GithubHelp home page GithubHelp logo

gregor-fausto / clarkia-bet-hedging Goto Github PK

View Code? Open in Web Editor NEW
0.0 1.0 0.0 4.03 MB

Scripts associated with manuscript "Bet hedging is not sufficient to explain germination patterns of a winter annual plant" (Siegmund et al.)

License: MIT License

R 100.00%

clarkia-bet-hedging's Introduction

clarkia-bet-hedging

Bet hedging is not sufficient to explain germination patterns of a winter annual plant.

Authors

  • Gregor-Fausto Siegmund, Cornell University, [email protected], [email protected]
  • David A. Moeller, University of Minnesota
  • Vincent M. Eckhart, Grinnell College
  • Monica A. Geber, Cornell University

This repository contains the scripts for the project on bet hedging in Clarkia xantiana ssp. xantiana.

DOI 2nd release, associated with resubmission of manuscript after one round of peer review. DOI 1st release, associated with first submission of manuscript.


Abstract

Bet hedging consists of life history strategies that buffer against environmental variability by trading off immediate and long-term fitness. Delayed germination in annual plants is a classic example of bet hedging, and is often invoked to explain low germination fractions. We examined whether bet hedging explains low and variable germination fractions among 20 populations of the winter annual plant Clarkia xantiana ssp. xantiana that experience substantial variation in reproductive success among years. Leveraging 15 years of demographic monitoring and 3 years of field germination experiments, we assessed the fitness consequences of seed banks and compared optimal germination fractions from a density-independent bet-hedging model to observed germination fractions. We did not find consistent evidence of bet hedging or the expected trade-off between arithmetic and geometric mean fitness, though delayed germination increased long-term fitness in 7 of 20 populations. Optimal germination fractions were 2 to 5 times higher than observed germination fractions, and among-population variation in germination fractions were not correlated with risks across the life cycle. Our comprehensive test suggests that bet hedging is not sufficient to explain the observed germination patterns. Understanding variation in germination strategies will likely require integrating bet hedging with complementary forces shaping the evolution of delayed germination.


Contributions

GS and MAG conceived of the ideas and analysis, using data collected by MAG, VME, and DAM. GS wrote the scripts, analyzed the data, and wrote the manuscript with input from MAG. All authors contributed critically to drafts of the manuscript.


Repository Directory

The repository is organized so that the analyses in the paper can be replicated.

  • data: Contains data used in the study. The data files listed below are found in a Dryad repository: https://doi.org/10.5061/dryad.np5hqbzx4. Contents of data files are documented further down in the README, as well as a README in the data repository.
    • metadata
      • attributes.csv: Describes the variables for all data files.
      • creators.csv: Documents the creators of the data files.
    • countFruitsPerPlantAllPlants.csv
    • countFruitsPerPlantFromPermanentPlots.csv
    • countSeedPerFruit.csv
    • countUndamagedDamagedFruitsPerPlantAllPlants.csv
    • countUndamagedDamagedFruitsPerPlantFromPermanentPlots.csv
    • seedBagsData.csv
    • seedlingFruitingPlantCountsPermanentPlots.csv
    • siteAbioticData.csv
    • springPrecipitationData.csv
    • viabilityData.csv
    • README.md: README file for the data folder.
  • models: Contains the statistical models written in JAGS language.
  • outputs: Folder to save output from R scripts.
  • products: Folder to save figures and diagrams for manuscript.
  • scripts: Contains R scripts to process data, fit models, and analyze output.
    • 001_prepareDataForModels: scripts to prepare data for model fitting
    • 002_fitStatisticalModels: scripts to fit statistical models
    • 003_runStatisticalModelDiagnostics: scripts to run model diagnostics
    • 004_checkStatisticalModels: scripts to perform model checks
    • 005_calculatePopulationModelParameters: scripts to calculate parameters for population model
    • 006_testHypotheses: scripts to test hypotheses in the manuscript
    • 007_createFiguresDiagramsTables: scripts to create figures, diagrams, and some tables for paper
    • 008_exploratoryAnalysis: scripts to run exploratory analyses conducted during peer review

Running primaryScript.R in the appropriate directory will create the folders outputs and products with the following file structure. Note that replicating the simulation and model fitting may be slow. We recommend testing the code in 003_statisticalModelFitting on a smaller number of replicates than the default.

