Data and code from: Leveraging modern coexistence theory to understand how stress modifies outcomes of diploid-polyploid competition: A demonstration and review
Data files
Jul 21, 2026 version files 2.09 MB
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Ashman.etal.body.size.csv
8.68 KB
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Ashman.etal.BootstrapGR.RData
1.96 MB
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Ashman.etal.performance.csv
72.74 KB
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Ashman.etal.resSA.csv
4.96 KB
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Ashman.etal.salt.pilot.TableS1data.csv
5.68 KB
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Ashmanetal.Recip.Salt.Analysis.Rmd
28.24 KB
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README.md
5.17 KB
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README.txt
5.16 KB
Abstract
Polyploid plants are overrepresented in harsh environments, leading to the speculation that stress tolerance is key to polyploid evolutionary and ecological success despite the challenges faced by new (neo) polyploids. Stress tolerance advantages often focus on individuals, but polyploid persistence, coexistence, or competitive exclusion involves populations. We review how Modern Coexistence Theory (MCT) provides a robust framework to understand how stress modifies outcomes of diploid-polyploid competition at the population level. We present a roadmap of the effective application of MCT highlighting considerations when deriving niche and competitive ability differences, and predicting the effect of stress on competitive outcomes. We review the handful of published studies and add new results from reciprocal invasion experiments with two pairs of synthetically derived neotetraploid and progenitor diploid cytotypes of Spirodela polyrhiza under stress and non-stress conditions. Together, studies reveal that stress can increase stabilizing niche differences and modify relative fitness differences in ways that alter coexistence predictions, but that results are species-, genotype-, or study-specific. Furthermore, studies point to body size and stress physiology as potential drivers, but much more work is needed. On balance, the emerging body of work serves as a strong motivator for applying MCT to more systems, more stresses, and more functional traits.
Dataset DOI: 10.5061/dryad.bvq83bkr9
Description of the data and file structure
GENERAL INFORMATION
This README.txt file was updated on June 26th 2026
A. Paper associated with this archive
Leveraging Modern Coexistence Theory to understand how stress modifies outcomes of diploid-polyploid competition: a demonstration and review. American Naturalist.
Brief abstract: The study discusses on how the Modern Coexistence Theory (MCT) provides a robust framework to understand how stress modifies outcomes of diploid-polyploid competition at the population level. We present a proof-of-concept reciprocal invasion experiment with two pairs of synthetically derived neotetraploid and progenitor diploid cytotypes of Spirodela polyrhiza under stress (salt) and non-stress conditions.
B. Originators
Tia-Lynn Ashman, University of Pittsburgh
Lacey D. Rzodkiewicz, University of Pittsburgh
Martin M. Turcotte, University of Pittsburgh
C. Contact information
Tia-Lynn Ashman and Martin M. Turcotte
tia1@pitt.edu and turcotte@pitt.edu
D. Dates of data collection
July, September, and October 2024
E. Geographic Location(s) of data collection
Growth chamber experiment, University of Pittsburgh, Pittsburgh, PA, USA
F. Funding Sources
Funding for this research was provided by grants (NSF DEB-2401148 and NSF DBI-2320251) and by the University of Pittsburgh through the Dietrich School of Arts and Sciences to MMT and T-LA
ACCESS INFORMATION
- Licenses/restrictions placed on the data or code
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
- Data derived from other sources
None
- Recommended citation for this data/code archive
Ashman, T.-L., Rzodkiewicz, L. R. and Turcotte, M.M. Leveraging Modern Coexistence Theory to understand how stress modifies outcomes of diploid-polyploid competition: a demonstration and review. The American Naturalist.
Files and variables
This data repository consists of 5 data files, 1 code script, and this README document, with the following data and code filenames and variables
- Ashman.etal.resSA.csv: Data for the resident population surface area before and after the experiment
- ID: Treatment and sublineage identifier
- Jar: Jar number of that particular experimental unit.
- Treatment: Salt (NaCl) or Control (Con) treatment
- Rep_Tray: Replication block (1-12)
- Final_SA: Final surface area of the resident population in cm^2
- Initial_SA: Initial surface area of the resident population in cm^2
- Ashman.etal.performance.csv: This file has the population dynamics data for the invasion (and monoculture) experiments
- ID: Treatment and sublineage identifier
- Jar: Jar number of that particular experimental unit.
- Inv_status: Whether that jar was invading (Inv) or growing as a monoculture (Mono)
- Treatment: Salt (NaCl) or Control (Con) treatment
- Rep_Tray: Replication block (1-12)
- Lineage: Duckweed lineage (SP.01 or SP.11)
- Focal_sublineage: Duckweed sublineage (SP.01.26, SP.01.10, SP.11.09, SP.11.11)
- Focal_ploidy: Ploidy of that sublineage (2X or 4X)
- Day_of_expt: Day of data collection (individuals added on day 2)
- Fronds_counted: Count of live individuals
- Ashman.etal.body.size.csv: Data file with individual surface area data
- ID: Treatment and sublineage identifier
- Jar: Jar number of that particular experimental unit.
- Treatment: Salt (NaCl) or Control (Con) treatment
- Rep_Tray: Replication block (1-12)
- Resident_ploidy: Ploidy of the residents (2X or 4X)
- Cluster: From which cluster was this individual measured
- Lineage: Duckweed lineage (SP.01 or SP.11)
- Daugther_1_area: Surface area of the first daughter in cm^2 in that cluster
- Daugther_2_area: Surface area of the second daughter in cm^2 in that cluster
- Ashman.etal.salt.pilot.TableS1data.csv: Data for the salt pilot experiment for Table S1
Lineage: Duckweed lineage (SP.01 or SP.11)
Ploidy: Ploidy of that sub lineage (2X or 4X)
Salt_Concentration_mM: 0 or 10 mM of NaCl
Rep: Replicate
Pilot.Jar: Jar number of that particular experimental unit.
Day: Experimental Day
Julian_date: Date of data collection
Frond_count: Count of live individuals - 3 photos were missing and thus there are no counts
- Ashman.etal.BootstrapGR.RData Bootstrapped growth rates, to help the script run faster. The code used to generate it is commented out in the script.
Code scripts and workflow
Ashmanetal.Recip.Salt.Analysis.Rmd: R Markdown file, Knitting the script produces an HTML file with all figures and analyses found in the manuscript.
OUTPUT
- Ashmanetal.Recip.Salt.Analysis.html: Rendered HTML R markdown output
- coex_metrics_table.html: Table S3 - Comparison of Coexistence Metrics
SOFTWARE VERSIONS
R version 4.6.0 (2026-04-24)
Packages
dplyr_1.2.1
tidyr_1.3.2
nlme_3.1-169
lme4_2.0-1
emmeans_2.0.3
car_3.1-5
gt_1.3.0
ggh4x_0.3.1
ggplot2_4.0.3
ggridges_0.5.7
REFERENCES
None
