Environ Geochem Health (2008) 30:127–133
DOI 10.1007/s10653-008-9150-4
O RI G I N A L P A P E R
Relationship between plant biodiversity and heavy metal
bioavailability in grasslands overlying an abandoned mine
A. J. Hernández · J. Pastor
Received: 15 October 2006 / Accepted: 18 June 2007 / Published online: 2 February 2008
© Springer Science+Business Media B.V. 2008
Abstract Abandoned metal mines in the Sierra de
Guadarrama, Madrid, Spain, are often located in areas
of high ecological value. This is true of an abandoned
barium mine situated in the heart of a bird sanctuary.
Today the area sustains grasslands, interspersed with
oakwood formations of Quercus ilex and heywood
scrub (Retama sphaerocarpa L.), used by cattle, sheep
and wild animals. Our study was designed to establish
a relationship between the plant biodiversity of these
grasslands and the bioavailability of heavy metals in
the topsoil layer of this abandoned mine. We conducted soil chemical analyses and performed a greenhouse evaluation of the eVects of diVerent soil heavy
metal concentrations on biodiversity. The greenhouse
bioassays were run for 6 months using soil samples
obtained from the mine polluted with heavy metals
(Cu, Zn, Pb and Cd) and from a control pasture. Soil
heavy metal and Na concentrations, along with the pH,
had intense negative eVects on plant biodiversity, as
determined through changes in the Shannon index and
species richness. Numbers of grasses, legumes, and
composites were reduced, whilst other species (including ruderals) were aVected to a lesser extent. Zinc had
A. J. Hernández
Department of Ecology, Universidad de Alcalá (Madrid),
EdiWcio Ciencias, Campus Universitario, Madrid, Spain
J. Pastor (&)
Department of Systems Ecology, IRN, CCMA, CSIC,
c/ Serrano 115, Madrid 28006, Spain
e-mail: [email protected]
the greatest eVect on biodiversity, followed by Cd and
Cu. When we compared the sensitivity of the biodiversity indicators to the diVerent metal content variables,
pseudototal metal concentrations determined by X-ray
Xuorescence (XRF) were the most sensitive, followed
by available and soluble metal contents. Worse correlations between biodiversity variables and metal variables were shown by pseudototal contents obtained by
plasma emission spectroscopy (ICP-OES). Our results
highlight the importance of using as many diVerent
indicators as possible to reliably assess the response
shown by plants to heavy metal soil pollution.
Keywords Polluted soils · Pb · Zn · Cu · Cd · Ba ·
diversity · Shannon index · Grasslands
Introduction
Soils are the main terrestrial sinks for chemical pollutants. Soil organisms and dynamic processes are
aVected by many pollutants, particularly toxic and persistent elements such as heavy metals (Adriano 2001).
However, despite much published information on the
eVects of metals on Xora (Kabata-Pendias and Pendias
2001; Freitas et al. 2004) and fauna (Nahmani and
Lavelle 2002), the available data on metal eVects on
soil ecosystems are extremely limited and of a very
basic nature (Edwards 2002).
The most obvious impacts of heavy metals are their
eVects on the species diversity of terrestrial plant
123
128
communities and this is often the main eVect assessed
in environmental impact studies. Thus, biodiversity is a
commonly used indicator of a pollutant’s eVects but
has mainly been applied to aquatic ecosystems (Monteiro et al. 1995; Gyedu-Ababio et al. 1999; Sharma et al.
2000), terrestrial microorganisms (Kandeler et al.
1996; Müller et al. 2002; Yao et al. 2006), and soil faunal communities (Urcelai et al. 2000; Nahmani and
Lavelle 2002). These studies have established that the
reduced density and diversity of species observed in
polluted habitats is the main contributor to changes in
community structure, yet there is relatively little information on the eVects of soil pollutants, such as metals,
on plant species richness and even less data concerning
eVects on diversity (Vangrosveld et al. 1996; Bagatto
and Shorthouse 1999; Vidic et al. 2006).
