Root functional parameters predict fine root ... - Wiley Online Library

Journal of Ecology

doi: 10.1111/1365-2745.12537

Root functional parameters predict fine root decomposability at the community level n Prieto1, Alexia Stokes2 and Catherine Roumet1* Iva de Montpellier – Universite Paul CNRS, Centre d’Ecologie Fonctionnelle et Evolutive (CEFE) UMR 5175, Universite 2 Valery – EPHE, 1919 Route de Mende, 34293 Montpellier Cedex 5, France; and INRA, Botanique et bioinformatique de l’architecture des plantes (UMR-AMAP), Bd de la Lironde, TA A-51/PS2 34398 Montpellier Cedex 5, France 1

Summary 1. Root quality is one of the main drivers of fine root decomposition, an important process controlling soil carbon (C) and nutrient cycling in most terrestrial ecosystems. Root quality is defined by chemical and morphological traits, which differ across species and thus communities. This trait variation is assumed to follow a trade-off between resource acquisition and conservation (i.e. the root economics spectrum). To what extent root quality or the economics spectrum influence fine root decomposition rates at the community level remains poorly understood, particularly within the context of land use change. 2. Changes in land use induce shifts in plant community composition, which also affect root distribution within the soil profile, resulting in changes in root quality. We hypothesize that at the community level, (i) root decomposability is driven by community root functional parameters (i.e. root traits measured at the community level), (ii) changes in root functional parameters among land use types and with soil depth translate into changes in root decomposability. 3. We collected shallow and deep fine roots (≤ 2 mm) from 20 plant communities across contrasting land use types in seven sites world-wide, ranging from agricultural crops to natural forests and determined their decomposition rate in standard conditions. Fine root quality was related to known values of functional parameters for these communities, including specific root length (SRL), carbon (C), nitrogen (N) and lignin concentrations. 4. A combination of chemical functional parameters (lignin, C and N concentrations) best explained root decomposition rates at the community level, whereas root economics remained a poorer predictor of decomposability rates. Among land use gradients, roots from agricultural and agroforestry communities decomposed faster than roots from forest sites. Across and within plant communities, a consistently greater decomposability in shallow roots was observed. Both land use and depth effects were explained by changes in root chemical traits at the community level. 5. Synthesis. Our results suggest that the conversion of plant communities from forests to agricultural lands leads to changes in root functional parameters that drastically increase root decomposition rates and may lead to major soil C losses, especially in shallow soil layers. Key-words: fine roots, functional traits, land use, plant–soil interactions, root decomposition, root economics spectrum, soil depth, trade-off

Introduction Plant litter decomposition is a key process in global carbon (C) and nutrient cycling and represents one of the largest C fluxes from terrestrial ecosystems to the atmosphere (Berg & Laskowski 2005; Berg & McClaugherty 2008). The contribution of fine roots to the decomposition process is crucial because fine roots are the main source of organic matter input *Correspondence author: E-mail: [email protected]

to the soil, especially at large depths (Berg & Laskowski 2005; Rasse, Peresta & Drake 2005; Kell 2012; Clemmensen et al. 2013; Freschet et al. 2013). The large variation in root decomposition rates reported among plant species (Silver & Miya 2001; Zhang et al. 2008) is likely to drive root decomposition rates at the community level. In heterogeneous plant communities, roots of several species are intermingled and decomposed together rather than in isolation. However, most studies on root decomposition concerned roots from individual species, which were only collected in shallow soil layers

