Plant and Soil 260: 1–17, 2004.© 2004 Kluwer Academic Publishers. Printed in the Netherlands.

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Changes in water extractable metals, pH and organic carbonconcentrations at the soil-root interface of forested soils

Veronique Seguin1,3, Christian Gagnon2 & François Courchesne1

1Departement de geographie, Universite de Montreal, C.P. 6128, succ. Centre-ville, Montreal, Quebec, Canada,H3C 3J7. 2Centre Saint-Laurent, Environment Canada, 105, McGill street, 7th floor, Montreal, Quebec, Canada,H2Y 2E7. 3Corresponding author∗

Received 5 August 2002. Accepted in revised form 26 June 2003

Key words: metals, pH, rhizosphere, solid phase organic carbon, water extraction, water extractable organic carbon

Abstract

Soluble metals are of nutritional and ecotoxicological interest as they are the most readily available form to thebiota. Metal solubility in soils is mostly controlled by pH and the organic matter content. The rhizosphere isgenerally considered as an environment enriched in organic matter and often more acidic (depending on nutritionalstatus of the plant) than the bulk soil. Yet, there is a lack of consensus on the distribution of metals at the soil-root interface. Consequently, the specific objectives of this paper are to compare the chemical properties and thewater extractable metal concentrations of the rhizosphere and the bulk soil of forest soil (1) along a gradient insoil contamination and (2) under different tree species. Two study areas were used: (1) Rouyn-Noranda (Canada)where samples were collected along a gradient in metal contamination at a distance of 0.5, 2 and 8 km downwindfrom a copper smelter; (2) Saint-Hippolyte (Canada) where the effect of three tree species (Abies balsamea, Acersaccharum and Betula papyrifera) was studied. In the field, the rhizosphere was operationally defined as the soiladhering to the roots after agitation, soil falling from the roots and the rest of the soil composing the bulk soil. Oncein laboratory, a second agitation was performed to separate the rhizosphere into an inner and an outer component.Water extractable metal concentrations (Al, Ca, Cd, Co, Cr, Cu, Fe, Li, Mg, Mn, Ni, Pb and Zn) were quantifiedeither with an ICP-AES or a GFAAS. Measurements of pH, electrical conductivity (EC), water-extractable organiccarbon (WEOC) and solid phase organic carbon (SPOC) were performed. Results systematically indicate that EC,WEOC and SPOC follow the sequence inner rhizosphere > outer rhizosphere > bulk soil. The pH is alwayslower in the inner rhizosphere than in the bulk soil, while the outer rhizosphere frequently shows an inconstantbehaviour. The results also show a clear gradient following inner rhizosphere > outer rhizosphere > bulk soil forwater extractable Al, Ca, Cd, Cu, Fe, Mg, Mn, Ni, Pb and Zn. Li, Co and Cr levels were below method detectionlimit in all cases. WEOC seems to be the main variable related to the water-extractable metals concentrations. Thegradient in metal contamination at Rouyn-Noranda was not as expected in the water extracts with the site at 2 kmfrequently presenting higher metal concentrations than the sites at 0.5 and 8 km. Moreover, a tree species effect didnot clearly immerge for any of the chemical properties studied. However, the water extractable Ca concentrationswere higher in the soil under Acer saccharum. The effects of the metal gradient and of the tree species may bemore pronounced if stronger extractants are used. The addition of an outer rhizosphere component is useful as itsbehaviour is not consistently intermediate between the inner rhizosphere and bulk soil.

Abbreviations: DOC – dissolved organic carbon; EC – electrical conductivity; MDL – method detection limit;SPOC – solid phase organic carbon; WEOC – water extractable organic carbon

∗ FAX No: 514-343-8008.E-mail: veronique.seguin@umontreal.ca

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Introduction

Since 1904, when Hiltner first defined the rhizosphereconcept, many contrasting characteristics between therhizosphere and the bulk soil have been documented.Usually, the rhizosphere is viewed as an acidified soilcomponent compared to the bulk soil, although alka-linization can be observed depending on the nutritionalstatus of the plant (Nye, 1981). Despite the gener-ally lower pH of the rhizosphere, the soil under theinfluence of roots contains more bacteria and fungithan the remainder of the soil (Marschner, 1995). Thisabundance is due to the larger amount of readily avail-able organic compounds derived from roots such asrhizodeposition (Grayston et al., 1996). The acidity,the organic matter content and the greater microbialactivity could explain the accelerated dissolution ofminerals observed in the rhizosphere, particularly foreasily weathered minerals (Courchesne and Gobran,1997).

Metal solubility and the mechanisms affectingtheir solubility can have crucial impacts on terrestrialand aquatic ecosystems. Most metals are essential nu-trients to plant growth, thus of practical relevance tothe productivity of agricultural and forest ecosystems.Some other elements are present in phytotoxic con-centrations or do not have known physiological rolesin plants, thus raising ecotoxicological concerns (Fer-gusson, 1990; McBride, 1994). In the same way,the capacity of plants to absorb metals is useful forphytoremediation techniques where plants are used todecontaminate soil (Lombi et al., 2001).

It is well established in the literature that pH andorganic matter content are two key factors influencingthe concentrations of metals. For example, the chem-ical activity of most metals increases as the pH ofthe solution decreases (Lindsay, 1979). Organic mat-ter, both in the dissolved and solid states, has a largespecific surface area and an elevated negative charge,thus attracting metals. Many strong bonds can thenbe established to bind metals to the organic matter(McBride, 1994).

