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Abstract Evolutionary adaptation can allow a population to persist in the face of a new environmental challenge. With many populations now threatened by environmental change, it is important to understand whether this process of evolutionary rescue is feasible under natural conditions, yet work on this topic has been largely theoretical. We used unique long-term data to parameterize deterministic and stochastic models of the contribution of 1 trait to evolutionary rescue using field estimates for the subalpine plant Ipomopsis aggregata and hybrids with its close relative I. tenuituba. In the absence of evolution or plasticity, the 2 studied populations are projected to go locally extinct due to earlier snowmelt under climate change, which imposes drought conditions. Phenotypic selection on specific leaf area (SLA) was estimated in 12 years and multiple populations. Those data on selection and its environmental sensitivity to annual snowmelt timing in the spring were combined with previous data on heritability of the trait, phenotypic plasticity of the trait, and the impact of snowmelt timing on mean absolute fitness. Selection favored low values of SLA (thicker leaves). The evolutionary response to selection on that single trait was insufficient to allow evolutionary rescue by itself, but in combination with phenotypic plasticity it promoted evolutionary rescue in 1 of the 2 populations. The number of years until population size would stop declining and begin to rise again was heavily dependent upon stochastic environmental changes in snowmelt timing around the trend line. Our study illustrates how field estimates of quantitative genetic parameters can be used to predict the likelihood of evolutionary rescue. Although a complete set of parameter estimates are generally unavailable, it may also be possible to predict the general likelihood of evolutionary rescue based on published ranges for phenotypic selection and heritability and the extent to which early snowmelt impacts fitness.
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Data for: Predicting the contribution of single trait evolution to rescuing a plant population from demographic impacts of climate change
{"Abstract":["Evolutionary adaptation can allow a population to persist in the face of a\n new environmental challenge. With many populations now threatened by\n environmental change, it is important to understand whether this process\n of evolutionary rescue is feasible under natural conditions, yet work on\n this topic has been largely theoretical. We used unique long-term data to\n parameterize deterministic and stochastic models of the contribution of\n one trait to evolutionary rescue using field estimates for the subalpine\n plant Ipomopsis aggregata and hybrids with its close relative I.\n tenuituba. In the absence of evolution or plasticity, the two studied\n populations are projected to go locally extinct due to earlier snowmelt\n under climate change, which imposes drought conditions. Phenotypic\n selection on specific leaf area (SLA) was estimated in 12 years and\n multiple populations. Those data on selection and its environmental\n sensitivity to annual snowmelt timing in the spring were combined with\n previous data on heritability of the trait, phenotypic plasticity of the\n trait, and the impact of snowmelt timing on mean absolute fitness.\n Selection favored low values of SLA (thicker leaves). The evolutionary\n response to selection on that single trait was insufficient to allow\n evolutionary rescue by itself, but in combination with phenotypic\n plasticity it promoted evolutionary rescue in one of the two populations.\n The number of years until population size would stop declining and begin\n to rise again was heavily dependent upon stochastic environmental changes\n in snowmelt timing around the trend line. Our study illustrates how field\n estimates of quantitative genetic parameters can be used to predict the\n likelihood of evolutionary rescue. Although a complete set of parameter\n estimates are generally unavailable, it may also be possible to predict\n the general likelihood of evolutionary rescue based on published ranges\n for phenotypic selection and heritability and the extent to which early\n snowmelt impacts fitness."],"Methods":["The study sites consisted of three “Poverty Gulch” sites in\n Gunnsion National Forest and one site “Vera Falls” at the Rocky Mountain\n Biological Laboratory, all in Gunnison County, CO, USA. Focal plants\n included two sets of plants. One set (data from 2009-2019) consisted of\n plants in common gardens at three sites: an I. aggregata\n site (hereafter “agg”), an I. tenuituba\n