A cline within an ecotype of the yellow monkeyflower, Mimulus guttatus
Data files
Aug 08, 2024 version files 172.87 KB
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coord.data.csv
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LH.pops.csv
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mim.complete.csv
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Ocean_Exposure.csv
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README.md
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Zambiasi_Lowry_2024_code_CLEANED.R
Abstract
A key goal of evolutionary biologists is to understand how and why adaptive genetic variation is partitioned within species. In the yellow monkeyflower, Mimulus guttatus (syn. Erythranthe guttata), coastal perennial populations collectively constitute a single genetically and morphologically differentiated ecotype. While the distinctiveness of the coastal ecotype has now been well documented, there is also variation in environmental factors across the range of the coastal ecotype that could drive differentiation among its component populations in a more continuous way. Based on previous observations of a potential cline within this ecotype, we quantified plant height across coastal perennial accessions from 69 total populations in two greenhouse common garden experiments. To evaluate possible environmental factors driving the relationship between plant height and latitude, we regressed height against multiple climatic factors, including temperature, precipitation, and coastal wind speeds. In both experiments, plant height was negatively correlated with latitude. Mimulus height correlated positively with annual precipitation and with mean wind speed, to a lesser degree, and negatively with annual mean temperature. We hypothesize that one or more of these factors drove clinal variation within the coastal ecotype. Overall, our study illustrates the complexity of how the distribution of environmental variation can simultaneously drive the evolution of distinct ecotypes as well as continuous clines within those ecotypes. These results are discussed in the context of the classic criticisms of ecotypes being intermediates in the process of speciation.
README: A cline within an ecotype of the yellow monkeyflower, Mimulus guttatus
https://doi.org/10.5061/dryad.4tmpg4fkh
GENERAL INFORMATION
Paper Citation
Zambiasi, T. and D. Lowry. 2024. A cline within an ecotype of the yellow monkeyflower, Mimulus guttatus. American Journal of Botany.
Author contact information
Thomas Zambiasi: tzambias@iu.edu
David Lowry: dlowry@msu.edu
Date of data collection
Main Experiment (PEFL): Fall/Early Winter 2019
Pilot Experiment (HonorsOpt): Fall 2019
Geographic location of data collection
Main Experiment (PEFL): Plant Ecology Field Lab greenhouse, Kellogg Biological Station, Hickory Corners, MI
Pilot Experiment (HonorsOpt): Plant Science Greenhouses, Michigan State University, East Lansing, MI
ACCESS INFORMATION
NA
DATA FILES AND VARIABLES
1. mim.complete.csv
File listing M. guttatus phenological and morphological measurements for individual plants grown in both pilot and main studies
- Experiment: factor indicating the experiment in which each plant was grown. PEFL = main experiment, HonorsOpt = pilot experiment
- Pop.: three-letter code for each M. guttatus population
- Line: number identifying the maternal line that each individual came from
- Inbred: factor identifying which selfing generation that individual was planted from. F = seeds collected from the field, G# = 1st, 2nd, 3rd (etc.) generation of selfing, ? = generation unknown, BLANK = seed envelope did not have a generation written, OP = Open Pollinated (likely selfed, but not done manually)
- Tray: number ID of the tray that each individual was kept in within the greenhouse
- Germination: date of first recorded germination (in spreadsheet's numerical format)
- Flower Day: date of first recorded flower opening (in spreadsheet's numerical format)
- FloweringTime: number of days between Flower Day and Germination for each individual
- Height: height of each plant at the time of first flower (in cm)
- Width: width of the second set of true leaves (PEFL, in cm) or stem (HonorsOpt, in mm)
- INL 1: length of the plant's first internode (HonorsOpt, in cm; PEFL, in mm)
- INL 2: length of the plant's second internode (HonorsOpt, in cm; PEFL, in mm)
- INL 3: length of the plant's third internode (HonorsOpt, in cm; PEFL, in mm)
- INL 4: length of the plant's fourth internode (HonorsOpt, in cm; PEFL, in mm)
- Corolla_W: corolla width for the first flower of each individual (only PEFL; in mm)
- Corolla_L: corolla length for the first flower of each individual (only PEFL; in mm)
- CalyxSpt: number of spots on the calyx of each individual's first flower (only PEFL)
- StolonNum: number of stolons growing from each individual (only PEFL)
NOTE: Any instances of "NA" in any cells mean "not available" and are used where certain data were not collected (corolla, calyx, and stolon info in HonorsOpt data), could not be collected (e.g., internode lengths on shorter plants), or were otherwise unavailable.