Because of its generally higher acidity combined toa large organic matter content, the rhizosphere shoulddiffer in metal concentrations and speciation com-pared to other soil components (Marschner and Röm-held, 1996). Surprisingly, the rhizosphere is mostlypresented as an environment that is impoverished inmetals (Wang et al., 2001), although not all metalshave the same behaviour (Youssef and Chino, 1989).As such, Sarong et al.. (1989) showed there were

lower concentrations of Zn in water extract of therhizosphere relative to the bulk soil. On the otherhand, some studies, particularly those dealing withfield samples, showed the contrary. For instance, Go-bran and Clegg (1996) as well as Courchesne et al.(2001) observed that metal concentrations in differ-ent fractions were higher in the rhizosphere. Also,Merckx et al. (1986) suggested that there were moremetals complexed with organic matter in the rhizo-sphere than in the bulk soil. As such, there is currentlyno consensus concerning the impact of roots and as-sociated microorganisms on metal concentrations andspeciation.

Soluble metals are of particular interest, as theyconstitute the most readily available chemical form toplants. In turn, knowledge on the influence that rootscan have on the solubility of metals is essential tobetter assess the bioavailability of metals. It is con-sidered that plants are mainly taking up their nutrientsfrom the soil solution (Linehan et al., 1985). Yet, rootscan impact on other forms of elements, especially sowhenever a deficiency develops. For example, it wasshown by Hinsinger and Gilkes (1997) that roots areable to dissolve phosphate rocks when these rocksrepresent the sole source of P and Ca in the soil sys-tem. Indeed, when lacking Fe or other metals, certainplants can acidify the surrounding soil and increasethe reducing capacity of their roots. Also, some plantscan release phytosiderophores to access less readilyavailable sources of metal nutrients (Marschner andRömheld, 1996).

Despite the abundance of recent studies on therhizosphere, there are still some important knowledgegaps. For instance, most investigations are performedin laboratory and thus cannot reproduce adequatelysome key environmental conditions. Moreover, themajority of these studies are done on cultivated spe-cies that are usually herbs or shrubs while only a fewresearches look at tree species (e.g. Courchesne etal., 2001; Gobran and Clegg, 1996). Also, the solidphase fractionation of metals in the rhizosphere andthe mechanisms that are involved, notably the roleof organic matter, are poorly known (Gobran et al.,1998).

Consequently, the specific objectives of this paperare to compare the chemical properties and the wa-ter extractable metal concentrations of the solid phasebetween the rhizosphere and the bulk components offorest soils (1) along a gradient in soil contaminationand (2) under different tree species. The environmentalgradients are selected because previous work showed

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that environmental factors can affect the rhizosphereproperties (e.g. Gobran et al., 1998). It is thus expectedthat different metal loadings in a soil could impact thedynamic of the soil-root interface. Moreover, differ-ent plant species are known to produce organic mattercompounds that vary in abundance and nature as afunction of species (Grayston et al., 1996). This couldmodify metal fractionation in the rhizosphere.

Materials and methods

Study sites

Two study areas were used for this research: (1)Rouyn-Noranda to sample along a gradient in soil con-tamination by metals and (2) Saint-Hippolyte to studysoils from forest stands dominated by different treespecies.

Rouyn-Noranda is located about 600 km north-west of Montréal, Canada (48◦ 14′ N, 79◦ 01′ W).Three sampling sites located at 0.5, 2 and 8 km down-wind of the Horne copper smelter were selected. Thesoil samples were all taken under trembling aspen(Populus tremuloides Michx) of similar ages (<30years old) growing in post-glacial lake sediments ofclay texture. The soils are classified as Luvisols bythe Canadian System of Soil Classification (Soil Clas-sification Working Group, 1998). Site characteristics(e.g. climate, parent material, topography) were con-stant at each site such that soil contamination throughatmospheric depositions represents the main variable.

The gradient in metal contamination away fromRouyn-Noranda induced by the operation of the Hornecopper smelter since 1927 has been extensively char-acterized. In the same direction as used in the currentstudy, the contamination in Cd, Cu, Ni, Pb and Zn at adepth of 15–30 cm is significantly detectable at 2 kmaway from the factory in mineral soils, but not at adistance of 5 km or more (Dumontet et al., 1992). Inorganic soils, the contamination can be detected alongthe same sampling axis at a greater distance from thesmelter (more than 24.5 km) and deeper in the soilprofile (more than 1 m) (Dumontet et al., 1990). Assuch, a gradient in pH and in metal concentrations wasexpected for the three sites at Rouyn-Noranda with thesite at 0.5 km having the highest metal concentrations.

The Saint-Hippolyte site is located 55 km northof Montréal, Canada (45◦56’N, 74◦01’W), in the Sta-tion de biologie des Laurentides of the Université deMontréal. Soil samples were taken under balsam fir

(Abies balsamea (L.) Mill), sugar maple (Acer sac-charum Marsh) and white birch (Betula papyriferaMarsh) stands with trees in each stands being rel-atively even-aged (Table 1). These tree species arecharacteristic of the forests of Southern Quebec. Themain environmental factors (e.g. climate, parent ma-terial, topography) were similar at each sampling site.The soils are considered as Podzols according to theCanadian System of Soil Classification (Soil Classific-ation Working Group, 1998). They formed in a sandyloam anorthosic till.

