www.nature.com/scientificreports
OPEN
Received: 20 April 2017
Accepted: 11 December 2017
Published: xx xx xxxx
Trace metals from historical mining
sites and past metallurgical activity
remain bioavailable to wildlife
today
Estelle Camizuli , , Renaud Scheiler , Stéphane Garnier , Fabrice Monna , Rémi Losno ,
Claude Gourault , Gilles Hamm , Caroline Lachiche , Guillaume Delivet , Carmela Chateau &
Paul Alibert
Throughout history, ancient human societies exploited mineral resources all over the world, even in
areas that are now protected and considered to be relatively pristine. Here, we show that past mining
still has an impact on wildlife in some French protected areas. We measured cadmium, copper, lead,
and zinc concentrations in topsoils and wood mouse kidneys from sites located in the Cévennes and the
Morvan. The maximum levels of metals in these topsoils are one or two orders of magnitude greater
than their commonly reported mean values in European topsoils. The transfer to biota was efective,
as the lead concentration (and to a lesser extent, cadmium) in wood mouse kidneys increased with soil
concentration, unlike copper and zinc, providing direct evidence that lead emitted in the environment
several centuries ago is still bioavailable to free-ranging mammals. The negative correlation between
kidney lead concentration and animal body condition suggests that historical mining activity may
continue to play a role in the complex relationships between trace metal pollution and body indices.
Ancient mining sites could therefore be used to assess the long-term fate of trace metals in soils and the
subsequent risks to human health and the environment.
he irst evidence of extractive metallurgy dates from the 6th millennium BC in the Near East1,2. Since then, mining and smelting activities have developed almost everywhere that humans have settled3,4, resulting in the emission of unexpectedly large amounts of metals into the environment, e.g., during the Roman Empire5,6. Deleterious
consequences on human health were observed as early as the 1st century BC, with Lucretius, for instance, pointing
out “the ill efects in the miners’ complexions” and writing “How deadly are the exhalations of gold mines!” (De
natura rerum, 4, 8087). Negative impacts of mining and smelting activities on animals and the environment were
also recognized long ago. During the 1st century BC, Vitruvius wrote that springs coming from mining areas were
very harmful (De Architectura, 8, 58), while Pliny the Elder, during the 1st century AD, noticed how silver mine
emissions afect all animals (Naturalis Historia, 33, 319).
With geographical shits of human settlements over time, some mining and/or smelting sites may have vanished from collective memory10–12. For instance, in the Morvan and Cévennes massifs (France), the older sites
remain diicult to identify in the ield, particularly in forested areas. Because of their outstanding landscapes
and biodiversity, both the Morvan and the Cévennes are recognized as nature parks, considered to be pristine
areas, relatively free from anthropogenic impact. hese areas have nonetheless experienced several phases of
mining and smelting, starting as early as the Bronze Age for the Morvan13–15 and at least from the Iron Age for
the Cévennes16.
UMR
, ArTeHiS, Université Bourgogne Franche-Comté–CNRS, Dijon,
, France. UMR
EDYTEM,
Université Savoie Mont Blanc–CNRS, Le Bourget-du-Lac cedex,
, France. UMR
, Chrono-Environnement,
Université Bourgogne Franche-Comté–CNRS, Besançon,
, France. UMR
, Biogéosciences, Université
Bourgogne Franche-Comté–CNRS, Dijon,
, France. IPGP, Paris, cedex ,
, France. UFR SVTE,
Université Bourgogne Franche-Comté,
, Dijon, France. Estelle Camizuli, Renaud Scheiler, Stéphane Garnier
and Fabrice Monna contributed equally to this work. Correspondence and requests for materials should be addressed
to E.C. (email: e.camizuli@wanadoo.fr)
SCIENTIFIC REPORTS | (2018) 8:3436 | DOI:
.
/s
-
-
-
1
www.nature.com/scientificreports/
MORVAN
M0
M1
M2
(47.165°N, 4.073°E)
Area free of mining activity
(46.915°N, 3.957°E)
Mining (19th-20th c. AD)
Smelting (130 AD – 426 AD)
Fe
(47.250°N, 3.645°E)
Mining (15th-16th c. AD)
Pb-Ag
C0
(44.378°N, 3.853°E)
Area free of mining activity
C1
(44.337°N, 3.667°E)
Mining and cleansing
19th-20th c. AD
Zn-Pb-Ag
C2
Google, ©2016 TerraMetrics. Inc. www.terrametrics.com
CÉVENNES
©IGN2016
BDalti®75m, ADMIN Express
BD Carthage®
(44.465°N, 3.623°E)
Smelting (11th-14th c. AD)
Pb-Ag
Figure 1. Location of the study sites where soils and small mammals were sampled. he Morvan Regional
Nature Park and the Cévennes National Park are both located in the Massif Central, France. Within each park,
three sites were selected based on their degree of contamination. M0 in the Morvan and C0 in the Cévennes
are free of mining and were used as reference sites. he coordinates of the centroid are given in WGS84 (EPSG
4326), decimal degrees (Lat, Long). he maps were created using QGIS sotware (QGIS Essen 2.14.6, http://
www.qgis.org), adapted by E. Camizuli from Google Satellite©2016 and IGN©2016.
In these parks, recent archaeological studies have identiied ancient metallurgical sites, their spatial extent
and the nature of their activities, together with palaeoenvironmental information17,18. Companion geochemical
studies on those sites have shown that soils and sediments can still be highly contaminated by various metals due
to their persistence in the environment10,19. However, a high concentration of metals in the abiotic environment
does not necessarily imply that any transfer to biota will be suicient to cause adverse efects on organisms20,21.
he transfer of an element from abiotic compartments to biota depends on the biological characteristics of the
targeted organisms as well as the bioavailability of the element, which is inluenced by the physico-chemical properties of both the pollutant and the medium22. At sites that have been contaminated in the past but are no longer
subject to polluting activities, bioavailability may have drastically decreased because of various physico-chemical
processes that immobilise metals in abiotic compartments, e.g., soils23. he degree of toxicity, once a metal has
been transferred into an organism, depends on the type of metal and on the defence mechanisms deployed by the
organism (excretion, storage under non- or less toxic chemical forms of the metal, etc.). Metals can be classiied
into two categories, according to their physiological role: “essential” elements are those metals that have a crucial
biological function in organisms (such as iron in haem, a component of haemoglobin), while “non-essential”
elements are those for which no biological function is known. Any deleterious efects of non-essential elements
generally occur at lower relative concentrations than those of essential elements, which can, however, still be toxic
at high levels.