  • outputs: Folder for output of simulations and model fitting
    • 001_prepareDataForModels: holds data in format ready for fitting models with JAGS
    • 002_fitStatisticalModels: holds (1) data used to fit models and (2) posterior samples obtained via MCMC
    • 003_runStatisticalModelDiagnostics: holds trace plots and histograms of R-hat
    • 004_checkStatisticalModels: holds PDFs of model checks
    • 005_calculatePopulationModelParameters: holds (1) posterior samples of the statistical model parameters and derived quantities including (2) parameters of the population model in lists, (3) parameters of the population model in matrices, and (4) computed annual values for per-capita reproductive success
    • 006_hypothesisTesting: holds files with optimal germination fractions and results of demographic bet hedging test
    • 007_createFiguresDiagrams: holds shapefiles for creating the map in Figure 1
    • 008_sampleSizeSummaries: holds text files summarizing sample sizes of datasets
    • 009_exploratoryAnalysis: holds text files related to the exploratory analyses conducted during peer review
  • products: Folder for figures
    • figures: directory to hold figures produced by scripts

Data

The data associated with the scripts in this Github folder are archived in the following Dryad repository: https://doi.org/10.5061/dryad.np5hqbzx4. Once the data files from the Dryad repository are downloaded, they should be added to the data folder. The contents of the data files are documented here.

Briefly, we used field surveys and experiments to observe components of above- and below-ground demography for 20 populations across the range of Clarkia xantiana ssp. xantiana. To collect data on seedling survival, fruit production, and seed set, we used field surveys. In each population, these surveys included observations in both permanent plots as well as additional, haphazardly sampled plots arrayed across the population. To observe emergence of seedlings and seeds remaining intact in the soil seed bank, we conducted field experiments, which were complemented with lab experiments in order to assay viability of seeds. Brief details for each dataset are provided here, and the manuscript associated with these datasets describes the survey and experimental methods in further detail.

countFruitsPerPlantAllPlants.csv

Observations of total fruit equivalents per plant from field surveys in 2006-2012. Data come from up to 15 plants per permanent plot, plus plants found across the site. The counts are of “undamaged fruit equivalents” per plant, and were made by counting the number of undamaged fruits, and then counting the damaged fruits and estimating how many undamaged fruits these damaged fruits amounted to.

variableName description
site Site acronym
countFruitNumberPerPlant Count of fruits on a plant; the count combined undamaged and damaged fruits into a single value when fruits were surveyed in the field
permanentPlot Binary variable indicating whether the plant on which fruits were counted was growing in one of 30 permanent plots at the site (1=true) or located in either an additional, haphazardly located plot or found by surveying the site (0=false)
damage Binary variable indicating whether the fruit that was used to count seeds was undamaged (0=false) or damaged (1=true); all observations in this dataset have NA here because the count is of total fruit equivalents
year Year in which observations were made

countFruitsPerPlantFromPermanentPlots.csv

Observations of total fruit equivalents per plant from field surveys in 2007-2012. Data come from up to 15 plants per permanent plot. The counts are of “undamaged fruit equivalents” per plant, and were made by counting the number of undamaged fruits, and then counting the damaged fruits and estimating how many undamaged fruits these damaged fruits amounted to.

variableName description
site Site acronym
transect Transect number
position Plot number
plantNumber Variable indexing the plants on which fruits per plant was recorded; the index starts at 1 in each permanent plot in each year at each site
countFruitsPerPlant Count of fruits on a plant; the count combined undamaged and damaged fruits into a single value when fruits were surveyed in the field
year Year in which observations were made

countSeedPerFruit.csv

Observations of seeds per fruit from seeds collected in the field in 2006-2020. From 2006-2020, data are for counts of seeds per undamaged fruit for up to roughly 30 fruits per site. From 2013-2020, the data also include the counts of seeds per damaged fruit.

variableName description
site Site acronym
year Year in which observations were made
damaged Binary variable indicating whether seeds were counted in a fruit that was undamaged (0=false) or damaged (1=true)
sdno Count of seeds

countUndamagedDamagedFruitsPerPlantAllPlants.csv

Observations of undamaged and damaged fruits per plant from field surveys in 2013-2020. Data come from up to 15 plants per permanent plot, plus plants found across the site. The counts are of “undamaged fruits” and "damaged fruits" on each plant.

