DOI: 10.5061/dryad.s7h44j1fb
title: Data from: Is adaptation associated with long-term persistence beyond a geographic range limit?

description: Adaptation to new habitats might facilitate species’ range shifts in
 response to climate change. In 2005, we transplanted experimental
 populations of coastal dune plant Camissoniopsis cheiranthifolia into four
 sites within and one site beyond its poleward range limit. Beyond-range
 transplants had high fitness and often delayed reproduction. To test for
 adaptation associated with experimental range expansion, we transplanted
 descendants from beyond and within-range populations after 10 generations
 in situ into two sites within the range, one at the range edge, and two
 sites beyond the range. We expected to detect adaptation to beyond-range
 conditions due to substantial genetic variation within experimental
 populations and environmental variation among sites. However, individuals
 from beyond-range experimental populations were not fitter than those from
 within the range when planted at either beyond-range site, indicating no
 adaptation to the beyond-range site or beyond-range environments in
 general. Beyond-range descendants also did not suffer lower fitness within
 the range. Although reproduction was again delayed beyond the range, late
 reproduction was not favored more strongly beyond than within the range,
 and beyond-range descendants did not delay reproduction more than
 within-range descendants. Persistence in beyond-range environments may not
 require adaptation, which could allow a rapid response to climate change.
description: Study species <em>Camissoniopsis
 cheiranthifolia </em>(Hornem. Ex Spreng.) W.L. Wagner & Hoch
 (Onagraceae) is a short-lived herbaceous perennial that inhabits open
 sandy patches of coastal dunes from San Quintin, Baja California, Mexico
 to Coos Bay, Oregon, USA. The species is common throughout its range,
 occurring in 87% of 124 dune sites surveyed (Samis & Eckert,
 2007). The northern range limit in Oregon has been stable as long as
 herbarium and natural history records have been collected in this region
 (i.e., 150 yrs; Samis & Eckert, 2007), despite nearly continuous
 dune habitat extending along the coast into southern Canada. Individuals
 usually live 1–3 years, but ~ 80% of individuals reproduce and die in
 their first year (Samis & Eckert, 2009). The species lacks obvious
 mechanisms for dispersal, with tiny (~ 0.15 mg) seeds dropping from
 low-lying fruits and passively dispersing with blowing sand, or often
 germinating within or directly below a mature fruit ([authors],
 <em>personal observation</em>). Populations in the northern
 part of the range where this study occurred are highly self-fertilizing (~
 86% seeds self-fertilized; Dart & Eckert, 2013) and all belong to
 the same genetic subdivision within the species (López-Villalobos
 & Eckert, 2018). Transplant
 experiment To test for adaptation to beyond-range
 conditions, we executed a transplant experiment including descendant
 individuals of the original genetically mixed experimental populations
 from all five planting sites. The experimental populations differed in
 genotypic composition, with those at sites W133 and E0 and beyond-range
 site B60 including genotypes from all eight source populations, and those
 at sites W36 and W102 including genotypes from only the four northernmost
 source populations (Table S1). In 2018, after each set
 of experimental populations had persisted for about 10–12 generations, we
 planted seed from descendants from each of the five sites (total
 <em>n</em> = 2951 seeds) in the glasshouse at Queen’s
 University, ON, Canada (Supp. Mat. S2). We then transported seedlings to
 Oregon and planted 7-wk old seedlings (<em>n</em> = 1081
 seedlings) into five sites; two within the range (W133 & W36), one
 at the range-edge (E0), the original beyond-range site (B60), and another
 site 220 km beyond the northern range limit (B220; Fig. 1C; Table S4). We
 planted 3 – 19 individuals into each of 19 1.8 m<sup>2</sup>
 blocks of suitable habitat per site (suitable habitat defined as in Samis
 & Eckert, 2009). This experiment was run in parallel with an
 experiment using seedlings from natural source populations, leading to
 unequal numbers of transplants from experimentally mixed source
 populations per block. Both experiments were randomized together for a
 total of 31 or 32 transplants per block, with adjacent plants 30 cm apart
 (Cross, 2022). Surveying the original beyond-range site in 2019 revealed
 that most experimental populations had spread beyond transplant blocks
 into similar habitats (i.e., open sandy areas), further justifying our
 definition of suitable habitat. Blocks were not weeded, watered, protected
 from herbivores, or manipulated in any way. Naturally occurring
 <em>C. cheiranthifolia </em>were not removed, and 31.6% of
 within-range blocks contained at least one natural individual.
