# Traits and functions of alpine plant communities respond strongly but not always sufficiently to in situ climate change

Billur Bektaş, Gemma Rutten, Amélie Saillard, Rodrigue Friaud, Cindy

Arnoldi, Julien Renaud, Maya Guéguen, Arnaud Foulquier, Jérôme

Poulenard, Emilie Lyautey, et al.

► To cite this version:

Billur Bektaş, Gemma Rutten, Amélie Saillard, Rodrigue Friaud, Cindy Arnoldi, et al. "Traits and functions of alpine plant communities respond strongly but not always sufficiently to in situ climate change." New Phytologist, 2025, 10.1111/nph.70503. hal-05344578

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## Traits and functions of alpine plant communities respond strongly but not always sufficiently to in situ climate change

<table><tr><td>Journal:</td><td>New Phytologist</td></tr><tr><td>Manuscript ID</td><td>Draft</td></tr><tr><td>Manuscript Type:</td><td>Full Paper</td></tr><tr><td>Date Submitted by the Author:</td><td>n/a</td></tr><tr><td>Complete List of Authors:</td><td>Bektaş, Billur; ETH Zurich D-USYS, Institute of Integrative Biology, Department of Environmental Systems Science; Université Grenoble Alpes, CNRS, LECA<br/>Rutten, Gemma; Universitat Bern, Geobotanik<br/>Saillard, Amélie; University Grenoble Alpes, CNRS, LECA<br/>Friaud, Rodrigue; École Normale Supérieure, Department of Biology, PSL University<br/>Arnoldi, Cindy; Universite Grenoble Alpes, UMR 5553<br/>Renaud, Julien; Universite Grenoble Alpes, Laboratoire d'Écologie Alpine<br/>Gueguen, Maya; Universite Grenoble Alpes, Laboratoire d'Écologie Alpine<br/>Foulquier, Arnaud; University Grenoble Alpes, Laboratoire d'Écologie Alpine<br/>Poulenard, Jerome; Université Savoie Mont Blanc, Université Grenoble Alpes, EDYTEM<br/>Lyautey, Emilie; Universite Savoie Mont Blanc, INRAE, CARRTEL<br/>CLEMENT, Jean-Christophe; Universite Savoie Mont-Blanc, CARRTEL<br/>Thuiller, Wilfried; Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, Laboratoire d'Écologie Alpine<br/>Münkemüller, Tamara; Univ. Grenoble Alpes, Laboratoire d'Écologie Alpine (LECA)</td></tr><tr><td>Key Words:</td><td>Plant functional traits, climate change, transplant experiment, leaf-root coordination, Ecosystem functions, Mycorrhizal colonization, alpine plants</td></tr><tr><td>Suggested Handling Editor:</td><td>Colleen Iversen</td></tr></table>
## Data Availability Statement

Our *Mandates Data Policy* requires data to be shared and a Data Availability Statement, so please enter one in the space below. Sample statements can be found [here](). Please note that this statement will be published alongside your manuscript, if it is accepted for publication.

Data will be publicly available upon submission. For peer review, the data is available at OSF with a view-only option: https://osf.io/j39um/?view_only=e8bb850c50bd4654b0b4cbfe572524a8

The code is publicly available: https://github.com/billurbektas/transalp_functional; traits.git
1 **Traits and functions of alpine plant communities respond strongly but not**
2 **always sufficiently to in situ climate change**

3

4 Billur Bektaş¹,², Gemma Rutten³, Amélie Saillard¹, Rodrigue Friaud⁴, Cindy Arnoldi¹, Julien

5 Renaud¹, Maya Guéguen¹, Arnaud Foulquier¹, Jérôme Poulenard⁵, Emilie Lyautey⁶, Jean-

6 Christophe Clément⁶, Wilfried Thuiller¹, Tamara Münkemüller¹

7

8 ¹Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, LECA, F-38000, Grenoble, France

9 ²Institute of Integrative Biology, Department of Environmental Systems Science, ETH Zürich,
10 Zürich, Switzerland

11 ³Institute of Plant Sciences, University of Bern, CH-3013 Bern, Switzerland

12 ⁴Departement of Biology, École Normale Supérieure, PSL University, Paris 75005, France

13 ⁵Univ. Savoie Mont-Blanc, Univ. Grenoble Alpes, CNRS, EDYTEM, F-73000 Chambéry, France

14 ⁶University Savoie Mont Blanc, INRAE, CARRTEL, Thonon-Les-Bains, France

15

16 Word count (4956): Introduction (1106), Materials & Methods (1825), Results (675), Discussion
17 (1350)

18 Figures: 7

19

20 **Summary**

21 Increasing climate warming and summer droughts are known to affect mountain plant
22 communities, their functional traits and life strategies. However, little is known about how
23 strongly and efficiently communities respond to climate change, and how tightly plant responses
24 are linked to responses of ecosystem functions. To test this, we transplanted alpine plant
25 communities to subalpine conditions, exposing them to warming and drying. We compared
26 these transplanted communities to alpine and subalpine control communities to assess their
27 responses. Five years after transplantation we found slower growth (e.g. lower leaf nitrogen)
28 and more outsourcing strategies (e.g. lower specific root length) in the warmer and drier
29 subalpine control communities compared to the alpine controls, probably due to drought. Traits
30 of warmed alpine communities shifted towards subalpine controls. However, neither below- nor
31 above-ground traits nor productivity of plants fully acclimated to subalpine conditions.

32 Nevertheless, plant litter decomposition rates, arbuscular colonization and bacterial biomass
33 showed no acclimation lag to the subalpine controls.