It must be taken into account that tree character-istics are not perfectly constant across species. Thisis particularly unfavourable to Acer saccharum, whichis systematically younger, the tree with the narrowestdiameter at breast height and has only an intermedi-ate height (Table 1). At the beginning of the previouscentury, the forest was affected by commercial wood-cuts and by fire in the middle of the 1920 (Bélanger etal., 2002). Because Acer saccharum generally followsBetula papyrifera in vegetation succession after eventssuch as fire and cuts, the former is usually younger.Note that for field replicate B of Acer saccharum, twotrees instead of one were necessary to collect enoughrhizosphere material for laboratory analysis.

Sample collection and soil component separation

At each of the sampling sites (i.e. three in Rouyn-Noranda, three in Saint-Hippolyte), three trees werecarefully uprooted. They constituted the replicatesused to assess field variability. Both rhizosphere andbulk samples originated from the upper B horizon (15–20 cm under the organic-mineral interface) to avoidthe direct influence of the organic horizons and toprovide enough roots to collect a sufficient volume ofrhizosphere soil. Roots averaging 0.5 mm to 1 cm indiameter were collected.

An initial separation between rhizosphere and bulkmaterials was performed at the sampling site. Theroots sampled were hand-shaken and the soil adheringto the roots was considered as rhizosphere material.The soil falling from the roots and the remainder of thesoil collected were regarded as bulk soil (Rollwagenand Zasoski, 1988). All samples were stored in plasticbags. Once in the laboratory, a second hand-separationwas achieved again by shaking the roots. The soil stilladhering to the roots after the second shaking wasregarded as the inner rhizosphere whereas the fallenmaterial was defined as the outer rhizosphere. During

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Table 1. Selected characteristics of the tree species at Saint-Hippolyte. Values represent the av-erage of the three trees sampled per species (four trees in the case of Acer saccharum). Standarddeviations are in parenthesis

Tree species Abies balsamea Acer saccharum Betula papyriferaa

Age (yr) 51.3 (5.5) 32.5 (4.7) 49.0 (8.7)

Height (m) 8.3 (3.0) 8.9 (1.2) 10.4 (1.7)

Diameter at breast height (cm) 23.0(3.3) 15.5 (2.7) 24.5 (6.1)

a Because the heart of one of the Betula papyrifera was affected by a disease, the average isslightly underestimated.

all these operations, contact with metallic tools wasavoided.

Because of soil volume constraints for chemicalanalyses, the inner rhizosphere samples from Saint-Hippolyte had to be pooled for each tree species toform a composite sample. However, instead of creat-ing a composite sample where a third of the final massoriginates from the soil taken under each tree, the en-tire mass of soil collected under each tree is used. Asa result, the final inner rhizosphere samples of Saint-Hippolyte are constituted of a varying percentage ofsoil originating from the different trees of the samespecies. Tree triplicates represent respectively 34.2,25.3 and 40.5% in weight of the inner rhizosphere forAbies balsamea, 17.3, 19.2 and 63.5% in weight forAcer saccharum and 13.7, 52.9 and 33.3% in weightfor Betula papyrifera. This pooling explains the useof the same value for each of the inner rhizospherereplicates of Saint-Hippolyte (see Tables 2–4). Whenaverage values for a site are presented, the outer rhizo-sphere and the bulk soil values are weighted accordingto these percentages to ensure a comparison of thethree soil components in Saint-Hyppolyte.

All soil components (inner and outer rhizosphere,bulk soil) were air-dried and sieved at 0.5 mm(Grinsted et al., 1982). The 0.5 mm particle limitwas used to avoid excessive texture difference betweenthe three soil components as roots may influenceparticle size (Leyval and Berthelin, 1991). Root frag-ments were taken off using plastic tweezers and staticelectricity.

Water extraction method

To perform the water extraction, 3.5 g of soil wasweighted in 50 mL centrifuge tubes and 35 mL ofultra-pure water was added to the soil (soil:solutionratio 1:10). The soil suspension was shaken for 2 hon an end-over-end mixer. Afterwards, the suspen-sion was centrifuged at 1400 g for 15 min and a 10

mL volume of the unfiltered solution was used for pHand electrical conductivity analyses. The remainingsolution was filtered using cellulose filters (OsmonicmicronSep mixed esters 0.45 µm) on a vacuum sys-tem. The water extracts were then acidified with 2%HNO3 and stored at 4 ◦C before metal analyses. Themetals present in the water extract are operationallydefined as water-soluble. They are considered as themetal fraction most readily available to the plants andcan be viewed as bioavailable (Linehan et al., 1985).

Chemical analyses

The pH and electrical conductivity (EC) of the water-extract, solid phase organic carbon (SPOC) and water-extractable organic carbon concentration (WEOC)were analysed in triplicates when sample mass al-lowed. Otherwise, analyses were duplicated.

EC and pH were measured on a 10 mL subsampleof the water extract. For pH, a combination pH elec-trode with calomel reference (Accumet) was used ona Fisher Accumet pH meter (825MP). EC was eval-uated using a Copenhagen radiometer electrode typeCDC 314 with a Copenhagen radiometer CDM 83conductivity meter.

