DOI: 10.5061/dryad.3n5tb2rfk
title: Data from: Translocation of an arctic seashore plant reveals signs of maladaptation to altered climatic conditions

description: Ongoing anthropogenic climate change alters the local climatic conditions
 to which species may be adapted. Information on species’ climatic
 requirements and their intraspecific variation is necessary for predicting
 the effects of climate change on biodiversity. We used a climatic gradient
 to test whether populations of two allopatric varieties of an arctic
 seashore herb (Primula nutans ssp. finmarchica) show adaptation to their
 local climates and how a future warmer climate may affect them. Our
 experimental set-up combined a reciprocal translocation within the
 distribution range of the species with an experiment testing the
 performance of the sampled populations in warmer climatic conditions south
 of their range. We monitored survival, size, and flowering over four
 growing seasons as measures of performance and, thus, proxies of fitness.
 We found that both varieties performed better in experimental gardens
 towards the north. Interestingly, highest up in the north, the southern
 variety outperformed the northern one. Supported by weather data, this
 suggests that the climatic optima of both varieties have moved at least
 partly outside their current range. Further warming would make the current
 environments of both varieties even less suitable. We conclude that
 Primula nutans ssp. finmarchica is already suffering from adaptational lag
 due to climate change, and that further warming may increase this
 maladaptation, especially for the northern variety. The study also
 highlights that it is not sufficient to run only reciprocal translocation
 experiments. Climate change is already shifting the optimum conditions for
 many species and adaptation needs also to be tested outside the current
 range of the focal taxon in order to include both historic conditions and
 future conditions.
description: Study species and seed sampling Siberian
 primrose (<i>Primula nutans</i>) is a small-statured perennial
 herb with a discontinuous, circumpolar distribution. The Fennoscandian
 subspecies <i>P. nutans</i> ssp.
 <i>finmarchica</i> (Jacq.) Á. Löve & D. Löve is a
 red-listed species (VU in Norway and NT in Finland with a disjunct
 distribution (Fig. 1). It comprises two morpho-ecological varieties
 (Mäkinen & Mäkinen, 1964): var. <i>finmarchica</i>
 (the northern variety) grows on the shores of the Arctic Sea, while var.
 <i>jokelae</i> (the southern variety)<i>
 </i>occurs by the Bothnian Bay and the White Sea. It is a habitat
 specialist that mainly grows in seashore and riverside meadows (Kreivi,
 Aspi, & Leskinen, 2011; Mäkinen & Mäkinen, 1964). The
 habitat preference of the Siberian primrose is believed not to be affected
 by specific habitat requirements - it is neither a halophyte nor does it
 require regular flooding (Mäkinen & Mäkinen 1964). Rather, its
 occurrence in these habitats is likely due to its poor ability to compete
 in combination with a tolerance to both salty conditions and flooding. It
 propagates sexually by seeds and vegetatively by stolons growing from the
 wintering buds and the rosettes (Mäkinen & Mäkinen, 1964).  On the
 basis of matrix models published by Björnström et al. (2011) individuals
 especially sterile rosettes can be relatively persistent and hence live
 for several years. The species is insect-pollinated and produces copious
 seeds that spread by gravitation, via water flows, and possibly also with
 birds (Ulvinen 1997). Due to the geographic distance
 (c. 400-550 km) between its two varieties var. <i>jokelae
 </i>and var. <i>finmarchica</i>, and the lack of obvious
 adaptations for efficient gene flow between the areas, the varieties are
 presumably genetically isolated, which is also reflected in their genetic
 differences (Kreivi et al., 2011). The main areas where the varieties
 occur are climatically different (Hällfors et al., 2016), and there is a
 clear difference in the requirement of colder night conditions for flower
 induction in the northern variety compared to southern variety (Mäkinen
 & Mäkinen, 1964). We sampled seeds from wild
 populations of both varieties of <i>Primula nutans </i>ssp.
 <i>finmarchica</i> from August to September 2012. Seeds of the
 southern variety<i> </i>were collected in five sites in
 Haukipudas and Ii in Finland, and seeds of the northern variety from six
 sites in Sør-Varanger in Norway. Seed sampling in Finland was approved by
 the Centre for Economic Development, Transport and the Environment in
 North Ostrobothnia, Finland, on July 7th, 2012 (approval number:
 POPELY/346/07.01/2012). For sampling seeds in Norway, no permit was needed
 as the species is not protected in Norway. Voucher specimens from each
 sampling site are deposited at the herbarium of the Finnish Museum of
 Natural History (H <i>sensu</i> Thiers 2016). From each site
 we collected seeds from 10 - 53 individuals (as available, following seed
 collecting guidelines; ENSCONET, 2009; Table S1) to obtain a
 representative sample. The number of seeds obtained from the collected
 capsules of each sampled individual varied from 0 to <i>c.</i>
 200. We stored the seed lot from each maternal individual separately and
 left them to dry and ripen at room temperature for a minimum of two weeks
 after which we placed them in a freezer (-18 to -20°C) for cold
 stratification to break dormancy. The seeds were kept in these conditions
 for about six months, until used to produce plant material for the
 translocation experiment (in spring 2013).