We therefore investigated whether trace metals (TMs) in soils surrounding ancient mining and metallurgical
sites from various periods in two parks, the Morvan Regional Nature Park and the Cévennes National Park, are
still bioavailable and, if so, toxic to wildlife. he aims of the present study were (i) to quantify the level of soil
contamination by four TMs directly linked to mining activity, (ii) to check whether these contaminants were
bioavailable to organisms such as the wood mouse, and inally (iii) to see if contamination ever occurred at levels
prejudicial to the organism’s health. Within each park, three sites were selected (Fig. 1): one free of mining, used as
a reference site (M 0 in the Morvan and C 0 in the Cévennes), one moderately contaminated (M1 in the Morvan
and C1 in the Cévennes), and one highly contaminated (M2 in the Morvan and C2 in the Cévennes). Four TMs
(two essential elements, copper (Cu) and zinc (Zn), and two non-essential elements, cadmium (Cd) and lead
(Pb)), were measured in topsoils (n = 261) and in the kidneys of wood mice (Apodemus sylvaticus, n = 157) sampled at the six study sites. hese four elements were selected because of the local geology of the study sites, where
past mining activities mainly exploited polymetallic sulphide ores. he potential toxic efects of these elements on
the local fauna were investigated by several proxies: body condition for nutritional status24–27, somatic indices for
possible histological damage28, and luctuating asymmetry (FA) for developmental instability29,30.
Results
Trace metal concentrations in topsoils. The TM concentrations in soils ranged from less than
0.5 mg·kg−1 to 54.2 mg·kg−1 for Cd, 11 mg·kg−1 to 212 mg·kg−1 for Cu, 85 mg·kg−1 to 8410 mg·kg−1 for Pb, and
SCIENTIFIC REPORTS | (2018) 8:3436 | DOI:
.
/s
-
-
-
2
www.nature.com/scientificreports/
Cd (mg · kg−1) Cu (mg · kg−1) Pb (mg · kg−1)
Morvan
Zn (mg · kg−1)
M0
<0.5 (LOD)
11
90
90
M1
3.2
212
4520
835
M2
54.2
81
8410
13800
C0
<0.5 (LOD)
11
85
107
C1
6.8
132
1580
1560
C2
10
105
4810
142
European Topsoils32
Mean value
0.28
17.3
32
68.1
French sewage sludge
for amendment*
Content limit
2
100
100
300
Intervention value
12
190
530
720
Cévennes
31
Dutch standards
Table 1. Maximum concentrations for Cd, Cu, Pb and Zn in topsoils of the six study sites compared to
reference values. *Under French regulations, sewage sludge for agricultural soil amendment must not contain
trace metal concentrations above these limits. LOD stands for Limit Of Detection.
90 mg·kg−1 to 13800 mg·kg−1 for Zn (Table 1 and Supplementary Table S1). Maximum levels for all the four TMs
studied were found in the contaminated sites of the Morvan region. he spatial distribution of TMs in soils shows
that higher concentrations were found in the mining and metallurgical sites, whatever the region considered
(Fig. 2a, Fig. 3a, Supplementary Fig. S1 for the Morvan and Supplementary Fig. S2 for the Cévennes). In the
Morvan, the three sites difered signiicantly (Kruskal-Wallis test, all p < 0.05) in terms of Cd, Cu, Pb and Zn
contents in topsoils (Fig. 2a and Fig. 3a), with all elements following the pattern M0 < M1 < M2 (Steel-Dwass
pairwise comparisons). In the Cévennes, the three sites difered for Cu and Zn contents with the pattern C2 <
C0 < C1 (Fig. 2a). he Cd concentrations were similar in C0 and C2, both were lower than in C1. he Pb concentrations were similar for the three study sites (Kruskal-Wallis test, p > 0.05) but C2 exhibited greater spatial
heterogeneity, ranging from 31 mg·kg−1 to 4810 mg·kg−1 (Fig. 3a and Supplementary Table S1).
Wood mouse population characteristics.
he wood mouse age structures difered signiicantly between
the two parks (χ2 = 8.48, p = 0.01, df = 2), but not between the three sites for either the Morvan (χ2 = 1.85, p =
0.76, df = 4) or the Cévennes (χ2 = 5.00, p = 0.29, df = 4). he sex ratios did not difer signiicantly between parks
or sites (χ2 = 0.47, p = 0.49, df = 1 for parks, χ2 = 2.22, p = 0.33, df = 2 for the Morvan and χ2 = 1.01, p = 0.6, df
= 2 for the Cévennes, Supplementary Fig. S3).
Trace metal concentrations in kidneys. he Cu concentrations in wood mouse kidneys ranged from
10.37 µg·g−1 to 22 µg·g−1, and the Zn concentrations ranged from 44.5 µg·g−1 to 160 µg·g−1 (Supplementary
Table S2). Except for Cu in the Cévennes with C1 < C0 − C2 (Tukey’s HSD test ater an analysis of variance
(ANOVA) with p < 0.05), essential element concentrations did not difer between the study sites (p > 0.05),
suggesting physiological (homeostatic) regulation (Fig. 2b). Concentrations of the non-essential elements in the
kidneys ranged from 0.05 µg·g−1 to 38 µg·g−1 for Cd and from 0.05 µg·g−1 to 19 µg·g−1 for Pb. Maximum concentrations were found in the contaminated sites of the Cévennes region (C1 for the Cd and C2 for Pb). he Cd
concentrations followed these patterns: M0 < M1 − M2 and C0 − C2 < C1. he Pb concentrations followed the
same pattern in both parks, showing no diferences between sites 0 and 1, but with both values lower than for site
2 (Fig. 3b).
Trace metal concentrations in wood mice in relation to biological and environmental parameters.
Multivariate linear models were used to investigate the relationship between TM concentrations in kidneys and
explanatory variables (site, TMs in soils, sex, and mass), for each TM separately. Both Cd and Zn concentrations in wood mouse kidneys were best explained by models combining study sites and body mass (Table 2, for
description of best-it models and Supplementary Table S3 for model parameters). he same pattern was observed
for Cu concentrations in wood mouse kidneys, with sex as an additional factor (Table 2 and Supplementary
Table S3). he Pb concentrations varied between sites as indicated above and increased with Pb concentrations
in soil (Table 2, Fig. 4a and Supplementary Table S3). he Cd concentrations in wood mouse kidneys increased
slightly with mass, while Cu and Zn concentrations decreased slightly (Table 2 and Supplementary Table S3).
