DOI: 10.5061/dryad.bk3j9kdqk
title: A transcontinental experiment elucidates (mal)adaptation of a cosmopolitan plant to climate in space and time

description: Climate change and the global spread of non-native species are two of the
 most significant threats to biodiversity and ecosystem function. Both
 these phenomena subject populations to novel conditions, either in space
 (species introductions) or in time (climate change), yet the role of
 adaptation in how populations respond to these rapid environmental shifts
 is poorly understood.  We conducted a large-scale
 trans-continental common garden experiment using white clover (Trifolium
 repens, Fabaceae) to test whether adaptive evolution to spatiotemporal
 variation in climate could contribute to the ecological success of one of
 the most widespread plant species in the world. Individuals from 96
 populations of Trifolium repens (white clover) from both its native
 (Europe) and introduced (North America) ranges were planted into four
 experimental common gardens located in northern (Uppsala, Sweden) and
 southern (Montpellier, France) Europe, and northern (Mississauga, Canada)
 and southern (Lafayette, USA) North America. We recorded plant sexual and
 clonal fitness in each common garden and assessed whether the strength of
 local adaptation differed between the native and introduced ranges and
 whether populations are rapidly adapting to climate change. Results show
 that local adaptation was only evident when populations were transplanted
 into common gardens located in the same range (native or introduced) from
 which they originated and was driven by stronger selection (due to
 climatic factors rather than herbivory) at lower latitudes in both ranges.
 Our results indicate rapid local adaptation across a large latitudinal
 gradient in introduced T. repens populations, along with an associated
 adaptation cost when transplanted back into the native range. We also find
 evidence of an adaptation lag in the northern common garden in the
 introduced range, with plants from historically warmer climates exhibiting
 the greatest fitness. These findings support two major conclusions: 1)
 white clover can rapidly adapt to spatial variation in climate in its
 introduced range as well as the native range, and 2) despite rapid
 adaptation to novel environments, introduced white clover populations are
 not keeping pace with rapid climate change. Overall, our results provide
 insight into the role of adaptation in facilitating the ecological success
 of non-native species in a rapidly changing world.
description: Readme file associated with the paper Albano et al., accepted at
 Ecological Monographs in September 2025. Title: A transcontinental
 experiment elucidates (mal)adaptation of a cosmopolitan plant to climate
 in space and time In this paper, we examine the strength and environmental
 drivers of local adaptation in Trifolium repens in multiple ranges, along
 with the ability of T. repens to adapt in the face of environmental
 change. We use a large-scale trans-continental common garden experiment
 using 1858 individuals from 96 populations of T. repens transplanted into
 four experimental gardens, located in the north (Mississauga, ON, Canada)
 and south (Lafayette, LA, USA) of the introduced North American range, and
 the north (Uppsala, Sweden) and south (Montpellier, France) of the native
 European range. This experiment addressed five research questions: (Q1)
 Are T. repens populations locally adapted to their climate of origin and
 does the strength of local adaptation differ across space? (Q2) Does T.
