Climate, soil resources and microbial activity shape the distributions of mountain plants based on their functional traits

Abstract

While soil ecosystems undergo important modifications due to global change, the effect of soil properties on plant distributions is still poorly understood. Plant growth is not only controlled by soil physico-chemistry but also by microbial activities through the decomposition of organic matter and the recycling of nutrients essential for plants. A growing body of evidence also suggests that plant functional traits modulate species' response to environmental gradients. However, no study has yet contrasted the importance of soil physico-chemistry, microbial activities and climate on plant species distributions, while accounting for how plant functional traits can influence speciesspecific responses. Using hierarchical effects in a multi-species distribution model, we investigate how four functional traits related to resource acquisition (plant height, leaf carbon to nitrogen ratio, leaf dry matter content and specific leaf area) modulate the response of 44 plant species to climatic variables, soil physico-chemical properties and microbial decomposition activity (i.e. exoenzymatic activities) in the French Alps. Our hierarchical trait-based model allowed to predict well 41 species according to the TSS statistic. In addition to climate, the combination of soil C/N, as a measure of organic matter quality, and exoenzymatic activity, as a measure of microbial decomposition activity, strongly improved predictions of plant distributions. Plant traits played an important role. In particular, species with conservative traits performed better under limiting nutrient conditions but were outcompeted by exploitative plants in more favorable environments. We demonstrate tight associations between microbial decomposition activity, plant functional traits associated to different resource acquisition strategies and plant distributions. This highlights the importance of plant-soil linkages for mountain plant distributions. These results are crucial for biodiversity modelling in a world where both climatic and soil systems are undergoing profound and rapid transformations.

Lags in phenological acclimation of mountain grasslands after recent warming

“…The increase in community plant growth and the competitive exclusion of slower‐growing alpine species will also change plant–soil feedbacks. According to the ‘fast–slow’ plant economics spectrum, faster growth is associated with more exploitative plant traits (and thus, functional strategies), especially under favourable environmental conditions (Martinez‐Almoyna et al., 2020; Reich, 2014). Such an above‐ground functional strategy shift towards the faster part of the economic spectrum will affect the micro‐organisms involved in plant litter composition (e.g.…”

Strong links between plant traits and microbial activities but different abiotic drivers in mountain grasslands

“…It is well understood that plant traits are linked to microbial community composition and functioning, directly and via plant litter quality (Fanin et al, 2014; Grigulis et al, 2013; Legay et al, 2014; Martinez‐Almoyna et al, 2020). In our study, plant traits associated with the plant conservative‐exploitative continuum (LMA, LNC and LDMC) were indirectly connected to SOM, as well as soil enzymatic activities, via a central link between plant traits and soil C/N.…”

“…Variables defining the compartments plant community, soil properties and climate are written next to them: C/N, soil carbon nitrogen ratio; LDMC, leaf dry matter content; LMA, leaf mass per area; LNC, leaf nitrogen content; SOM, organic matter. References for the specific linkages are indicated by numbers: 1: Bowman et al (2004); 2: De Vries et al (2012); 3: Freppaz et al (2007); 4: Grigulis et al (2013); 5: Legay et al (2014); 6: Martinez‐Almoyna et al (2020); 7: Mayor et al (2017); 8: Piton, Legay, et al (2020); 9: Quested et al (2007); 10: Sundqvist et al (2013), and references therein; 11: Van der Putten et al (2016), and references therein; 12: Wardle et al (2004), and references therein.…”

“…Moreover, most models used in previous studies to infer patterns in aboveground‐belowground linkages, such as structural equation models, assume causality and directionality. In particular, microbial community composition was mostly assumed to be the response variable (Boeddinghaus et al, 2019; De Vries et al, 2012; Delgado‐Baquerizo et al, 2018; but see Martinez‐Almoyna et al, 2020). However, aboveground‐belowground linkages result from interactions and feedbacks.…”

Altitudinal Zonation of Green Algae Biodiversity in the French Alps

“…Ten bioclimatic variables, estimated as averages over 1988–2018 were used: the mean of the annual temperature (TG), the growing degree days (GDD), the freezing degree days (FDD), these three variables were estimated at 1 and 10 cm below ground, the climatic water stress (CWD), the solar radiation, the total snow depth (DSN_T_ISBA) and the diurnal temperature range (DRT.air). Details on these variables are available in Martinez-Almoyna et al (2019) and Martinez-Almoyna et al (2020) Finally, two categorical variables: the type of environment ( Environment ) with two modalities, forest or open-area, and the soil horizon ( Horizon ) with two modalities, litter or deep soil, complete this description. It is common for environmental variables to be multi-colinear with respect to each other.…”