34 Significant but insufficient acclimation of plant functional traits and strategies is prone to result in
35 maladapted plant productivity, impairing competitiveness with better adapted subalpine species
36 and leading to the, temporally delayed, loss of ecosystem features specific to alpine
37 environments.
## 38 Introduction

Plant functional traits are essential predictors of plant performance (Soudzilovskaia et al., 2013; Adler et al., 2014; Falster et al., 2018) and ecosystem functioning under climate change (Violle et al., 2007). Trait-based approaches have allowed identifying trade-offs that underpin ecological strategies in large-scale distributions of plant species (Violle et al., 2012) and how variations in plant strategies can cascade into ecosystem functioning such as decomposition and above and belowground productivity and microbial activities (Suding et al., 2008; Lavorel & Grigulis, 2012). However, how plant functional strategies shift in local communities under ongoing climate change, and how strong these shifts are linked to ecosystem functions, is less clear.

Functional traits are not independent of each other. At the individual level, physiological trade-offs arise from the allocation of limited resources. Accordingly, at the species level, only a few plant functional strategies (i.e. successful trait combinations) along these essential trade-offs have shown to be evolutionarily viable in vascular plants (Díaz et al., 2016). Most studies supporting the idea of a few key trade-offs in plant functional trait variability focused on large spatial scales, including stark environmental gradients. However, trade-offs are not robust across environments (Ren et al., 2022) and under climate change; they may weaken, affording plants greater flexibility to rapidly adjust to new conditions and potentially enabling the emergence of novel strategies that were absent in previous conditions (Li et al., 2022; Wei et al., 2023) (but see (Cui et al., 2020)). Thus, if we are to use functional strategy shifts to better understand and early recognize vegetation responses to climate change, we need to establish these trade-offs at small spatial scales while taking into account plastic responses. Moreover, it is at community-level, where both individuals' trait changes and species' losses and gains play a role, that we can directly link the functional strategies to ecosystem functions (Mouillot et al., 2011; Funk et al., 2017; He et al., 2023). Whether or not species level trade-offs and functional strategies scale up to the community level, may depend on the underlying community assembly processes (Read et al., 2014; Rosbakh et al., 2015; Chalmandrier et al., 2017) and evidence is variable (Funk & Cornwell, 2013; Anderegg et al., 2018).

The first trade-off identified from leaf traits at species level and at large spatial scales was the leaf economics spectrum (Reich, 2014; Wright et al., 2004), as it can be interpreted through economic theory with nutrients, carbon and water as resources, rather than money. Plants invest either in low leaf mass per area (LMA) and high leaf nitrogen content (LNC) —a fast-
growing but short-lived strategy—or in leaf traits at the opposite end of the spectrum —a slow-growing but long-lived strategy. The “fast” strategy improves plant fitness under benign environmental conditions and on fertile soils, while the “slow” strategy is better adapted to stressful conditions such as challenging climates at high altitudes (Fig.1, Table S1-2). Plant vegetative height was suggested as a second dimension, with some species investing in early reproduction and staying small and others in becoming tall and thus in strong competitiveness for light (Price et al., 2014). Until recently, belowground traits were largely neglected in the description of plant strategies as data are more difficult to acquire. After being defined by (Freschet et al., 2010) and (Reich, 2014), Bergmann et al. (2020) revealed the root economics spectrum through a global root dataset and incorporated root traits into large-scale analyses of plant functional trade-offs (Fig. 1). At the one end of the spectrum, plants exhibit high root nitrogen content (RNC) and low root tissue density (RTD), representing “fast” strategies. Conversely, “slow” strategies are characterized by traits at the opposite end of the spectrum. Additionally, they revealed another root-specific trade-off, orthogonal to the root economics spectrum, between “do-it-yourself” and “outsourcing” strategies for resource uptake (i.e. nutrients and water): at the endpoint of this collaboration spectrum plants exhibit either high specific root length (SRL) for direct absorption or wider root diameters (RD) for arbuscular mycorrhizae symbiosis. The former is advantageous in resource-rich soils, while the latter benefits plants under resource scarcity or during drought or freezing events (Augé et al., 2015; Laughlin et al., 2021). Recent debates question the independence of RTD from the collaboration spectrum (Kong et al., 2019; McCormack & Iversen, 2019), and whether a fast vs. slow trade-off in root traits suggests distinct plant strategies (Carmona et al., 2021; Bueno et al., 2023; Weigelt et al., 2023) or align with a broader plant economics spectrum (Poorter et al., 2014; Weigelt et al., 2021), with answers even more elusive at community-level.

Under accelerating climate change in the European Alps, characterized by rising temperatures and more frequent summer droughts (Scherrer et al., 2022; Kotlarski et al., 2022), we anticipate changes in aboveground and root plant functional strategies at community level — through changes in individuals’ traits and species’ turnover —as well as impacts on ecosystem functions and microbial activities (Fig. 1). However, shifts in plant functional strategies will depend on the plasticity allowed by the strength of the trade-offs and selection of species demonstrating viable functional strategies under ecosystems’ limiting resources. In fact, a recent review on climate
change effects showed that shifts in leaf traits depend on whether water is limiting in the system (Myers-Smith et al., 2019). On the one hand, climate warming increases growing season lengths and energy input. Without drought, this may lead to a shift towards taller plants with faster and do-it-yourself functional strategies (Fig. 1, references at Table S1). This transition may enhance ecosystem productivity (Bektaş et al., 2021) and decomposition rates as, for example, the litter becomes more nutrient-rich and easily decomposable (Hagedorn et al., 2019), Changes in plants can further cascade to microbial communities in several ways (Weil et al., 2021): by increasing the abundance of bacteria-associated plants, enhancing litter quality and thus, bacterial activity, and reducing competition with fungi, as plants with do-it-yourself strategies are limited in their capacity to host mycorrhizal fungi. Increase in the bacterial activity (ie. a shift towards "bacterial energy channel" (Esperschütz et al., 2011), and increase in copiotroph organisms, (Fierer et al., 2007)) can indicate a fast-growth strategy for microbial communities as well and a favoring of the labile litter decomposition (Pugnaire et al., 2019). Increase of the soil nutrients might further enhance the fast and do-it-yourself strategies as well as the plant growth. On the other hand, increased drought and reduced snow cover during freeze periods elevate physiological stress, potentially leading to shorter plants with slower and outsourcing strategies (Fig. 1, references at Table S1). Such shifts may impede ecosystem productivity and decomposition rates due to nutrient-scarce and less decomposable litter. Together with increasing root diameter that can host more mycorrhizae and decreased competition with the bacterial communities, mycorrhizal activity in the roots can be further enhanced (Hagedorn et al., 2019). This enhancement of the "fungi energy channel" and oligotrophic organisms can lead to a favoring of the recalcitrant litter decomposition (Pugnaire et al., 2019; Osono, 2020). Slow litter decomposition and less availability of nutrients may further push plants towards slower and more outsourcing strategies. However, the extent to which climate change affects plants ecosystem functions and microbial activity directly or indirectly via changes in plant traits remains uncertain. Although disentangling the specific underlying processes (e.g., species turnover, litter content, or soil community competition) lies beyond the scope of this article, we quantify the indirect effects of climate-driven shifts in plant functional strategies on ecosystem functions and microbial activity.