© 2016 The Authors. Journal of Ecology © 2016 British Ecological Society

2 I. Prieto, A. Stokes & C. Roumet and very few have considered how root decomposition is regulated at the community level (Aulen, Shipley & Bradley 2012; Zhang et al. 2013; Mommer et al. 2015). There is evidence that the quality of fine roots is speciesspecific. Plant roots differ in chemical and morphological traits, which affect decomposition rates. This rates and this variation may be more important than the environmental variation, both among and within climates (Silver & Miya 2001; Zhang et al. 2008; Cusack et al. 2009). Root decomposition rates are positively correlated with root nitrogen (N) concentration (Vivanco & Austin 2006; Zhang et al. 2008), but negatively correlated with recalcitrant features such as lignin, C: N or lignin:N (Silver & Miya 2001; Aulen, Shipley & Bradley 2012; Freschet, Aerts & Cornelissen 2012; Smith et al. 2014; Roumet et al. 2016). Few studies have focused on the influence of root morphology (i.e. root diameter or specific root length, SRL) on decomposition rates and contrasting results have been reported (Hobbie et al. 2010; Birouste et al. 2012; Freschet, Aerts & Cornelissen 2012; Smith et al. 2014; Roumet et al. 2016). Whether root quality, and which root traits, drives fine root decomposition in a mixed plant community has not yet been examined. Changes in vegetation as a consequence of land use changes may affect fine root litter decomposition through shifts in plant community composition (Garnier et al. 2007; Chollet et al. 2014; Prieto et al. 2015). Changes in the species composition of the community alter the quality of overall fine roots in the community (Zhang et al. 2008; Holdaway et al. 2011; Prieto et al. 2015), given that plant species differ strongly in the quantity and quality of fine roots (Comas & Eissenstat 2004; Kerkhoff et al. 2006; Birouste et al. 2012). There is also growing evidence that, within plant communities, fine root quality changes with soil depth in relation to contrasted abiotic conditions (mainly resource availability and soil compaction) (Vanguelova et al. 2005; Makita et al. 2010; Prieto et al. 2015). We tested whether variations in fine root traits measured at the community level (i.e. the ‘functional parameters’ of plant communities after Violle et al. 2007) affect fine root decomposition measured in standard conditions (termed ‘litter decomposability’ hereafter). Therefore, we measured the decomposability of roots from contrasting plant communities located along land use intensity gradients, at two depths and across three climatic zones. In these plant communities, Prieto et al. (2015) demonstrated that fine roots from agricultural and agroforestry communities experiencing intense disturbance had better root quality (i.e. high root N concentration and low root dry matter and lignin contents) than less disturbed communities (i.e. natural forest communities). In addition, shallow roots were of better quality, compared to deep ones. In addition, Prieto et al. (2015) demonstrated a strong correlation between fine root functional parameters, and the existence of a root community economics spectrum (REScom). The REScom is defined as a syndrome of plant functional parameters summarized by a PCA axis that opposes, on one end, plant communities with root functional parameters associated with resource acquisition (high specific root length and

thin diameters) and on the other end, those communities with root traits associated with resource conservation (thick diameters and high root dry matter content and C and lignin concentrations, Prieto et al. 2015; Reich 2014). At the species level, recent studies demonstrated that traits characterizing leaf and stem economics strongly influenced leaf and stem decomposability (Santiago 2007; Bakker, Carre~ no-Rocabado & Poorter 2011; Freschet, Aerts & Cornelissen 2012). Such evidence, however, is scarce for roots and is still under debate (Freschet, Aerts & Cornelissen 2012). Thus, we wanted to test whether root quality and the REScom affect root decomposability at the community level, as previously reported at the species level (Silver & Miya 2001; Zhang et al. 2008; Cusack et al. 2009; Birouste et al. 2012; Solly et al. 2014; Roumet et al. 2016). The following specific hypotheses were addressed: (i) at the community level, fine root decomposability is driven by root functional parameters, following patterns similar to those reported at the species level; that is, roots of poor quality (high lignin concentration, lignin: N ratio and low N concentration) will decompose at slower rates and vice versa. If this first hypothesis is validated, we then hypothesize that (ii) roots will decompose faster as we move from forests to agricultural plant communities and (iii) roots from shallow soil layers will decompose faster than roots deeper in the soil profile. By addressing these hypotheses, we provide a better mechanistic understanding of how changes in land use can indirectly influence the decomposition of fine roots at different soil depths. These land use changes will have major implications for C and nutrient cycling due to the changes in root functional parameters.

Material and methods STUDY SITES AND EXPERIMENTAL DESIGN

This study was carried out in seven sites situated along a gradient of land use, ranging from agricultural, agroforestry or forestry systems, in three different climates (See Table S1 in Supporting Information). Three sites were situated in a tropical climate, three in a montane climate and one in a subhumid Mediterranean climate. More details on study sites are given in Prieto et al. (2015) and in Table S1. Within each of the sites, except the montane sites, three to four land use types spanning an agricultural intensification gradient were sampled. The different land use types chosen comprised agricultural fields with one species cultivated alone (CA); agroforestry sites with one tree species and the cultivated species (TC); agroforestry sites with one tree species and natural/regenerated vegetation, which were mostly herbaceous species (TV); fallow, that is regeneration phase after culture (FA) and secondary forests (FO). When there was no agricultural practice at a site (i.e. montane sites), only two land use types were selected: clusters of secondary forest (FO) and fallow areas created after tree thinning and mainly colonized by herbs and small shrubs (FA), (see Table S1 for additional details on land use types). ROOT SAMPLING