site (hereafter “ten”) and a site at the center of the natural\n hybrid zone (hereafter “hyb”). The second set consisted of plants growing\n in situ at two of the same Poverty Gulch sites (“agg” and “hyb”), and\n an I. aggregata site at Vera Falls (hereafter “VF”;\n data from 2017-2023). The common gardens were started\n from seed in 2007 and 2008. Measurements of SLA in these gardens began\n when plants were 2 years old, either 2009 or 2010 depending upon the\n garden, as they are only small seedlings during their first summer after\n seed maturation. By 2018, all but 15 of the 4512 plants originally planted\n had died, with or without blooming, and we stopped following these\n gardens. Starting in 2017, in situ vegetative plants at the I.\n aggregata site and the hybrid site whose longest leaf exceeded\n 25 mm were marked with metal tags to facilitate\n identification. In each year of the study, one leaf\n from each vegetative plant was collected in the field and transported on\n ice to the RMBL, 8 km distant. There each leaf was scanned with a flatbed\n scanner and analyzed using ImageJ to measure leaf area. The leaf was dried\n at 70 deg C for 2 hours and then weighed to obtain dry mass and calculate\n SLA as area/dry mass. For plants in the common gardens, SLA was measured\n on 982 leaves from 383 plants in 2009 – 2014. For in situ plants, SLA was\n measured on one leaf from each of 877 plants in 2017 – 2022. Fitness was\n estimated as the binary variable of survival to flowering. Plants that\n were still alive in 2019 in the common gardens or in 2023 at the end of\n the study were assumed to survive to flowering. These\n data were used to estimate selection differentials on SLA in each of 12\n years. We then combined this information with previous information on\n heritability and the effect of snowmelt date in the spring on mean\n absolute fitness, measured as the finite rate of population increase, from\n a previous demographic study. This information was used to parameterize\n models of evolutionary rescue that we developed. We developed two models\n that differed in how snowmelt timing changed: a Step-change model and a\n Gradual environmental change model and analyzed both deterministic and\n stochastic versions. All analysis and modeling was done in R ver\n 4.2.2. "],"TechnicalInfo":["# Data for: Predicting the contribution of single trait evolution to\n rescuing a plant population from demographic impacts of climate change\n Dataset DOI: [10.5061/dryad.ht76hdrtn](10.5061/dryad.ht76hdrtn) ##\n Description of the data and file structure File\n "mastervegtraitsSLA2023.csv" contains data on specific leaf area\n for Ipomopsis plants in the field. Files\n "masterdemography_insitu_2023.csv" and\n "masterdemography_commongarden.csv" provide the corresponding\n information on survival to flowering. File "snowmelt.csv"\n provides dates of snowmelt in the spring. File\n "selection_vs_snowmelt.csv" provides intermediate results on\n selection intensities from analysis with the first parts of the code\n "Campbell-EvolutionLettersMay2025.Rmd". File\n "IPMresults.csv" provides estimates of the finite rate of\n increase (lambda) predicted from the publication by Campbell\n [https://doi.org/10.1073/pnas.1820096116](https://doi.org/10.1073/pnas.1820096116) File "Campbell-EvolutionLettersMay2025.Rmd" provides the R code for statistical analysis and the deterministic and stochastic models of evolutionary rescue. All data analysis and modeling was done in R ver. 4.4.2 on a Windows machine. All necessary input data files are provided. The R code is annotated to indicate which portions produce analyses and figures in the manuscript. For the multipart figures 6-9 the code needs to be manually updated to produce each part of the figure before assembling them. In those cases, each part represents a model with a unique set of parameters. ### Files and variables #### File: Data\\_files\\_for\\_EVL\\_Campbell\\_2025.zip **Description:** All data files Blank cells are indicated by "." except in "selection_vs_snowmelt.csv" where they are indicated by "NA" **File:** mastervegtraitsSLA2023.csv * meltday = first day of bare ground at the Rocky Mountain Biological Lab (RMBL) in units of days starting with January 1 * year = year * site = site. agg = site with I. aggregata. hyb = site with natural hybrids. ten = site with I. tenuituba. VF = Vera Falls site containing I. aggregata. * idtag = metal tag used to identify plant * planttype = type of plant. AA = progeny of I. aggregata x I. aggregata. AT = progeny of I. aggregata x I. tenuituba. TA = progeny of I. tenuituba x I. aggregata. TT = progeny of I. tenuituba x I. tenuituba. F2 = progeny of F1 (either AT or TA) x F1. agg = natural I. aggregata. hyb = natural hybrid. * sla = specific leaf area in units of cm2/g * uniqueid = an id used to identify the plant uniquely across all years and sites **File:** masterdemography\\_insitu\\_2023.csv * site = site. agg = site with I. aggregata. hyb = site with hybrids. VF = Vera Falls site containing I. aggregata. * idtag = metal tag used to identify plant * yeartagged = year the plant was first tagged * flrlabelxx = label for plants flowering in year 20xx * stagexxxx = stage in year xxxx. 0 = dead. 1 = single vegetative rosette. 