Here, we aimed at quantifying shifts in above and belowground plant functional traits, ecosystem functions and microbial activities under experimental climate change in mountain grasslands. More specifically we asked: i) Can we disentangle fast vs. slow and do-it-yourself vs. outsourcing strategies at community level along an elevational gradient? ii) How do
138 functional traits change under experimental climate change, including warming and drying? iii)

139 How do experimental climate change induced changes in functional traits link to the above- and

140 below-ground ecosystem functions? We answered these questions by simulating *in situ* climate

141 change on alpine intact plant and soil communities by transplanting them to lower elevations.

142

<figure><img src="image_3.png" /><figcaption>143
**Fig. 1:** Conceptual framework of plant above- (in green) and below- (in blue) ground functional trait trade-offs, associated plant strategies in different environmental conditions and hypothesized links to ecosystem functions and microbial communities. According to the leaf economics spectrum, plants invest either in low LMA and high LNC, the fast-growing strategy, or in opposite traits and a slow-growing strategy. Plant size constitutes another dimension characterizing plants with higher growth capacity and competitiveness for competition for light. According to the root economics spectrum, plants either invest in low RTD and high RNC, the fast resource acquisition strategy, or in opposite traits and a slow resource acquisition strategy. Perpendicular to the root economics spectrum, the trade-off between RD and SRL characterizes plants' preference to outsource the resources uptake through mycorrhizal associates or a do-it-yourself strategy. Note that the debate continues if RTD aligns with the RD-SRL trade-off, and if leaf and root economics spectra constitute a whole plant economics spectrum. Here, we expect that with climate change these plant functional strategies shift at community level both through individuals' trait changes and species' turnover. These shifts will depend on the limiting conditions in the ecosystem. If</figcaption></figure>
climate change is providing more benign conditions for plants (red box), for example through the higher energy input over the year, then we can expect to see a shift towards taller plants with fast and do-it-yourself strategies followed by enhanced ecosystem productivity, decomposition rates and a shift towards increasing bacterial activity, a fast-growth strategy, in root-associated microbial communities further enhancing the labile litter decomposition. If climate change is leading to increasing drought and early spring freezing events, then we can expect to see a shift towards shorter plants with slow and outsourcing strategies followed by a decrease in the productivity and decomposition rates and a shift towards increasing mycorrhizal activity, a slow-growth strategy, in root-associated microbial communities further enhancing the recalcitrant litter decomposition. References linked to the hypotheses can be found on Table S1. (LMA: leaf mass per area, LNC: leaf nitrogen content, VH: vegetative height, RNC: root nitrogen content, RTD: root tissue density, RD: root diameter, SRL: specific root length.)

## 168 Materials & Methods

### 169 Study site and experimental design

To simulate climate change, i.e. climatic warming and drought, in the French Alps, we moved alpine grassland plots from high elevation to ~500m lower elevation in September 2016 (Bektaş et al., 2021). The alpine site "Galibier" (45°05'44"N 06°40'06"E at 2450 m altitude) and the subalpine site "Lautaret" (45°04'00"N 06°41'90"E at 1920 m altitude) were close to each other (~2km airline distance), had a similar orientation (South-East at alpine and South-South-West at subalpine site), bedrock (base-riched flysch) and soil (dystric cambisols). This system represents a relatively dry mountain grassland, and both alpine and subalpine zones are generally subject to water limitation (Leitinger et al., 2015). At the alpine site, communities were dominated by *Trifolium alpinum*, *Potentilla aurea*, *Plantago alpina*, *Carex sempervirens* subsp. *sempervirens* and *Poa alpina*. At the subalpine site, communities were dominated by *Patzkea paniculata* subsp. *paniculata*, *Festuca nigrescens*, *Carex sempervirens* subsp. *sempervirens*, *Festuca laevigata*, and *Plantago maritima* subsp. *Serpentina* (the complete list of species is given in Table S7). We transplanted 10 replicates of 4m² plots of vegetation with at least 20 cm of their intact belowground parts and the surrounding soils from the alpine to the subalpine site (AlpineWarmed plots). For the transport, each turf was cut in 4 x 1m² pieces and then reassembled in their original composition when re-planted. Around the turfs, we placed water-permeable root barriers to avoid root ingrowth from the natural vegetation. To control for the transplantation stress, we also horizontally transplanted 10 intact 1m² blocks at the alpine site (AlpineControls) and at the subalpine site (SubalpineControls), respectively. At both sites, cattle and sheep were excluded by electric fences and biomass was not removed after each growing season. More details on the experimental design can be found in Bektaş et al. (2021).
In 2021, the year of data collection, average July soil temperature was 3°C warmer at the subalpine site than at the alpine site and the snow free season was 56 days longer corresponding to a 33% increase (Fig. 2 b-c). In each plot, we measured the soil moisture 21 times during the growing season (from mid-June to August) with Campbell scientific HydroSense II and took the median soil moisture per plot. The average summer soil moisture was significantly lower in AlpineWarmed than in AlpineControl plots (difference between AlpineWarmed and AlpineControl: 12.73 +/- 1.05 %, Fig. 2d). In 2020, we also measured soil nutrients of each plot. A 0.5M K₂SO₄ solution was used to extract soil nitrate (NO₃⁻), ammonium (NH₄⁺), total dissolved nitrogen (TDN) (Jones & Willett, 2006), and phosphate (PO₄³⁻) from 10 g of fresh soil. Nitrogen (N) and phosphorus (P) concentrations were determined using an automated photometric analyzer (Gallery Plus, Thermo Fisher Scientific, Waltham, Massachusetts, USA) following standard colorimetric methods. Soil nitrate concentration as the plant-available nitrogen did not differ between AlpineControl and AlpineWarmed plots (Fig. 2f), but total soil P concentration decreased significantly with experimental climate change (difference between AlpineWarmed and AlpineControl: 84.97+/-23.43 mgP/kg, Fig. 2e).
<figure><img src="image_4.png" /><figcaption>**Fig. 2:** Change in climatic conditions and soil nutrients five years after transplantation of alpine communities from high-elevation to low-elevation (a). Under experimental climate change, increase in temperature and growing season length might create more benign conditions for plants (b-c). However, as the snow melts earlier, plants may be exposed to early and more frequent spring freezing events. Decrease in soil moisture (b) and in soil phosphorus (c) may create water and nutrient scarcity for plants, while nitrogen shows no significant change and a tendency to increase in transplanted plots (d). The direction of the arrows indicate an increase or a decrease with the transplantation of alpine communities to subalpine site. The acclimation lag after experimental climate change (in black dashed lines). Non-significant differences are shown in transparent lines.</figcaption></figure>