In 2012, in each land use type and site, roots were collected from a 3.0 9 2.0 m (6 m2) trench dug to a depth of 1.6 m. At the three

© 2016 The Authors. Journal of Ecology © 2016 British Ecological Society, Journal of Ecology

Root economics and litter decomposability 3 montane sites and the Mediterranean forest site, the soil was rocky and the maximum depth attained before encountering the bedrock was 60–80 cm at Premol, Bachat-Boulod and the forest site at Restinclieres and 20 cm at Achard. Within each trench, a large amount of roots (approximately 160 g fresh mass) were collected in the excavated shallow (top 20 cm) and deep soil layers (100–150 or 60–80 cm depending on sites, see Prieto et al. 2015 for details). These roots belonged to all species present in the neighbourhood of the trench and were representative of the roots present in the plant community. Agricultural (CA), agroforestry (TC) and tree with vegetation sites (TV) were very homogenous in their species composition and in fallow (FA) and forestry sites (FO), we dug the trench in a location carefully selected to be representative of the sites (Table S1). After collection, fresh root samples were taken to the laboratory and immediately washed gently to remove adhered soil particles. Roots were subsequently sorted to obtain living, fine roots (diameter ≤ 2 mm) with no sign of senescence. We used living roots because it was very difficult to identify and collect large enough quantities of dead roots in the field and it was not easy to assess their decomposition state. Living and decomposing roots form a continuum (Hobbie et al. 2010), and most studies have reported little or no difference in nutrient concentration between living and dead roots (McClaugherty, Aber & Melillo 1982; Aerts 1990; Freschet et al. 2010). For each site, land use type and root depth, several homogeneous root subsamples were prepared: three subsamples were conserved in distilled water and frozen until further root morphological measurements and four subsamples were oven-dried at 40 °C for 72 h before chemical analyses were conducted (see the Root functional parameters section). The remaining fine roots were separated into five or six subsamples and spread on filter paper to remove excess water and air-dried. Samples were then kept in the dark until the beginning of the decomposition experiment. Root samples from all sites were then sent to France, at the Centre d’Ecologie Fonctionnelle et Evolutive (CEFE, Montpellier), where root functional parameters and decomposability rates were determined. ROOT FUNCTIONAL PARAMETERS

Root functional parameter data were taken from Prieto et al. (2015). We will, however, present a brief description of how these were measured (see Prieto et al. 2015 for more details). Determination of root morphological functional parameters was conducted on three subsamples per trench and depth. Prior to scanning, frozen root samples were defrosted, sponged carefully to remove all excess water and weighed to determine their saturated mass (SM). Roots were then stained with a methyl violet solution (0.5 g L1) to increase contrast. Immediately after immersion, roots were rinsed, spread out in distilled water onto a mesh tray and finally transferred on a transparent acetate sheet and scanned at 400 dpi (Hummel et al. 2007). The resulting image was processed with image analysis software (Winrhizo pro, version 2009c, Regent Instrument, Quebec, Canada) to determine total root length (L) and mean root diameter. After scanning, roots were oven-dried at 60 °C for 72 h and then weighed to determine their dry mass (DM). Root dry matter content (RDMC; mg g1) was calculated as the ratio between DM and SM and specific root length (SRL; m g1) was calculated as the ratio between L and DM. Determination of root chemical functional parameters was conducted on four ground subsamples per trench and depth. The concentrations of water-soluble compounds, cellulose and lignin (mg g1) were obtained by the Van Soest method (Van Soest 1963) with a Fibersac 24 fibre analyser (Ankom, Macedon, NJ, USA). Root C and

N concentrations (RCC and RNC, respectively; mg g1) were measured using an elemental analyser (Thermo-Finnigan EA1112, Milan, Italy).

