Data from: Effects of a heat wave event on the chemical ecology of species interactions in the potato agroecosystem

Carvajal Acosta, Nalleli 1 2 3 ; Wetzel, William 4 ; Szendrei, Zsophia2; Snook, Joshua2 5

Research facility: Kellogg Biological Station Long Term Ecological Research

Published Oct 23, 2025 on Dryad. https://doi.org/10.5061/dryad.pzgmsbd1m

Data files

Oct 23, 2025 version files 62.69 KB

Abstract

Heat waves, brief periods of unusually high temperatures, are increasing in frequency and intensity globally. Such extreme weather events can alter plant chemistry, disrupting species interactions that contribute to pest suppression or increase their performance. Yet, most heat wave studies focus on pairwise interactions, leaving us with a poor understanding of how complex agroecosystems respond to temperature extremes. We addressed this knowledge gap by simulating an experimental heat wave in the field on potato plants (Solanum tuberosum) and the Colorado potato beetle (CPB), Leptinotarsa decemlineata (Coleoptera: Chrysomelidae), in the presence or absence of their mutualistic microbial symbionts and another pest, the potato aphid (Macrosiphum euphorbiae). Here we report changes in CPB performance and leaf chemistry, specifically, volatile organic compounds (VOCs) and glycoalkaloids content in host plants.

title: "Heat wave impact on the chemical ecology of multi-species interactions
in an agroecosystem"
author: "Nayeli Carvajal"
date: "2025-10-6"
output: html_document
editor_options:
markdown:
wrap: 72

knitr::opts_chunk$set(echo = FALSE)

https://doi.org/10.5061/dryad.pzgmsbd1m

GENERAL INFORMATION

Title of Dataset: “Heat wave impact on the chemical ecology of multi-species
interactions in an agroecosystem"
Author Information

A. Person(s) responsible for collecting the data Name:

Nayeli Carvajal, Institution: Michigan State University Address: 288 Farm
Ln, East Lansing, MI 48824 Email:
carvaj14@msu.edu{.email}

B. Principal Investigator Name:

William Wetzel Institution: Montana State University Address: Land
Resources & Environmental Sciences, Bozeman, MT USA. Email:
william.wetzel@montana.edu{.email}
Date of data collection (single date, range, approximate date):

June-October 2022
Geographic location of data collection:

MSU Kellogg Biological Station, MI, United States
Keywords used to describe the data topic:

chemical ecology, agroecology, Colorado potato beetle, potato aphid, heat
wave, symbiotic microbes, Solanum tuberosum, thermal stress
Language information:

English
Information about funding sources that supported the collection of
the data:

This project was supported by Agriculture and Food Research
Initiative Competitive Grant no. 2020-67013-31919 from the USDA
National Institute of Food and Agriculture.

DATA & FILE OVERVIEW

For each filename, a short description of what data it contains

"CPB_censuses.csv" contains data for larval count before and after the heat
wave and adult count.

“CPB_adult_fitness.csv” reports data for CPB adult sex and size as
determined by dry weight and pronotum length for each adult CPB collected in
the field.

"leaf_glycoalkaloids.csv" contains abundance data for glycoalkaloids from
host plants.

"leaf_volatiles.csv" contains leaf volatile abundance data from host plants.
Format of the file if not obvious from the file name: comma
separated values, file extension

“.csv”
Additional related data collected that was not included in the
current data package:

No
Are there multiple versions of the dataset?

No

SHARING/ACCESS INFORMATION

Licenses/restrictions placed on the data:

N/A
Links to publications that cite or use the data:

Carvajal-Acosta, et al. 2025. "Effects of a heat wave event on the chemical
ecology of species interactions in the potato agroecosystem".
Environmental Entomology. http:/DOI.10.1093/ee/nvaf104
Was data derived from another source?

No
Recommended citation for this dataset:

Carvajal-Acosta et al. (2025). Heat wave impact on the chemical ecology of
multi-species interactions in an agroecosystem.
Dryad, Dataset

METHODOLOGICAL INFORMATION

Description of methods used for collection/generation of data:

CPB survival and adult performance: We censused CPB larvae twice,
once before the heat wave and once after to quantify performance
(searching for 5 min. per plant).Adult beetles were collected in mid-August
prior to removing experimental cages, frozen immediately after collection,
oven-dried and sexed. We then weighted them and measured pronotum length
to assess adult performance.