 repens exhibit stronger local adaptation in its native range than in its
 introduced range? (Q3) What bioclimatic variables have the strongest
 impact on fitness at different latitudes in the native and introduced
 ranges of T. repens? (Q4) Are there adaptation lags to climate change in
 T. repens, such that populations originating from warmer and/or drier
 climates exhibit greater fitness than local populations? (Q5) What are the
 roles of cyanogenesis and herbivory in driving local adaptation? Three
 datafiles are used in order to address these research questions, with each
 of these files described below. Associated scripts are available on
 Zenodo.  1\. In order to assess local adaptation, we use a measure of
 climatic distance that was calculated using a Principal Component
 Analysis, combining six bioclimatic variables that were extracted from
 WorldClim (Version 2.1, February 2023) at a resolution of 30 seconds for
 each original T. repens population and common garden site (O’Donnell and
 Ignizio, 2012). The variables included were mean annual temperature
 (“BIO1”; MAT), maximum temperature of the warmest month (“BIO5”), minimum
 temperature of the coldest month (“BIO6”), annual precipitation (“BIO12”),
 precipitation of the wettest month (“BIO13”), and precipitation of the
 driest month (“BIO14”). Each variable was z-score standardized (and is
 therefore unitless). These z-score standardized values for each population
 of origin and each common garden location can be found in
 **Albano_et_al_2025_EM_WorldClim_z-standardized.csv** Columns A through F
 contain bioclimatic variables from BIO1 through BIO14 in increasing
 numerical order. Rows are not labeled because the code for conducting the
 PCA will not run properly if the dataframe does not contain only numerical
 values and column headers. \- Rows 2 through 48 contain bioclimatic data
 for all North American T. repens populations of origin \- Rows 49 through
 97 contain bioclimatic data for all European T. repens populations of
 origin \- Row 98 contains bioclimatic data for the Lafayette, LA, USA
 common garden location \- Row 99 contains bioclimatic data for the
 Mississauga, ON, Canada common garden location \- Row 100 contains
 bioclimatic data for the Montpellier, France common garden location \- Row
 101 contains bioclimatic data for the Uppsala, Sweden common garden
 location 2\. All identifying, genotyping, and fitness data for all
 individual T. repens plants in each common garden can be found in
 **Albano_et_al_2025_EM_Experiment_Data.csv** The columns contained within
 this dataset are explained below and are analyzed in
 **Albano_et_al_2025_EM_Analysis.r** \- Garden: The location of the common
 garden (Mississauga, Lafayette, Uppsala, or Montpellier) in which each T.
 repens individual was planted \- Position: The unique numeric position of
 each individual T. repens plant within each common garden location \-
 Population: The identification number for each sampled T. repens
 population. Populations 001 through 050 are from North America, ordered
 from furthest south to furthest north. Populations 056 through 159 are
 scattered throughout Europe. \- Rep: Replicate number within each
 population within each common garden location (1 through 5 in Toronto and
 Montpellier, 1 through 8 in Lafayette and Uppsala) \- ContOrigin: The
 continent from which each T. repens individual originated (NAM for North
 America or EUR for Europe) \- ContGarden: The continent on which the
 common garden is found into which each T. repens individual was planted
 (America or Europe) \- Latitude: Latitude of origin of each population.
 Units = decimal degrees \- Longitude: Longitude of origin of each
 population. Units = decimal degrees \- ChangeLat: Change in latitude for
 each plant between its location of origin and the common garden location.
 Units = decimal degrees \- Cyanotype: Describes 4 T. repens phenotypes
 (AcLi, Acli, acLi, or acli) with respect to HCN and its underlying loci
 based on the presence/absence of a dominant allele at each of two loci
 (Ac/ac or Li/li) \- Cyanogenesis: Describes whether or not a plant is able
 to produce HCN (AcLi = HCN+, Acli/acLi/acli = HCN-) \- Ac_ac: Describes
 whether or not a plant contains at least one dominant allele at the Ac/ac
 locus (Ac = yes, ac = no) \- Ac_ac_Num: Binomial representation of the
 Ac_ac column (Ac = 1, ac = 0) \- Li_li: Describes whether or not a plant
 contains at least one dominant allele at the Li/li locus (Li = yes, li =
 no) \- Li_li_Num: Binomial representation of the Li_li column (Li = 1, li
 = 0) \- Survived1st: Whether or not each individual plant survived the
 first growing season. Survived = 1, Did not survive = 0. *Note: the 1st