ROOT DECOMPOSABILITY EXPERIMENT

In October 2012, the potential decomposition rate (kpot, decomposability hereafter) of fine roots from all sites, land use types and depths, was assessed, according to the protocol described by Taylor & Parkinson (1988), and as modified by Ibrahima, Joffre & Gillon (1995). We prepared 216 polyamide litterbags (4 9 10 cm, 50 lm mesh size, Diatex, Villeurbanne, France); five to six litterbags per site, land use type and depth. No root material was available for deep roots in the following treatments: FO at Aquiares, FO and FA at Achard, FA at Bachat-Boulod, and CA at Restinclieres. Each litterbag was filled with 0.500 0.001 g of air-dried roots and was closed by folding the tissue twice and then stapling. Four additional subsamples of air-dried material from each trench and depth were oven-dried at 60 °C for 72 h to determine the air-dried/oven-dried weight ratio. Subsequently, these roots were incinerated at 500 °C for 8 h in a muffle furnace to determine their initial ash content. This ash content corresponds both to intrinsic minerals contained in the roots and soil particles adhered that were not completely removed during washing (Schlesinger & Hasey 1981). Litterbags were incubated in microcosms that made it possible to study root decomposition under standard conditions of soil, temperature and in the presence of similar microbial decomposer populations for all roots. The microcosms used consisted of a polyvinylchloride pipe, 15 cm in diameter and 15 cm high, fitted with a lid and with a sealed bottom. A grid, 2 cm above the bottom, divided the chamber into two parts: a usable space with a capacity of 1.5 L into which we placed a total of 1 kg of soil, and a 0.3 L drainage compartment. The soil (pH = 8.3, C = 13.6 g kg1, N = 1.1 g kg1, C:N = 12.6 and P = 0.026 g kg1) was a 2:1 mixture of soil from a common garden experiment at the CEFE (Montpellier, France) and the surface horizon soil from a nearby area. Within each microcosm, we buried one root decomposition bag horizontally, at a depth between 3 and 5 cm. The microcosms were kept in the dark at 22.0 0.06 °C, covered with a non-sealing plastic lid to avoid evaporation losses and watered weekly to keep soil moisture at 80% of field capacity. After a 16-week incubation period (from October 2012 to February 2013), litterbags were retrieved, opened and all the remaining roots were washed to eliminate potentially adhered soil particles, dried at 60 °C for 72 h and weighed for dry mass determination. Subsequently, the remaining roots were burned at 500 °C for ash content determination. We calculated kpot (g g1 year1) as follows: Mf ln M 0 kpot ¼ t where M0 is the initial and Mf the remaining mass expressed on an ash-free dry mass basis and t is the incubation time in years. Using k, we assumed a first-order exponential decay for all samples since decomposability was assumed to be at an early stage for all roots (Makkonen et al. 2012).

STATISTICAL ANALYSIS

We performed a principal component analysis (PCA) with the eight functional parameters used in Prieto et al. (2015) plus lignin:N, an important trait controlling fine root decomposition at the species level


4 I. Prieto, A. Stokes & C. Roumet (Silver & Miya 2001; Zhang et al. 2008; Solly et al. 2014). Mean values for each trench and each soil depth were used in the PCAs. The first three axes of the PCA, which were rotated with the Varimax procedure in order to strengthen the contrasts between axes (Craine & Lee 2003), explained 78.1% of the variance (Table S5; Fig. S1). As reported in Prieto et al.’s (2015) study, the first axis (PC1) explained 42.5% of the variation and represented a root economics spectrum (REScom) opposing plant communities with root functional parameters associated with resource acquisition (high SRL) to those associated with resource conservation (high values for root diameter, dry matter content, carbon, lignin concentration and lignin:N). To test the effect of root quality and the REScom on root kpot, we used general linear mixed model analysis (GLMMs) with functional parameters and the REScom as continuous fixed factors and site as a random effect to account for potential variability in climatic and soil conditions between sites. GLMMs testing the effect of root quality and the REScom were performed using the mean values for each trench and each depth. Root decomposability (kpot) and SRL were natural log (ln) transformed prior to analysis to comply with normality assumptions, and hence, a Gaussian error structure was used in the GLMM. We constructed all possible models combining the nine functional parameters and the REScom and alternative models were compared using the second-order Akaike information criterion that corrects for a small sample size (AICc, Burnham & Anderson 2002). Models with a difference in AICc > 4 indicate that these models have virtually no support and can be further omitted. When multiple models were selected (AICc < 4), we used a model averaging approach to select the variables on the combination of selected models and the relative contribution of each variable to this averaged model (Burnham & Anderson 2002). Variances of the models used for the AIC approach were estimated using maximum likelihood estimates (ML). To obtain an estimation of the fit of the best fitting model (i.e. the model with the lowest AICc) and that of the averaged model, we readjusted the model estimating the variance of the final model using restricted maximum likelihood estimates (REML). After adjusting the model with REML, we calculated the variance partition (R2) for the selected fixed factors according to Nakagawa & Schielzeth (2013).