Glycoalkaloids:
We analyzed potato’s four main glycoalkaloids (solanine, chaconine,
dehydrosolanine, and dehydrochaconine). Glycoalkaloids were extracted from
plant tissue and analyzed using LC/MS/MS at the Michigan State University’s
Mass Spectrometry and Metabolomics Core. Approximately 100 mg of plant tissue
from each plant were collected in pre-weighted 2 mL tubes. Frozen tissue was
ground in a pre-frozen bead beater (Retsch, MM400) at 30/s until fully ground.
Samples were extracted with 1 mL extraction buffer (80:20 v/v methanol:water,
0.1% formic acid, and 100 nM of digitoxin as internal standards). After
incubating at 4°C on a rocking platform for 16 hours, samples were
centrifuged at 4°C for 10 minutes at 14,000 rpm (Eppendorf, 5810 R).
Supernatants (10 µl) were diluted into a 990 µL cold extraction buffer and
stored at -20°C. Samples were analyzed using a Waters Xevo G2-XS Quadrupole-
Time-of-flight LC/MS/MS system with a Waters Acquity BEH-C18 UPLC column
(2.1 x 100mm) in positive ion mode. Compounds were eluted using a binary
gradient of solvent A (0.1% formic acid in water) and solvent B (acetonitrile)
at a flow rate of 0.3 mL/ minute at 40°C following a stepwise gradient:
98.0% A, 2.0% B; 0.50 min, 85.0% A, 15.0% B; 5.00 min, 40.0% A, 60.0% B;
7.00 min, 1.0% A, 99.0% B; 8.00 min, 1.0% A, 99.0% B; 8.01 min, 98.0% A,
2.0% B; 10.00 min, 98.0% A, 2.0% B.

Leaf volatiles: Leaf volatiles were collected immediately after the heat
wave event over a period of three days from 118 plants. Sampling occurred
between 11 AM and 2 PM during following dynamic headspace sampling procedure.
We selected one vegetative stem per plant of similar biomass and enclosed
them in a 35 x 35 cm nylon oven bags unsealed on one side. The bags were tied
with twisters and volatiles were allowed to equilibrate for 30 minutes, after
which, samples were pumped for 30 minutes through a scent trap using an air
sampling pump set to a pre-trap flow rate of 350 mL/min. Stems were saved,
dried, and weighted. Ambient controls (n=10) were taken from the area adjacent
to the experimental plots where air was collected using an empty oven bag and
sampled following the same methodology as the experimental samples.These
ambient samples were used to identify contaminants or background compounds
from surrounding vegetation.Leaf and ambient samples were analyzed using
thermal desorption Gas Chromatography-Mass Spectrometry (GC-MS), together
with one blank/unused scent traps to detect potential contaminants in the
trap system.
Methods for processing the data:

"CPB_survival.csv" No processing required. The dataset reports the raw
count data from the pre- and post-heat wave surveys and adult count. This
data was later processed for statistical analysis.

“leaf_glycoalkaloids.csv” We identified compounds in the Waters
MassLynx software based on mass spectrometry, confirmed with digitoxin as
internal standard, and quantified using the Waters Quanlynx MS software.
Prior to statistical analysis data was normalized to internal standards and
tissue sample mass.

“leaf_volatiles.csv" Peak deconvolution, integration, and tentative
compound identification were performed in the Automated Mass Spectral
Deconvolution and Identification System (AMDIS) using the 2020 NIST mass
spectrallibrary. Data filtering was performed in the bouquet package. Peaks
were included if they had mass spectral match scores greater than 80%, a
maximum peak area of at least 20,000 counts, and if they were present in more
than 20% of the samples. Additionally, we only included compounds with peak
areas four times higher than the mean area of the ambient and blank controls.
Caprolactam (compounds present in oven bags) and compounds with retention
times above 15 minutes were excluded as contaminants. Stems used for volatile
collection were saved, dried, and weighted. Volatile emissions were quantified
based on peak values and were standardized by dry weight of the sampled stem.

<!-- -->

Instrument- or software-specific information needed to interpret the
data:

Microsoft Excel or any other data processing software.
Describe any quality-assurance procedures performed on the data:
For leaf volatiles, we ensured that all identified compounds had about the
same retention times. Compounds with different retention times at the "second"
digit, were identified as "unknowns".
People involved with sample collection, processing, analysis and/or
submission: Michael Kalwajtys, Gabriel Veltri, Sarah Momimee, and Sophia
Knightly were involved in the field data collection. Averie Hannah, Rachel
Rantz, and Darla Knuth processed field data in the lab (i.e., measured and
weighted adult CPB). Alma N. Carvajal Acosta analyzed the data and submitted
the data sets.

I.- DATA-SPECIFIC INFORMATION FOR:

“CPB_censuses.csv”

Number of variables: 7
Number of cases/rows: 89
Variable List:

plant_ID (unique plant number)

herb_tmt (indicates the herbivore treatment combination assigned to
the plant)

heatwave_tmt (indicates the heat wave treatment consisting of heat
wave or ambient conditions assigned to the plant)

larval_count1 (indicates the number of CPB found in the plant in the
pre-heat wave census)

larval_count2 (indicates the number of CPB found in the plant in the
post-heat wave census)

adult_count (indicates the number of adult CPB collected from the plant)

aphid_count (number of aphids found initially in the plant, before the
hebivore and the heat wave treatments were applied)
Missing data codes: No.
Specialized formats or other abbreviations used: None.