2 = single inflorescence. 3 = multiple vegetative rosette. 4 = multiple inflorescence. * lengthxx = length of longest leaf in year 20xx in mm * leavesxx = number of leaves in rosette(s) in year 20xx **File:** masterdemography_commongarden.csv * site = site. agg = site with I. aggregata. hyb = site with natural hybrids. ten = site with I. tenuituba. * IDTAG = metal tag used to identify plant * Planttype = type of plant. AA = progeny of I. aggregata x I. aggregata. AT = progeny of I. aggregata x I. tenuituba. TA = progeny of I. tenuituba x I. aggregata. TT = progeny of I. tenuituba x I. tenuituba. F2full = full-sib progeny of F1 (either AT or TA) x F1. F2non = non full-sib progeny of F1 x F1. * stagexx = stage of plant in year 20xx. 0 = dead. 1 = single vegetative rosette. 2 = single inflorescence. 3 = multiple vegetative rosette. 4 = multiple inflorescence. * lengthxx = length of longest leaf in year 20xx in mm. * leavesxx = number of leaves in rosette(s) in year 20xx. **File:** snowmelt.csv * Year = year * Snowmelt = day of first bare ground at the RMBL in units of day starting with January 1. Values prior to 1975 were estimated. **File:** selection*vs*snowmelt.csv * meltday = day of first bare ground at the RMBL in units of day starting with January 1. * year = year * Sbyyearwithsite = standardized selection differential on SLA in model that includes site. These values are reproduced with standard errors in Table 1. * bwithsite = regression coefficient for raw survival on raw SLA in model that includes site. * meansurv = mean survival * covwsla = raw selection differential on SLA * bwithsitehyb = regression coefficient for raw survival on SLA at site hyb * meansurvhyb = mean survival at site hyb * covwslahyb = raw selection differential on SLA at site hyb used in the Gradual environmental change model * covwslaagg = raw selection differential on SLA at site agg used in the Gradual environmental change model * meansurvagg = mean survival at site agg * melthyb = estimated date of bare ground at site hyb * meltagg = estimated date of bare ground at site agg **File:** IPMresults.csv * site = site. agg = site with I. aggregata. hyb = site with natural hybrids. * day = predicted day of snowmelt (all predictions are from Campbell, D. R. 2019. Early snowmelt projected to cause population decline in a subalpine plant. PNAS (USA) 116(26) 1290-12906.) Units are days starting with January 1. * lambda = predicted finite rate of increase **File:** Campbell-EvolutionLettersMay2025.Rmd Contains R code for data analysis and modeling. All analysis and modeling was done in R ver 4.2.2."]}
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- PAR ID:
- 10652967
- Publisher / Repository:
- Dryad
- Date Published:
- Edition / Version:
- 3
- Subject(s) / Keyword(s):
- cimate change Natural selection phenotypic plasticity Plants FOS: Biological sciences FOS: Biological sciences
- Format(s):
- Medium: X Size: 39183 bytes
- Size(s):
- 39183 bytes
- Sponsoring Org:
- National Science Foundation
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Summary Vegetative traits of plants can respond directly to changes in the environment, such as those occurring under climate change. That phenotypic plasticity could be adaptive, maladaptive, or neutral.We manipulated the timing of spring snowmelt and amount of summer precipitation in factorial combination and examined responses of specific leaf area (SLA), trichome density, leaf water content (LWC), photosynthetic rate, stomatal conductance and intrinsic water‐use efficiency (iWUE) in the subalpine herbIpomopsis aggregata. The experiment was repeated in three years differing in natural timing of snowmelt. To examine natural selection, we used survival, relative growth rate, and flowering as fitness indices.A 50% reduction in summer precipitation reduced stomatal conductance and increased iWUE, and doubled precipitation increased LWC. Combining natural and experimental variation, earlier snowmelt reduced soil moisture, photosynthetic rate and stomatal conductance, and increased trichome density and iWUE. Precipitation reduction reversed the mortality selection favoring high stomatal conductance under normal and doubled precipitation, and higher LWC improved growth.Earlier snowmelt is a strong signal of climate change and can change expression of leaf morphology and gas exchange traits, just as reduced precipitation can. Stomatal conductance and SLA showed adaptive plasticity under some conditions.more » « less
