Prieto et al. Electronic Supplementary Material
Title: Root community traits along a land use gradient: evidence of a community-level economics spectrum
Iván Prieto1,2, Catherine Roumet1, Remi Cardinael2, Christian Dupraz2, Christophe Jourdan3, John Kim4, Jean Luc Maeght3,5, Zhun Mao6, Alain Pierret5,7,
Noelia Portillo1, Olivier Roupsard3, Chantanousone Thammahacksa5, Alexia Stokes3
Prieto et al. Electronic Supplementary Material
Table S1. Description of land use types at the different sites where roots were collected. Land use abbreviations are as follows: CA, monocultures (one
species); TC, agroforestry systems (2 species); FA, fallow, regeneration after cultivation; TV, trees with natural vegetation (multiple species, mostly herbs);
FO, secondary forest and associated understory (multiple species, mostly trees and woody plants). The abundance of herbs and trees is given as a percentage
foliar cover. Age to last disturbance (Dist) is the time (in years) to the last disturbance (ploughing or tree thinning), Soil N, soil nitrogen concentration; Soil P,
soil available phosphorus concentration; SOC, soil organic carbon concentration.
Country
Site
Land
use
type
Dominant species
Herbs
Trees
Dist
(% cover) (% cover) (years)
Soil N
(mg g-1)
Soil P
SOC
(mg kg-1) (mg g-1)
Costa Rica
Aquiares
(AQ)
CA
Coffea arabica L.
33
56
40
8.5
33
66.01
TC
C. arabica L.
25
Erythrina poeppigiana
Walp.
63
40
6.1
67
47.1
FO
Lozania sp.
Synechanthus
warscewiczianus
H. Wendi
Pentagonia sp.
26
66
100
6.4
11
59.75
CA
C. arabica L.
25
50
40
4.8
36
46.36
TC
C.arabica L.
E. poeppigiana Walp.
33
50
40
3.5
25
35.59
FO
Quercus sp. L.
Clusia sp. L.
Drimys
granadensis L.F.
12
80
100
2.6
8
46.06
Llano Bonito
(LB)
Laos
Houay Pano
(HP)
Prieto et al. Electronic Supplementary Material
France
France
CA
Oryza sativa L.
100
0
1
2.4
3
22.5
TC
O. sativa L.
Tectona grandis L.
80
20
1
2.7
3
17
FA
Chromolaena odorata 20
L.
Cratoxylum formosum
Benth. & Hook.
Callerya atropurpurea
Wall.
Saccharum
spontaneum L.
0
2
2.2
3
24.6
TV
T. grandis L.
20
80
15
2.1
4
18
CA
Triticum turgidum L.
subsp. durum
100
0
1
1
10
9.29
TC
T. turgidum L. subsp.
durum
Juglans regia L.
50
50
1
1.2
10
9.5
TV
J. regia L.
Vicia lutea L.
Medicago sp.
49
50
5
1
14
10.99
FO
Pinus sylvestris L.
Quercus ilex L.
18
70
20
1.8
7
20.53
Premol
(PR)
FA
Gallium rotundifolium 89
L., Lysimachia
nemorum L., Luzula
nivea L. DC
0
5
4.9
19
77
Bachat- Boulod
FO
Abies alba Mill.,
90
40
5.1
17
69.2
Restinclières
(RE)
10
Prieto et al. Electronic Supplementary Material
(BB)
Achard
(AC)
Picea abies L. Karst.,
Fagus Sylvatica L.
FA
Luzula nivea L. DC
55
Rhododendron
ferrugineum L.,
Vaccinium myrtillus L.
0
5
4.3
12
53.1
FO
Picea abies L. Karst,
Abies alba Mill
90
40
9.5
57
225.8
FA
Rhododendron
50
ferrugineum L.,
Vaccinium myrtillus L.
0
5
10.6
20
136.9
FO
Pinus uncinata Mill.,
Picea abies L. Karst
90
40
7.2
33
121.2
0
10
Prieto et al. Electronic Supplementary Material
Table S2. Loadings of the different variables characterizing land use types. Results are from a
principal component analysis (PCA); variables used in the PCA were species composition (%
herbaceous species), age of last disturbance (Dist), total soil nitrogen (Soil N), available soil
Phosphorus (Soil P; Olsen method) and soil organic carbon (SOC) concentrations and level of
fertilization (Fert); see table S1 for complete data on these variables. Squared loadings in bold
(>0.40) indicate the significance of the variables in the PCA (Richman et al 1998).
