Supplementary material to: Towards rainy winters: experimental icing impacts productivity and reproduction Mathilde Le Moullec, Anna-Lena Hendel, Matteo Petit Bon, Ingibjörg Svala Jónsdóttir, Øystein Varpe, René van der Wal, Larissa Teresa Beumer, Kate Layton-Matthews, Ketil Isaksen and Brage Bremset Hansen.

Table of content:

Table S1. Soil volumetric water content.

Table S2. Sampling dates and number of repeated measurements.

Table S3. Correlation coefficients between maximum NDVI and relative abundance.

Table S4. Summary statistic of Salix polaris phenophases.

Figure S1. Mesic habitat species composition.

Figure S2. Estimated NDVI curves across treatments and years.

Figure S3. Annual relative abundance.

Figure S4. Ordination of the mesic community species composition.

Figure S5. size traits of Salis polaris across years and treatments.

Figure S6. counts per year, treatment and species/group.

Figure S7. Annual probability curves of Salix polaris phenophases.

Table S1. Soil volumetric water content (i.e., soil moisture in %) measured with a ML3 ThetaProbe Sensor (HH2 Soil Moisture Meter from Delta-T Devices Ltd, UK, 1% accuracy, 5-10 cm depth) via repeated measurements at five points per plot, 3-15 times per summer (rounds). a) Soil moisture estimates and 95% CI per treatment and year, b) Pearson correlation coefficients between soil moisture and sub-surface (5 cm depth) temperature for years with repeated measurements across the growing season (2018-2019, df = 18). To compute these correlation coefficients we first fitted separate models for moisture and temperature , with treatment × day-of-year (factor) included as fixed effect, and repeated point measurements nested within plots nested within blocks included as random intercept structure. Then, the extracted fixed-effect estimates for each variable were correlated with each other. C = control, I = icing, IW = icing × warming, W = warming. a) Predictors Estimates CI (Intercept) [C, 2016] 37.85 29.39 – 46.31

treatment [I] -0.01 -4.34 – 4.32 treatment [IW] -3.56 -7.89 – 0.77 treatment [W] -0.11 -4.44 – 4.22 year [2017] 0.40 -8.08 – 8.87 year [2018] -5.52 -13.31 – 2.28

year [2019] -7.37 -15.85 – 1.10 year [2020] -1.39 -11.36 – 8.59 Random Effects Residuals 47.11 Blocks/Plots/Points 19.47 Blocks/Plots 17.77 Year/Round 37.57 Year 0.15 Block 9.14 N square 5 N plot 12 N block 3 N round 15 N year 5 Observations 5808 b) Treatment Correlation coefficient [95% CI]

C -0.69 [-0.87:-0.35] I -0.79 [-0.92:-0.49] IW -0.71 [-0.88:0.40] W -0.60 [0.82:-0.21]

Table S2. Sampling dates and number of measurement repeats (n). Abundance measurements represent the relative abundance measured by the point intercept method. For the Salix polaris leaf collection, the protocols varied between years: ‘Random’ indicates that S. polaris were gathered from five shoots collected at random (i.e., at five sub-square intercepts of the frame) and in 2018, the leaf’s respective shoot ID was available and used in the linear mixed-effect modelling; ‘Largest’ indicates that the biggest S. polaris leaf was collected in each 16 sub-squares per plot.

2016 2017 2018 2019 2020 Date of icing 3 – 4 Feb 22 – 23 Jan 4 – 5 Jan 24 – 25 Feb 18 – 19 Feb Date OTC setup 23 May 31 May 20 May 4 Jun 20 May NDVI rounds 23 Jun – 11 21 Jun – 30 01 Jun – 20 11 Jun – 17 10 Jun – 18 Aug (n = 9) Jul (n = 7) * Aug (n = 15) Aug (n = 9) Aug (n = 10) Phenology rounds 23 Jun – 13 22 Jun – 31 02 Jun – 21 07 Jun – 10 NA Aug (n = 12) Jul (n = 7) Aug (n = 14) Aug (n = 5) Flower counts 14 Jul 25 July 17 Jul 16 Jul 9 Jul Abundance 2 – 4 Aug 4 – 6 Aug 30 – 31 Jul 23 – 24 Jul NA measurements S. polaris leaf 5 Aug 2 Aug 30 Jul 30 Jul 28 Jul collection S. polaris leaf Random Random Random Largest Largest collection protocol * too short summer period to be included in the analysis

Table S3. Pearson’s correlation coefficients between plot-specific maximum NDVI and relative abundance estimates (assessed via point intercept method), separately for the two dominant species (Salix polaris, Alopecurus borealis), different groups of vascular plant species, and bryophytes.