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Abstract In ecological speciation, incipient species diverge due to natural selection that is ecologically based. In flowering plants, different pollinators could mediate that selection (pollinator-mediated divergent selection) or other features of the environment that differ between habitats of 2 species could do so (environment-mediated divergent selection). Although these mechanisms are well understood, they have received little rigorous testing, as few studies of divergent selection across sites of closely related species include both floral traits that influence pollination and vegetative traits that influence survival. This study employed common gardens in sites of the 2 parental species and a hybrid site, each containing advanced generation hybrids along with the parental species, to test these forms of ecological speciation in plants of the genus Ipomopsis. A total of 3 vegetative traits (specific leaf area, leaf trichomes, and photosynthetic water-use efficiency) and 5 floral traits (corolla length and width, anther insertion, petal color, and nectar production) were analyzed for impacts on fitness components (survival to flowering and seeds per flower, respectively). These traits exhibited strong clines across the elevational gradient in the hybrid zone, with narrower clines in theory reflecting stronger selection or higher genetic variance. Plants with long corollas and inserted anthers had higher seeds per flower at the Ipomopsis tenuituba site, whereas selection favored the reverse condition at the Ipomopsis aggregata site, a signature of divergent selection. In contrast, no divergent selection due to variation in survival was detected on any vegetative trait. Selection within the hybrid zone most closely resembled selection within the I. aggregata site. Across traits, the strength of divergent selection was not significantly correlated with width of the cline, which was better predicted by evolvability (standardized genetic variance). These results support the role of pollinator-mediated divergent selection in ecological speciation and illustrate the importance of genetic variance in determining divergence across hybrid zones.more » « less
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Anthropogenic nitrogen (N) addition might alter the evolutionary trajectories of plant populations, in part because it alters the abiotic and biotic environment by increasing aboveground primary productivity, light asymmetry, and herbivory intensity, and reducing plant species diversity. Such evolutionary impacts could be caused by N altering patterns of natural selection (i.e., trait-fitness relationships) and the opportunity for selection (i.e., variance in relative fitness). Because at the community level N addition favors species with light acquisition strategies (e.g., tall species), we predict that N would also increase selection favoring those same traits. We also hypothesize that N could alter the opportunity for selection via its effects on mean fitness and/or competitive asymmetries.To investigate these evolutionary consequences of N, we quantified the strength of selection and the opportunity for selection in replicated populations of the annual grass Setaria faberi Herrm. (giant foxtail) growing in a long-term N addition experiment. We also correlated our measures of selection and opportunity for selection with light asymmetry, diversity, and herbivory intensity to identify the proximate causes of any N effects on evolutionary processes. N addition increased aboveground productivity, light asymmetry, and reduced species diversity. Contrary to expectations, N addition did not strengthen selection for trait values associated with higher light acquisition such as greater height and specific leaf area (SLA); rather, it strengthened selection favoring lower SLA. Increased light asymmetry was associated with stronger selection for lower SLA and lower species diversity was associated with stronger selection for greater height and lower SLA, suggesting a role for these factors in driving N-mediated selection. The opportunity for selection was not influenced by N addition (despite increased mean fitness) but was negatively associated with species diversity. Our results indicate that anthropogenic N enrichment can affect evolutionary processes, but that evolutionary changes in plant traits within