# Species Traits as Practical Tools for Ecological Restoration of Marly Eroded Lands

Mélanie Burylo, Thierry Dutoit, Freddy Rey

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Mélanie Burylo, Thierry Dutoit, Freddy Rey. Species Traits as Practical Tools for Ecological Restoration of Marly Eroded Lands. Restoration Ecology, 2014, 22 (5), pp.633-640. 10.1111/rec.12113. hal-01329331

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# Species Traits as Practical Tools for Ecological Restoration of Marly Eroded Lands

Mélanie Burylo,<fnref n="1" /> Thierry Dutoit,<fnref n="3" /> and Freddy Rey<fnref n="1" />,<fnref n="2" />

## Abstract

Plant functional traits are increasingly used in restoration ecology because they have the potential to guide restoration practices at a broad scale. This article presents a trait-based multi-criteria framework to evaluate and predict the performance of 17 plant seedlings to improve ecological restoration of marly eroded areas in the French Southern Alps. The suitability of these species to limit soil erosion was assessed by studying both their response to erosive forces and their effect on erosion dynamics. We assumed that species efficiency could be explained and predicted from plant traits and we looked for trait-performance relationships. Our results showed that root slenderness ratio, the percentage of fine roots and root system topology, were the three root morphology traits best describing anchorage strength. Root system characterized by a long and thin tap root and many

fine lateral ramifications would be the best to resist concentrated runoff. Species response to burial mainly depended on growth form and morphological flexibility. The abilities of species in reinforcing the soil and reducing erosion rates were negatively correlated to root diameter and positively to the percentage of fine roots. Moreover, root system density and root tensile strength also influenced root reinforcement. Finally, the ability to trap sediment was positively correlated to leaf area and canopy density. Species were then scored and classified in four clusters according to their global performance. This method allows identifying species that possess both response and effect traits related to the goal of preventing erosion during ecological restoration.

**Key words:** burial, ecosystem services, plant traits, sediment trapping, soil erosion, soil fixation, uprooting.

## Introduction

At the present time, there is virtually no ecosystem on Earth free from alteration by human activities (Vitousek et al. 1997). Since a few decades, the degradation of ecosystems' functions and the loss of ecological services have accelerated constantly (Millemonium ecosystem assessment 2005), which made us rethink our relationship with nature and initiate ecological restoration of degraded lands (Hobbs & Harris 2001; Clewell & Aronson 2006). What we have learned from ecological theory and from the young science of restoration ecology provides a necessary conceptual background to design effective on-ground applications or to improve already existing restoration strategies (Young et al. 2005).

Specifically, plant traits represent a promising tool in the discipline of restoration of terrestrial plant communities and ecosystems. Identifying relationships between plant functional traits and environmental factors is a traditional objective in plant ecology (Lavorel et al. 2007). We are now moving a step

forward by using the functional approach to answer strongly applied questions and guide restoration practices (Gondard et al. 2003).

In extensive areas of the French Southern Alps, the conjunction of weathering of an erodible marly substrate, the Mediterranean and mountainous climate, with frost in winter and summer droughts interspersed with heavy rainfalls, and the pressure of human activities cause intense gully erosion (Descroix & Mathys 2003). As a result, the bedrock is covered with a loose weathering layer composed of disintegrated marl particles (Oostwoud Wijdenes & Ergenzinger 1998), which might be transported down the watersheds by concentrated runoff or shallow mass movements (Bouma & Imeson 2000). These processes are responsible for land gullying and the formation of badlands areas, important soil losses (up to 3.5 cm/yr<fnref n="1" /> [Lecompte et al. 1998] and 100 tons ha⁻<fnref n="1" /> yr⁻<fnref n="1" /> [Mathys et al. 2003]) and highly unstable soils. Erosion rates recorded in the French Southern Alps are among the highest worldwide (Pimentel et al. 1995). These processes have ecological impacts, such as the sedimentation of spawning habitat, as well as socioeconomic consequences, such as increased torrential flood hazard and the silting of hydroelectric dams (Verstraeten et al. 2006).