Changes in plant diversity are usually assessed by the
application of diversity indices, the Shannon index
being one of the most widely used (Spellerberg and
Fedor 2003). In other instances, the presence or absence
of indicator species are used to detect changes (Edwards
et al. 1996). Despite criticism regarding the use of such
indicators (van Straalen and Krivolutsky 1996), they
provide valuable information on the early eVects of pollution stress on the biota. The presence of a pollutant in
a habitat will either aVect the area occupied by each species or the resources used by each species, depending
upon the tolerance or sensitivity of the species (Salminen
et al. 2001). Consequently, the delicate balance between
members of a community will be disturbed as pollutants
eliminate the most sensitive populations. Thus, the
frequency distribution of species will be distorted to
varying degrees. Given that plant families such as
Gramineae, Cruciferae, Caryophyllaceae and Compositae contain species adapted to growing in soils polluted
with heavy metals, this study was designed to evaluate
heavy metal eVects on biodiversity (measured by the
Shannon index and diversity), as well as species richness of the main plant communities existing in an abandoned mine area in central Spain whose soils are
heavily polluted with heavy metals.
Materials and methods
Study area
The study area of 1.2 ha is an abandoned barium mine
(“La Asturiana”) situated north of Navas del Rey (SW
123
Environ Geochem Health (2008) 30:127–133
Madrid province, Spain) (40°24.886⬘ N, 4°15.283⬘ E;
30T 393543 E 4474627 N). It is one of the many
mines existing north of Madrid that were exploited in
the 19th and 20th centuries. The legacy left behind by
these mines is a series of dispersed landWlls that act as
a fairly unknown but constant source of pollution.
The mine, worked until 1945, is located at the contact between a granite massif and the Escorial-Villa
del Prado metamorphic complex (Peinado 1970).
Generically speaking, it is a biotite granite with feldspar phenocrystals. Barite appears in quartz seams at
the highest altitudes associated with sulphides, mainly
zinc blende, chalcopyrite and galena (Gutierrez et al.
1986). Besides the metals in the paragenesis (Pb, Zn,
Cu, Ba and Fe), Cd is commonly found in small quantities (ITGM 1990). The mine and its surroundings
occupy a plain crossed by a stream. This promotes the
re-entrainment of mine tailings through the actions of
water and wind. The abundance of sulphides may
have resulted in the dissemination of heavy metals via
the drainage network (Gutierrez-Maroto et al. 1989).
The soils of the mine area are cambisols (Monturiol
and Alcalá del Olmo 1990) and are classiWed as humic
and distric cambisols, eutric gleysols (in swamped
zones) (Gutierrez-Maroto et al. 1989) and regosols.
They are sandy, poor in clay with low levels of nutrients, especially P.
The vegetation on these siliceous soils is composed
of Quercus ilex woodland, Retama sphaerocarpa
scrub, under which pasture communities develop, and
riparian vegetation in the wetter zones. The pasture
communities correspond to diVerent ecosystems of
xeric to wet grasslands and tilled pastures, mainly
used by grazing cattle and wild animals.
Bioassay
A 6-month experimental bioassay was performed
under controlled conditions in a greenhouse (maximum
T 25°C, minimum T 15°C, relative humidity 60–70%,
16/8 h light/dark cycle; during the shortest days of the
year, the photoperiod was completed using OSRAM
400 W HQL MBF-U lamps) using samples of undisturbed soils taken from the area around the mine
entrance. As control, we used a mean soil sample taken
from several plots in adjacent grasslands with Retama
scrub (beyond the mine zone close to the village of
Navas del Rey). Portions of these soil samples were
Wrst analysed to determine heavy metal concentrations,
Environ Geochem Health (2008) 30:127–133
pH and organic matter (OM) content. The corresponding samples were then used to set up microcosms of
diVerent metal pollution levels, using 3 kg of soil for
each microcosm and then observe which plants developed from the soil’s natural seed bank. The sizes of the
microcosms were designed to cover the biodiversity of
the grasslands characteristic of the central peninsular
zone. In total, 27 microcosms, 30 cm long £ 21 wide
and 6 cm deep, were prepared as three replicates per
treatment (heavy metal pollution levels) and control.