populations are unlikely to parallel the shifts in plant traits observed at the community level. Data was collected in 2020 from a field experiment in a long-term ecological research site (Kellogg Biological Station LTER site in Michigan, USA). The Data folder contains 3 separate datasets as CSV files, each with accompanying .txt metadata files: 1) a dataset of individual-level data (Waterton2022_NitrogenEvolution_Individual_Data.csv); 2) a dataset of annual net primary productivity (ANPP; Waterton2022_NitrogenEvolution_ANPP_Data.csv); 3) a dataset of light measurements (Waterton2022_NitrogenEvolution_Light_Data.csv). An R script for reproducing the analyses and figures is available at https://doi.org/10.5281/zenodo.7121361. R statistical software is required to run the R script.more » « less
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Phenotypic plasticity can alter traits that are crucial to population\n establishment in a new environment, before adaptation can occur. How often\n phenotypic plasticity enables subsequent adaptive evolution is unknown,\n and examples of the phenomenon are limited. We investigated the hypothesis\n of plasticity-mediated persistence as a means of colonization of\n agricultural fields in one of the world’s worst weeds, Raphanus\n raphanistrum ssp. raphanistrum. Using non-weedy native populations of the\n same species and subspecies as a comparison, we tested for\n plasticity-mediated persistence in a growth chamber reciprocal transplant\n experiment. We identified traits with genetic differentiation between the\n weedy and native ecotypes as well as phenotypic plasticity between growth\n chamber environments. We found that most traits were both plastic and\n differentiated between ecotypes, with the majority plastic and\n differentiated in the same direction. This suggests that phenotypic\n plasticity may have enabled radish populations to colonize and then adapt\n to novel agricultural environments."],"TechnicalInfo":["# Growth Chamber Reciprocal Transplant Dataset\n [https://doi.org/10.5061/dryad.4mw6m90kb](https://doi.org/10.5061/dryad.4mw6m90kb) This dataset contains the phenotypic data collected from plants grown in the growth chamber reciprocal transplant experiment, as well as the conditions in the growth chambers. ## Description of the data and file structure The dataset contains three sheets: "Chamber Conditions", "Main Data", and "Leaf Data" (although much of the information in "Leaf Data" has been incorporated into "Main data") ### Chamber Conditions This sheet contains the temperature and day length set points for each chamber each week. All temperature and day length information from the two weather stations used (LGER and KBTL) were collected from [www.wunderground.com](http://www.wunderground.com). Variables: * Granada, Spain (LGER) - the dates from which we collected temperature and day length information from the Grenada, Spain weather station (LGER) to simulate in the Winter Annual chamber * HighTempGrenada - the Winter Annual chamber's daytime set points, based on the average maximum temperature in Grenada on a given day * LowTempGrenada - the Winter Annual chamber's nighttime set points, based on the average minimum temperature in Grenada on a given day * DayLengthGrenada - the length of time the Winter Annual chamber was in its day cycle (lights on and typically higher temps), based on length of visible light in Grenada * DayStartGrenada - programed start of day time in the Winter Annual growth chamber * DayEndGrenada - programmed end of day time in the Winter Annual growth chamber * Date Set - the real-life date on which we changed the chamber conditions. * Augusta, MI (KBTL) - the dates from which we collected temperature and day length information from the Augusta, MI, USA weather station (KBTL) to simulate in the Spring Annual chamber * HighTempAugusta - the Spring Annual chamber's daytime set points, based on the average maximum temperature in Augusta on a given day * LowTempAugusta - the Spring Annual chamber's nighttime set points, based on the average minimum temperature in Augusta on a given day * DayLengthAugusta - the length of time the Spring Annual chamber was in its day cycle (lights on and typically higher temps), based on length of visible light in Augusta * DayStartAugusta - programed start of day time in the Spring Annual growth chamber * DayEndAugusta - programmed end of day time in the Spring Annual growth chamber ### Main Data This sheet contains all of the data used in our analyses, as well as descriptors for plants and growth chambers. Variables: * Chamber # - the number designation of the four growth chambers used in this study * Environment - the growing conditions in a given