYMMDD |
| density | Plant density estimate | plants per m² |
| ht_1 - ht_10 | Individual vegetation height measurements | centimeters |
| year | Sampling year | year |
Derived Variables
The analysis script calculates:
- height_mean
- sq_density
- site_density
File: final_carinata_design.csv
Experimental design information.
| Variable | Description |
|---|---|
| site_id | Study site identifier |
| seed_treatment | Seed treatment category assigned to site |
| hb_treatment | Honey bee hive treatment (presence or absence) |
| farming_p | Farming practice classification |
| date | Experimental date |
| year | Sampling year |
Data Processing
Several derived variables used in the manuscript were calculated from the raw data.
Examples include:
- Floral sugar availability per flower
- Floral sugar availability per focal plant
- Quadrat-level floral resource estimates
- Site-level floral resource estimates
- Seed set metrics
- Pollination success metrics
Complete calculations are documented in:
analysis_main.R
Statistical Analyses
Analyses were conducted in R using generalized linear mixed-effects models (GLMMs).
Primary packages used:
- lme4
- glmmTMB
- ggplot2
- effects
- MuMIn
- emmeans
- sjPlot
R version: 4.3.2
Users reproducing analyses may need to modify working-directory paths contained in the original script.
Missing Values
Missing values are represented as NA.
NA values indicate one of the following:
- Measurements not recorded in the field.
- Variables not applicable to a particular observation.
- Data unavailable due to sampling constraints.
- Data removed during quality-control procedures.
Blank cells should be interpreted as missing information when encountered.
Contact
For questions regarding the dataset, metadata, or analyses, please contact the corresponding author associated with the manuscript.e dataset or analyses, please contact the corresponding author.