This depth corresponds to the Wrst 5 cm of soil in which
the greatest subterranean biomass is found. Each
microcosm was Wtted with a plastic drainage grid 1 cm
from the base. The pots were watered with deionised
water every other day and the growth of species,
mainly annual plants, from the soil’s seed bank examined on a regular basis to obtain inventories of the species, to prune annual species after Xowering/fruiting
and collect leachates.
Variables determined, chemical analyses
and statistical tests
The variables evaluated at the end of the bioassay were
overall plant cover and plant cover for each plant species, as well as total plant numbers and numbers of each
species present. Species richness (diversity ) was determined by counting the number of diVerent plant species
in each microcosm. The Shannon–Wiener diversity
index (H⬘) was calculated from species richness.
Despite there being no consensus as to the most
appropriate measure of heavy metal availability in
soils (Gray and Mclaren 2006), we opted for the use
of two procedures to determine pseudototal soil heavy
metal contents and a third method for available levels
(Lakanen and Ervio 1971). Soluble metal contents
were also determined in the leachates obtained from
the microcosms. Soil analyses (pH, OM, total N and
soil anions) were performed according to Hernández
and Pastor (1989). Portions of the soil samples taken
from the mine to set up the microcosms were sieved
(2 mm sieve) and then ground in an agate mortar.
Metals (Ba, Ca, Mg, K, Na, P, Fe, Mn, Al, Pb, Zn, Cu,
Cd, Ni and Cr) were determined by X-ray Xuorescence (XRF) and inductively coupled plasma-optical
emission spectroscopy (ICP-OES using a Model 4300
DV Perkin-Elmer ICP instrument). Soil samples for
spectroscopy (pseudototal element levels) were acid
digests prepared using a 4:1 mixture of HNO3 and
129
HClO4 using a digestion block. Available metals were
determined by the acetate-EDTA method (Lakanen
and Ervio 1971). Soluble element levels were
obtained by calculating the mean values of their contents in the leachates periodically obtained from each
microcosm.
Metal concentrations in leachates were determined
by ICP-OES. Log-transformed data were analysed by
calculating Pearson correlation coeYcients using
SPSS 13.0 software for Windows (SPSS Inc., 2004).
Results and discussion
Table 1 shows the main soil properties, including
pseudototal, EDTA-extractable and soluble contents of
the most represented heavy metals (Zn, Cu, Pb and Cd)
along with some of the soil factors that were observed
to aVect the diversity of these grassland communities.
Maximum levels recorded were 1,130 ppm for Zn,
888 ppm for Cu, 618 ppm for Pb and 17 ppm for Cd.
Soil pH ranged from 5.9 to 7.2 and OM content was
1.9-8.5%. The heavy metals present include those
derived from the rocks (granite and gneiss) such as Cr,
Ni, Cd and Ba and those that occur in the mine’s paragenesis in the form of Cu, Zn and Pb sulphides. The
concentrations of these elements in the soils were
greater than in the rocks suggesting their deposition in
formation processes. Pseudototal, EDTA-extractable
and soluble contents showed signiWcant correlation for
Zn, Cu, Cd and Pb, although correlations among the
diVerent Pb contents were less signiWcant. Gutierrez
Maroto et al. (1989) observed a log-normal distribution
of the natural populations of elements found in the
mine with the exception of Zn and relatively high geological levels of some of these metals. Like these
authors, we also noted positive correlations between
pseudototal contents of Pb–Cd, Zn–Ba, Cr–Ni and
Cu–Ni, but found no positive Pb–Ni correlations.