217

218 **Community-level leaf traits**
We measured community-level leaf traits *in situ* by sampling individuals with 5 cm distance along two diagonals of a 1m² part of each plot and thus 29 individuals in each plot (290 individuals sampled per experimental treatment). Since sampling occurred at the intersection of a 29-point ruler and a metal pin, a single plant usually made contact. In rare cases of multiple leaves touching, we selected the one with the greatest surface contact. This method naturally takes into account the coverage of the species as there is higher probability of sampling species with higher coverage. We measured the vegetative height (cm), leaf mass per area (kg/m²) and leaf nitrogen content (without petiole) (mg/g) based on the standardized protocol from Cornelissen *et al.*, 2003. Of the 82 species sampled across all experimental groups, 79% are arbuscular mycorrhizal, while 15% can be either mycorrhizal or non-mycorrhizal. The species composition includes 67% forbs, 27% graminoids, 5% legumes, and 1% shrubs. Among legumes, *Trifolium alpinum* is abundant in AlpineControl and AlpineWarmed communities (Fig. S4), while *Trifolium montanum*, *Trifolium pratense*, and *Trifolium alpestre* occur in SubalpineControl. Due to limited sampling material, LNC measurements were not possible for 0.3% of individuals in AlpineControl, 2.1% in AlpineWarmed, and 1% in SubalpineControl. Additionally, vegetative height data for one species was missing in both AlpineWarmed and SubalpineControl plots. None of the missing data were biased toward a specific species. After evaluating data quality, we excluded one LNC measurement from AlpineWarmed communities (Appendix S2). We calculated community-level leaf traits as the mean of log-transformed, standardized leaf traits for all sampled individuals per plot.

239

## Community-level root traits

We measured the community-level root traits *in situ* by collecting the fine roots with root ingrowth cores (Freschet *et al.*, 2021). In September 2020, we planted two soil ingrowth cores (15cm deep, 5cm diameter, plastic mesh size of 3mm) in each plot. The ingrowth cores were filled with river sand as a standardized root ingrowth medium, let one year in place, and sampled in September 2021 by merging the two cores of one plot into a single ziplock bag. Directly after sampling, we (i) washed the samples to separate fine roots from sand, (ii) weighed the fresh mass of the fine roots, (iii) scanned them to obtain measures of root diameter, length and volume (WinRhizo software), (iv) dried them for 72 hours at 65°C and weighed the dry mass and (v) measured root nitrogen content (RNC, mg/g) on dry and ground subsamples using an elemental analyser (FlashEA 1112: Fisher 302 Scientific, Waltham, Massachusetts, USA). We calculated specific root length (SRL) as the ratio of root length to root dry mass (m/g), and root tissue density (RTD, g/cm³), as the ratio of root dry mass to volume (Freschet *et al.*, 2021).

241

242

243

244

245

246

247

248

249

250

251

252
We log-transformed and standardized the root traits. Root cores in one SubalpineControl were missing. Hence, we gap-filled the values with the mean of the nine other replicates of SubalpineControl plots.

## Ecosystem functions and soil microbial activities

We focused on above- and below-ground ecosystem functions that are tightly linked to plant communities: Above- and below-ground plant productivity, decomposition of standardized recalcitrant (rooibos tea) and labile (green tea) litter (Keuskamp et al., 2013). We used dry mass of fine roots as a proxy of annual belowground biomass. As a proxy of annual aboveground biomass production, we measured in each plot in each week of the growing season the Normalized Difference Vegetation Index (NDVI) with Decagon ProCheck spectral reflectance sensor, and estimated the area under the NDVI curve from the snowmelt to snowfall in 2021 (Bektaş et al., 2021). Green (labile) and red (recalcitrant) teabags (Keuskamp et al., 2013) were installed for one year beneath the soil surface in each plot close to the soil ingrowth cores in September 2020, sampled in September 2021, and dried for 48h at 70°C to measure their dry mass. From this we calculated the decomposition rate as the difference of the initial dry mass of the teabag and the measured dry mass in 2021 divided by the initial dry mass.