2016 (df = 34) 2018 (df = 34) 2019 (df = 34) Total (df = 106) S. polaris 0.45 [0.14,0.68] 0.30 [-0.03,0.57] 0.46 [0.16,0.69] 0.40 [0.23,0.55] A. borealis 0.32 [-0.01,0.58] 0.23 [-0.11,0.52] -0.10 [0.42,0.24] 0.15 [-0.04,0.33] Vascular 0.42 [0.11,0.66] 0.38 [0.06,0.63] 0.36 [0.04,0.62] 0.36 [0.19,0.52] Vascular plants 0.15 [-0.19;0.46] 0.07 [-0.27;0.39] 0.04 [-0.29;0.36] 0.09 [-0.10;0.28] without S. polaris and A. borealis Bryophytes -0.40 [-0.64;-0.08] -0.22 [-0.51;0.11] -0.00 [-0.33;0.33] -0.19 [-0.37:-0.00]

Table S4. Summary statistic of Salix polaris phenophases in 2018, the summer with the highest number of monitoring rounds (n = 14) and complete vegetative and reproductive phenophases. Two separate models were fitted, with 1) fixed-effects including all treatments (as categories; C = control, I = icing, W = warming, IW = icing and warming combined), and 2) fixed-effects including icing and warming treatments as binomial variables and their interaction (I × W). For both model outputs, the columns ‘intercept’ (Int.), ‘I’ and ‘W’ are identical. Estimates and associated 95% CIs are on the logit-scale obtained from generalized linear mixed-effect models with phenophases following a binomial distribution. The random intercept structure was 16 sub-squares (S), nested within plots (P), nested within blocks (B). Estimates in bold have CIs non-overlapping with 0. Res. = residuals, Obs. = number of observations.

Leaves Female Male flowers Unfurling Expended Senescence Fully Flower Stigma Stigma Stigma Seed Anther Pollen Anther leaves leaves start senesced visible visible receptive senesced dispersal visible released senesced Int. 2.65 1.45 -0.35 -0.73 2.36 -0.11 -0.30 -0.43 -2.27 0.17 -0.25 -0.63 (2.10 – 3.19) (1.34 – 1.56) (-0.47 – -0.23) (-0.90 – -0.55) (1.89 – 2.83) (-1.08 – 0.87) (-1.15 – 0.56) (-1.13 – 0.26) (-3.12 – -1.42) (-0.12 – 0.46) (-0.56 – 0.05) (-0.88 – -0.37) I -0.69 -0.14 -0.01 -0.06 -0.51 -0.95 -0.77 -0.64 -0.82 -0.01 0.12 0.22 (-1.10 – -0.29) (-0.29 – 0.02) (-0.13 – 0.12) (-0.19 – 0.08) (-1.18 – 0.16) (-2.23 – 0.32) (-1.87 – 0.34) (-1.55 – 0.26) (-1.49 – -0.15) (-0.33 – 0.31) (-0.27 – 0.51) (-0.12 – 0.56) W 0.71 0.37 -0.08 -0.10 -0.48 0.08 -0.02 -0.19 0.10 0.24 0.39 0.18 (0.24 – 1.17) (0.19 – 0.55) (-0.22 – 0.05) (-0.24 – 0.04) (-1.18 – 0.23) (-1.24 – 1.40) (-1.16 – 1.12) (-1.12 – 0.74) (-0.56 – 0.77) (-0.13 – 0.60) (-0.03 – 0.82) (-0.19 – 0.56) IW 0.95 0.37 -0.08 -0.01 0.10 0.84 0.77 0.49 1.18 0.36 0.45 0.04 (0.48 – 1.41) (0.20 – 0.54) (-0.20 – 0.05) (-0.14 – 0.12) (-0.59 – 0.78) (-0.44 – 2.11) (-0.33 – 1.86) (-0.40 – 1.39) (0.58 – 1.79) (0.02 – 0.69) (0.06 – 0.85) (-0.30 – 0.39) I × W 0.93 0.14 0.01 0.15 1.09 1.71 1.55 1.33 1.90 0.13 -0.06 -0.36 (0.29 – 1.58) (-0.11 – 0.38) (-0.17 – 0.20) (-0.05 – 0.34) (1.08 – 1.09) (-0.13 – 3.55) (-0.04 – 3.15) (0.02 – 2.63) (0.96 – 2.84) (-0.36 – 0.63) (-0.64 – 0.52) (-0.87 – 0.15) Random Effects Res. 3.29 3.29 3.29 3.29 3.29 3.29 3.29 3.29 3.29 3.29 3.29 3.29 B/P/S <0.01 <0.01 <0.01 <0.01 0.95 0.59 0.39 0.13 0.15 <0.01 <0.01 <0.01 B/P 0.129 <0.01 <0.01 <0.01 0.32 1.72 1.27 0.84 0.31 0.07 0.12 0.08 \ B 0.16 <0.01 <0.01 0.02 <0.01 0.13 0.11 0.07 0.40 0.02 0.01 <0.01 Obs. 7566 7566 7566 7566 3638 3638 3638 3638 3638 2820 2820 2820