Toxic effects assessed by body condition, somatic indices, and fluctuating asymmetry.
Relationships between body condition and somatic indices were investigated with multivariate linear models
using study sites, the four TMs in wood mouse kidneys, and sex as explanatory variables. Body condition as
assessed by scaled mass index (SMI) was best explained by a model combining study sites, Cd and Pb concentrations in kidneys and the interaction between Cu or Zn concentrations in kidneys and sex (Table 3). he SMIs
varied according to the sites, increased with Cd concentrations and were negatively related to Pb concentrations
in kidneys (Fig. 4b and Supplementary Table S4). he SMIs were negatively inluenced by the interaction between
Cu concentrations and sex, and positively inluenced by the interaction between Zn concentrations and sex.
Somatic index data (scaled liver index - SLI, and scaled kidneys index - SKI) were best it by models including
study sites, sex and the interaction between Cu or Zn concentrations in kidneys and sex (Table 3). Like SMI, both
SKI and SLI were negatively related to the Cu × sex interaction and positively related to the Zn × sex interaction
(Supplementary Table S4). Concerning FA, preliminary tests were performed for all traits measured (here, length
SCIENTIFIC REPORTS | (2018) 8:3436 | DOI:
.
/s
-
-
-
3
www.nature.com/scientificreports/
Figure 2. (a) Distribution of topsoil concentrations of essential elements (Cu and Zn) at the six study sites.
Dutch intervention values for assessing soil contamination are represented by a red line31 (b) Distribution of
essential elements (Cu and Zn) kidney concentrations in wood mice sampled at the six study sites (dry mass
basis in). 0 < *** < 0.001 < ** < 0.01 < * < 0.05 < . < 0.1.
and width of lower molars) as recommended by Palmer29. hese tests did not suggest that directional asymmetry
(DA), antisymmetry (AS) or relationships between asymmetry and trait size could signiicantly bias FA estimates
(Supplementary Table S5). No signiicant correlations were found between absolute asymmetry distribution and
TM concentrations in kidneys (Supplementary Table S6). When compared to measurement error, FA10, a parameter used for FA assessment, was always signiicant (Supplementary Table S7), but no clear relationship was found
between levels of developmental instability assessed by FA and sites for either park (Supplementary Fig. S4).
Discussion
Even centuries ater mining and metallurgical activities have ceased, TM concentrations in soils surrounding such
sites still reach high levels. here is no European consensus on threshold concentrations of metals in soils, but the
Dutch government proposed a soil classiication scheme in which intervention values are deined. hese strict
values identify serious contamination of soils (12, 190, 530, and 720 mg·kg−1 dry matter for Cd, Cu, Pb, and Zn,
respectively) and indicate that remediation is necessary31. In the present study, 75 out of 261 soil samples (29%)
exceed the Pb intervention value, reaching 59% in the highly contaminated Morvan site, M2 (Fig. 3a). For both
Cd and Cu, only one sample out of 261 exceeds the Dutch intervention values, while Zn exhibits an intermediate
pattern, with 10% of the soils exceeding the threshold (Fig. 2a). Among the four metals studied and according to
this classiication, Pb concentrations represent the most important risk, which is probably linked to the nature of
the ore exploited (galena) and to the low mobility of Pb in the environment32. For Cd, while only one soil exceeds
the Dutch intervention threshold, this intervention limit is high (12 mg·kg−1) compared to the average concentration in European surface soils (0.28 mg·kg−1, Table 1)32. In France, Cd concentrations in sewage sludge-amended
agricultural soils must be lower than 2 mg·kg−1 (Table 1). As Cd is toxic to organisms at low doses, it should also
SCIENTIFIC REPORTS | (2018) 8:3436 | DOI:
.
/s
-
-
-
4
www.nature.com/scientificreports/
Figure 3. (a) Distribution of topsoil concentrations of non-essential elements (Pb and Cd) at the six study
sites. Dutch intervention values for assessing soil contamination are represented by a red line31 (b) Distribution
of non-essential elements (Pb and Cd) kidney concentrations in wood mice sampled at the six study sites (dry
mass basis in). he Lowest Observed Adverse Efect Levels (LOAELs) deined by Shore & Douben43,44 are
represented by a red line. 0 < *** < 0.001 < ** < 0.01 < * < 0.05 < . < 0.1.
Best-it models
n
log 10(Cukidneys) ∼ site + sex + mass
157
Df
F value
Pr(>F)
site
5
2.50
0.03*
sex
1
5.24
0.02*
mass
1
21.03
5
2.56
1
13.93
0.0003***
5
10.38
1.45 ⋅ 10−08***
1
9.33
0.003**
site
2
4.25
0.02*
mass
1
18.92
9.51 ⋅ 10−06***
157
log 10(Znkidneys) ∼ site + mass
0.14
site
mass
0.03*
157
log 10(Pbkidneys) ∼ site + log 10(Pbsoil )
0.35
site
log 10(Pbsoil )
79
log 10(Cdkidneys) ∼ site + mass
R2
0.60
0.23
4.24 ⋅ 10−05***
Table 2. Summary of best-it models for trace metals in wood mouse kidneys. Models relating trace metal
concentrations in kidneys to biological and environmental parameters, and trace metal concentrations in soils.
0 < *** < 0.001 < ** < 0.01 < * < 0.05 < . < 0.1.
SCIENTIFIC REPORTS | (2018) 8:3436 | DOI:
.
/s
-
-
-
5
www.nature.com/scientificreports/
Figure 4. he efect of Pb concentrations on wood mice. (a) Variation of Pb concentrations in wood mouse
kidneys in relation to both Pb concentrations in soils (abscissa) and sites (illustrated by diferent colours).
(b) Variation of body condition as assessed by scaled mass index (SMI) in relation to both Pb concentrations
in wood mouse kidneys (abscissa) and sites (illustrated by diferent colours). As the model was complex, we
present only two parameters inluencing the SMI (Pb concentrations in wood mice and site).