We also identified the soil microbial activities via measuring the percentage of arbuscular mycorrhizal colonization in the roots, and the number of 16S rRNA gene copy per root mass (g) as a proxy for bacterial biomass. Higher bacterial biomass in a given experimental group than others indicated stronger bacterial activity and thus, fast microbial activities of fast growing microbial communities. Higher mycorrhizal colonization in a given experimental group than others indicated stronger collaborative microbial activities. We quantified arbuscular structures within cleaned and stained root samples (Vierheilig et al., 1998, 2005)). To ensure equal sampling, we prepared slides from 1-cm segments of ten roots per community sample. Each segment was examined at three randomly chosen intersections, totaling 30 observation points per sample. To mitigate observer bias, these observations were independently replicated by three observers. Arbuscular colonization was then quantified as the median percentage of observed arbuscular presence across the three observers. Finally, we performed quantitative PCR (qPCR) on dry root samples (ie. related protocol specified at Appendix S1). We log-transformed and standardized all measurements. Moreover, a difference in decomposition rates of recalcitrant and labile litter can also indicate increase in fungal or bacterial energy channels, respectively.
287

288 **Statistical analyses**

289 To disentangle functional plant strategies, we built a principal component analysis (PCA) on leaf (LMA, LDMC, LNC) and root (i.e. SRL, RD, RNC, RTD) traits related to our two focal trade-offs measured in control plots (Fig. 1). We then tested with Horn's parallel analysis if two dimensions were sufficient enough to represent the variation in these traits (Franklin et al., 1995). We conducted a varimax rotation on the first two axes of this PCA to be able to assure a better interpretability of the components and of the trait loadings on the first two components (Carmona et al., 2021).

296

297 Communities acclimate to new climate conditions after transplantation through two processes: changes in individuals' traits and populations including species' relative abundance changes and turnover. However, note that the species turnover, especially through establishment of the surrounding subalpine species in the AlpineWarmed communities is low (Appendix S2). Thus, to investigate the effect of experimental climate change on the plant functional traits at community level, ecosystem functions and soil microbial activities, we calculated the experimental climate change effect (difference between AlpineWarmed and AlpineControl), community-level acclimation lag after experimental climate change (difference between SubalpineControl and AlpineWarmed) for each variable using ANOVAs (Table S8-10) (Bektaş et al., 2021). While the experimental climate change effect quantified the amount of change after transplantation, acclimation lags indicated how much change was further needed to reach a full acclimation under the assumption that the control communities are at a stable state and fully acclimated to their current conditions (a more elaborated discussion can be found at (Bektaş et al., 2021)). We adjusted the p-values with multivariate t-distribution adjustment for multiple tests.

312

313 We additionally investigated which change in the environmental conditions the transplanted alpine communities respond to. For this, we conducted a redundancy analysis (RDA) with the functional traits as response variables and with site-level soil temperature, plot-level soil moisture and plot-level soil nutrients (total phosphorus and nitrate concentration) as explanatory variables. RDA performs multiple linear regressions of multiple response variables followed by a PCA of the fitted values (Legendre & Legendre, 2012). RDA allows us to test the overall impact of different environmental conditions on all of the functional traits simultaneously. We tested the significance of the RDA model, RDA axes and explanatory variables with permutation tests

320
321 (ie.,1000 permutations of the plots, Table S3) (Borcard et al., 2011). We concluded that the
322 significant explanatory variable with the most proportion of the explained variance has the
323 strongest impact on the functional traits.

324
325 Finally, to assess the changes in the links between the community-level functional traits and
326 ecosystem functions and microbial activities with experimental climate change, we conducted a
327 redundancy analysis (RDA) with the ecosystem functions and microbial activities as response
328 variables, and with functional traits, experimental climate change (i.e., 0/1 for controls and
329 AlpineWarmed, respectively) and their two-way interaction as explanatory variables. Here, we
330 included both controls because we hypothesized that even if the functional traits and ecosystem
331 functions change from high to low elevation under control conditions, the link (ie., the
332 correlation) between them should remain the same but it should change (ie., temporarily broken
333 or sign of the correlation changes) under experimental climate change. We tested this with an
334 RDA and we chose to perform RDA because we did not want to assume a causal one-way
335 relationship between functional traits, ecosystem functions and microbial activities as there are
336 feedbacks within and between them. Because of the high correlation between labile and
337 recalcitrant litter decomposition rates (r = 0.49, p < 0.01), we only included labile litter
338 decomposition rate in the analysis. We tested the significance of the RDA model, RDA axes and
339 explanatory variables with permutation tests (ie.,1000 permutations of the plots, Table S4).

340 When a given functional trait was only significant without its interaction with the experimental
341 climate change, we concluded that the functional trait has a strong link to ecosystem functions
342 but the links do not change from controls to experimentally changed conditions. When only the
343 experimental climate change effect was significant, we concluded that there were experimental
344 climate change effects that we could not explain with the functional traits. When the interaction
345 between a given functional trait and experimental climate change was significant, we concluded
346 that the links (ie., magnitude or direction) between functional trait and ecosystem functions and
347 microbial activities change with the experimental climate change. When the variation explained
348 by the interaction between a functional trait and experimental climate change was as high as
349 that explained by the trait alone, we interpreted this as a tendency for the relationship (i.e.,
350 magnitude or direction) between the trait and ecosystem functions or microbial activities to shift
351 under experimental climate change.

352
We conducted the statistical analyses with R version 4.4.1 (R Core Team, 2024) with the following packages: emmeans (Lenth, 2022), vegan (Oksanen et al., 2022), paran (Dinno, 2018), psych (William Revelle, 2024).

## 356 Results

### 357 1) Can we disentangle functional trait trade-offs in control plots?

The first two axes of the PCA linked to the fast vs. slow and the do-it-yourself vs. outsourcing trade-offs (Fig. 3) explained 84% of the variation in functional trait space. Even though according to Horn's parallel analysis (Fig. S2), one axis from this PCA was enough to represent the variation, the first PCA axis alone explained only 48% of the variation in the functional trait space. After the varimax rotation; SRL and RD mainly loaded on the first rotated axis (loadings: -0.95, 0.88 respectively) representing the do-it-yourself vs. outsourcing trade-off, while LMA, LNC and RNC mainly loaded on the second axis (loadings on: 0.92, -0.81, -0.64, respectively) representing the fast vs. slow trade-off (Table S2). Thus, we showed that the hypothesized trade-offs (Fig. 1) partially occurred at community-level in sites at the same mountain slope and thus along a short environmental gradient. There are two exceptions: RTD mainly loaded on the first axis (loading: 0.89) together with SRL and RD (Fig. 3, Table S2) and vegetative height did not constitute a third orthogonal axis of plant size but equally loaded on the two axes (Table S2). AlpineControl communities exhibited a faster and more of a do-it-yourself strategy than SubalpineControl communities (Fig. 3 & 4).