 We monitored survival and reproduction during 20 visits to each
 planting site over 1321 days after transplanting, including visits at the
 end of each of four growing seasons (late November – mid-December, 2018 –
 2021). During years 1 and 2, we visited blocks throughout the growing
 season and at season end, whereas in years 3 and 4, we could only sample
 at season end due to COVID-19 travel restrictions. All transplants had
 died by year 4, and we consider total fruit production across three
 seasons to be lifetime reproductive success (Fig. 2). Because the species
 is highly selfing in this part of its range, fruit production represents
 both female and male fitness. Due to the large scale of this experiment,
 we used open-pollinated seed, but non-genetic maternal effects (such as
 seed provisioning; Roach & Wulff, 1987) are unlikely to contribute
 to fitness variation among source populations of <em>C.
 cheiranthifolia</em> as variation in seed mass among maternal
 families did not correlate with progeny fitness in the original experiment
 (Samis, 2007) or this experiment (Cross, 2022).
 Statistical analyses All analyses used R v.
 4.1.3 (R Core Team, 2022) through RStudio v. 2022.02.1.461 (RStudio Team,
 2022), using the tidyverse package v. 1.3.1 (Wickham et al.,
 2019). To test for adaptation to beyond-range
 conditions and potential tradeoffs (predictions 1–3), we fit variation in
 estimated lifetime fitness of individual plants using unconditional aster
 models (Shaw et al., 2008; aster pkg v. 1.1-2; Geyer, 2021). The models
 incorporated, for each year of life, whether an individual survived to
 reproduce or to season-end (Bernoulli; S = 0 or 1), whether it flowered
 (Bernoulli; F = 0 or 1), and how many fruit were set if it did flower (R =
 zero-truncated Poisson). Because plants were regularly surveyed throughout
 the first and second growing seasons, S1 and S2 indicates whether a plant
 survived to reproduce or to season end (see Fig. 2 for aster predecessor
 structure) and we used maximum fruit production observed during the
 growing season on each plant as R. However, we could only survey plants
 once in December 2020 due to COVID-19 travel restrictions, so S3 indicates
 survival to season-end, and it is possible that some plants survived to
 flower and perhaps even produce fruit but died before season-end.
 Moreover, season-end fruit number may not represent total fruit production
 if some plants lost reproductive branches due to damage. However, in years
 1 and 2 season-end fruit number correlated strongly with maximum fruit
 reproduction (Pearson’s <em>r</em> = +0.85 in yr 1 and +0.96
 in yr 2), so season-end fruit production is a reliable measure of total
 season fruit production in year 3. To test for fitness
 variation of experimental populations across planting sites, we fit
 variation in fitness components (Fig. 2) to a mixed-effects aster model
 (using the <em>reaster</em> function; aster pkg v. 1.1-2;
 Geyer, 2021) with experimental source population, transplant site, and
 their interaction as fixed effects and transplant block as a random
 effect. The significance of each fixed effect was evaluated with a
 likelihood ratio test performed using the <em>anova</em>
 function in base R. A significant interaction indicated the potential for
 local adaptation (Blanquart et al., 2013) and motivated a comparison of
 source populations at each site separately (predictions 1–3). Means and
 standard errors for lifetime fruit production were estimated for each
 source population at each site using a fixed-effects aster model (using
 the <em>aster</em> function and not including the effect of
 block; C. Geyer, <em>personal communication</em>). When source
 populations varied at a site, we compared the B60 experimental descendants
 to those from sources within the range using pairwise comparisons with
 fixed-effects aster models (mixed effects models generated inappropriate
 Fisher matrices). Pairwise comparisons involved contrasting models with
 and without source population (df = 1) as a fixed effect using likelihood