Table 2 provides diversity values for the plant
communities and the total plant cover values obtained
in the diVerent microcosms. Table 3 shows the correlations detected between soil heavy metal levels and
other soil factors, and the indicators of biodiversity
for the plant communities. It may be seen that the
main soil factors conditioning the plant biodiversity
of the mine region were the heavy metal (pseudototal,
bioavailable and soluble Zn, Pb, Cu and Cd) and Ba
contents of the soil, along with soil pH and Na levels.
123
123
198 § 13
Zn L&E (ppm)
16.7 § 2.1
Cd XRF (ppm)
74676 § 502
Cr XRF (ppm)
Ba XRF (ppm)
1140 § 315
34.3 § 5.6
0.3 § 0.6
1.4 § 0.8
2.7 § 0.8
47 § 21
3.3 § 1.1
25.7 § 3.5
47 § 5
55.8 § 96.6
0.7 § 0.4
2.4 § 0.7
75 § 6
0.4 § 0.1
46.8 § 6
237 § 48
469 § 21
2.2 § 0.8
12.2 § 6.5
7.4 § 1.8
128.3 § 7.6
0.20 § 0.02
4.5 § 0.3
6.3 § 0.2
Soil 2
1501 § 63
12.3 § 1.8
0.0 § 0.0
1.1 § 1.2
1.1 § 1.1
71 § 22
2.3 § 0.9
1608 § 72
16.3 § 0.7
0.0 § 0.0
0.7 § 0.6
0.3 § 0.6
41 § 8
2.3 § 0.7
33.4 § 3.8
55 § 5
13.8 § 2.9
0.0 § 0.0
35 § 3
12 § 3.1
115 § 6
80 § 17
0.2 § 0.0
7.1 § 1.2
159 § 9
224 § 9
2.3 § 1.3
37.3 § 9.2
12.2 § 3.8
187.3 § 5.1
0.33 § 0.01
7.2 § 0.7
6.1 § 0.1
Soil 4
202 § 104
82 § 5.3
249 § 9
290 § 11
0.3 § 0.1
14.8 § 2.1
96 § 5
134 § 9
2.7 § 1.8
32.7 § 9.6
10.1 § 2.9
118.2 § 9.8
0.30 § 0.02
5.7 § 0.8
6.7 § 0.1
Soil 3
1737 § 58
22.7 § 2.5
0.0 § 0.0
1193 § 379
33.0 § 2.6
0.3 § 0.6
2.4 § 1.1
1.1 § 1.1
0.7 § 0.6
77 § 20
3.3 § 0.9
25.8 § 6.4
48 § 5
0§0
0§0
13 § 3
89 § 6
0.1 § 0.0
13.7 § 1.9
104 § 11
170 § 9
1.7 § 0.7
4.5 § 1.3
7.5 § 1.6
130.5 § 4.6
0.12 § 0.03
2.4 § 0.6
6.2 § 0.3
Soil 6
1.1 § 1.0
32 § 16
3.3 § 0.7
17.8 § 2.2
43 § 3
0.0 § 0.0
20 § 3
92 § 4
92 § 5
0.2 § 0.1
13.3 § 0.7
134 § 8
191 § 11
2.5 § 0.5
27.7 § 4.0
15.8 § 2.7
139.7 § 6.5
0.29 § 0.02
6.1 § 0.2
6.0 § 0.1
Soil 5
673 § 34
30.3 § 3.1
0§0
0§0
0§0
27 § 12
1.4 § 0.9
5. § 1.7
20 § 1.5
0§0
0§0
111 § 5
57 § 23
0.2 § 0.0
2.5 § 0.6
72 § 6
107 § 4
2.3 § 1.3
12.7 § 2.1
6.4 § 0.9
92.2 § 6.6
0.13 § 0.01
1.9 § 0.1