variableName description
site Site acronym
countUndamagedFruitNumberPerPlant Count of undamaged fruits on a plant
countDamagedFruitNumberPerPlant Count of damaged fruits on a plant
permanentPlot Binary variable indicating whether the plant on which fruits were counted was growing in one of 30 permanent plots at the site (1=true, 0=false)
year Year in which observations were made

countUndamagedDamagedFruitsPerPlantFromPermanentPlots.csv

Observations of undamaged and damaged fruits per plant from field surveys in 2013-2020. Data come from up to 15 plants per permanent plot. The counts are of “undamaged fruits” and "damaged fruits" on each plant.

variableName description
site Site acronym
transect Transect number
position Plot number
plantNumber Variable indexing the plants on which fruits per plant was recorded; the index starts at 1 in each permanent plot in each year at each site
countUndamagedFruitsPerPlant Count of undamaged fruits on a plant
year Year in which observations were made
countDamagedFruitsPerPlant Count of damaged fruits on a plant

seedBagsData.csv

Observations of intact seeds and germinants from the seed bag burial experiment, conducted from October 2005-October 2008. The experiment consisted of 3 experimental rounds, starting in October 2005, 2006, and 2007. The data in this file includes counts of intact seeds and germinants. The data for the lab component of the seed bag burial experiment is found in viabilityData.csv.

variableName description
site Site acronym
transect Transect number
position Plot number
bagNo Bag number
round Experimental round in which the bag was buried
yearStart Year in which the experimental round started; bags were buried In October of this year
age Number of years the bag had been buried when it was collected from the field in October
yearData Year in which observations were made for this bag; the bag was dug up in January and October of this year
seedlingJan Count of seedlings in the bag when it was dug up in January
intactJan Count of intact, ungerminated seeds in the bag when it was dug up in January
totalJan Sum of the count of seedlings and intact, ungerminated seeds in the bag when it was dug up in January
intactOct Count of intact seeds in the bag when it was dug up in October

seedlingFruitingPlantCountsPermanentPlots.csv

Observations of seedlings and fruiting plants in permanent plots from 2006-2020. Data are counts of seedlings in permanent plots in January/February censuses, and counts of fruiting plants in permanent plots in June/July censuses.

variableName description
site Site acronym
transect Transect number
position Plot number
year Year in which observations were made
seedlingNumber Count of seedlings in 0.5 m x 1 m permanent plot; NA if not recorded
fruitplNumber Count of fruiting plants in 0.5 m x 1 m permanent plot; NA if not recorded

siteAbioticData.csv

Summary of abiotic variables associated with each study site in the long-term study of Clarkia xantiana ssp. xantiana demography.

variableName description
site Site acronym
siteName Full name for site
easting Geographic position reported as eastward measured distance, reported for UTM zone 11, NAD 1927 (units of 100 meters)
northing Geographic position reported as northward measured distance, reported for UTM zone 11, NAD 1927 (units of 100 meters)
elevation Height above sea level (meters)
area Size of the Clarkia xantiana ssp. xantiana population at the study site (hectares)
surfaceRock Dominant soil parent material

springPrecipitationData.csv

Cumulative spring precipitation at each of the study sites and years in the long-term study of Clarkia xantiana ssp. xantiana demography. A full description of the methods used to estimate cumulative precipitation at the study sites is given in the following publication: (Eckhart et al. 2011; https://doi.org/10.1086/661782).

variableName description
site Site acronym
year Year in which observations were made
springPrecipitation Cumulative precipitation from February to June, estimated from daily rainfall measurements at weather stations in the field and interpolated to the location of study populations (units of millimeters)

viabilityData.csv

Observations from lab germination assays and viability assays that are associated with the seed bag burial experiment. The lab experiments were conducted with seeds from seed bags that were recovered from the field in October 2006, 2007, and 2008. The data for the field component of the seed bag burial experiment is found in seedBagsData.csv.

variableName description
site Site acronym
bagNo Bag number
round Experimental round in which the bag was buried
age Number of years the bag had been buried when it was collected from the field in October
block Block number for the Petri dishes used in germination trials
germStart Count of seeds starting the germination trials
germCount Count of seeds germinating over the course of the germination trials
viabStart Count of seeds tested in the viability trials
viabStain Count of seeds staining red in the viability trials

clarkia-bet-hedging's People

Contributors

gregor-fausto avatar

Watchers

 avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.