SPOC was determined following a titration methodusing potassium dichromate and ferrous sulphate(modified from Walkley-Black) (Carter, 1993). Forthe WEOC measurements, a second water-extractionwas carried out using the same method. This water-extract was filtered as for metals but acidified with2% H2SO4. For each solution, the absorbance wasdetermined at 254 nm using a spectrophotometer. Inparallel, 26 representative samples of all soil com-ponents were analysed on a Shimadzu 5000 totalcarbon analyser. The WEOC was estimated with alinear regression established between the absorbancevalues and the total carbon concentrations (Moore,1985). The regression equation for Rouyn-Norandawas WEOC = 88.6∗absorbance + 21.9 (r = 0.87). For

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Table 2. Chemical properties of the three soil components at each site. Values in parenthesis are standard deviations calculated using methodtriplicates. Standard deviations are not given if soil mass was insufficient to perform all analyses and that analysis was performed only onceor in duplicate

pH electrical conductivity (µS cm−1) SPOCa (g kg−1) WEOCb (g kg−1)

Sitec inner outer bulk Stat.d inner outer bulk Stat. inner outer bulk Stat. inner outer bulk Stat.

rhizo. rhizo. rhizo. rhizo. rhizo. rhizo. rhizo. rhizo.

Rouyn-Noranda (soil contamination)RN 0.5 A 4.80 4.69 4.67 150 55.0 45.5 51.6 38.3 24.3 1.38 0.68 0.37

(0.02) (0.02) (0.05) (7.6) (2.2) (2.1) (1.0)

RN 0.5 B 4.55 4.51 4.60 165 69.6 43.3 62.1 42.1 29.0 1.61 0.98 0.39

(0.00) (0.01) (0.03) NS (1.5) (2.8) (0.1) ∗∗ (4.1) ∗∗ ∗∗RN 0.5 C 4.59 4.55 4.64 121 59.0 44.7 41.3 33.3 23.6 1.28 0.75 0.42

(0.02) (0.03) (0.04) (9.4) (2.2) (0.8)

RN 2 A 4.60 4.76 4.87 148 57.8 45.2 80.7 38.0 29.8 1.46 0.95 0.72

(0.01) (0.03) (1.8) (2.3) (8.8)

RN 2 B 4.57 4.69 4.84 ∗∗ 125 53.4 40.9 ∗∗ 59.8 26.8 19.5 ∗∗ 1.46 0.86 0.69 ∗∗(0.01) (0.02) (0.01) (1.0) (0.9) (2.9)

RN 2 C 4.68 4.78 4.97 146 61.3 37.6 58.7 36.4 20.6 1.66 1.04 0.78

(0.03) (0.03) (0.03) (8.5) (0.2) (0.5) (5.2)

RN 8 A 4.91 5.02 5.27 95.2 49.9 30.3 37.9 19.9 9.91 1.50 1.10 0.81

(0.02) (0.01) (0.03) (1.2) (0.5) (0.5)

RN 8 B 5.06 5.00 5.06 NS 102 57.8 46.0 ∗∗ 42.7 27.7 22.4 ∗∗ 1.49 1.21 0.88 ∗∗(0.02) (0.01) (0.02) (0.9) (0.7) (1.5)

RN 8 C 4.91 5.05 5.28 129 58.3 29.8 47.3 21.9 8.11 1.85 1.21 0.92

(0.01) (0.01) (0.04) (5.9) (5.3) (0.6)

Saint-Hippolyte (tree species)SH Ab A 4.87 4.81 4.97 99.0 46.0 33.3 118 68.9 56.1 0.99 0.53 0.37

(0.00) (0.05) (2.0) (1.5) (9.2)

SN Ab B 4.87 4.75 4.92 99.0 48.2 27.3 118 76.7 51.4 0.99 0.67 0.37

(0.01) (0.01) ∗ (1.2) (0.2) ∗∗ (9.2) (5.2) (4.3) ∗∗ ∗∗SH Ab C 4.87 4.89 4.99 99.0 47.4 28.5 118 91.4 81.1 0.99 0.59 0.37

(0.01) (0.01 (1.3) (0.9) (9.2) (5.7) (6.2)

SN As A 5.16 5.15 5.31 134 60.4 27.4 106 82.9 48.8 1.48 0.80 0.46

(0.02) (0.03) (2.9) (1.2)

SN As B 5.16 5.10 5.27 ∗ 134 53.2 28.0 ∗∗ 106 77.4 51.6 ∗∗ 1.48 0.74 0.47 ∗∗(0.01) (0.01) (0.7) (1.0)

SH As C 5.16 5.20 5.22 134 43.0 33.8 106 76.9 68.2 1.48 0.73 0.54

(0.02) (0.06) (0.7) (1.5)

SH Bp A 4.95 4.77 4.89 101 53.1 36.9 104 129 100 1.10 0.80 0.61

(0.03) (0.04) (1.2) (1.9) (7.8)

SH Bp B 4.95 5.00 50.1 NS 101 36.3 26.9 ∗∗ 104 72.5 67.9 ∗ 1.10 0.53 0.48 ∗∗(0.05) (0.03) (1.3) (1.7) (1.6)