6.1 § 0.1
Soil 7
686 § 43
28.7 § 2.9
0§0
0§0
0§0
17 § 12
0.7 § 0.7
4.6 § 1.6
21 § 1.6
0§0
0§0
122 § 6
67 § 26
0.2 § 0.0
2.4 § 0.7
75 § 6
105 § 4
2.0 § 1.0
602 § 75
35.7 § 9.5
0§0
0§0
0§0
39 § 11
1 § 0.4
12.1 § 2.1
25 § 5
0§0
0§0
11 § 1
29 § 4
0.1 § 0.1
0.2 § 0.2
37 § 3
55 § 3
1.4 § 0.5
11.8 § 1.5
9.8 § 1.7
17.7 § 4.2
84.8 § 7.9
6.0 § 1.5
0.17 § 0.03
3.4 § 0.4
5.9 § 0.1
Soil 9
69.3 § 14.5
0.12 § 0.01
2.0 § 0.2
6.2 § 0.1
Soil 8
XRF, X-ray Xuorescence; ICP-OES, inductively coupled plasma-optical emission spectroscopy; L&E, Lakanen & Ervio method. Soil samples (1–8) taken from diVerent sites of
the same mine. Sample 9 was the control soil
2.5 § 0.4
2.7 § 0.6
Cd L&E (ppm)
5.5 § 1
62. § 17
Cu leachate (g)
Cd ICP OES (ppm)
170 § 12
100 § 4.6
215 § 26
Cu XRF (ppm)
Cu L&E (ppm)
100 § 102
Pb leachate (g)
Cu ICP OES (ppm)
52 § 3
Pb L&E (ppm)
105 § 7
771 § 20
Zn ICP OES (ppm)
Pb ICP OES (ppm)
796 § 18
Zn XRF (ppm)
0.3 § 0.1
3.7 § 1.2
Na (mg/100 g)
619 § 16
58.1 § 13.7
K (mg/100 g)
Zn leachate (ppm)
21.2 § 3.6
Pb XRF (ppm)
211.3 § 11.5
0.34 § 0.02
N (%)
Mg (mg/100 g)
7.1 § 0.6
Ca (mg/100 g)
6.6 § 0.2
OM (%)
Soil 1
pH
Descriptors
Table 1 Mean pH, OM, total N, macronutrient and heavy metal values of the soil samples
130
Environ Geochem Health (2008) 30:127–133
84.0 § 8.3
41.8 § 7.6
51.2 § 8.7
46.2 § 11.4
127.8 § 24.3
59.7 § 12.3
64.5 § 5.2
47.7 § 15.5
40.3 § 6.4
5.3§1.1
“Others” no.
Plant cover (%)
5.7 § 0.6
10.0 § 0.0
7.7 § 1.2
6.0 § 1.0
5.0 § 0.0
7.0 § 2.0
10.7 § 1.5
7.0 § 1.0
3.3 § 0.6
Compositae no.
7.7 § 2.5
4.0 § 1.0
1.3 § 1.5
4.0 § 1.0
3.7 § 1.5
4.7 § 1.5
3.7 § 0.6
3.7 § 0.6
2.3 § 1.1
4.0 § 0.0
5.0 § 2.0
6.0 § 2.6
3.0 § 1.0
3.7 § 2.1
1.3 § 0.6
Leguminosae no.
2.3 § 0.6
3.7 § 0.6
4.3 § 1.2
25.3 § 0.6
5.7 § 0.6
4.3 § 0.6
3.0 § 1.0
4.7 § 0.6
6.3 § 1.5
5.3 § 2.1
1.7 § 1.1
2.61 § 0.19
Gramineae no.
2.0 § 0.0
17.3 § 2.1
2.43 § 0.18
2.34 § 0.12
17.3 § 3.8
17.0 § 1.0
2.12 § 0.21
2.15 § 0.23
19.7 § 3.2
27.0 § 7.0
2.89 § 0.25
2.21 § 0.31
15.3 § 3.5
16.3 § 2.5
13.7 § 2.3
Species no.