growth chamber, with "Winter Annual" corresponding to the "Grenada, Spain (LGER)" columns in Chamber Conditions, and "Spring Annual" corresponding to "Augusta, MI (KBTL)" * Ecotype - variety of* R. raphanistrum*, either weedy or native * Population - the six source populations used in this study identified by their location codes, with the final two letters denoting country or state (FR=France, ES=Spain, NY=New York, NC=North Carolina) and the first two letters denoting a specific location in those areas (available in Table 1 of the manuscript) * Matriline - a line number is listed when discrete matrilines are known from field collections, but not for seeds collected in bulk (in which case the cell will be blank) * Flat - plants were arranged into four flats in each chamber, and the flats within a chamber were each assigned a number (1-4) * Position - the position of each plant within a flat was also tracked and pots were assigned a position number (1-35) * Pot# - Number assigned to each plant to give it a unique identifier -- for plants with individual matrilines tracked, pot # only went up to 2, while plants with unknown matrilines had pot numbers up to 40 to ensure individuals could be tracked * Plant Date - the date seeds were sown into each pot * Germ[1-5] - the date that each one of 5 seeds planted emerged as a germinant -- blank cells indicate that a germinant did not emerge * Plant Kept - the emergence date of the single plant that remained in the pot after excess germinants were thinned; missing values mean no germinants emerged or did not survive past the seedling stage * Days to Emergence - calculated as the day of emergence minus the planting date; missing values mean no germinants emerged or did not survive past the seedling stage * Rosette Photo Date - the date on which overhead and side photos of plants were taken, also the day the plants first showed signs of bolting (buds visible); missing values mean the plant did not survive to bolting * \\# Rosette Leaves - the number of leaves in the basal rosette, counted on the day of bolting; missing values mean the plant did not survive to bolting * Rosette Height - the vertical height of the tallest free-standing basal rosette leaf, measured from the height of the soil (cm); missing values mean the plant did not survive to bolting * 1st flower date - the date on which the first flower on a plant opened; missing values mean the plant did not survive to flowering * Days to First Flower - calculated as 1st flower date minus emergence date; missing values mean the plant did not survive to flowering * 1st Flower Height - measured on the first flower date, it is the vertical distance from the soil to the point at which the first open flower's pedicel connects to the main stalk (cm); missing values mean the plant did not survive to flowering * Ovule # - collected from typically the third flower to open, it is the number of ovules in one flower of a given plant; missing values mean the plant did not survive to flowering or ovules were not clearly visible * Notes - any additional information on a plant that we tracked * Blossom Photo Date - the date on which we took top and side photographs of at least the third flower to open, taken at the same time that ovule number was counted; missing values mean the plant did not survive to flowering * PetalLength - measured using a top-view photo in Image J, the distance from the tip of the petal to where it meets the floral tube in the center of the floral display (mm); missing values mean the plant did not survive to flowering or the view in the photo was obscured so the measurement could not be taken * PetalWidth - measured using a top-view photo in Image J, the distance from the widest part of the petal, perpendicular to the line measured for petal length (mm); missing values mean the plant did not survive to flowering or the view in the photo was obscured so the measurement could not be taken * Tube - measured using a side-view photo in Image J, the length of the most clearly visible petal from where it meets the pedicel to the apex of its curve outward (mm); missing values mean the plant did not survive to flowering or the view in the photo was obscured so the measurement could not be taken * LAnther - measured using a side-view photo in Image J, the length of the anther of the long stamen from where it meets its filament to its tip (mm); missing values mean the plant did not survive to flowering or the view in the photo was obscured so the measurement could not be taken * LFilament - measured using a side-view photo in Image J, the length of the frontmost (closest to the camera) long filament from where it meets the pedicel to where it meets its anther (mm); missing