To test for general depth and land use type effects on root decomposability, we performed a nested GLMM with depth nested within land use type and climate as fixed factors and site as a random factor to control for potential sampling location effects. For this analysis, we used all the subsamples collected from each trench and depth (n = 5– 6). As only one trench per land use type was sampled, subsamples from each trench and depth were not independent from each other. We thus used a compound symmetric covariance matrix that partitions the total variance into a within-subjects variation (subsamples from the same trench and depth) and a between-subjects variation (factors) in the model. Additionally, to test for depth and land use type effects within each of the sites, we performed general linear models (GLMs) for each individual site with depth nested within land use type as fixed factors. Here again we used a symmetric covariance matrix to account for the non-independence of the subsamples collected within each trench and depth. Data shown throughout the text are means SEM (standard error of the mean). All calculations and statistical analyses were performed with the R software (v. 2.15.3) using the packages ade4, MuMIn, effects, Hmisc, multcomp, lme4 and nlm (R Development Core Team 2013).

Results PREDICTING ROOT DECOMPOSABILITY

Variation in root kpot was best explained by models that included chemical rather than morphological functional parameters (Table 1; Fig. 1). The best fitting model (i.e. the model with the lowest AICc) included lignin, RNC and RCC and explained 87% of the variability in kpot. Lignin and RCC were negatively related to kpot (Fig. 1a,c), whereas RNC was positively correlated with kpot (Fig. 1b). When models with a DAICc < 4 were averaged, all functional parameters, except mean diameter and cellulose concentration, were selected. The relative weight of the functional parameters in the aver-

Table 1. Best fitting general linear mixed models between fine root decomposability (kpot), fine root functional parameters and the root economics spectrum (REScom, axis 1 scores in the PCA presented in Fig. S1), ordered by their AICc values and Akaike weights (Wi). Of all possible models, shown are models with a difference in AICc (DAICc) < 4 with the best fitting model (lowest AICc). Shaded cells indicate variables that were selected in a given model and the relative importance of each variable on the average model was calculated using a model averaging approach (Relative variable importance). The proportion of the variation of the best and average fitted models were R2 = 0.87 and R2 = 0.81, respectively All sites AICc

Variable DAICc

27.8 0.00 26.5 1.29 25.5 2.27 24.9 2.96 24.8 3.00 24.4 3.40 24.2 3.64 23.9 3.87 23.8 3.98 Relative variable importance

Wi

Lignin

RNC

RCC

Lignin:N

REScom

SRL

Water soluble

RDMC

0.83

0.68

0.47

0.37

0.17

0.11

0.06

0.05

0.34 0.18 0.11 0.08 0.08 0.06 0.06 0.05 0.05

Lignin, lignin concentration; RNC, root nitrogen concentration; RCC, root carbon concentration; lignin:N, lignin to nitrogen ratio; REScom, root community economics spectrum; SRL, specific root length; water-soluble, water-soluble compound concentration; RDMC, root dry matter content (n = 36–40). © 2016 The Authors. Journal of Ecology © 2016 British Ecological Society, Journal of Ecology

Root economics and litter decomposability 5

Fig. 1. Relationships between fine root decomposability rates (kpot), root chemical and morphological functional parameters and the root economics spectrum (REScom; axis 1 scores in the PCA presented in Fig. S1) for plant communities in contrasting land use types and sites. Grey symbols represent roots from shallow soil layers and black symbols represent roots from deep soil layers, samples from the Restinclieres site are indicated with squares. Statistical models are general linear mixed models with kpot as an independent variable, the corresponding root functional parameter or the REScomm as a continuous fixed factor and site as a random factor; n = 36–40. When significant, displayed are the model-predicted relationships (dashed line) with 95% confidence intervals (dotted lines). Note the ln scale for kpot and SRL.