 Experimental design and plant material We
 set up a common garden experiment in 2013 in five botanic gardens located
 in Estonia and Finland, and on research station grounds in Norway. We
 chose to use botanic gardens as testing grounds instead of natural sites
 to avoid genetic contamination of natural populations by introducing alien
 genotypes, as well as for logistical reasons and legal restrictions of
 introducing species outside their natural range. We
 chose the seeds for producing experimental plants for the trial through a
 hierarchical randomized method. For each experimental garden, we selected
 material from three seed sampling sites per variety. From each site, we
 randomly chose five maternal individuals. We anticipated that not all
 seeds would germinate and therefore we sowed eight seeds per maternal
 individual (120 seeds per variety for each site) although we needed only
 three seedlings per maternal individual (45 seedlings per variety for each
 site). We used the F1 offspring for our tests for two
 main reasons. Producing a ‘refresher’ generation between collecting the
 seeds and growing the experimental plants would have been difficult or
 impossible in uniform conditions as the two varieties flower in different
 temperatures conditions (Mäkinen & Mäkinen 1964). Second, even in
 the best case, this would have delayed the experiment by at least one,
 possibly 2–3 years, due to the life history of the focal species.
 Nevertheless, a recent meta-analysis (Yin et al. 2019) concluded that
 perennial plants show hardly any transgenerational responses (i.e.,
 effects on the offspring of the ancestor environmental conditions),
 whereby it is not likely that the use of F1 offspring significantly
 affected our results. We sowed each seed in a 6 × 6 cm
 pot with commercial sowing soil (Kekkilä) mixed with sand, vermiculite and
 perlite (5:2:2:0.5 litres, respectively), and with a thin layer of sand on
 top. The seeds were sown in six cohorts, five weeks before intended
 planting at each experimental garden. They were left to germinate in a
 greenhouse in Kumpula Botanic Garden in Helsinki, first in a small
 greenhouse inside the actual greenhouse to enable suitable temperatures
 during early spring. Temperature conditions varied between 18 and 24 ⁰C
 and lighting was set to 12 h of extra light (400 W) during daytime, in
 addition to the day light reaching the plants through the greenhouse
 walls. Due to poor germination and growth, possibly
 caused by supraoptimal temperature or a lack of nutrients or light, the
 seedlings were moved out of the small greenhouse into the actual one to
 allow cooler temperatures and more light (10–18 ⁰C). The moving followed
 the same order and time intervals as the sowing so that each cohort spent
 the same amount of time in the small greenhouse. Five days after the move,
 the pots were given a one-time nutrient addition with a general commercial
 fertilizer (Kekkilä Taimi-Superex).  This is a common procedure when using
 nutrient poor germination soil. Without fertilization of the soil after
 seed germination the growth usually comes to a halt.
 For each experimental garden we selected 45 seedlings of each
 variety, so that each variety was represented by three seed sampling
 sites, each of which contributed five seedlings from three different
 maternal individuals. If there were not enough seedlings from a certain
 maternal individual, we complemented the design with seedlings from
 another maternal individual of the same seed sampling population (in 69
 cases). If there was no other such maternal individual, we used seedlings
 from another maternal individual from another seed sampling population but
 of the same variety (in 21 cases). Because of a delayed
 spring in 2013, establishing the experimental plots had to be postponed by
 three weeks to avoid frozen soil and frost that could kill the seedlings
 after planting. The approximately two-month-old seedlings were transported
 and planted during May–June 2013, starting from the southernmost garden in
 mid-May (Tartu, Estonia) and reaching north (Svanvik, Norway) in late
 June. The intention was to follow the advance of the season so as to plant
 as early as possible while avoiding frost damage. In each experimental
 garden, we planted the seedlings in three 165 × 145 × 20 cm experimental
 plots with a minimum distance of 30 m between the plots, following a
 randomized block design. A filter cloth was placed at the bottom to
 prevent the ground soil from affecting the growing conditions and to help
 retain moisture. The plots were filled with fine sand and peat mixture (75
 and 25 volume-%, respectively) with some added dolomite lime. The
 intention was to roughly mimic the seashore meadow soils where the species
 grows in the wild while using commercially available soils that could be
 obtained in large quantities by a commercial soil provider and transferred
 to the all experimental gardens. The aim with using the same substrate was
 to homogenise (to certain extent) the growth conditions and thus to be
 able to separate the thermal effect from other effects.