2.33 § 0.15
1.96 § 0.9
Shannon index
Soil 6
Soil 5
Soil 4
Soil 3
Soil 2
Soil 1
Descriptors
Table 2 Mean (§SD) biodiversity and plant cover values for the plant communities growing in the microcosms
Soil 7
Soil 8
Soil 9
Environ Geochem Health (2008) 30:127–133
131
In three soil types with similar heavy metal contents
to our soils (900 ppm Zn, 300 ppm Cu, 150 ppm Ni,
9 ppm Cd) Kandeler et al. (1996) noted that heavy
metal pollution severely reduced the functional diversity of their microbial communities. Vangrosveld
et al. (1996) reported that the diversity of higher plant
species and saprophytic fungi was extremely low in a
bare industrial area polluted with Zn, Pb, Cu and Cd.
As in our study, Koptsik et al. (2003) found that in
heavy metal polluted soils, the order of the major
diversity indices was highly related to soil properties,
suggesting that heavy metal and nutrient contents are
the best soil-related predictors of species diversity in
polluted areas, and that soil contamination and nutritional disturbances contribute signiWcantly to the vegetation damage observed in ecosystems.
Shannon index values and species richness were
negatively and signiWcantly correlated with the
contents of these metals in the soils. For Zn and
Cu, correlation indices were higher with respect to
EDTA-extractable and soluble elements than with
pseudototal levels. Bagatto and Shorthouse (1999)
noted that when water-soluble concentrations of Cu
and Ni in the upper horizons of mine soils decreased,
Xoral diversity increased. Yao et al. (2006) observed
reduced population diversity, as reXected by the
Shannon index, of the microbial communities of
Cu-polluted red soils. Vidic et al. (2006) also detected
a negative correlation between soil Pb, Zn, and Cd
concentrations and several plant biodiversity markers
determined across a pollution gradient.
When we examined the eVects of heavy metals on
families or groups of species, it was noted that the number of Gramineae species was fairly insensitive to total
soil metal contents, while species numbers were aVected
by soluble Zn and Pb levels and by soil pH. Bioavailable
Cd and Cu levels and pseudototal Pb and Ba concentrations mainly aVected the number of legume species.
EVects on Compositae were mainly produced by bioavailable and soluble Zn contents. The “other” species
behaved similarly in response to soil heavy metal, pH
and Na values. Of the four groups, the “others” seemed
to be the best indicators of soil metal pollution, since this
group includes many plants related to human activities
such as: Anagallis arvensis L., Brassica barrelieri (L.)
Janka, Echium plantagineum L., Erodium cicutarium
(L.) L´Her, Geranium molle L., Plantago coronopus L.,
Plantago lagopus L. and Spergularia rubra (L.) J et C
Presl. Similar observations have been made using other
123
132
Environ Geochem Health (2008) 30:127–133
Table 3 Correlations between biodiversity markers for the plant communities, pseudototal, bioavailable and soluble metal contents
and other chemical and physical properties of the soils from the abandoned mine
Soil
Shannon
index
Species no.
Gramineae,
no. of species
Leguminosae,
no. of species
Compositae,
no. of species
Others, no.
