An official website of the United States government
{"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."]}
more »
« less
Growth chamber reciprocal transplant dataset
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
- PAR ID:
- 10640772
- Publisher / Repository:
- Dryad
- Date Published:
- Edition / Version:
- 3
- Subject(s) / Keyword(s):
- FOS: Natural sciences FOS: Natural sciences phenotypic plasticity adaptive evolution agricultural weeds plasticity-mediated persistence
- Format(s):
- Medium: X Size: 120657 bytes
- Size(s):
- 120657 bytes
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Premise of the StudyNew growth in the spring requires resource mobilization in the vascular system at a time when xylem and phloem function are often reduced in seasonally cold climates. As a result, the timing of leaf out and/or flowering could depend on when the vascular system resumes normal function in the spring. This study investigated whether flowering time is influenced by vascular phenology in plants that flower precociously before they have leaves. MethodsFlower, leaf, and vascular phenology were monitored in pairs of precocious and non‐precocious congeners. Differences in resource allocation were quantified by measuring bud dry mass and water content throughout the year, floral hydration was modelled, and a girdling treatment completed on branches in the field. Key ResultsPrecocious flowering species invested more in floral buds the year before flowering than did their non‐precocious congeners, thus mobilizing less water in the spring, which allowed flowering before new vessel maturation. ConclusionsA shift in the timing of resource allocation in precocious flowering plants allowed them to flower before the production of mature vessels and minimized the significance of seasonal changes in vascular function to their flowering phenology. The low investment required to complete floral development in the spring when the plant vascular system is often compromised could explain why flowers can emerge before leaf out.more » « less
-
We assessed mechanistic temperature influence on flowering by incorporating temperature-responsive flowering mechanisms across developmental age into an existing model. Temperature influences the leaf production rate as well as expression of FLOWERING LOCUS T (FT), a photoperiodic flowering regulator that is expressed in leaves. The Arabidopsis Framework Model incorporated temperature influence on leaf growth but ignored the consequences of leaf growth on and direct temperature influence of FT expression. We measured FT production in differently aged leaves and modified the model, adding mechanistic temperature influence on FT transcription, and causing whole-plant FT to accumulate with leaf growth. Our simulations suggest that in long days, the developmental stage (leaf number) at which the reproductive transition occurs is influenced by day length and temperature through FT, while temperature influences the rate of leaf production and the time (in days) the transition occurs. Further, we demonstrate that FT is mainly produced in the first 10 leaves in the Columbia (Col-0) accession, and that FT accumulation alone cannot explain flowering in conditions in which flowering is delayed. Our simulations supported our hypotheses that: (i) temperature regulation of FT, accumulated with leaf growth, is a component of thermal time, and (ii) incorporating mechanistic temperature regulation of FT can improve model predictions when temperatures change over time.more » « less
-
{"Abstract":["Traits conserved across evolutionary time often provide compelling\n examples of key adaptations for a given taxonomic group. Tetradynamy is\n the presence of four long stamens plus two short stamens within a flower\n and is conserved across most of the roughly 4000 species in the mustard\n family, Brassicaceae. While this differentiation in stamens is\n hypothesized to play a role in pollination efficiency, very little is\n known about the potential function of the two stamen types. The present\n study sheds new light on this mystery using wild radish (Raphanus\n raphanistrum), a widespread and well-studied tetradynamous plant. We used\n data collected from slow-motion videos of pollinators visiting wild radish\n flowers to test three non-mutually exclusive adaptive hypotheses: 1) short\n and long stamens are specialized for either feeding or pollinating, 2)\n short and long stamens are specialized for different pollinator taxa, and\n 3) the presence of short and long stamens increases pollinator movement\n and thus effectiveness. We find evidence consistent with hypothesis three,\n but no evidence for hypotheses one or two. Thus, tetradynamy may be an\n adaptation for generalized pollination, enabling effective visits by the\n variety of pollinators visiting most species of Brassicaceae."],"TechnicalInfo":["# Data from: Testing adaptive hypotheses for an evolutionarily conserved\n trait through slow-motion videos of pollinators The data contained in\n these files was generated from close observation of slow-motion video\n footage by the same experimenter