 ratio tests as above. To account for the multiple comparisons, we held the
 Type I error rate at 5% using sequential Bonferroni. Higher fitness of B60
 descendants compared to within-range descendants when planted at B60 would
 be consistent with adaptation to beyond-range conditions (prediction 1),
 and when planted at B220 with adaptation to beyond-range environments more
 broadly (prediction 2). At within-range sites, lower performance of B60
 descendants compared to those from within-range experimental populations
 would be consistent with a cost to adaptation to beyond-range environments
 (prediction 3). To test whether variation in
 reproductive timing impacted lifetime fruit production, we reanalyzed data
 from the 2005 experiment to investigate whether delayed reproduction was
 associated with higher fitness and whether any such association was
 stronger beyond than within the range (the first part of prediction 4). In
 2005, most transplanted individuals that successfully reproduced were
 semelparous (80.7%), so most of the variation in timing of reproduction
 involved whether semelparous individuals flowered in their first or second
 year. In contrast, 2018 was very dry, which doubled pre-reproductive
 mortality (66.4% of 1077 plants in 2018 vs. 35.1% of 3782 plants in 2005)
 and delayed reproduction of those that survived. In 2005, 74.6% of
 reproductive plants flowered in their first year compared to only 5.8% in
 2018. To quantify reproductive timing in a way that captured variation in
 2018 and could be compared between experiments, we calculated, for each
 reproductive plant, the weighted year of fruit production
 Y<sub>w</sub> = (F<sub>1</sub>*1 +
 F<sub>2</sub>*2 +
 F<sub>3</sub>*3)/(F<sub>1</sub> +
 F<sub>2</sub> + F<sub>3</sub>), where
 F<sub>i</sub> is the number of fruits produced by an
 individual in year <em>i</em>. Y<sub>w</sub>
 averaged (± 1 SE)  2.15 ± 0.017 in the 2018 experiment (range = 1–3,
 median = 2.00) and 1.35 ± 0.009 in the 2005 experiment (range = 1–2.99,
 median = 1.00; Table S3). The effect of delaying
 reproduction on lifetime fruit production in 2005 was evaluated using two
 complementary analyses. First, we compared lifetime fruit production
 between the semelparous individuals that reproduced in their first vs.
 second year. At site E0, only five plants flowered in their second year,
 so this site was excluded from analysis. Individuals from the four Oregon
 source populations were planted at all five sites in 2005, whereas
 individuals from the four California source populations were only planted
 at three sites in 2005 (see Fig. 1), so we analyzed these two groups
 separately. Variation in lifetime fruit number was fit to a generalized
 linear model with negative binomial errors and reproductive timing, site,
 and their interaction as potential predictors using the
 <em>glm.nb</em> function in the MASS package (v. 7.3-60,
 Venables and Ripley, 2002). Second, we regressed lifetime fruit production
 over weighted year of fruit production (Y<sub>w</sub>) using a
 generalized linear model with negative binomial errors
 (<em>glm.nb</em>) and evaluated whether this regression varied
 among planting sites by including site and the interaction between site
 and Y<sub>w</sub> as potential predictors. For both analyses,
 the significance of predictors was evaluated with likelihood ratio tests
 using the <em>Anova</em> function in the car package (v.
 3.1-2, Fox and Weisberg, 2019). For both analyses, the interaction term
 was significant, so we performed the analyses for each site
 separately. We tested whether plants tended to delay
 reproduction when planted beyond the range in 2018 and evaluated the
 second part of prediction 4 that the descendants from B60 would exhibit
 delayed reproduction across all planting sites by fitting variation in
 Y<sub>w</sub> to linear models with either site or
 experimental source population, respectively, as a potential predictor and
 significance evaluated as above.
description: # Data from: Is adaptation associated with long-term persistence beyond a
 geographic range limit?