### 372 2) How do functional traits change under experimental climate change?

Just like SubalpineControl communities, AlpineWarmed communities exhibited slower and more outsourcing strategies than AlpineControl communities (Fig. 4). Experimental climate change effects on traits related to the fast vs. slow trade-off included an increase in LMA and a decrease in LNC and RNC (Fig. 4). Experimental climate change effects on traits related to the do-it-yourself vs. outsourcing trade-off included an increase in RTD and a decrease in SRL (while the increase in RD was not significant). Moreover, vegetative height tended to increase under experimental climate change but the effect was not significant. Interestingly, for LMA, RTD, RNC and SRL, we did not observe significant acclimation lags of communities, i.e. differences between SubalpineControl and AlpineWarmed plots, with the exception of VH (smaller in AlpineWarmed than in SubalpineControl, Fig. 4), LNC (higher in AlpineWarmed than in SubalpineControl) and RD (narrower in AlpineWarmed than in SubalpineControl). The redundancy analysis shows that functional traits respond the most to the changes in soil
386 moisture (34% of explained variance in functional traits) but also to the changes in temperature

387 (14% of explained variance in functional traits) under experimental climate change (Fig. 5).

388

<figure><img src="image_5.png" /><figcaption>389

**Fig. 3:** Community-level functional trait space constructed with a principal component analysis followed by a varimax rotation with fast vs. slow and do-it-yourself vs. outsourcing trade-offs of the control plots (circles). Fast vs. slow trade-off is constructed from LNC, RNC and LMA. Do-it-yourself vs. outsourcing is constructed from SRL, RD and RTD. Diamond shapes indicate the centroids of the control plots. (VH: Vegetative height, LNC: leaf nitrogen content, LMA: leaf mass per area, RNC: root nitrogen content, SRL: specific root length, RD: root diameter, RTD: Root tissue density)</figcaption></figure>

397

398
<figure><img src="image_6.png" /></figure>

Significant differences → * → ns

399
400
401
402
Fig. 4: Community-level functional trait values of experimental plots. The experimental climate change effect (in black solid lines) is the difference between AlpineWarmed and AlpineControl plots. The direction of the arrows indicate an increase or a decrease with the experimental climate change effect. The acclimation lag after experimental climate change (in black dashed lines) is the difference between the AlpineWarmed and SubalpineControl plots. Non-significant differences between experimental plots are transparent. Error bars represent 95% confidence intervals. Trait values are log-transformed and z-score normalized. (VH: Vegetative height, LNC: leaf nitrogen content, LMA: leaf mass per area, RNC: root nitrogen content, SRL: specific root length, RD: root diameter, RTD: Root tissue density). A visualisation of non-transformed values can be found in Fig. S12.

<figure><img src="image_7.png" /></figure>

<figure><img src="image_8.png" /></figure>

Fig. 5: a) Redundancy analysis (RDA) between functional traits and environmental conditions as induced by the experimental climate change. Grey and colored arrows indicate response and explanatory variables, respectively. Centroids of the experimental plots are indicated in diamond shaped points. The RDA correlation triplot is constructed with scaling = 2 meaning that the angles between variables reflect correlations between them. b) Proportion of variance explained by each variable. Significant variables are indicated with a star (*). (VH: Vegetative height, LNC: leaf nitrogen content, LMA: leaf mass per area, RNC: root nitrogen content, SRL: specific root length, RD: root diameter, RTD: Root tissue density). A visualisation of non-transformed values can be found in Fig. S12.
423 length, RD: root diameter, RTD: Root tissue density) Note that the soil temperature was

424 measured at site-level whereas all the other variables at plot-level.

425

426

427

428

429

430

431

For Peer Review
<figure><img src="image_9.png" /><figcaption>Fig. 6. Ecosystem functions and microbial activities of the experimental plots. The experimental climate change effect (in black solid lines) is the difference between AlpineWarmed and AlpineControl plots. The direction of the arrows indicate an increase or a decrease with the experimental climate change. The acclimation lag after experimental climate change (in black</figcaption></figure>
437 dashed lines) is the difference between the AlpineWarmed and SubalpineControl plots. Non-
438 significant differences between experimental plots are transparent. Values are log-transformed
439 and z-score normalized. Error bars represent 95% confidence intervals. A visualisation of non-
440 transformed values can be found in Fig. S13.

<figure><img src="image_10.png" /></figure>

441
442 **Fig. 7:** a) Redundancy analysis (RDA) between ecosystem functions (response variables: litter decomposition, above- and belowground productivity, bacterial biomass) and explanatory variables, including functional traits, experimental climate change and their two-way interactions (denoted ":eCC"). Grey and colored arrows indicate response and explanatory variables, respectively in a). Centroids of the experimental plots are indicated in diamond shaped points.
443
444
445
446
447 The RDA correlation triplot is constructed with scaling = 2 meaning that the angles between variables reflect correlations between them. b) Proportion of variance in ecosystem functions explained by each variable. Significant variables are indicated with a star (*). (VH: Vegetative height, LNC: leaf nitrogen content, LMA: leaf mass per area, RNC: root nitrogen content, SRL: specific root length, RD: root diameter, RTD: Root tissue density, AC: Arbuscule colonization, eCC: Experimental climate change)
448
449
450
451
452
453
454
455
456
457 Under experimental climate change, all ecosystem functions and microbial activities were enhanced with significant increases of above-ground productivity and decomposition rates and non-significant increases of below-ground productivity, arbuscular colonization and bacterial

**3) Cascading effects from experimental climate change via functional traits to ecosystem functions and microbial activities?**

457
458
459
Under experimental climate change, all ecosystem functions and microbial activities were
enhanced with significant increases of above-ground productivity and decomposition rates and
non-significant increases of below-ground productivity, arbuscular colonization and bacterial
biomass (Fig. 6). Decomposition rates fully acclimated while the increase in above-ground productivity was not enough to reach full acclimation (i.e. AlpineWarmed productivity was significantly lower than SubalpineControl). Interestingly, below-ground productivity also tended to increase (i.e. even though non-significantly) with experimental climate change even though under subalpine conditions SubalpineControl plots have lower productivity than AlpineControl plots.