for each variable. ## Description of\n Files ### MainData.csv Data related to slow-motion video analysis,\n including plant information, anther and stigma contact, and number of\n movements Missing data are indicated by "NA" #### Basic Video\n Info in Columns A:F * VideoID: unique individual video identifier *\n PlantID: unique individual plant identifier with the following format -\n "PopulationCode FamilyCode-Replicate" * PopulationCode: BINY =\n natural population, Sep = separation-selected, Exsertion =\n exsertion-selected * FamilyCode: unique 3-5 character code for a given\n maternal seed family * Replicate: individual plant number between 0 and 9,\n where replicate 0 is indicated by the lack of a hyphen and number * Date:\n date of observations * Year: year of observations * Pollinator: taxa of\n visiting pollinator * VideoLength: total length of visit in 1/8 real-time\n seconds #### Feeding Info in Columns G:N * G:K are binary columns in which\n 1 indicates the visit included foraging in the given category, 0 indicates\n lack of foraging, and ? indicates uncertainty ("Short" = short\n stamen anthers, "Long" = long stamen anthers) * L:N summarize\n the info from G:K in different ways * Foraging: whether the visit included\n foraging on nectar, pollen, or both * Feed_All: for visits including\n pollen-foraging, whether foraging was on short stamen anthers, long stamen\n anthers, or both * Feed_Bin: same as Feed_All but groups "Long"\n and "Short" into "One" #### Contact Info in Columns\n O:AM Columns have the following format:\n "ResponseVariable_BodySection_FlowerPart" * ResponseVariable is\n what kind of contact is being recorded and can take three values: * sec:\n duration of contact in 1/8 real-time seconds * bin: binary contact, 1 =\n contacted and 0 = not contacted * n: count of body sections contacted\n (sums binary contact with Legs, Ventral, Side) * BodySection is the part\n of the pollinator body contacted and can take four values: Ventral, Side,\n Legs, or Total (sum of prior 3) * FlowerPart is the part of the flower\n contacted by the pollinator and can take 4 values: S (short stamen\n anthers), L (long stamen anthers), Stigma, or Anthers (both short and long\n stamen anthers) #### Movement Info in Columns AN:AR * Between_Moves: # of\n movements from feeding on one stamen to another * Within_Moves: # of\n movements within stamen types, combining movements from long to long\n stamen ("Long.Long_Moves") and movements from short to short\n stamen ("Short.Short_Moves") * Total_Moves: total # of movements\n from one stamen to another ### DyeSwab.csv Data from small preliminary\n test in which 3 bees were swabbed with gelatin cubes after visiting\n flowers with short and long stamens marked with different colors of\n fluorescent dye. * ID: unique individual bee identifier * BodySection: the\n body section swabbed * NParticles: count of dye particles contained in\n gelatin swab * StamenType: type of stamen matching the color of counted\n particles ### Final_Analysis_Dryad.R R script of all analyses used in the\n paper. * Details provided as comments within script. * The script was run\n in RStudio running R v. 4.4.2."]}more » « less
-
Abstract Many attachments to a scanning electron microscope (SEM), such as energy dispersive x‐ray spectroscopy, extend its function significantly. Typically, the application of such attachments requires that the specimen has a planar surface at a specific orientation. It is a challenge to make the plane of a microscale specimen satisfy the orientation requirement since they are visible only in an SEM. An in‐situ procedure is needed to adjust specimen orientation by using stage rotation and tilting functions, in the process of which the key is to determine the initial orientation. This study proposed and tested top‐down and side‐view approaches to determine the orientation of a planar surface inside an SEM. In the top‐down one, the projected area is monitored on SEM images as stage rotation and tilt angles are adjusted. When the surface normal is along the electron beam direction, the area has a maximum value. In the side‐view approach, the stage is adjusted so that the projection appears to be a straight horizontal line on the SEM image. Once the orientation of the specimen for top‐down or side‐view observation is determined, the original can be calculated, and a desired orientation can be realized by manipulating the stage. The procedures have been tested by analyzing planar surfaces of spherical particles in Al‐Cu‐Fe alloy in the form of facets. The measured angles between two surfaces are consistent with those expected from crystallographic consideration within 2.7° and 1.7° for the top‐down and side‐view approaches, respectively. Research HighlightsTop‐down and side‐view approaches have been proposed and tested for in‐situ determination of specimen planar surface orientation in a Scanning Electron Microscope.The measured angles between two surfaces are consistent with those expected from crystallographic consideration within 2.7° and 1.7° for the top‐down and side‐view approaches, respectively.more » « less