of species
Plant cover
(%)
Zn XRF
¡0.397*
¡0.430*
¡0.226
¡0.182
¡0.349 (R)
¡0.326 (R)
¡0.349 (R)
Zn ICP-OES
¡0.408*
¡0.448*
¡0.167
¡0.294
¡0.305 (R)
¡0.347 (R)
¡0.328 (R)
Zn L&E
¡0.554**
¡0.557**
¡0.304 (R)
¡0.210
¡0.431*
¡0.463*
¡0.309 (R)
Zn leachate
¡0.421*
¡0.602**
¡0.622**
¡0.114
¡0.488**
¡0.323 (R)
¡0.214
Pb XRF
¡0.553**
¡0.600**
¡0.366 (R)
¡0.427*
¡0.323 (R)
Pb ICP-OES
¡0.055
¡0.113
¡0.024
¡0.262
0.032
¡0.399*
¡0.275
¡0.041
¡0.069
Pb L&E
¡0.277
¡0.213
¡0.160
¡0.113
¡0.191
¡0.085
¡0.227
Pb leachate
¡0.380*
¡0.496**
¡0.586**
¡0.267
¡0.169
¡0.209
¡0.094
Cu XRF
¡0.432*
¡0.313 (R)
0.006
¡0.224
¡0.139
¡0.318 (R)
¡0.226
Cu ICP¡OES
¡0.370 (R)
¡0.241
0.017
¡0.120
¡0.117
¡0.247
¡0.181
Cu L&E
¡0.516**
¡0.435*
¡0.362 (R)
¡0.166
¡0.425*
¡0.274
Cu leachate
¡0.498**
¡0.420*
¡0.288
Cd XRF
¡0.630***
¡0.533**
¡0.113
¡0.063
0.162
¡0.326 (R)
¡0.224
¡0.415*
¡0.098
¡0.284
¡0.528**
¡0.313 (R)
Cd ICP-OES
¡0.418*
¡0.348 (R)
¡0.107
¡0.209
¡0.229
¡0.322 (R)
¡0.272
Cd L&E
¡0.432*
¡0.412*
¡0.051
¡0.424*
¡0.049
¡0.379*
¡0.307 (R)
Cr XRF
¡0.362 (R)
¡0.332 (R)
¡0.371 (R)
¡0.047
0.222
0.108
0.201
Ba XRF
¡0.455*
¡0.391*
¡0.025
¡0.383*
¡0.122
¡0.349 (R)
¡0.222
pH
¡0.512**
¡0.653***
¡0.583***
¡0.313 (R)
¡0.281
¡0.444*
¡0.435*
Na
¡0.580**
¡0.629***
¡0.236
¡0.236
¡0.491**
¡0.533**
¡0.180
*** SigniWcant at the 0.001 level; ** signiWcant at the 0.01 level; * signiWcant at the 0.05 level; (R) reliable at the 90% signiWcance
level
XRF, X-ray Xuorescence; ICP-OES, inductively coupled plasma-optical emission spectroscopy; L&E, Lakanen and Ervio method
taxonomic categories or groups of organisms. Thus,
Gyedu-Ababio et al. (1999) reported that the number of
nematode genera was signiWcantly negatively correlated
with the metals Zn and Fe in the substrate, and Bouwman et al. (2001) observed the intense suppression of
bacterial growth and number of bacterivorous nematodes
related to high soil Cu levels (170 mg kg¡1). Nahmani
and Lavelle (2002) linked high total soil Zn contents to
the reduced density and diversity of earthworms and
other macrofaunal communities, the composition of
these communities changing with the degree of pollution. Plant cover was also negatively correlated with the
Zn, Ba, Na and sand contents of the soils, and positively
correlated with the silt content.
Conclusions
Our Wndings indicate that the varying heavy metal
and Na contents of the mine soil have negative
repercussions on plant biodiversity, with eVects
123
observed on both the Shannon index and species
richness. Of the four groups of plant analysed, it
was the group of miscellaneous species that seemed
to be the best indicator of heavy metal soil pollution. The reason for this is that this group contained
many ruderal species related to human activities,
while the grasses, legumes and composites are
essentially pasture plants.
Greatest eVects on biodiversity variables were
recorded for Zn, followed by Cd, Cu and Pb. When
we compared the sensitivity of the diVerent metal
content variables to biodiversity, overall, pseudototal
levels determined by XRF were the most sensitive
followed by available and soluble contents. Worse
correlations between biodiversity indicators and
heavy metal contents were recorded for the pseudototal contents determined by ICP-OES.
Acknowledgements This study was funded by an MEC Project
CTM2005-02165/TECNO, the EIADES Program of the CM
and a grant from the Spanish Ministry of the Environment.
Environ Geochem Health (2008) 30:127–133
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