Restoration of eroded lands has a long history in the French Southern Alps. Since 1860, massive afforestation projects were carried out on nearly 300,000 ha (Vallauri et al. 2002) to recreate a vegetation cover on bare areas and reduce erosion

<footnote n="1">¹Irstea Grenoble, UR EMGR, 2 rue de la papeterie, BP 76, 38402 Saint-Martin-d'Hères cedex, France</footnote>

<footnote n="2">²Address correspondence to F. Rey, email freddy.rey@irstea.fr</footnote>

<footnote n="3">³IMBE, UMR-CNRS, IRD, IUT d'Avignon, site Agroparc BP 61207, 84911 Avignon cedex 09, France</footnote>
<figure><img src="image_2.png" /><figcaption>Figure 1. Trait-based methodological framework for ecological restoration of marly eroded ecosystems. Species response to erosion (1) and species effect on erosion (2) are studied using a functional approach in order to identify plant traits that enable the prediction of species performance in eroded ecosystems. The results are used to improve existing restoration strategies and design new ones (3) (* see Lavorel and Garnier, 2002 for response and effect traits definition).</figcaption></figure>

rates (Stokes et al. 2008). Nevertheless, vegetation coloniza-
tion was not successful everywhere and natural regeneration
and understory establishment are sometimes slow and ineffec-
tive (Vallauri 1997). Therefore, erosion remains strong in many
areas. At the present time, budgetary restrictions enjoin to find
out and develop minimal restoration actions, that is, which guar-
antee low soil loss rates with the fewest interventions (Rey
2009).

Within this context, there is a growing need, both from
practitioners and scientists, to predict species performance for
erosion control in order to target the most suitable species for
eroded land restoration, evaluate land vulnerability to erosion
or assess the outcomes of ecological restoration. In degraded
ecosystems subjected to intense erosion, the ecological per-
formance of a plant species depends first on its response to
erosive perturbation, that is, resistance to mechanical forces,
determined by response traits, and then on its effect on erosive
dynamics, that is, soil protection, determined by effect traits
(Fig. 1). Several studies have investigated the interactions
between one single species and erosive forces to assess its
suitability for erosion control (Shi et al. 2004; Mickovski et al.
2005). Many other studies have compared several species'
efficiency in order to identify important plant traits with regards
to one erosion process (Bochet et al. 2000; De Baets et al. 2007;
Isselin-Nondedeu & Bédécarrats 2007). However, very few
attempts were made to study the performance of several species
for erosion control considering different plant functions and
both species response and effect (but see De Baets et al. 2009).

In this article, we present the trait-based approach we applied
to evaluate species performance for erosion control in marly
badlands of the French Southern Alps and to identify relevant
predictive plant traits (Fig. 1). Investigations focused on plant
seedlings, that is, juvenile individuals in the first 5 years of
development or with a basal diameter less than 2 cm, which
are more vulnerable to environmental perturbations but which
might already have a critical influence on erosion. On the basis
of field observations and the knowledge of erosion processes,
that is, concentrated runoff in gully beds and shallow mass

movements on gully slopes, five criteria, related both to species
response to erosion and species effect on erosion, were selected
to assess all important components of species efficiency for
erosion mitigation. This information is then aggregated at the
species scale to bring out a full evaluation of species perfor-
mance. What we intend here is to point out the implications of
such a multi-criteria trait-based approach for ecological restora-
tion of marly eroded lands, and discuss how the results are
efficient and can be really integrated into practical restoration
processes.

Methods

To identify plant traits which might have a predictive role for efficient ecological restoration, five experiments were carried out from 2006 to 2010. The results of each of these experiments have individually already been published (Burylo et al. 2009, 2011, 2012a, 2012b, 2012c), which give insight into the relationship between species performance for erosion control and plant traits for several ecological functions related to soil protection.

Five ecological functions, selected on the basis of erosion
processes observed in the field, were investigated to evalu-
ate species performance and suitability for erosion control
(Table 1). To have an impact on erosion processes, species must
first withstand concentrated flow and mass movements, the two
main processes in marly eroded lands (Bouma & Imeson 2000).
Therefore, the first two functions related to species response
to environmental forces. The three remaining criteria related to
species effect on erosive dynamics. Soil protection by vegetation
can be either active, by stabilizing the soil and thus reducing ero-
sion rates, or passive, by trapping sediment and thus enhancing
sedimentation (Rey et al. 2004):

1 Species response to erosion:

- resistance to uprooting by concentrated runoff

- resistance to burial under sediment

2 Species effect on erosion:

- soil fixation against concentrated flow erosion

- soil fixation against shallow mass movements

- sediment trapping by aerial parts of plants.