Redundancy analysis (RDA) revealed that a large portion of the variation in ecosystem functions and microbial activities (~70%) was explained by functional traits and experimental climate change effects (Fig. 7). When considered together with their interaction with experimental climate change, above- and belowground traits (along with their interactions with experimental climate change) explained comparable amounts of variation in ecosystem functions and microbial activities (Fig. 7b). However when considered alone (i.e. without their interaction with experimental climate change), aboveground traits had significant effects and accounted for the largest proportion of explained variation. Whereas, of the belowground traits, only RNC had a significant effect (Table S6, Fig. 7). While none of the interactions between individual traits and experimental climate change were statistically significant, the interaction of belowground traits with experimental climate change still explained nearly as much variation as these traits alone. This shows that there is a tendency that the links between the below-ground functional traits and ecosystem functions and microbial activities become disrupted. Overall, the experimental climate change alone was not significant and only explained less than 3% of the variation in ecosystem functions and microbial activities.

## 482 Discussion

The response of plant communities to climate change is recognized as one of the fundamental mediators of environmental change impacts on ecosystem functions and microbial activities. Here, we studied the responses of plant functional strategies to 5 years of *in situ* climate change and the cascading effects on related ecosystem functions. We observed strong experimental climate change effects on the functional traits related to two dominant trade-offs. Nevertheless, communities did not reach full acclimation for either of the trade-offs. Moreover, we observed that changes in functional traits cascaded to changes in ecosystem functions. Most of the variance in ecosystem functions and in microbial communities were explained by the above-ground functional traits and links between traits and ecosystem functions did not change under experimental climate change. In contrast, the links between below-ground functional traits and
ecosystem functions along with microbial communities showed a tendency to become disrupted under climate change. Interruptions of such links between plant strategies and ecosystem functions might challenge our capacity to predict the trajectories of plant and soil communities and their associated ecosystem functions under climate change.

497

498 **Species' orthogonal trade-offs upscale to communities**

We showed that in a small-scale community-level experiment with a relatively short environmental gradient, fast vs. slow and do-it-yourself vs. outsourcing trade-offs can well explain trait variation. As shown earlier in large-scale observations on species distributions along stark environmental gradients (Bergmann et al., 2020; Weigelt et al., 2021), these two dimensions were orthogonal to each other and sufficient to represent plant functional strategies with the exception of root tissue density that aligned rather with the do-it-yourself vs. outsourcing trade-off. To our knowledge, there is so far a single study that investigated the presence of orthogonal trade-offs simultaneously in leaf and root traits at community-level in a natural context (Lachaise et al., 2022). Here, in addition, we showed that this framework of orthogonal trade-offs can be particularly useful in determining abiotic drivers of acclimation stress for plants and studying ongoing climate change on shifts in plant functional strategies.

510

511 **Soil moisture determines the functional strategies and their acclimation to climate**
512 **change in mountain grasslands**

One of the questions under climate change (and in our experiment) is whether the increasing temperatures and the associated increased energy input leads to more benign conditions for higher altitude mountain plants, or whether the increased drought, especially during summers, will limit plant growth. In our experiment, we found that above-ground plant productivity in the warmer and drier subalpine sites was higher than in the colder and less dry alpine sites and productivity of alpine communities increased when they were transplanted to warmer and drier conditions. This indicates that plant productivity overall benefited more from the additional energy input than it suffered from added drought. However, plant functional strategies responded differently. The colder and less dry alpine communities were faster and more do-it-yourself compared to the warmer and drier subalpine communities and the transplanted alpine communities became slower and more outsourcing after transplantation. These differences were both driven by the differences in species composition (Fig. S3-4) and trait plasticity. Overall, plant functional strategies were more influenced by the additional drought than by the added energy. Such drought responses have been reported earlier (Laughlin et al., 2021;
Lachaise et al., 2022), as mycorrhizae supported plant growth under drought (Augé et al., 2015), and communities adopted slow growth strategies to withstand drought. Our community-level results highlighted the sensitivity of the alpine vegetation to drought events that are increasingly frequent under climate change and in line with landscape-level findings (Choler, 2023). Thus, community-level responses of functional traits both through plasticity and species turnover to drought even at local scale can serve as early warning signals of changes in functional composition of alpine plant biodiversity.

**Asynchronous acclimation in functional strategies: transient biotic interactions?**

Root traits (except root diameter) and leaf mass per area, important traits in determining plants' resilience to drought (Poorter et al., 2009; Blumenthal et al., 2020; Laughlin et al., 2021), acclimated more efficiently to experimental climate change (i.e. complete resemblance to subalpine communities) than vegetative height, important in determining plants' growth capacity and competitiveness for light (Craine & Dybzinski, 2013). This is perhaps showing that under multiple environmental changes, there is a priority in community-level plastic responses: alpine communities primarily dedicate resources to construct more resilient roots and leaves (or such species are selected in the communities) under drought than growing taller and acquire competitive advantage when there is more energy in the system. This might be a disadvantage for alpine species especially when these communities are being invaded by taller, thus more competitive (i.e., for acquiring light) subalpine species as they migrate upslope to follow their abiotic niche under future climate change (Lenoir et al., 2008). In our experiment, communities were not only exposed to climate change but also to establishment of new species from the surrounding subalpine communities (Appendix S2). Yet, colonization events were not as frequent in our experiment in contrast to other transplant experiments (Bektaş et al., 2024). For example, one of the tallest and very abundant species in the subalpine communities, *Patzkea paniculata* subsp. *paniculata*, did not colonize the warmed alpine communities at all until now (Fig. S4). Colonization lags may occur when seeds fail to establish under a closed canopy.