2. coord.data.csv
File listing the locations of origin (collection locations) for each of the M. guttatus populations.
- PopCode: three-letter code for each M. guttatus population
- Latitude: latitude of origin for the given M. guttatus population
- Longitude: longitude of origin for the given M. guttatus population
3. LH.pops.csv
File listing each M. guttatus population and its life history
- PopCode: three-letter code for each M. guttatus population
- LifeHistory: factor describing the life history of each M. guttatus population. A = annual, P = perennial, A/P = can be either
4. Ocean_Exposure.csv
File listing the population codes for each M. guttatus population, their distance from the ocean, and a binary indicator of whether they were exposed to the ocean or protected.
- Population Name: three-letter code for each M. guttatus population
- Distance from the beach (m): distance from the population collection site to the beach (in meters)
- Exposed to Open Ocean: a binary indicator of whether a population was exposed to the ocean or not. 0 indicates a protected population, and 1 indicates an exposed population.
- Notes: column containing notes about how some populations were protected, location information, etc.
- PopCode: three-letter code for each M. guttatus population
- Latitude: latitude of origin for the given M. guttatus population
- Longitude: longitude of origin for the given M. guttatus population
NOTE: Many cells in the notes column have been left blank because there was no additional information to include for those populations. Other cells in other columns may be labeled as "NA", meaning "not available". These NAs have been included when we lacked data (such as distance from shore, exposure, or geographic coordinates) for any of the listed populations.
ADDITIONAL DATA NOTES:
1. Our analyses included data detailing the average monthly wind speeds at the latitudes of origin for each M. guttatus population, in a file we named popwind.csv. These data were collected from the NREL Wind Prospector online tool; the original version of this tool was taken offline, but similar information can be gathered from the linked site (https://wrdb.nrel.gov/data-viewer) using the WIND Toolkit dataset to look at wind speed (m/s). Below, we've listed the columns that were in our dataset as an example of how we set up the data to work with our code.
- Latitude: latitude of origin of each M. guttatus population
- windJan: average wind speed (m/s) in January at the given latitude
- windFeb: average wind speed (m/s) in February at the given latitude
- windMarch: average wind speed (m/s) in March at the given latitude
- windApril: average wind speed (m/s) in April at the given latitude
- windMay: average wind speed (m/s) in May at the given latitude
- windJune: average wind speed (m/s) in June at the given latitude
- windJuly: average wind speed (m/s) in July at the given latitude
- windAug: average wind speed (m/s) in August at the given latitude
- windSept: average wind speed (m/s) in September at the given latitude
- windOct: average wind speed (m/s) in October at the given latitude
- windNov: average wind speed (m/s) in November at the given latitude
- windDec: average wind speed (m/s) in December at the given latitude
NOTE: Some cells we labeled in our file as "NA", meaning "not available". Because the NREL dataset only included wind speeds for locations in the contiguous United States, we filled rows with "NA" for any latitudes not within the scope of the NREL data.
2. Our analyses also included Bioclim data we downloaded from WorldClim (Fick and Hijmans 2017). However, the getData() function we used to import the data into R will not be present in future versions of the raster package, so R should suggest the package geodata as a workaround. The existing code in the BIOCLIM DATA section of our script should still work so long as Bioclim data has been downloaded for the specific coordinates of the populations we used in this experiment. We have left our original code intact in the included script because it worked with the versions of R and the packages that we had, as well as to show what we originally did.