SH Bp C 4.95 4.83 5.06 101 52.2 27.1 104 79.4 61.1 1.10 0.72 0.43

(0.02) (0.02) (1.6) (0.5)

aSPOC = Solid-phase organic carbon.b WEOC = Water extractable organic carbon.c The site codes are coded as follows: the first two letters refer to the study site (RN = Rouyn-Noranda; SH = Saint-Hippolyte); the centralsection of the code refers to the factor studied, either the gradient of metal contamination in Rouyn-Noranda (0.5 = 0.5 km; 2 = 2 km; 8 =8 km from the smelter) or the tree species in Saint-Hippolyte (Ab = Abies balsamea; As = Acer saccharum; Bp = Betula papyrifera); thelast letter refers to field replication.d Stat. = results of the non parametric Freidman test: NS = not significant; ∗ = p ≤0.10; ∗∗ = p ≤ 0.05.

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Table 3. Major element concentrations in the water extraction. Values in parenthesis represent standard deviation of laboratory triplicates. Standarddeviations are not given if soil mass was insufficient to perform all analyses and that analysis was performed only once or in duplicate. The sitecodes are as in Table 2

Al (mg kg−1) Ca (mg kg−1) Fe (mg kg−1) Mg (mg kg−1) Mn (mg kg−1)

Site inner outer bulk Stat. a inner outer bulk Stat. inner outer bulk Stat. inner outer bulk Stat. inner outer bulk Stat.

rhizo. rhizo. soil rhizo. rhizo. soil rhizo. rhizo. soil rhizo. rhizo. soil rhizo. rhizo. soil

Rouyn-Noranda (soil contamination)RN 0.5 A 60.8 17.9 10.6 18.4 21.3 14.2 15.8 6.18 2.10 11.7 7.49 3.80 2.89 3.33 1.64

(1.7) (1.6) (0.2) (1.5) (0.2) (0.2) (0.3) (0.44) (0.03) (0.4) (0.22) (0.02) (0.20) (0.08) (0.02)

RN 0.5 B 66.2 29.1 11.1 21.2 21.3 10.9 25.5 11.9 2.02 15.2 9.81 3.77 4.64 5.10 1.72

(1.4) (0.7) (0.1) ∗∗ (0.7) (0.4) (0.2) ∗ (0.5) (0.4) (0.04) ∗∗ (0.5) (0.04) (0.09) ∗∗ (0.14) (0.05) (0.06) NS

RN 0.5 C 47.4 20.0 13.0 25.7 23.1 20.2 13.1 6.96 3.22 13.6 8.69 5.21 3.94 3.96 4.42

(0.6) (0.8) (0.3) (0.6) (0.7) (0.2) (0.4) (0.20) (0.09) (0.5) (0.04) (0.02) (0.08) (0.14) (0.06)

RN 2A 42.9 32.6 23.4 65.8 39.8 36.9 15.9 19.0 14.6 24.2 13.2 11.2 5.29 4.91 1.65

(0.8) (1.7) (1.7) (0.5) (0.9) (1.1) (0.3) (0.3) (0.20) (0.06)

RN 2B 55.0 25.9 23.0 32.2 28.0 28.3 16.4 13.7 14.6 18.8 9.82 8.50 7.84 2.77 1.11

(2.5) (1.0) (4.3) ∗∗ (0.7) (0.9) (0.3) ∗ (1.2) (0.9) (3.4) NS (0.6) (0.20) (0.84) ∗∗ (0.58) (0.08) (0.04) ∗∗RN 2 C 43.8 24.5 17.9 58.9 45.5 31.9 13.7 12.6 10.3 19.1 12.0 7.94 5.97 4.75 1.24

(2.1) (2.6) (0.4) (0.06) (1.7) (2.2) (0.4) (0.51) (0.10) (0.09)

RN 8 A 45.5 39.8 25.7 46.6 28.9 17.7 20.4 23.8 16.6 30.0 18.9 12.3 3.24 1.36 0.47

(0.9) (6.4) (6.6) (1.9) (0.7) (1.0) (1.0) (3.8) (7.2) (0.6) (1.3) (2.1) (0.13) (0.06) (0.10)

RN 8 B 36.7 35.0 24.6 33.2 27.8 22.4 14.1 17.7 14.8 21.4 16.3 12.5 2.37 1.95 1.71

(2.2) (1.1) (0.7) ∗∗ (1.4) (0.3) (0.6) ∗∗ (0.6) (0.8) (0.6) NS (0.7) (0.4) (0.3) ∗∗ (0.1) (0.06) (0.06) ∗∗RN 8 C 55.1 41.0 40.4 52.3 29.0 22.2 18.2 23.5 29.1 35.4 18.6 17.4 3.05 1.33 0.56

(7.0) (0.6) (6.7) (0.5) (1.3) (0.6) (2.3) (0.7) (4.0) (2.2) (0.4) (1.1) (0.04) (0.07) (0.04)

Saint-Hippolyte (tree species)SH Ab A 20.4 9.33 3.68 12.3 6.74 6.18 2.72 2.57 1.11 15.4 6.90 4.35 0.52 0.30 0.22

(0.76) (0.14) (0.25) (0.09) (0.30) (0.08) (0.63) (0.12) (0.02) (0.01)

SH Ab B 20.4 15.0 4.20 12.3 6.49 58.3 2.72 4.46 0.76 15.4 5.63 3.15 0.52 0.33 0.34