For each ecological function, the relationship between plant
traits and species performance was analyzed according to the
following steps:

1 Species selection

2 Evaluation of species performance to withstand erosive forces and reduce erosion

3 Traits measurement

4 Data analyses to relate plant traits and species performance.

The four following parts give summarized information on the
methods used but more detail information is available in the
corresponding papers. From the results of these experiments, a
global and synthetic analysis of species performance, topic of
this article was then carried out.
<table><caption>**Table 1.** Summary and main characteristics of the five experiments carried out to evaluate species performance for erosion control following a trait-based and multi-criteria approach.</caption><thead><tr><th>Function</th><th>Performance Index</th><th>Number of Species</th><th>Id Numbers</th><th>Type of Study</th><th>Growth Form</th><th>Source References</th></tr></thead><tbody><tr><td>Resistance to uprooting</td><td>σ (in MPa)</td><td>12</td><td>3–6, 8–13,<br>15–16</td><td>In situ</td><td>H, S, T</td><td>Burylo et al. (2009)</td></tr><tr><td>Resistance to burial</td><td>Survival<br>Height<br>Biomass</td><td>9</td><td>4, 7–10,<br>14–17</td><td>Ex situ<br>Common<br>garden</td><td>S, T</td><td>Burylo et al. (2012b);<br>Burylo (2010)</td></tr><tr><td>Soil fixation<br>Concentrated flow</td><td>RSD (%)</td><td>3</td><td>1, 15, 17</td><td>Ex situ<br>Laboratory</td><td>H, T</td><td>Burylo et al. (2012c)</td></tr><tr><td>Shallow mass movements</td><td>ΔS (in kPa)</td><td>6</td><td>1–2, 6, 13,<br>15–16</td><td>In situ</td><td>H, S, T</td><td>Burylo et al. (2011)</td></tr><tr><td>Sediment trapping</td><td>RTS (in<br>g.cm<sup>-3</sup>)</td><td>4</td><td>4, 8–9, 15</td><td>Ex situ<br>Laboratory</td><td>S, T</td><td>Burylo et al. (2012a)</td></tr></tbody></table>

σ, critical uprooting stress resisted by species; RSD, relative soil detachment during concentrated flow; ΔS, additional soil cohesion provided by roots and reducing shallow mass movements; RTS, relative trapped sediment during concentrated flow; Id number refers to species in Supplementary material; growth forms are H, herbaceous; S, shrubs; T, trees.

## Species Selection

One hundred and fifty years after the first ecological restoration projects on marly badlands in the French Southern Alps, Austrian black pine stands established successfully on originally bare soils. However, under the forest canopy, plant communities are mainly made of early successional assemblages composed of pioneer or post-pioneer, xerophilous or mesoxerophilous species (Vallauri 1997; Vallauri et al. 2002). On the basis of previous floristic surveys (Vallauri 1997; Burylo et al. 2007; unpublished reports), a set of 17 species fairly representative of the local flora was selected among dominant species (Supporting Information, Table S1). This set consisted of herbaceous as well as woody species, but was mainly composed of the most common shrubs of the eroded areas. For each experiment, species were picked from this preselected set of 17 species.

## Evaluation of Species Performance

To assess species resistance to uprooting, *in situ* uprooting tests were performed on plant seedlings. Traction force was applied on individual plants until uprooting. The critical stress σ (MPa) was calculated as the maximum force reached before uprooting divided by plant stem basal cross-sectional area, and used to compare anchorage strength among species (Burylo et al. 2009).

Tolerance to burial was determined from survival, height and biomass production of seedlings grown in common garden and buried under various sediment heights (Burylo et al. 2012b).

As gully erosion is characterized both by concentrated runoff and shallow mass movements, two indices were used to assess species potential for soil stabilization. To compare species effect on concentrated flow erosion by studying their seedlings, relative soil detachment (RSD, %) was calculated using flume experiments as the ratio of the mass of sediment detached from root-permeated soil samples to the average mass of sediment detached from bare soil samples (Burylo et al. 2012c). Additional soil cohesion due to roots ΔS (in kPa) was calculated to

compare species efficiency to prevent shallow mass movements (Burylo et al. 2011). ΔS was obtained from data on root tensile strength and root area ratio collected in the field and was calculated from 10 to 60 cm depth.

Flume experiments were performed to evaluate plant seedling abilities for sediment trapping. Relative trapped sediment (RTS in g.cm⁻³) was calculated as the mass of sediment trapped by individual plants per unit volume of canopy (Burylo et al. 2012a).