 In each plot, we planted 30 seedlings (i.e., 90 seedlings per
 garden) in a grid, c. 21 cm from each other and 30 cm from the wooden
 frame. In each plot, 15 seedlings were of the southern and 15 of the
 northern variety, placed in a random order. We placed light metal cages on
 top of each plot to prevent large animals from interfering with the
 experiment. Plots were irrigated with <i>c</i>. 20 litres of
 water once a week during the growing season to keep the soil sufficiently
 moist. Although precipitation is part of climate, the effects of which we
 attempt to measure, we considered basic watering of the trials necessary
 as this is a sea-shore plant naturally exposed to high water tables. This
 watering regime was not intended to directly resemble the seashore meadows
 in nature, where the water level can vary substantially and occasionally
 even flood the plants. Instead, we applied irrigation to avoid large
 effects of drought, which this seashore species growing on occasionally
 inundated meadows, would not endure. Thus, watering was done only to the
 amount to compensate for the fact that our test sites were not at the
 shoreline, i.e. to mimic the natural sites of the primrose up to a certain
 baseline so that the plants would not die because of an unnatural
 unfavourable moisture regime. Plots were also weeded when deemed necessary
 to avoid effects of competition from other species, as our focus was not
 on the effect of competition on plant performance. Since almost 50% of the plants
 died during the first summer (139 individuals of the northern variety and
 57 of the southern; likely due to small seedling size and too little
 irrigation), in the autumn of 2013, the experimental plots were
 supplemented with left-over plants that had been growing outdoors in
 Kumpula botanic garden in Helsinki during the summer. We chose new plants
 repeating the plant selection process described above for situation where
 there were not enough representatives of the preselected maternal
 individual for the experimental garden. We recorded the planting time, to
 enable differentiating between original and new plants in subsequent
 analyses. Altogether, 614 individuals were planted in the five gardens
 during the early and late summer visits. To describe
 the performance of individuals, we measured their survival, size, and
 flowering (whether they flowered, how many flowers they produced, and
 when) from year 2014 to 2016.  The fitness of genotypes can be described
 as the relative success with which they transmit their genes to the next
 generation (Silvertown & Charlesworth, 2001). Because of the
 limited temporal extent of our study and because we do not measure the
 individual's fitness through its ability to produce viable progeny,
 we focus on key plant performance measures likely to correlate with
 fitness. Survival is a definite measure of fitness as a dead individual
 cannot transmit genes, but survival can also be stochastic. Also, the
 physical size of an individual and reproductive output, such as abundance
 of flowering, tend to correlate with plant fitness (Silvertown &
 Charlesworth, 2001). Each spring (2014, 2015, and 2016) we recorded
 flowering presence and abundance. Flowering was inventoried approximately
 every second day for 14 days after the first flower appeared in that
 garden in the specific year. In the autumn of the same years, we recorded
 survival and photographed each surviving plant from above. We assessed
 plant size from photographs, through digitally cutting out and measuring
 the area (cm<sup>2</sup>) of the visible vegetative parts. We
 used the size at the time of planting as a measurement of original size,
 but 24 individuals lack data on that due to missing photographs or
 insufficient resolution. These individuals were therefore not included in
 the analyses, and our total N is reduced from 614 to 590.
 Weather and climatic data For describing the
 climatic conditions at the seed sampling sites and experimental gardens,
 we obtained data on historic climatic conditions (1970–2000; 10 min
 resolution) and future projections (CMIP5 for 2050, 10 minutes resolution,
 HADGEM2-ES model) through the Worldclim database (Fick & Hijmans,
 2017). These climatic data were downloaded in R using the <i>getData
 </i>function in the <i>raster </i>package (Hijmans,
 2019). Additionally, we modelled plant performance as a function of mean
 annual temperature in the experimental gardens during 2013­-2016. The
 weather data were obtained from the Gridded Agro-Meteorological Data in
 Europe (Joint Research Centre, 2014), which contains meteorological
 parameters from European weather stations interpolated on a 25x25 km grid.
 We used the function <i>biovar </i>in the package
 <i>dismo </i>(Hijmans et al., 2017) to calculate bioclimatic
 variables of the weather data in R. Occurrence
 data To produce Figure
 1a in the original manuscript, we obtained occurrence data of the
 varieties. Var. <i>finmarchica</i> occurs by the Arctic Sea in
 N-Norway and var. <i>jokelae</i> by the Bothnian bay in
 Finland and Sweden and the White Sea in Russia. The source for occurrence
 points are: Global Biodiversity Information Facility (GBIF 2013); Kastikka
 (Finnish plant distribution database; Lampinen, Lahti, & Heikkinen
 2012); unpublished records from the of Finnish Environment Institute;
 occurrences in Russia based on information from herbarium specimens (from
 collections in the herbarium of the Finnish Museum of Natural History [H
 sensu Thiers 2016] and the herbarium of the University of Turku [TUR sensu
 Thiers 2016] and manually included occurrence points based on visually
 inspecting the distribution map by Hultén and Fries [1986]).
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