Figure S1. Mesic habitat species composition. Percentage of species or species groups recorded during point intercept monitoring (i.e., average number of hits per plot). Estimates and their 95% confidence intervals were obtained from generalized linear mixed-effects model (Poisson distribution) with species/groups as fixed-effect and a random intercept structure including plot nested within block and year (2016-2019, 3 blocks ,12 plots, 1584 observations).

Figure S2. Estimated NDVI curves (with 95% CIs) across treatments and years. C = control, I = icing, IW = icing × warming, W = warming. The increased primary production of I and IW, in comparison to C, seemed to decrease over the years. However, this observation can be confounded with the natural fluctuations of ambient temperatures and timing of soil-thaw onset. For instance, the soil-thaw onset in spring 2020 occurred synchronously across blocks and plots (all control plots thawed over four days instead of e.g., over one month as in the year before, Table 1) and was followed by a heat wave in July. In that last year of the experiment, NDVI was very high across treatments, including controls, i.e., at the same level as in icing and icing × warming treatments in other years. This may reflect a contemporary ‘threshold’ in primary production of this community, beyond which it is possibly limited by nutrient availability.

Figure S3. Annual relative abundance of two dominant vascular plants, (a) Salix polaris and (b) Alopecurus borealis, as well as (c) all vascular plants present (‘total vascular’). The y-axis represents the number of hits per plot (0.25 m2). C = control, I = icing, IW = icing × warming, W = warming.

Figure S4. Non-metric multidimensional scaling (NMDS) ordination of the mesic community species composition. Points represent the plots’ coordinates. The R-function ‘metaMDS’ in the vegan package was used. The large overlap of the ellipses demonstrates that the overall community compositions is similar across years and treatments. C = control, I = icing, IW = icing × warming, W = warming.

Figure S5. Leaf size traits of Salis polaris across years and treatments, represented as contrast plots (i.e., controls are the reference level, marked by the zero line). The effect size of the (a) leaf area and (b) leaf dry mass are on the log-scale.

Figure S6. Flower counts per year, treatment and species/group. S. polaris and B. vivipara (combining inflorescence with flowers and/or bulbils) represent the species with the largest proportion of flowers in the community. The ‘graminoids’ group combines A. borealis, L. confusa and P. arctica. Estimates were obtained from generalized linear mixed-effects models following a Poisson distribution for each year separately, with species × treatment included as fixed effect and a random intercept structure of plots nested within blocks. C = control, I = icing, IW = icing × warming, W = warming. The 95% CIs correspond to a model without the species distinction.

(a)

(b)

Figure S7. Annual probability curves of Salix polaris phenophases. (a) Leaves reaching senescence phenophases (Start sen. = leaves start senescing, Fully sen. = leaves fully senesced). (b) Female flowers reaching mature phases (Stigma rec. = stigma receptive to pollen, Stigma sen. = stigma senescing, Seed disp. = Seed dispersal). Estimates were computed with generalized linear mixed-effect models, accounting for the replicated structure of the study design (i.e., random effects); shaded areas represent the 95% CIs associated with the fixed effects. Red tick marks on the x-axis represent sampling days. The phases represented are the ones which have sufficient monitoring frequency for robust estimates. C = control, I = icing, IW = icing × warming, W = warming.