Best-it models
n
Df
F value
Pr(>F)
R2
SMI ∼ site + log 10Cd + log 10Cu + log 10Pb + log 10Zn + sex + log 10Cu × sex + log 10Zn × sex
154
0.24
site
5
3.26
0.008**
log10(Cdkidneys)
1
4.58
0.03*
log10(Pbkidneys)
1
5.59
0.02*
log10(Cukidneys) × sex
1
10.78
0.001**
log10(Znkidneys) × sex
1
11.45
0.0009***
SLI ∼ site + log 10Cu + log 10Zn + sex + log 10Cu × sex + log 10Zn × sex
155
0.30
site
5
7.28
log10(Cukidneys) × sex
1
10.05
log10(Znkidneys) × sex
1
5.88
4.26 ⋅ 10−06***
0.002**
0.02*
SKI ∼ site + log 10Cu + log 10Zn + sex + log 10Cu × sex + log 10Zn × sex
155
0.25
site
5
5.38
0.0001***
log10(Cukidneys) × sex
1
10.95
0.001**
log10(Znkidneys) × sex
1
10.52
0.001**
Table 3. Summary of best-it models for body condition and somatic indices. Models relating body condition
and somatic indices to biological and environmental parameters and trace metal concentrations in wood mouse
kidneys. 0 < *** < 0.001 < ** < 0.01 < * < 0.05 < . < 0.1.
be considered for risk assessment. Maximum levels of Cd and Zn were around 200 times higher than their commonly reported values in European topsoils, while Cu was 12 times and Pb 2–3 times higher32 (Table 1). Apart
from these locally high concentrations, TM contents in topsoils are highly heterogeneous (Supplementary Fig. S1
and Fig. S2), complicating risk assessment. Such heterogeneity is also observed in modern mining or smelting
sites33,34 and can be explained by the spatial distribution of exploitation facilities in relation to the surrounding
habitat (e.g., interception of metals emitted in the air by the canopy35).
Metal toxicity depends not only on the concentration of a substance in a medium but also on its bioavailability, a complex combination of the physico-chemical characteristics of the pollutant in abiotic compartments and
the biological characteristics of organisms36. he irst component, known as “environmental availability”, represents the physico-chemically driven desorption processes that determine the mobile proportion of the total metal
SCIENTIFIC REPORTS | (2018) 8:3436 | DOI:
.
/s
-
-
-
6
www.nature.com/scientificreports/
concentration in a soil. Among the numerous parameters that determine this availability, time generally lead
to immobilisation of metals, a process named “ageing” 22,23. he second component, known as “environmental
bioavailability”, represents physiologically driven uptake processes that occur when an organism and a pollutant
co-occur in time and space (namely, the “exposure” of an organism). In the present work, our aim was to examine
whether these high, spatially heterogeneous concentrations of metals were bioavailable to organisms by measuring TM levels in wood mouse kidneys. For the two essential elements, concentrations did not difer among sites,
suggesting their eicient (homeostatic) regulation37. Concentrations measured here are similar to values found
in other studies on wood mice38,39. However, the non-essential elements Cd and Pb showed marked diferences
between sites, with higher concentrations in the mining and smelting areas, showing that these metals are still
bioavailable to wildlife. Concentrations of Pb in wood mouse kidneys measured in the present study are of the
same order of magnitude as those measured in animals sampled around a non-ferrous smelter still in activity in
Antwerp (Belgium)38. hey are, however, below the concentrations observed in wood mice in the surroundings of
Metaleurop Nord, a Pb and Zn smelter in activity from 1894 to 2003 in northern France28,40. Direct comparisons
between all these values must be undertaken with caution because the sites difer in terms of metal concentrations
in soils, soil properties, and/or exposure (diet). Biota-to-soil accumulation factors (BSAFs)41, i.e. the ratio of TM
concentrations in organisms to TM concentrations in soils, can be used to compare TM transfer. In the present
study, the BSAF for Pb at the most contaminated Morvan site (M2, median Pb concentration in soils of 1115) is
0.0008, approximately three times lower than the value measured (0.0029) at a Metaleurop Nord site, which presented a similar Pb concentration in soils (median Pb concentration in soils of 1357)40. his lower value suggests
less Pb transfer in the present study, which may indicate lower availability of this metal in soils afected by ancient
mining contamination, as suggested by Camizuli et al.42.
Once a pollutant has been taken up by an organism, toxic efects will occur only if various defence mechanisms
are overcome. In this study, Cd and Pb concentrations in wood mouse kidneys are below the Lowest Observed
Adverse Efect Levels (LOAELs), as deined by Shore and Douben43,44 (Fig. 3b), suggesting that toxic efects are
unlikely to occur. However, we found a signiicant negative relationship between SMI and kidney Pb concentrations. he SMI is a measure of body condition that is oten deined as a measure of the energetic (or nutritional)
state of an animal25. Even if the calculation and interpretation of such indices are still much debated24,27, these
indices are assumed to be related to itness. Here, we used the SMI, which has recently been shown to be a better
indicator of the relative size of energy reserves than condition indices based on ordinary least squares residuals
(see Peig and Green25, for details). Although several studies have shown a decline in the body condition of small
mammals from polluted sites compared to controls45,46, confounding factors like food availability, habitat quality
or other chemical elements may contribute to the complex relationships that are observed between pollution and
body indices28. herefore the negative relationship between SMI and Pb concentrations, observed in this study,
cannot simply be interpreted as implying a direct causal relationship. Other relationships that remain complex
to interpret are the positive correlation between SMI and Cd concentrations in kidneys, and the interactions
between essential element concentrations (Cu and Zn) and sex. hese complex relationships between the body
condition of free-ranging vertebrates and both essential and non-essential elements clearly require further investigation. Somatic indices (the relative size of internal organs), which may reveal oedema in individuals exposed
to toxic compounds46, did not exhibit any clear relationship with metals. Concerning FA, relationships between
the degree of developmental instability of populations and the level of the environmental and/or genetic stress to
which they were subjected have already been demonstrated10,47. In this study, FA10 was detected, but no relationship was found with the sampling site. his result is not in agreement with a study on aquatic ecosystems in the
Cévennes National Park, which showed that wild trout were afected by increasing developmental instability in
relation to mining contamination10.