Variables
Axis 1 (48 %)
Axis 2 (21.5 %)
% Herbs
0.67
-0.06
Dist
-0.56
0.07
Soil N
-0.87
0.03
Soil P
-0.75
-0.56
SOC
-0.87
0.19
Fert
0.16
-0.96
Prieto et al. Electronic Supplementary Material
Table S3. Sums of squares (SS), degrees of freedom (df), F-values and adjusted R2 (Adj-R2) for the nested general linear models (GLMs) for fine root
functional parameters (FP, n=106 for morphological and n=154 for chemical FP). A symmetrical compound 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 was included to
account for non-independency of the samples from each trench and depth. Functional parameter abbreviations are as in Fig. 1
RDMC (mg g-1)
Dm (mm)
SRL (m g-1)
RNC (mg g-1)
SS
df
F-value
SS
df
F-value
SS
df
F-value
SS
df
F-value
Depth
0.265
1
8.51**
0.005
1
0.23
0.114
1
0.53
0.979
1
34.23***
Climate
1.219
2
19.54***
0.085
2
2.14
4.557
2
10.56***
3.832
2
66.97***
Climate.Site
0.491
2
7.86***
0.103
2
2.57+
1.884
2
4.37*
0.346
2
6.04**
Climate.Site.Land use
4.905
11
14.3***
4.522
11
20.56***
33.051
11
13.93***
12.347
13
33.2***
Adj-R2
0.71
86
14.94***
0.70
86
14.72***
0.67
86
12.97***
0.83
132
37.55***
RCC (mg g-1)
Soluble (mg g-1)
Cellulose (mg g-1)
Lignin (mg g-1)
Depth
0.002
1
0.68
0.014
1
0.53
0.001
1
0.1
0.151
1
6.18*
Climate
0.163
2
33.73***
2.501
2
48.46***
0.453
2
17.55***
9.122
2
186.48***
Climate.Site
0.001
2
0.25
0.110
2
2.13
0.166
2
6.42**
0.627
2
12.82***
Climate.Site.Land use
0.262
13
8.33***
1.396
13
4.16***
1.115
13
6.65***
15.029
13
47.26***
132
16.22***
0.63
132
14.20***
0.90
132
70.66***
Adj-R2
0.76
132 25.91***
0.67
For F-values: ***P<0.001;**P<0.01; *P<0.05 and +P<0.1
Prieto et al. Electronic Supplementary Material
Table S4. Sums of squares (SS), degrees of freedom (df), F-values and adjusted R2 (Adj-R2) for the nested general linear models (GLMs) for coarse root
functional parameters (FP, n=87 for morphological and n=120 for chemical FP). A symmetrical compound 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 was included to account
for non-independency of the samples from each trench and depth. Functional parameter abbreviations are as in Fig. 1
RDMC (mg g-1)
Dm (mm)
SRL (m g-1)
RNC (mg g-1)
SS
df
F-value
SS
df
F-value
SS
df
F-value
SS
df
F-value
Depth
0.004
1
0.15
0.015
1
0.95
0.042
1
0.15
0.468
1
15.22***
Climate
0.977
2
20.34***
0.355
2
11.24***
6.273
2
11.12***
0.795
2
12.91***
Climate.Site
0.216
2
4.49*
0.176
2
5.57**
0.486
2
0.86
0.087
2
1.41
Climate.Site.Land use
0.908
8
4.73***
1.161
8
9.2***
11.373
8
5.04***
12.986
9
46.89***
Adj-R2
0.50
70
6.67***
0.58
70
8.83***
0.38
70
4.46***
0.82
102
33.80***
RCC (mg g-1)
Soluble (mg g-1)
Cellulose (mg g-1)
Lignin (mg g-1)
Depth
0.027
1
16.14***
0.047
1
1.28
0.049
1
3.34+
0.025
1
0.71
Climate
0.101
2
30.5***
2.443
2
33.12***
0.139
2
4.78*
4.870
2
68.03***
Climate.Site
0.001
2
0.45
0.469
2
6.36**
0.014
2
0.49
0.319
2
4.45*
Climate.Site.Land use
0.098
6.61***
0.973
9
2.93**
0.523
9
3.98***
6.223
9
19.32***
102
8.72***
0.38
102
5.44***
0.75
102
23.28***
Adj-R2
9
0.75
102 22.7***
0.51
For F-values: ***P<0.001;**P<0.01; *P<0.05 and +P<0.1
Prieto et al. Electronic Supplementary Material
Fig. S1 Principal component analysis (PCA) of variables characterizing the different land use
types in our study. Results are from a principal component analysis (PCA); variables used in the
PCA were species composition (% herbaceous species, Herb), age of last disturbance (Dist), soil
nitrogen (Soil N), soil P (Soil P) and soil organic carbon (SOC) concentrations and level of
fertilization (Fert); see table S1 for complete data on these variables. Arrows show projections
of the variables within the PCA. Green, light green and dark green dots represent tropical sites,
yellow dots represent sub-humid Mediterranean sites and blue, dark blue and light blue dots
represent subalpine sites. Names of sites are abbreviated next to dots and defined in Table S1