II. DATA-SPECIFIC INFORMATION FOR:

"CPB_adult_fitness.csv"

Number of variables: 7
Number of cases/rows: 119
Variable List:

plant_ID (unique plant number)

herb_tmt (indicates the herbivore treatment combination assigned to
the plant)

heatwave_tmt (indicates the heat wave treatment consisting of heat
wave or ambient conditions assigned to the plant)

pronotum_length (measured length of pronotum in mm)

mass (dry weight of adult CPB in mg)

sex (sex of specimen either male or female)

notes (any observation on the state of specimen)
Missing data codes: N/A
Specialized formats or other abbreviations used: N/A for "not available"
unidentifiable data.

III. DATA-SPECIFIC INFORMATION FOR:

“leaf_glycoalkaloids.csv"

Number of variables: 8
Number of cases/rows: 149
Variable List:

plant_ID (unique plant number)

herb_tmt (indicates the herbivore treatment combination assigned to
the plant)

heatwave_tmt (indicates the heat wave treatment consisting of heat
wave or ambient conditions assigned to the plant)

leaf_mass (weight of the leaf material in mg used to extract glycoalkaloids)

solanine (concentrations of solanine detected in leaf material)

through....

d_chaconine (concentrations of dehydrochanonine detected in leaf material)
Missing data codes: No
Specialized formats or other abbreviations used: dehydro prefix was abreviated
as "d_" for dehydrochaconine and dehydrosolanine.

IV. DATA-SPECIFIC INFORMATION FOR:

“leaf_volatiles.csv"

Number of variables: 61
Number of cases/rows: 118
Variable List:

plant_ID (unique plant number)

herb_tmt (indicates the herbivore treatment combination assigned to
the plant)

heatwave_tmt (indicates the heat wave treatment consisting of heat
wave or ambient conditions assigned to the plant)

collection_date (the date the sample was collected)

alpha-Copaene (indicates emission rates of alpha-Copaene emitted from leaf
samples in 1 hr, representing abundances)

through....

Tricyclo[2.2.1.0(2,6)]heptane, 1,7-dimethyl-7-(4-methyl-3-pentenyl)-, (-)-
(indicates emission rates of this compound emitted from leaf samples in 1 hr,
representing abundances)
Missing data codes: No
Specialized formats or other abbreviations used: No

Experimental design

To assess the effect of a heat wave event on pest performance and plant chemistry in different ecological contexts, we conducted a field experiment during the 2022 growing season at the Michigan State University Kellogg Biological Station (KBS) (Hickory Corners, MI). We generated a 4-day heat wave event on potato plants exposed to damage by CPB larvae with or without microbial symbionts and/or simultaneous damage by potato aphids.

CPB colony

All larvae were obtained from a colony maintained at the KBS greenhouse facilities with adults sourced from the Montcalm Research Station, MI. We obtained CPB without symbiotic bacteria by splitting the colony into separate cages with antibiotic-free and antibiotic-treated potato plants. Antibiotic-treated plants were sprayed thoroughly with an antibiotic solution consisting of 5 % Tetracycline, 5 % Neomicine, and 2.5 % Streptomycine in DI water.

Field experiment

We planted seed potatoes individually within 1 m² plots in mid-May. When plants began sprouting and before naturally occurring CPB populations arrived, we allowed a subset of plants to be colonized by natural populations of potato aphids and covered the rest with 1 m² by 80 cm tall mesh cages (Lumite, Inc., GA). When plants were about six weeks old, they were assigned to one of the following herbivory treatment combinations: 1) “control” plants with no herbivores; 2) “CPB” alone; 3) CPB treated with antibiotics “CPB(ab)”; 4) CPB with aphids “CPB+aphid”; and 5) antibiotic-treated CPB with aphids “CPB(ab)+aphid”. Plants in the “CPB” and “CPB(ab)” groups received 10 CPB neonate larvae from the antibiotic-free and the antibiotic-treated colony, respectively. For the “CPB+aphid” and “CPB(ab)+aphid” treatment groups, we added CPB larvae from their corresponding colonies as described above to the aphid colonized plants and covered with the protective cages.