(0.2) (0.16) ∗∗ (0.49) (0.30) ∗ (0.21) (0.03) ∗ (0.24) (0.16) ∗∗ (0.01) (0.01) ∗SB Ab C 20.4 11.1 3.86 12.3 7.53 7.72 2.72 1.61 0.36 15.4 6.32 2.81 0.52 0.31 0.29

(0.06) (0.15) (0.40) (0.30) (0.03) (0.03) (0.07) (0.14) (0.01) (0.05)

SH As A 27.6 12.7 4.50 29.9 27.9 17.6 2.08 0.94 0.45 30.0 10.3 3.36 0.84 0.42 0.21

(0.0) (0.38) (2.0) (0.4) (0.02) (0.10) (0.6) (0.13) (0.01) (0.00)

SH As B 27.6 13.2 5.14 29.9 24.4 16.3 2.08 1.38 0.62 30.0 10.0 4.45 0.84 0.54 0.36

(1.0) (0.69) ∗∗ (1.2) (0.5) ∗∗ (0.02) (0.15) ∗∗ (0.0) (0.95) ∗∗ (0.01) (0.04) ∗∗SH As C 27.6 9.07 4.73 29.9 17.0 16.5 2.08 1.22 0.51 30.0 5.15 4.00 0.84 0.45 0.34

(0.13) (0.04) (1.0) (0.3) (0.05) (0.01) (0.23) (0.05) (0.04) (0.01)

SH Bp A 27.0 20.0 12.6 17.2 12.7 13.7 2.51 2.48 1.79 20.6 6.69 3.64 1.00 0.40 0.20

(0.3) (0.0) (1.0) (0.4) (0.14) (0.04) (0.41) (0.12) (0.03) (0.01)

SH Bp B 27.0 7.54 6.53 17.2 6.56 10.8 2.51 1.13 0.71 20.6 3.29 2.85 1.00 0.21 0.23

(0.13) (0.11) ∗∗ (0.22) (0.1) ∗∗ (0.06) (0.01) ∗ (0.06) (0.06) ∗∗ (0.01) (0.00) NS

SN Bp C 27.0 14.5 6.17 17.2 15.3 16.4 2.51 2.83 0.67 20.6 7.81 3.85 1.00 1.34 0.40

(0.1) (0.12) (0.9) (0.4) (0.05) (0.02) (0.19) (0.06) (0.6) (0.03)

aStat. = results of the non parametric Freidman test: NS = not significant; ∗ = p ≤0.10; ∗∗ = p ≤ 0.05.

Saint-Hippolyte, the regression equation was WEOC= 93.3∗absorbance + 22.2 (r = 0.95).

Metal analyses

The elements analysed were: Al, Ca, Cd, Co, Cr, Cu,Fe, Li, Mg, Mn, Ni, Pb and Zn. These elements are ofinterest both in term of plant nutrition and from an eco-

7

Table 4. Trace element concentrations in the water extraction. Values in parenthesis represent standard deviation of laboratory triplicates. Standarddeviations are not given if soil mass was insufficient to perform all analyses and that analysis was performed only once or in duplicate. The sitecodes are as in Table 2

Cd (µg kg−1) Cu (mg kg−1) Ni (µg kg−1) Pb (µg kg−1) Zn (mg kg−1)

Site inner outer bulk Stat.a inner outer bulk Stat. inner outer bulk Stat. inner outer bulk Stat. inner outer bulk Stat.

rhizo. rhizo. soil rhizo. rhizo. soil rhizo. rhizo. soil rhizo. rhizo. soil rhizo. rhizo. soil

Rouyn-Noranda (soil contamination)RN 0.5 A 65.3 36.8 39.8 1.82 0.65 0.17 171 54.4 44.9 <18.0 <18.0 <18.0 3.77 1.83 1.00

(5.8) (2.5) (3.2) (0.04) (0.6) (0.02) (3) (4.1) (2.4) (0.10 (0.03) (0.05)

RN 0.5 B 167 90.5 37.5 2.81 1.48 <0.14 150 67.9 41.0 <18.0 <18.0 <18.0 6.71 3.44 1.36

(4) (2.0) 1.0) ∗ (0.01) (0.01) ∗∗ (2) (7.2) (2.4) ∗∗ (0.26) (0.03) (0.06) ∗∗RN 0.5 B 174 105 76.9 2.33 1.04 0.64 119 53.0 45.4 <18.0 <18.0 <18.0 4.80 2.70 1.67

(4) (5) (3.0) (0.12) (0.01) (0.02) (5) (2.4) (4.8) (0.16) (0.01) (0.06)

RN 2 A 150 70.6 23.5 3.51 1.80 0.58 146 59.1 55.7 42.0 31.9 <18.0 2.11 0.90 0.50

(7.1) (0.06) (0.02) (0.04) (3.4) (0.7) (2.4) (0.04) (0.03)

RN 2 B 168 63.6 50.8 2.15 1.08 0.70 264 72.3 63.1 <18.0 <18.0 <18.0 2.87 0.92 .66

(6) (0.8) (3.1) ∗∗ (0.03) (0.02) (0.02) ∗∗ (11) (3.3) (7.5) ∗∗ (0.22) (0.00) (0.16) ∗∗RN 2 C 181 73.6 40.1 3.03 1.84 1.04 140 56.3 53.4 <18.0 <18.0 <18.0 1.95 0.97 0.47

