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Plant and Soil_Electronic Supplementary material
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What nurse shrubs can do for barren soils: rapid productivity shifts associated
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with a 40 year ontogenetic gradient
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Navarro-Cano JA*, Verdú M, García C, Goberna M
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José Antonio Navarro-Cano (*corresponding author). Centro de Investigaciones
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sobre Desertificación (CSIC-UVEG-GV), Carretera Moncada - Náquera, Km 4.5. E-
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46113, Moncada, Valencia, Spain; phone: +34 963424126; Fax: fax: +34 963424160; e-
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mail: jose.a.navarro@uv.es
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(A)
(A)
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(B)
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(C)
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Fig. S1. (A) Overview of the study system. Serra de Crevillent (Alacant, SE Spain).
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Gypsum outcrops are dominated by the shrub O. tridentata. (B) This species determines
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a patch-gap mosaic with gaps partially covered by sealing crusts and some gypsophytes
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and the patches mainly attracting non-gypsophyte species. (C) View of the community
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of facilitated species below the canopy of an adult O. tridentata.
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(A)
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1 cm
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(B)
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50
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R
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0.5 mm
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Fig. S2. Stem cross section of a 25 year old Ononis tridentata individual. (A) The four
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transects analysed from the pith to the cortex are shown in a whole section. (B) Detail of
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the annual growth rings (arrows) shaped by the light earlywood − dark latewood
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sequence and one of the frequent perpendicular rays (R) for lateral conduction (40×).
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4
40
Temperature (ºC)
(A)
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y  18.64 
18.05
x
R2 = 0.81
p < 0.0001
30
25
20
15
10
0
10
20
30
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Light intensity (µmol·m-2·sec-1)
Age (years)
200
(B)
y  12.87 
132.71
x
R2 = 0.76
p < 0.0001
150
100
50
0
0
10
20
30
40
30
40
Age (years)
Gravimetric humidity (%)
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y  0.89  0.08 x  0.0002 x 2 (C)
R2 = 0.48
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p < 0.0001
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3
2
1
0
0
10
20
Age (years)
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Fig. S3. Micro-environment characterization of Ononis patches along the studied
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ontogenetic gradient. Soil surface temperature (A), light intensity (B) and gravimetric
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humidity (C) measurements from April 2013 are shown. Analytical methods are given
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in the main text.
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Litter biomass (g·m-2)
700
y
600
500
483.3
 (x  15.17 )
6.58
1 e
R2 = 0.65
p < 0.0001
400
300
200
100
0
0
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10
20
30
40
Age (years)
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Fig. S4. Regression model showing the sigmoidal fit of Ononis Age on the litter
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biomass. The regression equation, explained variance and significance of the F-test are
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shown. Data are given on an oven-dried weight mass.
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160
R2 = 0.36
p < 0.0001
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Ca (g·kg-1)
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B (mg·kg-1)
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y  20.02  2.85 x  0.05 x 2
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120
60
100
40
80
y
60
40
20
R2 = 0.34
p < 0.0001
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0
20
0
0
20
30
40
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y  2.39  0.52 x  0.01x 2
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R2 = 0.36
p < 0.0001
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0
10
14
12
10
8
6
20
30
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y  4.31  0.59 x  0.01x 2
R2 = 0.26
p < 0.001
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Fe (g·kg-1)
Cu (mg·Kg-1)
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10.44
 (x  0.06 )
2.35
1 e
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10
4
5
2
0
50
0
0
10
20
30
y  1.30  0.10 x  0.002 x 2
R2 = 0.15
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10
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y  126.2  11.8 x  0.24 x 2
30
40
R2 = 0.27 p < 0.001
Mn (mg·kg-1)
400
30
300
20
200
10
100
0
1.2
0
p < 0.05
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Mg (g·kg-1)
500
0
0
10
20
30
40
18
0
10
20
30
40
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1.0
Ni (mg.kg-1)
Mo (g·kg-1)
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0.8
0.6
0.4
12
10
8
6
4
0.2
y  0.39  0.02 x  0.0003 x 2 R2 = 0.36
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p < 0.0001
0.0
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0
10
20
30
40
0
R2 = 0.29 p < 0.001
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20
30
40
30
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y  5.46  1.45 x  0.02 x 2
R2 = 0.42
p < 0.0001
Zn (mg·kg-1)
Ni (g·kg-1)
50
40
60
30
40
20
20
10
0
0
0
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y  5.44  0.45 x  0.009 x 2
0
10
20
Age (years)
30
40
0
10
20
Age (years)
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Fig. S5. Soil surface micro-nutrient values along the studied ontogenetic gradient.
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Regression curves showing lesser residual sum of squares are showed. Data are given
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on an oven-dried weight mass. Analytical methods are given in the main text.
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Seedling biomass (g)
0.07
0.07
y  0.055  0.003x  0.001x 2
R2 = 0.19
0.06
0.05
0.05
0.04
0.04
(A1)
0.03
-2
1.8
1.6
Root-shoot ratio
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0
p < 0.0001
1.2
1.2
1.0
1.0
-2
0
Soil fertility (PC1)
2
20
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y  1.597  0.026 x  0.0002 x 2
R2 = 0.21
p < 0.0001
1.6
1.4
(B1)
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1.8
1.4
0.8
(A2)
0.03
2
y  1.259  0.094 x  0.005x 2
R2 = 0.18
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p < 0.0001
0.06
p < 0.0001
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y  0.003  0.002 x  0.00003x 2
R2 = 0.18
(B2)
0.8
0
10
20
30
Age (years)
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Fig. S6. Regression models showing the quadratic fits of: (A1) the barley seedling
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biomass (above- + belowground biomass) as a function of the increasing chemical
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fertility determined by the Ononis ontogenetic gradient, (A2) the barley seedling
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biomass as a function of the estimated Ononis age below which the soil samples used in
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the fertility bioassay were collected, (B1) the barley root-shoot ratio
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(belowground·aboveground-1 biomass) as a function of the increasing chemical fertility
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determined by the Ononis ontogenetic gradient and (B2) the barley root-shoot ratio as a
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function of the estimated Ononis age. The regression equations, explained variances and
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significance of the F-tests are shown. Each point is the average ± SE of 36 seedlings
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after three weeks in a growth chamber. Data are given on an oven-dried weight basis.
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-1
y
2500
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 (x  14.53 )
8.88
1 e
-1
3000
R2 = 0.73
p < 0.0001
2000
1500
1000
500
0
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Beta-glucosidase (µmol PNP·g-1·h-1)
Basal Respiration (mg CO2-C·kg ·day )
Phosphatase activity (µmol PNP·g-1·h-1)
Microbial biomass C (mg C·kg-1)
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14
10
20
30
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y  9.92  5.81x  14.81x 2
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R = 0.89
p < 0.0001
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10
8
6
4
2
0
0
10
20
30
40
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y  0.781  3.569 x  0.073x 2
R2 = 0.22
p = 0.003
100
80
60
40
20
0
0
35
10
20
30
40
30
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y  0.52  1.397 x  0.018 x 2
2
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R = 0.81
p < 0.0001
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20
15
10
5
0
0
10
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Urease activity (mg NH4+-N·g-1·h-1)
Age (years)
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y  0.72  0.06 x  0.001x 2
2
R = 0.91
p < 0.0001
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4
3
2
1
0
0
10
20
30
40
Age (years)
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Fig. S7. Soil microbial productivity parameters along the studied ontogenetic gradient.
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Regression curves showing lesser residual sum of squares are showed. Analytical
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methods are given in the main text.
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