Taken together these results show that several centuries ater mining and smelting activities have ceased, metals are still bioavailable to wildlife, with Pb, and to a lesser extent Cd, concentrations increasing in wood mouse
kidneys in relation to soil concentrations. Further studies should be undertaken to determine the precise TM
transfer mechanisms that occur in our study sites from the environment to animals (ingestion of soil, animal and
plant materials, inhalation of contaminated dust/soil particles, and/or direct transfer through dermal contact).
he BSAFs suggest, however, that bioavailability might be lower in soils afected by ancient mining than in soils
that have been more recently contaminated. Higher concentrations of Pb in the kidneys of individuals from the
most contaminated sites and the negative relationship between these concentrations and SMI raise the issue of the
present-day consequences of past anthropogenic activities on wildlife. Speciic biomarkers of exposure such as the
induction of metallothioneins, a protein involved in the homeostasis of essential elements and in the regulation of
non-essential ones40, could be envisaged in future studies. Biomarkers of toxic efects, for instance related to the
oxidative stress that exposure to trace metals may generate48 or to histological pathologies49, would also provide
further insight into the possible toxic efects that may occur in wildlife. Nature Parks are now protected areas and
are considered to be relatively pristine, but in the past, they oten were the setting for economic and industrial
activities. Ancient industrial activities might sometimes have vanished from collective memory but may still
represent a risk that deserves investigation.
Methods
Topsoil sampling and analysis.
Sampling units for topsoils were either 100 m × 100 m (M1, M2, C1) or
200 m × 200 m (M0, C0, C2) plots, because of logistical and time constraints (see Supplementary Fig. S1 for the
Morvan and Supplementary Fig. S2 for the Cévennes). Vegetation and litter were removed before topsoil sampling. For each plot, a composite sample of ∼1 kg, stored in a hermetic polyethylene bag, was prepared from 5
auger samples (0–20 cm depth), following a 20 m cross-shaped pattern. In the laboratory, samples were air-dried,
sieved to 2 mm, and carefully quartered. Subsamples of the 261 topsoils were inely ground in an acid-cleaned
agate mortar for elemental analyses. Concentrations of Cd, Cu, Pb, and Zn were measured by inductively coupled
SCIENTIFIC REPORTS | (2018) 8:3436 | DOI:
.
/s
-
-
-
7
www.nature.com/scientificreports/
plasma atomic emission spectroscopy (ICP-AES) ater pseudo-total aqua regia digestion at Actlabs (Ontario,
Canada). his chemical method was chosen because we targeted anthropogenic pollution that is easily extractable, and thus bioavailable to wildlife. Analytical quality control was doubly checked (i) by Actlabs measuring
18 replicates, 8 blanks and several certiied reference materials (CRMs) and (ii) by inserting another 25 duplicates and JSD-1, JSD-2, BCSS-1 and PACS-1 CRMs (stream, estuarine, and harbour sediments, respectively) as
blind samples. he Actlabs protocol set the limits of detection (LODs) at 0.5 mg·kg−1 for Cd, 1 mg·kg−1 for Cu,
2 mg·kg−1 for Pb and 2 mg·kg−1 for Zn (see Supplementary Tables S8 and S9 for details).
Small mammal sampling and analysis.
Small mammal sampling was conducted on 10 plots of 100 m
× 100 m at each site (Supplementary Figs S1 and S2). hese plots were randomly chosen for the two reference sites (M0 and C0) and at the location of anthropogenic activities for the contaminated sites. Wood mice
were trapped between mid-September and mid-October 2010. Sampling authorisations were obtained from the
DREAL Bourgogne (French regional territory agency in charge) and from the Cévennes National Park. For each
of the 10 selected plots, a line of 25 baited traps was set with alternating INRA (door-) and snap-traps, spaced 4 m
apart. An extra chamber was added to the classical INRA trap to increase the survival of trapped animals. Traps
were set for 3 to 5 consecutive days to ensure an adequate number of samples and were checked and rebaited
each morning. he wood mice caught alive were immediately sacriiced by cervical dislocation in accordance
with relevant guidelines and regulations50,51 and frozen as soon as possible ater their capture. hey were stored
at −20 °C until dissection in the laboratory. All small mammals captured were determined at the species level
by molecular analysis (sequencing of the cytochrome b gene) of a tissue sample performed by a service provider (ADNid laboratory). Body wet mass was used as an estimator of age45,52,53. Combined with reproductive
status, three age categories were constructed: juvenile (J), subadult (SA), and adult (A), as in Peig and Green26
(Supplementary Table S10). For all specimens body mass was measured to the nearest 0.01 g and body length to
the nearest 0.01 mm. Livers and kidneys were dried to constant mass and weighed to the nearest 0.001 g. Kidneys
were inely ground in an acid-cleaned agate mortar. Concentrations of Cd, Cu, and Zn for the kidney samples
(Apodemus sylvaticus, n = 157) were measured by ICP-AES with ultrasonic nebulisation for Cd, while Pb concentrations were measured by ICP-MS, both ater total aqua regia digestion. Analytical quality was veriied using
blanks, CRMs (BCR 185 R, bovine liver; NIST 1547, peach leaves; DOLT-4, dogish liver; DORM-3, ish protein)
and duplicates (see Supplementary Tables S11 and S12 for details).
Ethics statement. he experiments were performed in 2010, i.e. before the application in France of the
DIRECTIVE 2010/63/EU OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL of 22 September
2010 on the protection of animals used for scientiic purposes. his European Directive became applicable in
2013, through the “Décret No. 2013-118 du 1er février 2013 relatif à la protection des animaux utilisés à des ins
scientiiques”. Before 2013, the capture of non-protected free-ranging rodent species immediately followed by
their sacriice was not considered to be an experiment on live animals and thus did not require protocol approval
by an ethical committee. However, as stated above, care was taken to apply euthanasia protocols appropriate for
small rodents in the ield, and sampling authorizations were obtained from the appropriate administrative bodies.
Body condition and somatic indices.