## Trait Measurements

On the basis of a literature survey, relevant plant traits with regard to the different plant functions were selected and mean trait values were measured for each species in each experiment on a representative sample of individuals (5–10 individuals). For resistance to uprooting and soil fixation functions, root morphological traits were mostly chosen, whereas above-ground morphological traits were measured for sediment trapping experiment. Tolerance to burial was characterized by traits describing rather plant physiology.

## Data Analyses

Data analyses consisted of three successive steps. First, to compare species performances, analyses of variance or Kruskal-Wallis nonparametric test, when the assumption of normality was not respected (Shapiro-Wilk's test), were used with performance indices as the independent variable and species as the dependent variable. However, for resistance to burial, species performance was evaluated by comparing buried plants to unburied ones (control) using Student's t test for biomass, and by monitoring plants' height through time with repeated measures analyses of variance.

Following species ranking according to their efficiency for erosion control, a second type of analyses was performed to compare species morphology. After parametric assumptions
were checked, analyses of variance were used with plant traits as the independent variables, while species identity was defined as the dependent variable.

Third, plant traits were related to species performance in a last step. Several types of analyses, such as correlation analyses, discriminant analyses, and principal components analyses, were used in the different experiments according to the dataset.

All Analyses were carried out with Statistica (version 8.0 for Windows, Statsoft, 1984).

## Global Analysis of Species Potential for Erosion Control

On the basis of the results of the five above-mentioned experiments, scores were attributed to each of the 17 species studied in each of the five functions, that is, resistance to uprooting, resistance to burial, soil reinforcement against concentrated flow erosion, soil reinforcement against shallow mass movements, and sediment retention. Scores were used to evaluate species ecological performance and ranged from 1 to 4 with increasing values associated to increasing performances (i.e. 1 = low, 2 = medium, 3 = high and 4 = very high performance). Two scoring methods were used. For species for which we had quantitative performance values (Table 2), data were simply rescaled from 1 to 4 to attribute scores. For other species, the scoring was based on plant traits identified as relevant to predict performance. Various sources were used to determine trait values, or range of values, but mainly qualitative observations, scientific and technical reports and botanical handbooks (Rameau et al. 1993; Lauber & Wagner 1998). A cluster analysis was then performed to group species with similar performances into

different clusters (Statistica version 8.0 for Windows, Statsoft, 1984). Euclidian distances and Ward's methods were used to measure similarity between species and to link clusters together, respectively.

## Results

### Identifying Relevant Predictive Plant Traits

Results of the experiments showed that seedlings efficiency for erosion control varied substantially among species (Table 2).

Values of mean critical stress $\sigma$, evaluating species resistance to uprooting, ranged from 2.77 for *Lavandula angustifolia* to 9.08 MPa for *Ononis natrix*. Analyses highlighted the influence of three traits describing root morphology on anchorage strength: root slenderness ratio, defined as tap root length $LR_1$ divided by root diameter D, the percentage of fine roots, that is, with diameter less than 0.5 mm, and root system topology, describing root system branching pattern. Root system characterized by a long and thin tap root and many fine lateral ramifications would be the best to resist concentrated runoff.

Burial experiment showed that species response could be positive, neutral, or negative, and that it mainly depended on growth form and morphological flexibility, that is, species ability to reallocate biomass after environmental disturbance.

RSD values revealed that plant species, at the early stages of their development, strongly reinforce the soil and reduce erosion rates by 95% for the most efficient ones. Differences among species were negatively correlated to root diameter and