(2.4) (3.7) (0.02) (0.03) (5.3) (7.3) (0.02) (0.01)

RN 8 A 38.4 14.4 2.79 0.75 0.49 0.18 55.4 42.7 40.8 52.8 34.2 <18.0 0.37 0.21 <0.13

(3.0) (0.4) (0.13) (0.03) (0.02) (0.1) (3.6) (3.0) (3.8) (2.1) (3.7) (0.00) (0.04)

RN 8 B 34.1 20.6 7.98 0.72 0.50 0.37 53.0 37.7 35.4 69.8 38.2 19.3 0.31 0.25 <0.13

(3.6) (0.3) (0.16) ∗∗ (0.04) (0.01) (0.01) ∗∗ (1.0) (1.1) (2.2) ∗∗ (0.7) (5.3) (1.8) ∗∗ (0.04) (0.01) ∗∗RN 8 C 50.8 15.3 3.54 0.85 0.45 0.20 111 42.7 33.7 47.0 35.3 <18.0 0.42 0.22 0.22

(3.7) (0.5) (0.21) (0.04) (0.01) (0.01) (11) (4.5) (2.2) (3.4) (2.5) (0.02) (0.02) (0.15)

Saint-Hippolyte (tree species)SH Ab A 6.93 4.83 2.65 <0.14 <0.14 <0.14 42.3 30.0 <17.0 <18.0 <18.0 <18.0 0.31 <0.13 <0.13

(0.21) (0.08) (2.2)

SH Ab B 6.93 7.27 3.99 <0.14 <0.14 <0.14 42.3 33.0 20.5 <18.0 <18.0 <18.0 0.31 0.22 0.13

(0.04) (0.22) ∗ (3.2) (1.8) ∗∗ (0.01) (0.03) ∗SH Ab C 6.93 4.63 1.26 <0.14 <0.14 <0.14 42.3 34.0 <17.0 <18.0 <18.0 <18.0 0.31 0.16 <0.13

(0.04) (0.12) (4.4) (0.00)

SH As A 5.01 5.10 1.51 <0.14 <0.14 <0.14 32.0 19.7 <17.0 <18.0 <18.0 <18.0 0.35 <0.13 <0.13

(0.23) (0.06) (1.1)

SH As B 5.01 3.47 1.02 <0.14 <0.14 <0.14 32.0 30.8 <17.0 <18.0 <18.0 <18.0 0.35 <0.13 0.13

(0.21) (0.10) ∗ (0.8) ∗∗ (0.17) NS

SH As C 5.01 1.34 1.11 <0.14 <0.14 <0.14 32.0 <17.0 <17.0 <18.0 <18.0 <18.0 0.35 <0.13 <0.13

(0.10) (0.05)

SH Bp A 5.63 4.41 2.04 <0.14 <0.14 <0.14 32.2 17.3 17.4 <18.0 <18.0 <18.0 0.38 0.16 <0.13

(0.14) (0.02) (3.0) (5.5) (0.02)

SH Bp B 5.63 1.66 2.31 <0.14 <0.14 <0.14 32.2 <17.0 <17.0 <18.0 <18.0 <18.0 0.38 <0.13 <0.13

(0.25) (0.10) ∗ NS ∗SH Bp C 5.63 3.62 2.19 <0.14 <0.14 <0.14 32.2 19.8 <17.0 <18.0 <18.0 <18.0 0.38 0.19 0.15

(0.42) (0.20) (3.6) (0.03) (0.09)

aStat. = results of the non parametric Freidman test: NS = not significant; ∗ = p ≤0.10; ∗∗ = p ≤ 0.05.

toxicological perspective (Fergusson, 1990; McBride,1994). The Al, Ca, Co, Cr, Cu, Fe, Li, Mg, Mn andZn concentrations in the water extracts were measuredusing ICP-AES whereas GFAAS was employed for

Cd, Ni and Pb. The method detection limit (MDL) wasdetermined following Centre Saint-Laurent (2001).

8

Statistical analyses

All statistical analyses were carried on the softwareSPSS 10.0 for Windows. In order to statistically as-sess the differences between the three soil componentsas well as between sites of a same sampling area, aFriedman test was used. In all these cases, the n valueinvolved is small: n=3 for the soil components (fieldreplicates); n=9 for comparisons at Rouyn-Noranda;n=7 for comparisons at Saint-Hippolyte because of thepooling of the inner rhizosphere component. As such,normality cannot be postulated and a non-parametrictest is selected. As the number of groups (k) is largerthan 2, the Friedman test was selected (Legendre andLegendre, 1998). Hence the degree of freedom is 2in all cases. As a consequence of the small n value,two levels of significance were used: p < 0.10 and p<0.05.

For regression analyses, the normality was testedwith a Kolmogorov-Smirnoff test prior to the regres-sion because all the data available for a specific vari-able per site (Rouyn-Noranda n=27, Saint-Hippolyten=21) were used. When distributions were not nor-mal, a log transformation was performed. Correlationbetween variables was determined using a Durbin-Watson test. Linearity was also checked. The signi-ficance level was set to α = 0.05.