aged model showed a strong effect on four chemical variables, lignin (83% of the variance), RNC (68%), RCC (47%) and lignin:N (37%) (Table 1). This model explained a lower percentage of the variability than the best fitting model (R2 = 0.81). In this model, lignin, RCC, lignin:N, and RDMC were negatively correlated with kpot (Fig. 1a,c,d,h), whereas RNC, REScom, SRL and water-soluble compound concentration were positively correlated with kpot (Fig. 1b,e,f,g). These relationships could be influenced by samples from the Mediterranean site (Restinclieres) that had a twofold greater kpot as compared to other sites (Figs 1, S1 and S2). Thus, to ensure the observed effects were not biased by the Restin-

clieres samples, we tested these models excluding this site from the analyses (Table S2). Results showed that the best fitting model included lignin and RNC (Table S2) as already found when all sites were considered. ROOT DECOMPOSABILITY BETWEEN LAND USE TYPES AND SOIL DEPTHS

Root decomposability (kpot) differed significantly between land use types globally (Fig. 2, Table S3). Overall, fine roots from forests (FO), that is with a greater abundance of woody species and less disturbance, decomposed at slower rates than


6 I. Prieto, A. Stokes & C. Roumet roots from the other land use types did (Fig. 2). This land use pattern was consistent within each of the sites except Premol and Aquiares (Fig. S2, Table S4). In Premol (Fig. S2d), the lack of differences between land use types was driven by the similar shallow root kpot (Tukey’s HSD, P = 0.20), whereas deep root kpot was slower at the forest site (Tukey’s HSD, P < 0.05). In Aquiares (Fig. S2c), root kpot was slightly higher at forest sites (Tukey’s HSD, P < 0.05) but no data on deep root kpot were available. Overall, kpot was significantly higher in shallow roots (1.37 0.06 g g1 year1) compared to deep roots (1.18 0.06 g g1 year1; Table S3). This overall difference was mainly due to higher kpot in shallow roots in monocultures (CA) and in forests (FO; Fig. 2). Within sites, differences between shallow and deep roots were apparent in three out of the six sites where differences could be tested (Llano Bonito, Premol and Restinclieres; Fig. S2). Locally, when differences between depths were observed, shallow roots always had higher kpot than deep roots. This result was the case in monocultures (CA), in agroforestry communities (TC) and in forest sites (FO) (except for Llano Bonito Fig. S2b). At Premol, shallow roots decomposed faster in both fallow (FA) and forest communities (FO).

Discussion Our study provides new insights on the role of chemical root functional parameters driving root decomposition at the community level. We demonstrated that, similar to results obtained at the species level (Zhang et al. 2008; Roumet et al. 2016), variations in root decomposability were strongly

Fig. 2. Decomposability rates (kpot; mean SEM) for fine roots collected at two soil depths (grey bars – shallow: 0–20 cm; black bars – deep: 100–150 or 60–80 cm) in seven sites and under different land use types (see Material and methods section and Table S1 for additional details on statistical results). Values of fine root kpot are shown for all sites together. Different letters indicate significant differences between land use types and asterisks indicate significant differences between depths within each land use type (Tukey’s post hoc test, P < 0.05). Land use types are: CA, monocultures (one species); TC, agroforestry systems (two species); FA, fallow, regeneration after cultivation (multiple species); TV, trees with natural vegetation (multiple species, mostly herbs); and FO, secondary forest and associated understorey (multiple species, mostly trees and woody plants).

controlled by root quality, especially by a combination of lignin concentration, lignin:N, C and N concentrations. Differences in these traits at the community level resulted in large variations in root decomposability between plant communities from contrasting land use types and between soil depths (Prieto et al. 2015). Our results from plant communities worldwide suggest that changes in plant communities due to agricultural intensification increase root decomposability, which could potentially decrease soil C inputs, particularly in shallow soil layers where most root biomass is produced (Schenk & Jackson 2002, 2005). CONSISTENT FUNCTIONAL PARAMETER CONTROL ON ROOT KPOT