<table><caption>**Table 2.** Species performance values selected to evaluate species response and effect to/on erosive processes and significant predictive traits.</caption><thead><tr><th rowspan="2">Species name</th><th rowspan="2">Growth form</th><th colspan="2">Response to Erosion</th><th colspan="3">Effect on Erosion</th></tr><tr><th>Uprooting<br>σ (MPa)</th><th>Burial<br>Global response</th><th>Fixation 1<br>RSD (%)</th><th>Fixation 2<br>ΔS (kPa)</th><th>Trapping<br>RTS (g/cm³)</th></tr></thead><tbody><tr><td>Achnatherum calamagrostis</td><td>H</td><td>—</td><td>—</td><td>7.74</td><td>2.69</td><td>—</td></tr><tr><td>Aphyllantes monspeliensis</td><td>H</td><td>—</td><td>—</td><td>—</td><td>7.40</td><td>—</td></tr><tr><td>Anthyllis vulneraria</td><td>H</td><td>7.93</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>Buxus sempervirens</td><td>S</td><td>8.38</td><td>→</td><td>—</td><td>—</td><td>1.59</td></tr><tr><td>Dorycnium pentaphyllum</td><td>S</td><td>4.82</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>Genista cinerea</td><td>S</td><td>8.68</td><td>—</td><td>—</td><td>7.81</td><td>0.56</td></tr><tr><td>Hippophae rhamnoides</td><td>S</td><td>—</td><td>→</td><td>—</td><td>—</td><td>—</td></tr><tr><td>Juniperus communis</td><td>S</td><td>6.13</td><td>→</td><td>—</td><td>—</td><td>—</td></tr><tr><td>Lavandula angustifolia</td><td>S</td><td>2.77</td><td>→</td><td>—</td><td>—</td><td>2.06</td></tr><tr><td>Ononis fruticosa</td><td>S</td><td>8.54</td><td>→</td><td>—</td><td>—</td><td>—</td></tr><tr><td>Ononis natrix</td><td>S</td><td>9.08</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>Staehelina dubia</td><td>S</td><td>3.52</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>Thymus serpyllum</td><td>S</td><td>4.96</td><td>—</td><td>—</td><td>2.16</td><td>—</td></tr><tr><td>Acer campestre</td><td>T</td><td>—</td><td>→</td><td>—</td><td>—</td><td>—</td></tr><tr><td>Pinus nigra</td><td>T</td><td>3.58</td><td>→</td><td>14.67</td><td>0.52</td><td>1.06</td></tr><tr><td>Quercus pubescens</td><td>T</td><td>7.38</td><td>→</td><td>—</td><td>1.11</td><td>—</td></tr><tr><td>Robinia pseudo acacia</td><td>T</td><td>—</td><td>→</td><td>4.57</td><td>—</td><td>—</td></tr><tr><td>Traits identified</td><td></td><td>LR<sub>1</sub>/D<br>%FR<br>Topology</td><td>Growth form<br>Morphological flexibility</td><td>D<br>%FR</td><td>Growth form<br>RAR<br>RTS</td><td>LA<br>Canopy density</td></tr></tbody></table>

$LR_1$, tap root length; D, root diameter; %FR, fine root percentage; RAR, root area ratio; RTS, root tensile strength; LA, mean leaf area.

For response to burial, arrows indicate a positive, neutral or negative global response of species evaluated from survival, height and biomass. Fixation 1 is for species effect during concentrated runoff erosion and Fixation 2 is for species effect during shallow mass movements. ΔS values are given at 10 cm depth.
<table><caption>**Table 3.** Scores evaluating ecological performance of species for erosion control.</caption><thead><tr><th rowspan="2">Species name</th><th colspan="2">Response to Erosion</th><th colspan="3">Effect on Erosion</th><th rowspan="2">Mean Score</th></tr><tr><th>Uprooting</th><th>Burial</th><th>Fixation 1</th><th>Fixation 2</th><th>Trapping</th></tr></thead><tbody><tr><td>Achnatherum calamagrostis</td><td>4</td><td>4</td><td><strong>3</strong></td><td><strong>3</strong></td><td>4</td><td>3.6</td></tr><tr><td>Aphyllantes monspeliensis</td><td>4</td><td>3</td><td>3</td><td><strong>4</strong></td><td>4</td><td>3.6</td></tr><tr><td>Anthyllis vulneraria</td><td><strong>3</strong></td><td>2</td><td>2</td><td>2</td><td>1</td><td>2</td></tr><tr><td>Buxus sempervirens</td><td><strong>4</strong></td><td><strong>3</strong></td><td>4</td><td>4</td><td><strong>3</strong></td><td>3.6</td></tr><tr><td>Dorycnium pentaphyllum</td><td><strong>2</strong></td><td>3</td><td>3</td><td>3</td><td>3</td><td>2.8</td></tr><tr><td>Genista cinerea</td><td><strong>4</strong></td><td>3</td><td>3</td><td><strong>4</strong></td><td><strong>3</strong></td><td>3.4</td></tr><tr><td>Hippophae rhamnoides</td><td>4</td><td><strong>3</strong></td><td>4</td><td>4</td><td>3</td><td>3.6</td></tr><tr><td>Juniperus communis</td><td><strong>3</strong></td><td><strong>3</strong></td><td>4</td><td>4</td><td>1</td><td>3</td></tr><tr><td>Lavandula angustifolia</td><td><strong>1</strong></td><td><strong>3</strong></td><td>4</td><td>4</td><td><strong>4</strong></td><td>3.2</td></tr><tr><td>Ononis fruticosa</td><td><strong>4</strong></td><td><strong>3</strong></td><td>4</td><td>3</td><td>4</td><td>3.6</td></tr><tr><td>Ononis natrix</td><td><strong>4</strong></td><td>3</td><td>4</td><td>3</td><td>3</td><td>3.4</td></tr><tr><td>Staehelina dubia</td><td><strong>1</strong></td><td>3</td><td>3</td><td>3</td><td>4</td><td>2.8</td></tr><tr><td>Thymus serpyllum</td><td><strong>2</strong></td><td>3</td><td>3</td><td><strong>3</strong></td><td>3</td><td>2.8</td></tr><tr><td>Acer campestre</td><td>3</td><td><strong>4</strong></td><td>3</td><td>2</td><td>2</td><td>2.8</td></tr><tr><td>Pinus nigra</td><td><strong>1</strong></td><td><strong>3</strong></td><td><strong>2</strong></td><td><strong>1</strong></td><td><strong>2</strong></td><td>1.8</td></tr><tr><td>Quercus pubescens</td><td><strong>3</strong></td><td><strong>4</strong></td><td>1</td><td><strong>1</strong></td><td>2</td><td>2.2</td></tr><tr><td>Robinia pseudo acacia</td><td>3</td><td><strong>4</strong></td><td><strong>4</strong></td><td>2</td><td>2</td><td>3</td></tr></tbody></table>