values mean the plant did not survive to flowering or the view in the photo was obscured so the measurement could not be taken * SAnther - measured using a side-view photo in Image J, the length of the anther of the short stamen from where it meets its filament to its tip (mm); missing values mean the plant did not survive to flowering or the view in the photo was obscured so the measurement could not be taken * SFilament - measured using a side-view photo in Image J, the length of the frontmost (closest to the camera) short filament from where it meets the pedicel to where it meets its anther (mm); missing values mean the plant did not survive to flowering or the view in the photo was obscured so the measurement could not be taken * Pistil - measured using a side-view photo in Image J, the length of the pistil made by drawing a line down the center of the pistil from the top of the stigma to where it meets the pedicel (mm); missing values mean the plant did not survive to flowering or the view in the photo was obscured so the measurement could not be taken * AntherExsertion - calculated as long filament length minus the tube length (mm); missing values mean the plant did not survive to flowering or that either one of the values needed for the measurement was missing * AntherSeparation - calculated as long filament length minus the short filament length (mm); missing values mean the plant did not survive to flowering or one or that either one of the values needed for the measurement was missing * FlowerSize - the geometric mean of all floral traits (excluding anther exsertion and anther separation; mm); missing values mean the plant did not survive to flowering or one or more flower trait was missing * LeafWidth - measured using either a top-view or side-view photo in Image J, the distance between each edge of the leaf measured at its widest point, with the line being perpendicular to the central leaf vein on the largest fully visible leaf (more information in the Leaf Data sheet; cm); missing values mean the plant did not survive to bolting or a picture was not taken * LeafLength - measured using either a top-view or side-view photo in Image J using the segmented line tool, follow the central vein of the largest visible leaf from the center of the rosette to the tip of the leaf (more information in the Leaf Data sheet; cm); missing values mean the plant did not survive to bolting or a picture was not taken ### Leaf Data This sheet includes some additional information about Leaf Length and Leaf Width measurements. Side image was only used when leaf was not flat or clearly visible in the top image. Variables: * Top Photo Image - image ID of the top view photo of the plant being measured * Ecotype - the ecotype of the plant (more information in Main Data) * Population - the population that the plant belongs to (more information in Main Data) * Plant Label - the label visible in the image -- includes population, matriline (when available), and pot # * Leaf Width (cm) - measured using the top-view photo in Image J, the distance between each edge of the leaf measured at its widest point, with the line being perpendicular to the central leaf vein on the largest fully visible leaf; missing values mean that a picture was not taken or the leaf was obscured in the top view photo * Leaf Length 1 (cm) - measured using the top-view photo in Image J using the segmented line tool, follow the central vein of the largest visible leaf from the center of the rosette to the tip of the leaf; missing values mean that a picture was not taken or the leaf was obscured in the top view photo * Side Photo Image - Image ID of the side view photo of the plant being measured; side image was only used when leaf was not flat or clearly visible in the top image, so missing values indicate that the length and width of the leaf could be reliably measured using the top view photo * Leaf Length 2 (cm) - measured using the side-view photo in Image J using the segmented line tool, follow the central vein of the largest visible leaf from the center of the rosette to the tip of the leaf; missing values mean that a picture was not taken or that the length of the leaf could be reliably measured using the top view photo * Leaf Width 2 (cm) - measured using the side-view photo in Image J, the distance between each edge of the leaf measured at its widest point, with the line being perpendicular to the central leaf vein on the largest fully visible leaf; missing values mean that a picture was not taken or that the width of the leaf could be reliably measured using the top view photo * Notes - any additional information about the the measurement of a particular plants' leaf length or width"]}more » « less