Heat wave treatment

After one week of initiating bioassays, half of these plants were assigned randomly to either an ambient or heat wave group. Each herbivore x heat wave treatment combination had 15 replicates, totaling 120 plants. We simulated a single 4-day heat wave event in mid-July using an electric 300-Watt ceramic heater (Tempco, Inc., IL) hung in the opening of a pyramidal open-top chamber with a wood frame and anti-condensate greenhouse plastic sides (6 mil, 91 % light transmittance, Poly-Ag Corp., CA). This system increased daily temperatures by an average of 10 °C and 4 °C at night, achieving average temperatures of 41.84 °C ± 9.86 (diurnal) and 25.16 °C ± 4.2 (nocturnal) in the heat wave plots compared to 31.8 °C ± 9.26 (diurnal) and 21.91 °C ± 3.43 in ambient plots.

Data collection

Insect performance

We censused CPB larvae twice, once before the heat wave and once after to quantify performance (searching for 5 minutes per plant). Adult beetles were collected in mid-August prior to removing experimental cages, frozen immediately after collection, oven-dried and sexed. We then weighted them and measured pronotum length to assess adult performance.

Plant chemistry

We analyzed potato’s four main glycoalkaloids (solanine, chaconine, dehydrosolanine, and dehydrochaconine), and leaf volatiles to assess whether heat stress changes plant secondary chemistry under different types of biotic stresses. Glycoalkaloids were extracted from plant tissue and analyzed using LC/MS/MS at the Michigan State University’s Mass Spectrometry and Metabolomics Core.

Approximately 100 mg of plant tissue from each plant were collected in pre-weighted 2 mL tubes. Frozen tissue was ground in a pre-frozen bead beater (Retsch, MM400) at 30/s until fully ground. Samples were extracted with 1 mL extraction buffer (80:20 v/v methanol:water, 0.1% formic acid, and 100 nM of digitoxin as internal standards). After incubating at 4°C on a rocking platform for 16 hours, samples were centrifuged at 4 °C for 10 minutes at 14,000 rpm (Eppendorf, 5810 R). Supernatants (10 µL) were diluted into a 990 µL cold extraction buffer and stored at -20 °C. Samples were analyzed using a Waters Xevo G2-XS Quadrupole-Time-of-flight LC/MS/MS system with a Waters Acquity BEH-C18 UPLC column (2.1 x 100 mm) in positive ion mode. Compounds were eluted using a binary gradient of solvent A (0.1% formic acid in water) and solvent B (acetonitrile) at a flow rate of 0.3 mL/ minute at 40°C following a stepwise gradient: 98.0 % A, 2.0 % B; 0.50 min, 85.0 % A, 15.0 % B; 5.00 min, 40.0 % A, 60.0 % B; 7.00 min, 1.0 % A, 99.0 % B; 8.00 min, 1.0 % A, 99.0 % B; 8.01 min, 98.0 % A, 2.0 % B; 10.00 min, 98.0 % A, 2.0 % B. We identified compounds in the Waters MassLynx software based on mass spectrometry, confirmed with digitoxin as internal standard, and quantified using the Waters Quanlynx MS software. Prior to statistical analysis data was normalized to internal standards and tissue sample mass.

Leaf volatiles were collected immediately after the heat wave event over a period of three days from 118 plants including at least 10 replicates per each treatment combination. Sampling occurred between 11 AM and 2 PM during which time temperatures ranged from 23-43 °C following dynamic headspace sampling procedure. Briefly, we selected one vegetative stem per plant of similar biomass and enclosed them in a 35 x 35 cm nylon oven bags (Reynolds, USA) unsealed on one side. The bags were tied with twisters and volatiles were allowed to equilibrate for 30 minutes, after which, samples were pumped for 30 minutes through a scent trap using an air sampling pump (Ointik; Push-Pull Active Air Sampling Vacuum Pump) set to a pre-trap flow rate of 350 mL/min. Stems were saved, dried, and weighted. Ambient controls (n = 10) were taken from the area adjacent to the experimental plots where air was collected using an empty oven bag and sampled following the same methodology as the experimental samples. These ambient samples were used to identify contaminants or background compounds from surrounding vegetation.

Leaf and ambient samples were analyzed using thermal desorption Gas Chromatography-Mass Spectrometry (GC-MS), together with one blank/unused scent traps to detect potential contaminants in the trap system. Peak deconvolution, integration, and tentative compound identification were performed in the Automated Mass Spectral Deconvolution and Identification System using the 2020 NIST mass spectral library. Data filtering was performed in the bouquet package. Peaks were included if they had mass spectral match scores greater than 80 %, a maximum peak area of at least 20,000 counts, and if they were present in more than 20 % of the samples. Additionally, we only included compounds with peak areas four times higher than the mean area of the ambient and blank controls. Caprolactam (compounds present in oven bags) and compounds with high retention times (above 15 minutes) were excluded as contaminants. Stems used for volatile collection were saved, dried, and weighted. Volatile emissions were quantified based on peak values and were standardized by dry weight of the sampled stem.