Scores range from 1 to 4 (1 = low, 2 = medium, 3 = high, and 4 = very high performance). Scores in bold have been determined from the six studies published by Burylo (2010) and Burylo et al. (2009, 2011, 2012a, 2012b, 2012c). Other scores have been determined from the literature (Rameau et al. 1993; Lauber & Wagner 1998).

positively to the percentage of fine roots. ΔS values showed that shrubs and grasses were better than trees to prevent shallow mass movements. Moreover, root system density and root tensile strength also influence root reinforcement.

Finally, the ability to trap sediment during concentrated flow erosion was positively correlated to leaf area and canopy density.

## Species Potential for Erosion Control

Species scoring revealed important differences among the 17 species selected in this study (Table 3). Mean scores ranged from 1.8 for *Pinus nigra* to 3.6 for several shrubs and grasses such as *Achnatherum calamagrostis*, *Buxus sempervirens*, *Hippophae rhamnoïdes*, and *Ononis fruticosa*.

From the hierarchical tree resulting from species clustering, four clusters were selected, allowing grouping species according to their efficiency to withstand and then to reduce erosion (Table 4). Cluster 1 has the higher mean score and is composed of shrubs and grasses having high potential both to withstand erosive forces and to prevent soil erosion and soil losses. Clusters 2 and 3 have a similar mean score of 2.9 but group species having different ecological performances. On the one hand, species belonging to cluster 2, *Juniperus communis*, *Acer campestre* and *Robinia pseudo acacia*, are efficient to resist uprooting and burial and to stabilize the soil but have low potential for sediment trapping. On the other hand, species from cluster 3, *Dorycnium pentaphyllum*, *Lavandula angustifolia*, *Staehelina dubia* and *Thymus serpyllum*, present low anchorage strength but high potential to tolerate burial under marly sediment, to stabilize the soil and to trap sediment. Cluster 4 groups the least efficient species, having medium potential to withstand erosion and low impact on erosion rates and soil losses.

## Discussion

The study presented here demonstrated how a trait-based approach enables fast prediction of species performance for erosion control in marly badlands. In addition, our study considered both response and effect traits related to erosion dynamics which is rather rare in the scientific literature.

Among the four clusters which were clearly identified in this study, cluster 1 is composed of native shrubs and grasses supposed to be the most suitable to prevent erosion. Given that these species are dominant in marly gullies (Vallauri 1997; Rey et al. 2005; Burylo et al. 2007), and that some of them (*Ononis fruticosa*, *Hippophae rhamnoïdes*, and *Achnatherum calamagrostis*) were used during restoration operations based on secular knowledge (Vallauri et al. 2002), this result is thus consistent. Tree species are absent from cluster 1, confirming the major influence of low vegetation, which offers a good ground cover, on erosion processes (Rey 2003, 2004). Clusters 2 and 3 are composed of species having a relatively high potential for erosion control. However, species from cluster 2 have better anchorage but lower sediment retention ability. This difference highlights the importance of growth forms in predicting species performance, as cluster 2 counts two trees among the three species, whereas cluster 3 only counts low shrubs. Cluster 4 groups the least efficient species. Surprisingly, *Pinus nigra*, the most widespread species in the study area, was identified as the least suitable species for erosion control.