More specific details about the Bioclim variables can be found online (https://www.worldclim.org/data/bioclim.html#google_vignette), but we will briefly list what each variable number represents here:
- 1: annual mean temperature
- 2: mean daytime temperature range
- 3: isothermality
- 4: temperature seasonality
- 5: warmest month's maximum temperature
- 6: coldest month's minimum temperature
- 7: annual temperature range
- 8: wettest quarter's mean temperature
- 9: driest quarter's mean temperature
- 10: warmest quarter's mean temperature
- 11: coldest quarter's mean temperature
- 12: annual precipitation
- 13: wettest month's precipitation
- 14: driest month's precipitation
- 15: precipitation seasonality
- 16: wettest quarter's precipitation
- 17: driest quarter's precipitation
- 18: warmest quarter's precipitation
- 19: coldest quarter's precipitation
CODE SCRIPTS AND WORKFLOW
1. Zambiasi_Lowry_2024_code_CLEANED.R
R script containing all steps to data cleaning, analysis, and visualization for the experiments and results described in Zambiasi and Lowry (2024)
SOFTWARE VERSIONS
R, v4.2.1 (R Core Team 2022)
R Studio, 2023.12.0+369 "Ocean Storm" Release (Posit Team 2023)
loaded packages:
- dplyr: v1.1.2
- ggplot2: v3.5.0
- viridis: v0.6.2
- DHARMa: v0.4.6
- kableExtra: v1.4.0
- webshot2: v0.1.1
- magick: v2.8.3
- writexl: v1.5.0
- tibble: v3.2.1
- lme4: v1.1-35.1
- lmerTest: v3.1-3
- Matrix: v1.6-5
- car: v3.1-2
- stats: v4.2.1
- plyr: v1.8.9
- tidyr: v1.3.1
- nlme: v3.1-157
- reshape2: v1.4.4
- raster: v3.6-26
- sp: 2.1-3
- devtools: v2.4.5
- colorRamps: v2.3.4
- Hmisc: v5.1-2
- gridExtra: v2.3
- geodata: v0.5-9
- corrplot: v0.92
- sf: v1.0-15
- rnaturalearth: v1.0.1
- rnaturalearthdata: v1.0.0
- cowplot: v1.1.3
- googleway: v2.7.8
- ggrepel: v0.9.5
- ggspatial: v1.1.9
- rgeos: v0.6-1
- maps: v3.4.2
- factoextra: v1.0.7
- base: v4.2.1
- datasets: v4.2.1
- graphics: v4.2.1
- grDevices: v4.2.1
- methods: v4.2.1
- utils: v4.2.1
REFERENCES
- Draxl, C., B. M. Hodge, A. Clifton, and J. McCaa. 2015a. Overview and Meteorological Validation of the Wind Integration National Dataset Toolkit (Technical Report, NREL/TP-5000-61740). National Renewable Energy Laboratory, Golden, CO, USA.
- Draxl, C., B. M. Hodge, A. Clifton, and J. McCaa. 2015b. The Wind Integration National Dataset (WIND) Toolkit. Applied Energy 151: 355-366.
- Fick, S. E., and R. J. Hijmans. 2017. WorldClim 2: new 1km spatial resolution climate surfaces for global land areas. International Journal of Climatology 37: 4302-4315.
- King, J., A. Clifton, and B. M. Hodge. 2014. Validation of Power Output for the WIND Toolkit (Technical Report, NREL/TP-5D00-61714). National Renewable Energy Laboratory, Golden, CO, USA.
- Posit Team. 2023. RStudio: Integrated Development Environment for R. Posit Software, PBC, Boston, MA.
- R Core Team. 2022. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.