Our first hypothesis was supported because fine root decomposability of contrasted plant communities can be predicted from a combination of root chemical functional parameters. Interestingly, among functional parameters, the best predictors of root decomposability were lignin, N and C concentrations and lignin:N, that is the same as for traits at the species level (Silver & Miya 2001; Zhang et al. 2008; Aulen, Shipley & Bradley 2012; Birouste et al. 2012; Freschet, Aerts & Cornelissen 2012; Solly et al. 2014; Roumet et al. 2016). Lignin is a recalcitrant compound (Berg & Laskowski 2005), constituting a low-energy source for microbes that is decomposed at much lower rates than other compounds such as cellulose or hemicellulose (Lemma et al. 2007; Lindedam et al. 2009), which likely slowed down decomposition rates (Berg & McClaugherty 2008). Consistent with Birouste et al. (2012), high RNC increased root decomposability. Nitrogen is often a limiting resource for microbial decomposer communities and, when available, is rapidly used increasing decomposition rates (Berg & McClaugherty 2008). We did not find support for a strong effect of the PCA axis representing the REScom on root decomposability. It appeared a much weaker predictor than the combination of lignin, N and C concentrations. One reason for this could be that REScom is more based on morphological (Diameter, SRL and RDMC) than on chemical parameters (mainly lignin, lignin:N and RCC; Fig. S1), that are poorer predictors of root decomposability. Moreover, RNC seems to be decoupled from root economics both at the species and at the community levels (Chen et al. 2013; Geng et al. 2014; Prieto et al. 2015; Valverde-Barrantes, Smemo & Blackwood 2015) and was also an important parameter controlling root decomposability in this study. FUNCTIONAL PARAMETER-MEDIATED LAND USE AND DEPTH EFFECTS ON ROOT KPOT

In support of our second hypothesis, root decomposability increased with changes in plant communities following agricultural intensification. The higher decomposability of roots was observed in intensive agricultural land uses (CA, TC), whereas root decomposability was lower in land uses comprising plant communities with less disturbance and a greater percentage of slower-growing woody species, for example


Root economics and litter decomposability 7 trees with natural vegetation or secondary forests (FA, FO). These results need however to be interpreted carefully since one trench per land use type was used in each of the sites, which may limit the conclusions drawn concerning land use type effects within each site individually. However, when taking all sites into account, we found that globally, these differences were likely explained by changes in root chemistry among land use types. Two of the main features that negatively affected root decomposability in this experiment, that is lignin and C concentrations, decreased globally when shifting from forests to agricultural land (Prieto et al. 2015). Similarly, fine root decomposition rates were also reported to decrease in situ along a successional gradient from early colonized grasslands to mature forests (Zhang et al. 2013), mainly associated with a decrease in the quality of fine roots. Therefore, we propose that a potential explanation for the observed changes in root decomposability among land use types is an indirect effect of changes in the composition of plant communities (Holdaway et al. 2011; Prieto et al. 2015). For example, in intensive agricultural land use types (CA and TC), the quality of roots is higher because the dominant species (i.e. wheat or rice) are mostly fast-growing species that have high N and low lignin concentrations (Lambers & Poorter 1992). Additionally, this effect is expected to increase through fertilization of the plots (Prieto et al. 2015). Previous studies have shown that fine root biomass was lower in agricultural fields compared to forest sites (Jackson, Mooney & Schulze 1997; Zhang et al. 2013). In combination with their faster decomposability, this result suggests that if root quality is a driver of decomposition (Zhang et al. 2008), then land use intensification may decrease the below-ground organic matter inputs in these soils. This implication remains to be tested in the field but is in line with previous studies that reported a decrease in soil organic carbon when forests were replaced with tree or crop plantations (Guo & Gifford 2002). Although our data suggest a land use effect on root decomposability mediated by changes in community root functional parameters, further studies using a larger number of replications (i.e. several trenches) per land use type would be needed to confirm the generality of this conclusion. In support of our third hypothesis, under standardized conditions, fine roots from shallow soil layers decomposed faster than roots from deep soil layers. Consistently, deep roots had greater lignin concentration, lower root N concentration (Prieto et al. 2015) and greater lignin:N (22.96 1.44 vs. 27.21 1.71 for shallow and deep roots, respectively), that is three of the main functional parameters that negatively impacted root decomposability (Fig. 1). Analogous to land use change effects, the faster decomposability in shallow roots may be the result of an indirect effect of changes in root abundance and composition at different soil depths. These depth effects were mainly found in roots from agricultural fields (CA), forests (FO) and more locally in roots from agroforestry sites (TC). In agricultural monocultures, changes in quality with soil depth can be attributed solely to changes in root traits of the single species, likely associated with changes in soil properties (i.e. soil nutrients or soil compaction) and/or root