Body condition was assessed by the scaled mass index (SMI), and
somatic indices were estimated using standard major axis (SMA) regression of ln-mass on ln-length as recommended by Peig and Green25,26. As the slope of this regression bSMA did not difer signiicantly between sites, it
was estimated on the entire dataset excluding pregnant females for SMI (n = 154), and on the dataset excluding
outliers for scaled somatic indices (n = 155). he SMA regression consists of estimating the predicted body mass
(SMI) or the predicted organ mass (SLI for the liver, SKI for the kidneys) for each individual i when body length
is standardised. Calculations for SMI follow the equation:
SMIi = mi ×
L 0bSMA
Li
where mi is the body mass and Li the body length of the individual i, bSMA is the slope of the regression of ln-body
mass on ln-body length and L0 the arithmetic mean of body length for the population.
he scaled liver index SLIi and scaled kidney index SKIi values were similarly computed using organ mass
instead of body mass. In this study, the bSMA values were 2.90 (95% conidence interval: 2.62–3.20) for SMI, 3.54
(95% conidence interval: 3.10–4.05) for SLI, and 2.91 (95% conidence interval: 2.55–3.31) for SKI. According
to Peig and Green (2009, 2010), the bSMA value for SMI usually lies between 2.5 and 3.2, which can be used as a
guideline to identify reliable estimates of the allometric exponent in mammals28.
Weighted TM concentrations in topsoils.
To account for the mobility of the wood mouse (home range
of 2500 m²)54, a weighted TM concentration of the corresponding topsoil was calculated for each individual.
his weighted concentration was calculated as the average of the TM concentration in the topsoil of the 8 plots
surrounding the plot where the wood mouse was captured, with the capture plot being weighted twice. hese
weighted TM concentrations were used in the statistical models.
he Quantum GIS free sotware55 was used for mapping.
Statistical treatment and regression analysis used the smart, lmodel2, stats, and pgirmess packages from the R
sotware56.
Data processing and statistical treatment.
SCIENTIFIC REPORTS | (2018) 8:3436 | DOI:
.
/s
-
-
-
8
www.nature.com/scientificreports/
Topsoils. he non-parametric Kruskall-Wallis test was used to assess the diferences in topsoil TM concentrations between sites in each park because the residues were not normally distributed. When the Kruskall-Wallis
test was signiicant (p < 0.05), pairwise comparisons were made using Steel-Dwass post-hoc tests57.
TM in wood mice. A parametric ANOVA test was used to assess the diferences in TM concentrations in wood
mouse kidneys between sites in each park. When the ANOVA test was signiicant (p < 0.05), pairwise comparisons were made using Tukey’s HSD test. Linear models were used to investigate the relationships between TM
concentrations in kidneys and explanatory variables. Multivariate models were built with biological variables
(mass and sex; age and size were dropped because of their relation to mass), geographical variable (site), and corresponding weighted TM concentrations in soils as explanatory variables. Biologically meaningful interactions
(soil concentrations × sex and mass × sex) were also taken into account. As the range of TM concentration values
in relation to sites did not always overlap, testing the interaction site × concentration in soil was not allowed58.
Statistical treatments for Cd were only performed with the M1, M2, C1 sites, as M0, C0 and M2 presented too
many censored data for Cd in soils. he best-it model was selected using a backward stepwise regression. he
drop1{stats} function combined with an F test was used; this method corresponds to a type II ANOVA. For each
step, the explanatory variable with the largest p-value was deleted until the inal step, giving the best-it model,
where all p-values were below the α = 0.05 level (Supplementary Table S13 for model selection). ANOVA tests
were performed on the selected models. Model normality was examined by looking at plots of the standardised
residuals versus leverage. Model outputs were satisfactory.
Body condition and somatic indices. Backward stepwise regression was also applied to determine whether body
condition and somatic indices varied with geography, individual characteristics, or levels of individual contamination. Multivariate models were built with biological variables (only sex, as we considered SMIs), a geographical variable (site), and the four TM concentrations in kidneys as explanatory variables. Biologically meaningful
interactions (kidney TM concentrations × sex) were also taken into account (Supplementary Table S14 for model
selection).
Fluctuating asymmetry. In this study, six bilateral morphometric traits were selected for luctuating asymmetry
(FA) assessment: length and width of the three lower molars (Supplementary Fig. S5). All measurements were
performed twice to control for measurement error. he FA consists of subtle random variations between each
side (right, R and let, L) of bilateral traits that are supposed to be perfectly identical. hese variations relect the
inability of individuals to correct errors occurring during early development. It has been shown that both genetic
and environmental stresses decrease developmental stability59. he FA has been proposed as a useful tool to assess
individual quality30. In fact, three types of biological asymmetry can be distinguished on the basis of the analysis
of right minus let (R − L) frequency distribution: directional asymmetry (DA), antisymmetry (AS) and FA. he
DA shows a pattern of normal R − L variation distributed about a mean point that is signiicantly diferent from
zero. he AS shows a pattern of R − L variation distributed about a mean point of zero, but with a frequency
distribution departing from normality30. he FA shows a normal distribution of R − L values with a mean of
zero. Among these three asymmetries, only FA provides an estimation of developmental instability. he presence
of DA and AS, together with measurement error, can bias FA estimation. A series of preliminary analyses was
performed for each study trait as recommended by Palmer29. Individual FA levels were then estimated for each
trait using absolute asymmetry. Linear models were computed to assess the relationship between |R − L| values
and kidney TM concentrations. Population FA levels were estimated for each trait using FA10, i.e., between-sides
variance corrected for measurement error, obtained from the results of linear mixed models with sides (ixed) ×
individuals (random) (see Palmer29, for details). Fisher tests were then performed for each trait studied to explore
inter-site diferences.
Data availability.
All data generated or analysed during the current study are included in this published
article and the Supplementary Information ile.
References
1. Hauptmann, A. he archaeometallurgy of copper: evidence from Faynan, Jordan. Natural science in archaeology (Springer, Berlin,
Germany, 2007).
2. Radivojević, M. et al. On the origins of extractive metallurgy: new evidence from Europe. Journal of Archaeological Science 37,
2775–2787 (2010).
3. Tylecote, R. F. A history of metallurgy (Institute of Materials, London, UK, 1992).
4. Craddock, P. T. Early metal mining and production (Edinburgh University Press, Edinburgh, UK, 1995).
5. Nriagu, J. O. A history of global metal pollution. Science 272, 223–224 (1996).
6. Rosman, K. J. R., Chisholm, W., Hong, S., Candelone, J.-P. & Boutron, C. F. Lead from Carthaginian and Roman Spanish Mines
Isotopically Identiied in Greenland Ice Dated from 600 B.C. to 300 A.D. Environmental Science & Technology 31, 3413–3416 (1997).
7. Lucretius. De natura rerum. A. Ernout (ed.), tome 2, books 4-6 (De la Nature, Les Belles Lettres, Paris, France, 1971).