 growing season was 2020 for NAM and 2021 for EUR* \- MaxArea1st: The
 maximum lateral area taken up by each plant throughout the monthly
 measurements of the first growing season. Units = cm^2 \- GrowthRate1st:
 Growth rate of each plant during the first growing season, measured as
 ln(maximum lateral area) minus the ln(initial lateral area) divided by the
 # of days between those timepoints. Units = cm^2/day \- Herbivory1st: The
 % of leaf area consumed by herbivores, averaged across 5 trifoliate leaves
 per plant \- FloweredFull: Whether or not each individual plant flowered
 during the full experiment (both growing seasons). Flowered = 1, Did not
 flower = 0. \- SeededFull: Whether or not each individual plant produced
 seed during the full experiment (both growing seasons). Produced seed = 1,
 Did not produce seed = 0. \- FlowerHeadNumberFull: The total number of
 flower heads produced by each individual plant throughout the full
 experiment (both growing seasons) \- SeedSetMassFull: The total seed set
 mass produced by the flower heads collected from each individual plant
 throughout the full experiment (both growing seasons). Units = grams \-
 WeightedCD: The climatic distance between each population of origin and
 each common garden location, calculated using the 3 most influential
 dimensions in a principal component analysis containing 6 bioclimatic
 variables of interest and weighted by the % of variation explained by each
 of the 3 most influential dimensions (unitless). \- MATdiff: The
 difference in mean annual temperature (bio1, not z-standardized) between
 each T. repens population of origin and each common garden location. Units
 = degrees Celcius \- bio1diff: The difference in mean annual temperature
 (WorldClim bio1, z-standardized - unitless) between each T. repens
 population of origin and each common garden location \- bio5diff: The
 difference in mean temperature of the warmest month (WorldClim bio5,
 z-standardized - unitless) between each T. repens population of origin and
 each common garden location \- bio6diff: The difference in mean
 temperature of the warmest month (WorldClim bio6, z-standardized -
 unitless) between each T. repens population of origin and each common
 garden location \- bio12diff: The difference in annual precipitation
 (WorldClim bio12, z-standardized - unitless) between each T. repens
 population of origin and each common garden location \- bio13diff: The
 difference in precipitation of the wettest month (WorldClim bio13,
 z-standardized - unitless) between each T. repens population of origin and
 each common garden location \- bio14diff: The difference in precipitation
 of the driest month (WorldClim bio14, z-standardized - unitless) between
 each T. repens population of origin and each common garden location \-
 MA_1st_z: (z-standardized - unitless) The maximum lateral area taken up by
 each plant throughout the monthly measurements of the first growing season
 \- GR_1st_z: (z-standardized - unitless) Growth rate of each plant during
 the first growing season, measured as ln(maximum lateral area) minus the
 ln(initial lateral area) divided by the # of days between those timepoints
 \- FH_Full_z: (z-standardized - unitless) The total number of flower heads
 produced by each individual plant throughout the full experiment (both
 growing seasons) \- SS_Full_z: (z-standardized - unitless) The total seed
 set mass produced by the flower heads collected from each individual plant
 throughout the full experiment (both growing seasons) 3\. In order to
 calculate climatic distance, we used the resultant PCA loadings for each
 T. repens population of origin and each common garden location. Climatic
 distance was calculated using only the first three dimensions, because
 they cumulatively account for 97% of variation, but all six dimensions are
 included in the dataset for completeness. Exported from
 **Albano_et_al_2025_EM_ClimaticDistancePCA.r** as:
 **Albano_et_al_2025_EM_Climatic_Distance_PCA_Scores.csv** The six
 dimensions are labeled as Dim.1 through Dim.6 in columns A through F.
 Again, rows are not labeled because the subsequent code required for
 generating PCA figures will not run properly if the dataframe does not
 contain only numerical values and column headers. \- Rows 2 through 48
 contain PCA scores for all North American T. repens populations of origin
 \- Rows 49 through 97 contain PCA scores for all European T. repens
 populations of origin \- Row 98 contains PCA scores for the Lafayette, LA,
 USA common garden location \- Row 99 contains PCA scores for the
 Mississauga, ON, Canada common garden location \- Row 100 contains PCA
 scores for the Montpellier, France common garden location \- Row 101
 contains PCA scores for the Uppsala, Sweden common garden location