Concrete applications of our results regarding different levels of ecosystem management and restoration have to be addressed. They can be adapted for finding solutions to different issues such as (1) soil loss, when it threatens agricultural activities (Jin et al. 2008); (2) biodiversity loss, which can disturb vegetation and animal habitats (Mkanda 2002); (3) silting of reservoirs, caused
<table><caption>**Table 4.** Species clustering according to their potential for erosion control.</caption><thead><tr><th></th><th>Uprooting</th><th>Burial</th><th>Fixation 1</th><th>Fixation 2</th><th>Trapping</th><th>Mean score</th></tr></thead><tbody><tr><td>Cluster 1</td><td>4</td><td>3.1</td><td>3.6</td><td>3.6</td><td>3.4</td><td><strong>3.5</strong></td></tr><tr><td></td><td colspan="6">High performances to withstand erosive forces and to mitigate erosion both by stabilizing the soil and trapping sediment<br><i>Achnatherum calamagrostis, Aphyllantes monspeliensis, Buxus sempervirens, Genista cinerea, Hippophae rhamnoïdes, Ononis fruticosa, Ononis natrix</i></td></tr><tr><td>Cluster 2</td><td>3</td><td>3.7</td><td>3.7</td><td>2.7</td><td>1.7</td><td><strong>2.9</strong></td></tr><tr><td></td><td colspan="6">High potential to resist uprooting and burial as well as to stabilize the soil, low efficiency for sediment retention<br><i>Juniperus communis, Acer campestre, Robinia pseudo acacia</i></td></tr><tr><td>Cluster 3</td><td>1.5</td><td>3</td><td>3.25</td><td>3.25</td><td>3.5</td><td><strong>2.9</strong></td></tr><tr><td></td><td colspan="6">Low resistance to uprooting, high performance to tolerate burial, stabilize the soil and trap sediment<br><i>Dorycnium pentaphyllum, Lavandula angustifolia, Staehelina dubia, Thymus serpyllum</i></td></tr><tr><td>Cluster 4</td><td>2.3</td><td>3</td><td>1.7</td><td>1.3</td><td>1.7</td><td><strong>2</strong></td></tr><tr><td></td><td colspan="6">Medium potential to withstand erosion, low efficiency to reinforce the soil and trap sediment<br><i>Anthyllis vulneraria, Pinus nigra, Quercus pubescens</i></td></tr></tbody></table>

by sediment accumulated after erosion and transport, compromising the functioning of these structures (Verstraeten et al. 2006); and (4) flooding, also caused by sediment deposition in river beds (Steiger et al. 2001). Therefore, the choice of the right species and bioengineering works to use will vary depending on the types of problem requiring action. For example, if soil or biodiversity conservation is the final objective, erosion control is required, that is, preventing soil particles from being destructured and removed. However, if reducing the sediment yield in rivers is the final objective, sediment control is then required, that is, it may be possible to let erosion occur upstream and only retain the sediment before it reaches the river bed.

Restoration ecology aims to provide practitioners with “clear concepts, models, methodologies and tools” in order to support and improve the restoration of degraded ecosystems (SER 2004). Given the complexity and diversity of ecological restoration practice, which is a multi-scale process involving various disciplines, there are many ways for scientists to give their contribution. In marly badlands in the French Southern Alps, restoration can be seen through spatial scales, from the plot of a few square metres to the gully of about 1 ha, and to the watershed of several square kilometres, each of these management scales going with comparable ecological scales, that is, the plant, the community/ecosystem and the landscape.

This study, carried out at the species scale, can have immediate implications at the most local scale of the plot. Plant traits can be used to target the most suitable species for erosion control by combination with erosion intensity, local topography and climate. For example, on gully sides, where high slopes increase uprooting hazards and where soil stabilization to reduce erosion rates is a major objective, species from clusters 1 and 3 would be the best options. In gully beds, goals are rather to trap sediment and to reduce soil losses. Depending on whether gully beds have been restored to reduce concentrated flow and make the slope gentler, species from cluster 1 or from both clusters 1 and 2 should be selected, respectively. In addition, the present results could also be extrapolated in other eroded areas, such as in China (Stokes et al. 2010), insofar as species have similar traits. However, if this trait approach might be applicable to other sites,

such method is susceptible to work only on lands with similar lithological characteristics, such as fine alluvial materials. Application on acidic sites is possible, as far as adapted species are identified. Climatic conditions must also be close to those of mountainous and Mediterranean terrains, and not too dry such as in semi-arid lands, or with too heavy rainfall events.