8. Vitruvius. De Architectura. L. Callebat (ed.), book 8 (De l’architecture, Les Belles Lettres, Paris, France, 1973).
9. Pliny the Elder. Naturalis Historia,. A. Ernout (ed.), book 33 (Histoire naturelle, Les Belles Lettres, Paris, France, 1983).
10. Monna, F. et al. Wild Brown Trout Afected by Historical Mining in the Cévennes National Park, France. Environmental Science &
Technology 45, 6823–6830 (2011).
11. Camizuli, E. et al. Impact of trace metals from past mining on the aquatic ecosystem: A multi-proxy approach in the Morvan
(France). Environmental Research 134, 410–419 (2014).
12. Didier, C. Postmining Management in France: Situation and Perspectives. Risk Analysis 29, 1347–1354 (2009).
13. Monna, F. et al. History and environmental impact of mining activity in Celtic Aeduan territory recorded in a peat bog (Morvan,
France). Environmental Science and Technology 38, 665–673 (2004).
14. Joufroy-Bapicot, I. et al. Environmental impact of early palaeometallurgy: pollen and geochemical analysis. Vegetation History and
Archaeobotany 16, 251–258 (2007).
SCIENTIFIC REPORTS | (2018) 8:3436 | DOI:
.
/s
-
-
-
9
www.nature.com/scientificreports/
15. Forel, B. et al. Historical mining and smelting in the Vosges Mountains (France) recorded in two ombrotrophic peat bogs. Journal of
Geochemical Exploration 107, 9–20 (2010).
16. Baron, S., Carignan, J., Laurent, S. & Ploquin, A. Medieval lead making on Mont-Lozère Massif (Cévennes-France): Tracing ore
sources using Pb isotopes. Applied Geochemistry 21, 241–252 (2006).
17. Cauuet, B., Mossière, B., Tamas, C. & Vialaron, C. La minière de la Pâture des Grangerands. In Guichard, V. (ed.) Recherches sur le
Mont Beuvray et son environnement - Deuxième rapport intermédiaire du programme triennal 2009–2011, 37–61 (Centre
archéologique européen, Bibracte, 2010).
18. Allée, P., Paradis, S., Boumédiène, F. & Rouaud, R. L’exploitation médiévale du plomb argentifère sur le mont Lozère. ArchéoSciences
34, 177–186 (2011).
19. Baron, S., Carignan, J. & Ploquin, A. Dispersion of Heavy Metals (Metalloids) in Soils from 800-Year-Old Pollution (Mont-Lozère,
France). Environmental Science and Technology 40, 5319–5326 (2006).
20. Peijnenburg, W. et al. Implementation of bioavailability in standard setting and risk assessment? Journal of Soils and Sediments 2,
169–173 (2002).
21. Lanno, R., Wells, J., Conder, J., Bradham, K. & Basta, N. he bioavailability of chemicals in soil for earthworms. Ecotoxicology and
Environmental Safety 57, 39–47 (2004).
22. van Gestel, C. A. Physico-chemical and biological parameters determine metal bioavailability in soils. Science of The Total
Environment 406, 385–395 (2008).
23. Lock, K. & Janssen, C. R. Influence of Aging on Metal Availability in Soils. In Ware, G. W. (ed.) Reviews of Environmental
Contamination and Toxicology, 178, 1–21 (Springer New York, 2003).
24. Schulte-Hostedde, A. I., Zinner, B., Millar, J. S. & Hickling, G. J. Restitution of mass-size residuals: validating body condition indices.
Ecology 86, 155–163 (2005).
25. Peig, J. & Green, A. J. New perspectives for estimating body condition from mass/length data: the scaled mass index as an alternative
method. Oikos 118, 1883–1891 (2009).
26. Peig, J. & Green, A. J. The paradigm of body condition: a critical reappraisal of current methods based on mass and length.
Functional Ecology 24, 1323–1332 (2010).
27. Green, A. J. Mass/length residuals: measures of body condition or generators of spurious results? Ecology 82, 1473–1483 (2001).
28. Tête, N. et al. Can Body Condition and Somatic Indices be Used to Evaluate Metal-Induced Stress in Wild Small Mammals? PLOS
ONE 8, e66399 (2013).
29. Palmer, A. R. Fluctuating asymmetry analyses: a primer. In Markow, T. A. (ed.) Developmental instability, its origins and evolutionary
implications., 335–364 (Kluwer Academic Publishers, Dordrecht, Netherlands, 1994).
30. Palmer, A. R. & Strobeck, C. Fluctuating asymmetry analyses revisited. In Polak, M. (ed.) Developmental instability: causes and
consequences, 279–319 (Oxford University Press, New York, USA, 2003).
31. van Lynden, G., Mantel, S. & van Oostrum, A. Guiding principles for the quantitative assessment of soil degradation - with a focus
on salinization, nutrient decline and soil pollution. Tech. Rep., Food and Agriculture Organization of the United Nations, Rome,
Italy (2004).
32. Kabata-Pendias, A. Trace elements in soils and plants (CRC Press, Taylor & Francis Group, Boca Raton, USA, 2011), 4th edn.
33. Douay, F. et al. Contamination of woody habitat soils around a former lead smelter in the North of France. Science of he Total
Environment 407, 5564–5577 (2009).
34. Fritsch, C. et al. Spatial distribution of metals in smelter-impacted soils of woody habitats: Inluence of landscape and soil properties,
and risk for wildlife. Chemosphere 81, 141–155 (2010).
35. Branford, D., Fowler, D. & Moghaddam, M. V. Study of Aerosol Deposition at a Wind Exposed Forest Edge Using 210Pb and 137Cs
Soil Inventories. Water, Air, and Soil Pollution 157, 107–116 (2004).
36. Peijnenburg, W. & Jager, T. Monitoring approaches to assess bioaccessibility and bioavailability of metals: Matrix issues. Ecotoxicology
and Environmental Safety 56, 63–77 (2003).
37. Eisler, R. Handbook of chemical risk assessment: Health Hazards to Humans, Plants, and Animals - Volume 1 Metals (Lewis
Publishers, Boca Raton, USA, 2000).
38. Beernaert, J., Scheirs, J., Leirs, H., Blust, R. & Verhagen, R. Non-destructive pollution exposure assessment by means of wood mice
hair. Environmental Pollution 145, 443–451 (2007).