However, we observed several open soil patches in our communities and instances where colonization occurred from the borders by clonal species. In fact, Bektas et al. (2024) showed with more than 40 different whole-community transplant experiments worldwide with varying plot sizes and experimental designs that colonization lags persisted at the end of the experiments when the transplanted high-elevation communities exhibited fast-growing strategies. In our experiment and beyond, such lags in colonization events might have been due to persistence of fast strategies in alpine communities giving them a competitive advantage in acquiring soil
nutrients and water or by maintaining the soil conditions and microbial activity in their favor and preventing the establishment of new subalpine species. In fact, transplanted communities in Austrian and the Swiss Alps, initially exhibiting slow-growth strategies, were colonized significantly by subalpine species which caused a complete switch in fast-growing functional strategies (Schuchardt et al., 2023). Together with our results, this shows that the initial functional state of the mountain grassland communities is an important determinant of their functional and taxonomic trajectory under climate change.

## Disruption of below-ground functional traits and functions under climate change

In our experimental communities, functional traits explained a large part of the variation of ecosystem functions and microbial activities, suggesting that climate change induced changes in functional traits cascade to ecosystem functions and microbial activities. However, some of the links between functional traits and ecosystem functions were not in line with our expectations. Ecosystem productivity and fast decomposition rates, often associated with fast-growing plant strategies (Poorter et al., 2009; Pietsch et al., 2014) and hypothesized to be associated with do-it-yourself plant strategies, were associated with slow and outsourcing strategies in our experiment. Interestingly, these relationships were not altered with climate change treatments either. In fact, slow-growing subalpine communities and warmed alpine communities, despite being exposed to drought, had longer growing seasons than the alpine communities under alpine conditions and thus, they had the opportunity to grow longer, increasing the community productivity (Bektaş et al., 2021). But in comparison under the same warm and dry subalpine conditions, the slower and more outsourcing subalpine communities were more productive than the faster and more do-it-yourself alpine communities. Therefore, it seems like there is no clear trade-off between higher productivity and slow-growth in mountain grasslands.

Under experimental climate change, above-ground traits responded strongly but insufficiently (i.e. acclimation lags remained) but links between traits and functions remained unchanged and above-ground productivity increased, even so with acclimation lags remaining. In contrast, below-ground traits responded strongly and efficiently (except root tissue density). However, the links between traits and ecosystem functions showed a tendency to be altered with climate change and below-ground productivity tended to change in the “counterintuitive” direction (i.e. in a different direction than expected given the subalpine control communities). This may indicate a breaking coordination of below- and above-ground plant acclimation potentially due to
opposing responses to simultaneously increasing energy input and drought stress, and with consequences for some ecosystem functions. While above-ground functional traits remain good predictors of ecosystem functions under climate change, this could only be a transient state and disruptions between below-ground traits and ecosystem functions can be early warning signals of acclimation problems.

Limitations & Perspectives

While we demonstrated fast but insufficient acclimation of alpine plant community traits to climate change, a clearer understanding of acclimation lags requires decomposing trait acclimation into plasticity and species turnover. Fully achieving this would require sampling all individuals, which is impractical for long-term experiments. However, hyperspectral and high-resolution 3D imagery could estimate above-ground traits efficiently.

Moreover, this study provides only proxies for changes in decomposition rates and microbial activities. Targeted sequencing of arbuscular mycorrhizae and litter-decomposing bacteria, or full genome sequencing, could offer a more complete picture of plant-soil feedbacks under climate change. Future research should also examine how microbial acclimation lags influence plant community responses. Finally, a global synthesis of 40+ transplant experiments revealed a common trend of rapid convergence toward low-elevation communities under warming, yet colonization and extinction lags persist (Bektaş et al., 2024). Variation in responses was linked to initial climate conditions and functional diversity, underscoring the context dependency of ecological processes. Given the logistical challenges of local experiments, cross-study analyses within transplant networks are essential to test the generality of these results and reveal context-dependencies on changes in leaf and root traits under climate change.

Conclusion

In this study, we confirmed that fast vs. slow and do-it-yourself vs. outsourcing orthogonal trade-offs of plants upscale to plant communities with the exception of root tissue density, that they vary with climatic conditions along mountain slopes, and that they respond to experimental climate change. Tracking the transient dynamics of these strategies, until they reach full acclimation, under simultaneous warming and drying allowed us to detect their rapid, yet not always successful acclimation. Our study highlights the importance of multiple stressors in altitudinal gradients, and that climate change effects beyond warming such as drought can lead the direction of the responses. The cascading effects between functional traits and ecosystem
628

functioning, and the impairment of their links under climate change, show that studying the

629

transient dynamics of functional traits can reveal early warning signals.

630

## Acknowledgements

631

This research was funded by the TransAlp project (ANR-20-CE02-0021) and the internal

632

funding of Laboratoire d'Ecologie Alpine. This study would not have been possible without the

633

help of Master's students of the 2021-2022 BEE program at Université Grenoble Alpes and

634

Université Savoie Mont Blanc. We thank Viet Tran-Khac for their support in laboratory

635

measurements.

636

## Competing interests

637

Authors declare no competing interests.

638

## Author contributions

639

BB, GR, WT and TM designed the research. BB, GR, AS, JR, MG, JCC, JP and TM conducted

640

the fieldwork and data collection. BB, GR, AS, AF, JP, EL, TM and JCC conducted the

641

laboratory work. BB and RF conducted the data analysis. BB led the interpretation and writing of

642

the manuscript with substantial support from TM. All authors contributed to the final version of

643

the manuscript.

644

## Data availability

645

Data will be publicly available upon submission. For peer review, the data is available at OSF

646

with a view-only option: https://osf.io/j39um/?view_only=e8bb850c50bd4654b0b4cbfe572524a8

647

The code is publicly available: https://github.com/billurbektas/transalp_functionalgit</code>

648

649

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