In eroded marly watersheds, gullies are considered the functional units from the erosion dynamics and restoration actions viewpoints. The combination of geological and topological data, social and ecological issues, and purely economic cost-effectiveness approaches, lead to the identification of priority areas for ecological restoration (Rey 2009). Within these areas, questions are then: Which gullies should we restore? How can we evaluate restoration effectiveness in gullies? Gully selection is based on a classification considering gully beds' longitudinal profile and the percentage of low vegetation cover in gully beds. This classification and the diagnosis of gully vulnerability to erosion could be improved by adding a third axis of vegetation composition integrating plant traits.

Whatever the restoration project, evaluation is always a major step that often requires using the modelling tool. In the present case, a model simulating vegetation evolution after ecological restoration using bioengineering works was designed to give the probability to have a vegetation cover able to halt erosion several years after restoration (Delcros et al. 2009). This model simulates vegetation growth taking into account surrounding vegetation as a seed source, and plant-plant interactions and plant resistance to intense rainfall events, as factors influencing vegetation survival and development. To model resistance to intense rainfalls, species were classified along a resistance gradient according to their morphological traits on the basis of the results of resistance to uprooting (Burylo et al. 2009).

Despite the use of plant functional traits at the gully scale to make the diagnosis of vulnerability towards erosion and to evaluate restoration projects, a functional evaluation of plant communities or ecosystems, similar to the one proposed here at the plant scale, is still missing. The question of how vegetation interacts with, and influences erosion processes can also be asked at the community scale. Recent advances in theoretical
ecology suggest that ecosystem properties and processes depend strongly on the functional traits of the dominant species (i.e. mass ratio hypothesis, Grime 1998; Mokany et al. 2008). Therefore, scaling up from individuals to communities and ecosystems can be carried out using functional traits as a tool to link across different levels of organization and better explain biorhexistasy thresholds, that is, the balance between vegetation and erosion dynamics (Erktan et al. 2013). While plant traits can easily be used at the scales of the plant and communities, at the broader landscape scale, where restoration strategies are designed, considerations about hydrological and ecological connectivity or geomorphology predominate.

In this study, we demonstrated how a trait-based approach can explain interactions between vegetation and erosion processes. Yet, despite their potential interest, plant traits remain underutilized in the restoration of degraded ecosystems, and to date, few studies have integrated such a functional component into the restoration process. Hobbs and Norton (1996) urged the need to develop general and transferable methodologies from one situation to another for large-scale restoration projects. To a larger extent, such trait-based approach could also be very well adapted in different areas and with different plant species (Clark et al. 2012). Nevertheless, the effectiveness of the clusters identified on ecosystem functioning and erosion prevention will be now definitively validated only by the realization of real restoration actions at a broad scale in the field.

## Implications for Practice

* A trait-based approach enables fast prediction of species performance for erosion control in marly badlands of the French Southern Alps, by considering both response and effect traits related to erosion dynamics.

* Plant functional traits appear as a promising tool to target suitable species for ecological restoration, thus guiding practitioners for deciding where, when, and how to plan effective erosion control in the French Southern alps.

* These results also allow diagnosing ecosystems vulnerability to degradation, whether it is erosion, invasion, or another factor, or to evaluate restoration projects.

* The methodology evolved in this paper could be very well applied outside the French Southern Alps, in similar lithological, topographic, and climatic conditions.

## Acknowledgments

We thank S. Labonne, D. Lemoine, S. Le Stradic, F. Cottard, and S. Meistermann for help in collecting data, in the laboratory and in the field. We also thank E. Buisson, S. Gaucherand, and C. Roumet for methodological advices and discussions, F. Grassein for support as well as statistical advices and help during experimental design, two anonymous reviewers for their comments and R. Jaunatre for final lecture. Finally, we greatly thank Electricité de France (EDF), Agence de l'eau Rhône, Méditerranée et Corse, Région Provence-Alpes-Côte-d'Azur, and European Union (FEDER program "L'Europe s'engage en

PACA avec le Fonds Européen de Développement Régional") for financial support.

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## Supporting Information

Additional Supporting Information may be found in the online version of this article:

**Table S1.** Name, growth form (H, herbaceous; S, shrubs; T, trees), and successional stage of the 17 species selected.