39. Rogival, D., Scheirs, J. & Blust, R. Transfer and accumulation of metals in a soil–diet–wood mouse food chain along a metal pollution
gradient. Environmental Pollution 145, 516–528 (2007).
40. Fritsch, C. et al. Responses of wild small mammals to a pollution gradient: Host factors inluence metal and metallothionein levels.
Environmental Pollution 158, 827–840 (2010).
41. Veltman, K., Huijbregts, M. A. J. & Hendriks, A. J. Cadmium bioaccumulation factors for terrestrial species: Application of the
mechanistic bioaccumulation model OMEGA to explain ield data. Science of he Total Environment 406, 413–418 (2008).
42. Camizuli, E. et al. Impact of historical mining assessed in soils by kinetic extraction and lead isotopic ratios. Science of he Total
Environment 472, 425–436 (2014).
43. Shore, R. F. & Douben, P. E. T. Predicting Ecotoxicological Impacts of Environmental Contaminants on Terrestrial Small Mammals.
In Ware, G. W. (ed.) Reviews of Environmental Contamination and Toxicology, 134, 49–89 (Springer New York, 1994).
44. Shore, R. F. & Douben, P. E. he ecotoxicological signiicance of cadmium intake and residues in terrestrial small mammals.
Ecotoxicology and Environmental Safety 29, 101–112 (1994).
45. Nunes, A., da Luz Mathias, M. & Crespo, A. Morphological and haematological parameters in the Algerian mouse (Mus spretus)
inhabiting an area contaminated with heavy metals. Environmental Pollution 113, 87–93 (2001).
46. Sánchez-Chardi, A., Peñarroja-Matutano, C., Ribeiro, C. A. O. & Nadal, J. Bioaccumulation of metals and efects of a landill in small
mammals. Part II. he wood mouse. Apodemus sylvaticus. Chemosphere 70, 101–109 (2007).
47. Marchand, H., Paillat, G., Montuire, S. & Butet, A. Fluctuating asymmetry in bank vole populations (Rodentia, Arvicolinae) relects
stress caused by landscape fragmentation in the Mont-Saint-Michel Bay. Biological Journal of the Linnean Society 80, 37–44 (2003).
48. Isaksson, C. Pollution and Its Impact on Wild Animals: A Meta-Analysis on Oxidative Stress. EcoHealth 7, 342–350 (2010).
49. Tête, N., Durfort, M., Riefel, D., Scheiler, R. & Sánchez-Chardi, A. Histopathology related to cadmium and lead bioaccumulation
in chronically exposed wood mice, Apodemus sylvaticus, around a former smelter. Science of he Total Environment 481, 167–177
(2014).
50. Leary, S. et al. AVMA Guidelines for the Euthanasia of Animals. Tech. Rep., American Veterinary Medical Association, Schaumburg
(2007).
51. Sikes, R. S. & Gannon, W. L. Guidelines of the American Society of Mammalogists for the use of wild mammals in research. Journal
of Mammalogy 92, 235–253 (2011).
52. Erry, B. V., Macnair, M. R., Meharg, A. A. & Shore, R. F. Seasonal Variation in Dietary and Body Organ Arsenic Concentrations in
Wood Mice Apodemus sylvaticus and Bank Voles Clethrionomys glareolus. Bulletin of Environmental Contamination and Toxicology
63, 567–574 (1999).
53. Milton, A., Cooke, J. A. & Johnson, M. S. Accumulation of Lead, Zinc, and Cadmium in a Wild Population of Clethrionomys
glareolus from an Abandoned Lead Mine. Archives of Environmental Contamination and Toxicology 44, 0405–0411 (2003).
54. Wijnhoven, S., Velde, G. V. D., Leuven, R. S. E. W. & Smits, A. J. M. Flooding ecology of voles, mice and shrews: the importance of
geomorphological and vegetational heterogeneity in river loodplains. Acta heriologica 50, 453–472 (2005).
SCIENTIFIC REPORTS | (2018) 8:3436 | DOI:
.
/s
-
-
-
10
www.nature.com/scientificreports/
55. Quantum GIS Development Team. Quantum GIS Geographic Information System. Open Source Geospatial Foundation Project.
http://qgis.osgeo.org (2010).
56. R Development Core Team. R: A language and environment for statistical computing. (R Foundation for Statistical Computing,
Vienna, Austria, 2008).
57. Critchlow, D. E. & Fligner, M. A. On distribution-free multiple comparisons in the one-way analysis of variance. Communications
in statistics. heory and methods 20, 127–139 (1991).
58. Quinn, G. P. & Keough, M. J. Experimental design and data analysis for biologists (Cambridge University Press, New-York, USA,
2002).
59. Polak, M. (ed.) Developmental instability: causes and consequences (Oxford University Press, New-York, USA, 2003).
Acknowledgements
We are grateful to the FEDER (No. 34328), the Regional Council of Burgundy (No. 2010-9201AAO050S04040),
the University of Burgundy (No. 2010-BQR-068), the Cévennes National Park and Bibracte for funds. The
Morvan Regional Nature Park and the Cévennes National Park are thanked for their constant support. he French
Ministry of Research is thanked for the Ph.D. grant of Estelle Camizuli. We wish to thank Clémentine Fritsch,
Nicolas Tête, and Patrick Giraudoux for their valuable help and Patrick Giraudoux speciically for developing the
pgirmess package.
Author Contributions
E.C., F.M., P.A. and R.S. planned and designed the study. Soil samples and small mammals were collected by C.G.,
E.C., F.M., G.H., P.A. and R.S. C.L. and G.D. prepared all the samples for geochemical analysis. E.C. and R.L.
performed the ICP analysis of kidney tissues. E.C., F.M., P.A., R.L., R.S. and S.G. designed statistical treatments
and interpreted the data. E.C., R.S., F.M., S.G. and P.A. wrote the irst drat of the manuscript, and all the authors
discussed the results and commented on the manuscript.
Additional Information
Supplementary information accompanies this paper at https://doi.org/10.1038/s41598-018-20983-0.
Competing Interests: he authors declare no competing interests.
Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and
institutional ailiations.
Open Access This article is licensed under a Creative Commons Attribution 4.0 International
License, which permits use, sharing, adaptation, distribution and reproduction in any medium or
format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. he images or other third party material in this
article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the
material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the
copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
© he Author(s) 2018
SCIENTIFIC REPORTS | (2018) 8:3436 | DOI:
.
/s
-
-
-
11