function (Vanguelova et al. 2005; Makita et al. 2010; Prieto et al. 2015). However, in roots from agroforestry and forestry sites, changes in root functional parameters with soil depth could also be explained by differences in rooting depths between species (i.e. herbaceous and woody species), the latter often being more deeply rooted (Schenk & Jackson 2002). This result likely biased the abundance of roots towards greater proportions of high-quality roots from herbaceous species in shallow soil horizons (Prieto et al. 2015), leading to higher decomposability. Nonetheless, these changes may be further enhanced by differences in the root traits of individual species along the soil profile (Vanguelova et al. 2005; Makita et al. 2010). If we were to extrapolate our results, the combination of both the presence of high-quality roots in shallow soils and more suitable soil conditions (i.e. higher temperatures and microbial densities and activity, Gill & Burke 2002; Fierer, Schimel & Holden 2003) might lead to even greater decomposition rates in situ than those reported in our study, lowering below-ground soil C inputs in shallow soils even further. Nonetheless, our study should be complemented with field experiments to test whether the differences in root decomposability observed along the land use gradient are conserved in situ and whether they lead to differences in soil organic carbon concentrations. Other factors such as the specific soil microclimate and the structure of soil decomposer communities need to be taken into account since these are crucial regulators of soil carbon dynamics (Silver & Miya 2001; Clemmensen et al. 2013; Keiser, Knoepp & Bradford 2013).

Conclusions This study emphasizes the potential of fine root functional parameters, particularly lignin, C, N concentrations and lignin:N, as a tool in understanding root decomposability in plant communities. At a community level, the coupling between root quality (mainly root chemistry) and root decomposability may have important implications for plant community control over soil processes. However, more in-depth studies of these effects in situ are needed to fully understand the implications of these functional changes on ecosystem processes. In a context of the fast and large-scale agricultural intensification that is currently taking place (IPCC 2007), root functional parameters from plant communities may provide a tool to understand and predict the consequences of land use changes on ecosystem properties and services.

Acknowledgements We are grateful to the Agence Nationale de la Recherche in France for funding this work (Ecosfix ANR-10-STRA-003-001) and the Ecosfix Consortium for helping collect the root material at the different sites. Noelia Portillo, Alain Blanchard, David Degueldre and Jeremie Devaux (CEFE-CNRS) helped prepare the microcosms and the litterbags and conduct the controlled chamber decomposition experiment. Alain Pierret, Olivier Roupsard and Christian Dupraz provided the necessary technical and human infrastructure at the different field sites in Laos, Costa Rica and Restinclieres, respectively. We are also grateful to Jerome Perez (INRA) who helped develop a data base to store the project data, Gilles Le Moguedec (INRA) who helped with the statistical analysis and Pablo Garcıa-Palacios who read a final version of the manuscript and


8 I. Prieto, A. Stokes & C. Roumet provided useful comments. All morphological and chemical analyses were conducted at the Plateforme d’Analyses Chimiques en Ecologie (technical facilities of the Labex Centre Mediterraneen de l’Environnement et de la Biodiversite) and the decomposition experiment was carried out at the Terrain d’Experiences facilities, both at the Centre d’Ecologie Fonctionnelle et Evolutive (CEFECNRS), Montpellier, France.

Data accessibility Data available from the Dryad Digital Repository (Prieto, Stokes & Roumet 2016).

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Received 4 August 2015; accepted 4 January 2016 Handling Editor: Liesje Mommer

Supporting Information Additional Supporting Information may be found in the online version of this article: Figure S1. Principal component analysis (PCA) of fine root morphological and chemical functional parameters defining the root economics spectrum. Figure S2. Decomposability rates (kpot; mean SEM) for fine roots collected at two soil depths (grey bars – shallow: 0–20 cm; black bars – deep: 100–150 or 60–80 cm) in seven sites and under different land use types. Table S1. Description of the different land use types and species composition and abundance at the different sites. Table S2. Best fitting general linear mixed models (GLMMs) between fine root decomposability (kpot) and fine root functional parameters excluding samples from the Mediterranean site ordered by their AICc values and Akaike weights (Wi). Table S3. Summary statistics for land use type, climate and depth effects on root decomposability (kpot). Table S4. Summary statistics for land use type and depth effects at each individual site on root decomposability (kpot). Table S5. Loadings between root functional parameters and the first, second and third axes in the principal component analysis.
