Data and code from: Early herbivory attracts and facilitates subsequent specialist herbivores with consequences for plant performance
Data files
Jul 24, 2026 version files 681.55 KB
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2024_Field_Data__-_Combined_Raw_Data_(3).csv
195.90 KB
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Chapter3_RScript.R
101.86 KB
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Dataset_2_-_Greenhouse_NoChoice_-_Paper_4_-_Clean_OffspringSQB_Performance_Data_2.csv
10.60 KB
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Dataset_3_-_Greenhouse_Choice_-_Paper_4_-_Choice_GH_Raw.csv
16.48 KB
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Dataset_3_-_Greenhouse_Choice_-_Paper_4_-_No-Choice_GH_Offspring_Raw.csv
4.03 KB
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Dataset_3_-_Greenhouse_Choice_-_Paper_4_-_Sheet5_(1).csv
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Field_survey_of_A._vittatum__A._tristis__and_C._setosa_at_Fellenz_Family_Farm__-_Clean_Data_(1).csv
242.18 KB
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FieldData2024.R
103.13 KB
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README.md
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Abstract
Plants are often attacked by multiple insect herbivores throughout their lifetime. Early-arriving herbivores play a critical role in shaping plant responses, which in turn affects subsequent interactions. Later-arriving herbivores can exploit damaged plants but their role in modifying interactions and plant performance remains unclear. Thus, it is important to examine host plant preferences in late-arriving herbivores, the cues guiding their behavior, and the consequences of multiple herbivores. To better understand these interactions and downstream effects, we examined interactions between two insect herbivore specialists, Acalymma vittatum (striped cucumber beetle) and Anasa tristis (squash bug), which often overlap in sequence on shared Cucurbitaceae host plants. We characterized natural succession patterns, identified the cues influencing early- and late-arriving herbivores, and tested the preference–performance hypothesis by determining whether the field-identified cues driving A. tristis attraction and oviposition predicted improved offspring performance on plants previously colonized by A. vittatum. Finally, we investigated how A. vittatum-mediated recruitment of A. tristis influenced plant growth and reproductive traits, by manipulating herbivory from both species in field experiments.
This data deposit contains the data underlying the analyses presented in our manuscript, Early herbivory attracts and facilitates subsequent specialist herbivores with consequences for plant performance. It includes six data files, two R script files, and accompanying documentation describing the variables, units, and methods used for data collection and processing from a three-year period (2022–2024). Measurements include counts of insect colonization on cultivated plants, behavioral and performance metrics for individual insects and insect groups, and measurements of plant traits and yield. Data were collected from cultivated cucurbit species, including Cucurbita pepo, Cucumis sativus, and Citrullus lanatus, in Ithaca, New York, and the surrounding area.
Authors
Matthew Barrett and coauthors
Description
This dataset contains the data and analysis scripts used in the manuscript Early herbivory attracts and facilitates subsequent specialist herbivores with consequences for plant performance. Data were collected between 2022 and 2024 in Ithaca, New York, and the surrounding area.
Contents
This repository contains the following CSV files and R scripts. All relevant unique variables are described for clarity and reproducibility
Data Files
A. vittatum and A. tristis abundance and distribution of 2022 field survey
File: Field_survey_of_A._vittatum__A.tristis__and_C.setosa_at_Fellenz_Family_Farm-Clean_Data(1).csv
Description: enables comparison of A. vittatum and A. tristis abundance and distribution across multiple plants.
Relevant unique variables and info:
Plant_IDs - unique plant ID
Variety - categorical variable of plant species
Sample_Date - date of sampling events
No_Beetles_Observed - count data of A. vittatum
No_SQB_Adults - count data of A. tristis
No_SQB_Clutches - count data of A. tristis
No_SQB_Eggs - count data of A. tristis
No_Leaves - count data of plant traits
No_Flowers - count data of plant traits
No_Fruits - count data of plant traits
Percent_Beetle_Damage - visually estimate percentage of A. vittatum induced foliar damage in increments of 5
Choice and no-choice bioassays on A. tristis adults and offspring
Data files:
File 1: Dataset_2_-Greenhouse_NoChoice-Paper_4-_Clean_OffspringSQB_Performance_Data_2.csv
Description: Growth and survival data on A. tristis offspring. Enables comparison of A. tristis offspring performance on plants damaged or undamaged by A. vittatum.
Relevant unique variables and info:
PlantID - unique plant ID
Block - block replicate
Treatment - categorical variable
Number_NymphsAdded - count data of A. tristis
Number_NymphsRecovered - count data of A. tristis
NymphEndMass(mg) - continuous data of A. tristis in milligrams
File 2: Dataset_3_-Greenhouse_Choice-Paper_4-_Choice_GH_Raw.csv
Description: Enables comparison of A. tristis adult choices in bioassays
Relevant unique variables and info:
Bug ID - unique A. tristis ID
Conditions - categorical variable denoting what binary choice conditions
60-min - choice at 60 min
120-min - choice at 120 min
24-hours - choice at 24 hours
File 3: Dataset_3_-Greenhouse_Choice-Paper_4-_No-Choice_GH_Offspring_Raw.csv
Description: enables comparison of A. tristis offspring performance on different plant varieties
Relevant Unique variables and info:
ID - unique plant ID
Plant_Variety - categorical variable of plant species
No. Nymph Start - count data of A. tristis
No. Nymph End - count data of A. tristis
End_mass(mg) - - continuous data of A. tristis in milligrams
File 4: Dataset_3_-Greenhouse_Choice-Paper_4-Sheet5(1).csv
Description: enables comparison of A. tristis adult oviposition on different plant varieties
Relevant Unique variables and info:
Bug ID - unique insect ID
Plant_Variety - categorical variable of plant species
Time - categorical variable of time sampled
No_Clutches - count data of A. tristis
No_Eggs - count data of A. tristis
Plant performance and yield data of 2024 field experiment of A. vittatum and A. tristis herbivory
File: 2024_Field_Data__-Combined_Raw_Data(3).csv
Description: enables comparison of A. vittatum and A. tristis herbivory on plant performance and yield
Relevant Unique variables and info:
Plant_ID - unique plant ID
Row - row location in experimental research field
Block - replicate unit
Plant_Species - categorical variable of plant species
Treatment - categorical variable of herbivory treatment
Sample_Date - date of sampling events
Plant_Death - categorical variable of plant death
No_Beetles - count data of subsequent A. vittatum
%_Damage - - visually estimate percentage of A. vittatum induced foliar damage in increments of 5
No_Male_Flowers - count data of plant traits
No_Female_Flowers - count data of plant traits
No_Fruit - count data of plant traits
Total_Fruit_Mass(lbs) - countinous data of plant yeild
No_Leaves - count data of plant traits
Missing values are recorded as NA.
R scripts
File: Chapter3_RScript.R
Description: Analysis of 2022 field survey of A. vittatum and A. tristis abundance and distribution across multiple cucurbit crops; choice and no-choice bioassays on A. tristis
File: FieldData2024.R
Description: Analysis of 2024 field experiment of A. vittatum and A. tristis herbivory on plant performance and yield
Software
Analyses were conducted in R and RStudio (v. 4.4.0; R Core Team, 2025), using the scripts provided. Required R packages are listed in the scripts.
Contact
For questions regarding the dataset, please contact:
mb2657@cornell.edu