 [https://doi.org/10.5061/dryad.s7h44j1fb](https://doi.org/10.5061/dryad.s7h44j1fb) We have provided data on plant survival, growth, and reproduction measured throughout the experiment (over four growing seasons 2018-2021). The raw data in TransplantData2018 was processed into aster format in AsterData2018 (wide and long versions provided and used in Rmd). Various pre-planting data is provided, including the number of seeds per fruit from the fruits that were collected in the field in 2017 and used in the 2018 transplant experiment, greenhouse germination, mortality after transport to Oregon, and pre-planting sizes (right before planting in the field sites). We also provide environmental/climate data. All data analysis and figure production are in the BR_adaptation R Markdown file. We also provide a Cam_Aster.R file which includes the pre-processing of data to prepare it for aster analyses. ## Description of the data and file structure The datasets provided are as follows. **TransplantData2018.csv** - In-field measurements of transplants throughout the experiment.  * plant_id: three-digit code indicating where the individual was planted; sites OPR = W133; OBU = W36; OHF = E0; OSJ = B60; OBS = B220. First number is the block where it was planted, second number is the individual position.  * site: planting site * round: round of data collection (1-20). Round 15 is end of season 2018; round 18 is end of season 2019; round 19 is end of season 2020; round 20 is end of season 2021. * date: date of measurements * page: datasheet page number * plot: planting block * obs: observer * plant_pos: plant position (in block; last number in plant_id * pl: plant length (mm) * pw: plant width (mm) * rl: rosette length (mm) * rw: rosette width (mm) * sec: number of secondary branches (coming out from the rosette) * tert: number of tertiary branches (coming off secondary branches) * quat: number of quaternary branches * L5: number of branches less than 5 cm long * X5_10: number of branches 5-10 cm long * X10_15: number of branches 10-15 cm long * G15: number of branches &gt; 15 cm long * bud: number of buds * ab: number of aborted buds * of: number of open flowers * sf: number of spent flowers * dfr: number of developing fruit * mfr: number of mature fruit * afr: number of aborted fruit * lvs: number of leaves in the rosette * herb: number of rosette leaves that are herbivorized * ch: number of rosette leaves that have been bitten completely off * scr: scribe initials * notes: in-field notes about plant * ent_notes: notes from the data enterer * enterer: data entry initials * *Columns created after field data collection complete* * buds: number of buds * db: is the buds divided into small and large buds (Y/N) * div_buds: small and large buds separated by \_ * smbud: number of small buds (&lt;5 mm long) * lgbud: number of large buds (&gt;5 mm long)  * pa: plant area (l x w; mm^2) * ra: rosette area (l x w; mm^2) * reproOutput: number of reproductive structures (buds, flowers, or fruits; not aborted) * logpa: log10 pa * logRO: log10 reproOutput * sum_branches: total number of branches * logbranches: log10 sum_branches * day: day of date * month: month of date * year: year of date * doy: day of year * sqrtRO: square root of reproOutput * order: dataset ordering * latitude: latitude of planting site * order2: more dataset ordering * occupant: ID of the occupant from the roottrainer * rt_pos: roottrainer position (for verification) * tray_cell: position in plug trays in greenhouse from before transfer to roottrainers * maternal_line: ID of the maternal line (source genotype) * uniqueMatID: ID of the mother plant from the field (2017 fruit collection) * source: source population  * L5mc: are there multiple categories of branches in the L5 column? * X510mc: are there multiple categories of branches in the 5-10 column? * X1015mc: are there multiple categories of branches in the 10-15 column? * G15mc: are there multiple categories of branches in the G15 column? * mc1: L5 if there were multiple categories * secL5: number of secondary branches less than 5 cm long * tertL5: number of tertiary branches less than 5 cm long * quatL5: number of quaternary branches less than 5 cm long * mc2: X5-10 if there were multiple categories * sec5_10: number of secondary branches 5-10 cm long * tert5_10: number of tertiary branches 5-10 cm long * quat5_10: number of quaternary branches 5-10 cm long * mc3: X10_15 if there were multiple categories * sec10_15: number of secondary branches 10-15 cm long  * tert10_15: number of tertiary branches 10-15 cm long  * quat10_15: number of quaternary branches 10-15 cm long  * mc4: G15 if there were multiple categories * secG15: number of secondary branches &gt;15 cm long  * tertG15: number of tertiary branches &gt;15 cm long  * quatG15: number of quaternary branches &gt;15 cm long  **AsterData.Rdata** includes transplant fitness data processed for aster analyses: aster_dat3 (wide format) and aster_dat4 (long format).  * plant_id: three-digit code indicating where the individual was planted; sites OPR = W133; OBU = W36; OHF = E0; OSJ = B60; OBS = B220. First number is the block where it was planted, second number is the individual position. (as in transplant data above) * site: planting site * occupant: ID of the occupant from the roottrainer * block: planting block / plot (same as plot in transplant data above) * rt_pos: roottrainer position (for verification) * tray_cell: position in plug trays in greenhouse from before transfer to roottrainers * maternal_line: ID of the maternal line (source genotype) * uniqueMatID: ID of the mother plant from the field (2017 fruit collection) * source: source population  * f1: reproduction in year 1 (binary) * f2: reproduction in year 2 (binary) * f3: reproduction in year 3 (binary) * m1: survival in year 1 (binary) * m2: survival in year 2 (binary) * m3: survival in year 3 (binary) * r1: reproductive output in year 1 (count; number of fruits) * r2: reproductive output in year 2 (count; number of fruits) * r3: reproductive output in year 3 (count; number of fruits) *Long form data includes the same identifier columns, plus the following.* * varb: name of column f1-r3 in wide format data * resp: value of column f1-r3 in wide format data * id: ID for aster analysis * root: for aster analysis, root = 1 * rs: indicates whether the resp is the count of reproduction (ie., if varb = r#, then rs = 1, otherwise rs=0) **TransplantData_05_ReproTiming**.csv: data from 2005 experiment for use in the reproductive timing analyses. * NewSite: planting site * NewSource: source population * FamilyID: maternal line identifier * plant_id: transplant identifier * Recip: whether the source-site combination was part of the full reciprocal transplant (at the four northernmost within-range sites); see Samis et al. 2016 for more information * ThreeSite: if the transplant site is W133, E0, or B60 * S1: transplant survival in year 1 (binary) * R1: transplant reproduction in year 1 (binary) * F1: number of fruits produced in year one (count) * S2: transplant survival in year 2 (binary) * R2: transplant reproduction in year 2 (binary) * F2: number of fruits produced in year 2(count) * S3: transplant survival in year 3 (binary) * R3: transplant reproduction in year 3 (binary) * F3: number of fruits produced in year 3 (count) * totFrt: F1 + F2 + F3; total number of fruit * ReproCat: category of reproduction; No Report, Yr1Only, Yr1and2, Yr2Only, Yr2and3, or AllThree * fruit_timing: timing of fruit production *** Chris * reproductive: was the plant reproductive (binary) * reprotimes: how many years did the plant reproduce (1x, 2x, 3x, or NA) * repro1x: 1 if reprotimes = 1x, 0 if reprotimes = 2x or 3x, NA if non-reproductive * semelyr2: was it semelparous (reproduced only in one year) and the year of reproduction was year 2? (binary) **TransplantData_18_ReproTiming**.csv: data from 2018 experiment for use in the reproductive timing analyses. Column definitions are all repeated from either AsterData or TransplantData_05_ReproTiming. ## Sharing/Access information If you require additional data or explanation, please contact the authors. Data was derived from the following sources: * Data collected by authors * ClimateNA: Wang, T., Hamann, A., Spittlehouse, D., & Carroll, C. (2016). Locally downscaled and spatially customizable climate data for historical and future periods for North America. *PloS One*, 11, e0156720. [www.climatena.ca](http://www.climatena.ca).  ## Code/Software We have provided the main R code file used to process this data for the manuscript. We used R version 4.1.3 and RStudio.