Data for: Thermal plasticity of multiple traits varies more within than between populations of Plantago lanceolata at its northern range edge
Hällfors, Maria H.; Robson, Matthew; Burg, Skylar; Pentikäinen, Santtu; Koivusaari, Susanna; Luoto, Miska; Nezval, Jakub; Pech, Radomir; Saastamoinen, Marjo; Schulman, Leif; Sirén, Jukka; Susi, Hanna
- Publisher
- Zenodo
- Language
- en
Abstract
Temperature plays a pivotal role in defining the distribution of species and the fitness of individuals within species' ranges. Phenotypic plasticity can allow individuals to cope with varying environmental conditions, including rapid climate change. Populations at range edges experience more variable conditions than core populations and thus are hypothesized to exhibit higher thermal plasticity. However, as the strength of plasticity often varies between individuals, it can also differ among local populations at range edges. We studied the extent of and variation in thermal plasticity for several traits within and between populations of the perennial herb Plantago lanceolata L. (Plantaginaceae) at its northern range edge. We sampled seeds from nine sites within a 50 x 50 km region and grew them under three temperature regimes in a greenhouse. We measured traits related to size, flowering, pathogen responses, and inflorescence pigmentation. We expected to find higher plasticity in traits less strongly connected to fitness, and that differences between individuals would outweigh differences between populations in underpinning this variation in plasticity. Our results show thermal plasticity in leaf size and abundance, flowering probability and abundance, and pigmentation. Notably, we also found increased pathogen symptoms and higher infection rates of one of two viruses screened, highlighting the potential for changes in pathogen sensitivity and exposure under climate change. Importantly, in all traits but flower abundance, more variation in plasticity was attributable to differences within populations than between populations. Although this contribution was small in magnitude compared to thermal effects on traits, the higher intra- versus interpopulation variation in plasticity suggests that differences between individuals provide most of the variation in thermal plasticity, which may be driven by small-scale variations in habitat conditions, highlighting the need for conservation strategies that consider microhabitat variation to support short-term adaptive responses to thermal variability.
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1 Supplementary Information for: Hällfors, M.H., Robson T.M., Burg S., Pentikäinen S., Koivusaari S. H. M., Luoto M., Nezval J., Pech R., Saastamoinen M., Schulman L., Sirén J., Susi H.: Thermal plasticity of multiple traits varies more within than between populations of Plantago lanceolata at its northern range edge. Contents: Figures S1-S7 Table S1-S3 References
2 Figure S1. June and July temperature in Åland, Finland during 1960-2020 in relation to experimental treatments. The point and lines in light grey, grey and dark grey show minimum, median and maximum temperatures, respectively. The lines are smoothed conditional means fitted using ggplot in R (Wickham, 2016). The dashed horizontal lines in blue, peach and red show night (lower) and day (upper) temperatures set for the thermal experiments for the cold, mean and warm treatments, respectively.
3 Figure S2. Typical chromatogram of separated phenolic compounds obtained from HPLC-DAD analysis recorded at 270 nm. HCA – hydroxycinnamic acid derivatives; FLV – flavonoids.
4 Figure S3. UV-VIS absorption spectra of phenolic compounds detected by HPLC-DAD. A) flavonoid derivatives, B) hydroxycinnamic acid derivatives.
5 Fig S4. Measured trait response across temperature treatment (summarized across populations) for A) leaf size, B) number of leaves; C) flower presence; D) number of flowers; E) flavonoid content of peak area mAU.s/ d.w. mg; F) HCA content; G) blue light reflection of inflorescence bracts; H) proportion of leaves with pathogen symptoms; I) number of individuals with or without PLCaV infection J) number of individuals with or without PlLV infection; K) total number virus infections per individual (0, 1=either PLCaV or PlLV infection; 2=both infections). Data presented per population in Fig S4. Estimated effects in main text Fig. 2 and Table 1.
6 Fig S5. Measured trait response across temperature treatment (separately per population) for A) leaf size, B) number of leaves; C) flower presence; D) number of flowers; E) flavonoid content of peak area mAU.s/ d.w. mg; F) HCA content; G) blue light reflection of inflorescence bracts; H) proportion of leaves with pathogen symptoms; I) number of individuals with or without PLCaV infection J) number of individuals with or without PlLV infection; K) total number virus infections per individual (0, 1=either PLCaV or PlLV infection; 2=both infections). Data presented per across populations in Fig S3. Estimated effects per population in Fig. S7.
7 Figure S6. Correlation plots of measured traits A) across treatments, and in the B) cold, C) mean and D) warm treatments. The correlation plots were created using the ggpairs function in the GGally pacakage in R (Schloerke et al., 2024).
8 Fig S7. Posterior mean and credible intervals for the average response per treatment temperature and population (different colors). A) Leaf size, B) number of leaves; C) flowering probability; d) number of flowers, E) flavonoid content; F) HCA content; G) blue light reflection; H) proportion of leaves with pathogen symptoms; I) probability of PLCaV infection J) probability of PlLV infection; K) probability of virus infections. Estimated effects (on the latent, i.e., modelled, scale) in main text Table 1. Estimated effects across populations in main text Fig 2.
9 Table S1. Information on seed sampling locations. Population Sampled individuals Y-coord X-coord Location Municipality A 50 60.06770 20.071867 Söderby Lemland B 50 60.13275 19.989163 Österkalmare Jomala C 50 60.17423 19.523903 Skeppsvik Eckerö D 28 60.22434 19.559542 Storby Eckerö E 17 60.27522 20.240213 Hulta Sund F 39 60.25415 20.228615 Mångstekta Sund G 26 60.26042 20.178783 Strömbolstad Sund H 20 60.08355 19.906516 Gregersö, Möckelö Jomala I 48 60.06605 19.951663 Espholm, Ytternäs Mariehamn
