Data and code from: Differences in stomatal conductance between leaf shape genotypes of Ipomoea hederacea suggest divergent ecophysiological strategies
Data files
May 13, 2026 version files 29.20 KB
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README.md
1.98 KB
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Singhal2025_Ihederacea_data.csv
4.96 KB
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Singhal2025_Ihederacea.R
7.28 KB
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Singhal2025_KSR_weather_data.csv
10.97 KB
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Singhal2025_README.txt
1.77 KB
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Singhal2025_weather.R
2.24 KB
Abstract
Intraspecific variation in leaf shape affects many physiological processes but its impact on plant distribution is underexplored. Using a common garden, we studied daytime thermoregulation of lobed and entire leaf genotypes of Ipomoea hederacea, which displays a latitudinal leaf shape cline. Both leaf shapes maintained similar temperatures but entire leaf genotypes had significantly increased stomatal conductance in warmer/sunnier weather. With less potential water loss, lobed genotypes may have advantages in drier conditions. Lobed genotypes are more common in the north of the species’ range, which receives less summer precipitation, suggesting water availability as a potential clinally varying selective agent.
This README file was generated on 2026-04-27 by Yash Kumar Singhal
Yash Kumar Singhal, Julia Anne Boyle, and John R. Stinchcombe
Published: February 2025
Data Collection: July 2024
Description of the data and file structure
Files and variables
File: Singhal2025_Ihederacea_data.csv
Description: Raw data for leaf ecophysiology
Variables:
- cond = Leaf stomatal conductance (mmol/m2s)
- temp = Leaf temperature (deg C)
- col and row = column and row in spatial grid
- quad = quadrant specified by column and row
- shape = leaf shape (L = Lobed, E = Entire)
- day = day of measurement (July 24th or 26th, 2024), displayed on plots as "weather"
File: Singhal2025_Ihederacea.R
Description: R file for main plots and statistical analysis shown in figure 1.
Uses data and field names from Singhal2025_Ihederacea_data.csv loaded in as data frame named "all"
Note: The p value for effect of day/weather on stomatal conductance generated by the linear model was erroneously recorded as <0.001 on fig 1.d while it is actually 0.0274. The interpretation of all results remains the same.
File: Singhal2025_KSR_weather_data.csv
Description: Weather data from KSR weather station for sampling periods
- day = July 24th or 26th, 2024
- min of the day = timestamp (minute since 0000)
- par = PAR, photosynthetically active radiation (uE)
- temp = air temperature (deg C)
- pressure = air pressure (mBAR)
- wind speed = (m/s)
- gust speed = (m/s)
Note: There was no precipitation recorded during the sampling interval on either day.
File: Singhal2025_weather.R
Description: R file for weather data analysis in table 1.
Uses data and field names from Singhal2025_KSR_weather_data.csv loaded in as data frame named "all"