Results and discussion

Analytical and field variability

The results indicate that the analytical variability isgenerally small (Tables 2–4). This small analyticalvariability was not expected because the rhizosphereis a relatively heterogeneous environment at the mmscale (e.g. Marschner, 1995). As such, the results tendto indicate that the operational method used in thisstudy to separate soil components is appropriate. Still,the rhizosphere obtained by our method is probably‘diluted’ by the bulk material and the effect of rootson soil is thus underestimated. The differences ob-served between the three soil components in this studyprobably correspond to a lower limit.

On the other hand, the field replication can giverise to a large spatial variability (Tables 2–4). At thesame sites, the field variability can exceed the differ-ence between soil components. For example, at siteRN 0.5 the average difference between the highestand the lowest pH value of the three soil components

is 0.10 pH unit while the field variability of the in-ner rhizosphere reaches 0.25 pH unit. Such variabilityobviously complicates the identification of significantdifferences between soil components.

Root-induced changes of the pH and the electricalconductivity of water extracts

Despite the marked biogeochemical differencesbetween the two study areas, the pH values at bothRouyn-Noranda and Saint-Hippolyte are in a similarrange of 4.51–5.31 (Table 2). A general pH trend canbe observed for most soil following the sequence innerrhizosphere < outer rhizosphere < bulk soil. In fact,the inner rhizosphere is always more acidic than thebulk soil except for the sites RN 0.5 A and SH Bp A.However, the outer rhizosphere appears to be the mostacidic soil component at nine sites out of 18.

For a given site, the differences between soil com-ponents, although significant in most cases, were notvery pronounced. The mean difference between themost and the least acidic soil components of a givensite is about 0.15 pH unit. The largest difference (0.37pH unit) occurred between the bulk soil and the innerrhizosphere of the RN 8 C site, whereas the smallestdifference (0.05 pH unit) was observed for the RN 8 Bsite between the inner rhizosphere or the bulk soil andthe outer rhizosphere.

Most studies on the soil-root interface show anacidification of the rhizosphere, although alkalinisa-tion is also observed. In this context, it can be con-sidered that the results obtained are in good agreementwith the literature. However, the results are stronglydependent of the experimental conditions. Some pHdifferences between the bulk soil and the rhizospherewere shown to reach 2 and even 3 pH units (Gahoonia,1993; Tagliavini et al., 1995). Yet, most of the studiespresenting large pH differences were performed un-der laboratory conditions magnifying the effect of rootin the natural environment. For example, in order toobtain a difference of 2,4 pH units between the rhizo-sphere and the bulk soil, Grinsted et al. (1982) used aroot mat that reaches a density of root of 450 cm cm−3

with a soil lacking P and where N is available onlyunder the nitrate form (Hedley et al., 1982).

The model developed by Nye (1981, 1986) indic-ates that a difference between the soil components oftwo pH units is highly unlikely and that a one-unitdifference should be a maximum under field condi-tions with a soil pH approaching 5.3. At that pH, theacidity diffusion coefficient is at its lowest, increasing

9

the effect of the roots (Nye, 1981). In agreement withNye’s model and the current study, most field worksdo not reveal differences between the rhizosphere andthe bulk soil that are comparable in magnitude to thoseobserved in the laboratory. Gobran and Clegg (1996)obtained a maximum difference of 0.6 pH unit in aBh horizon of a Swedish forest soil. Courchesne et al.(2001) also found differences between 0.05 and 0.5 pHunit in forest soils from Québec, Canada.

The main process explaining the pH differencesbetween the rhizosphere and the bulk soil is the equi-libration of the cation-anion balance (Hedley et al.,1982; Nye, 1981). Roots simultaneously take upcations and anions. However, one ion type is usuallytaken up in a greater amount, thus inducing disequilib-rium in the cation-anion balance. In order to maintainthe electroneutrality at the soil/plant interface, theplant will compensate by releasing OH− or H+ de-pending on whether anions or cations, respectively, aretaken up in excess (Nye, 1981). According to this pro-cess, acidification of the rhizosphere will occur whenthe uptake imbalance favours cations.

There is a pronounced trend in EC following thesequence inner rhizosphere > outer rhizosphere >

bulk soil (Table 2). The EC of the inner rhizosphere is2.2 (RN 8 B) to 4.9 (SH As A) times higher than thatof the bulk soil. For this variable, the outer rhizospherepresents values that are more similar to the bulk soilthan to the inner rhizosphere.

Although data on electrical conductivity are notfrequently reported, contrasts of a similar magnitudewere obtained by Gobran and Clegg (1996) for forestsoils from Sweden. According to these authors, theorganic matter content seems to be related to the con-ductivity. A significant relationship was also recordedbetween the conductivity and the WEOC (Rouyn-Noranda r = 0,75; Saint-Hippolyte r = 0,94) and theSPOC (Rouyn-Noranda r = 0,87; Saint-Hippolyte r =0,75) in the current study.

Root-induced changes on WEOC and SPOC

The proximity of roots has a direct influence on theorganic matter content, either in the solid phase orin the water extracts. For both types of organic car-bon content, the sequence follows inner rhizosphere> outer rhizosphere > bulk soil (Table 2). The onlyexception noted is for SPOC at site SH Bp A where theouter rhizosphere has the greatest content because ofthe pooling of the three tree inner rhizosphere samples.The WEOC of the inner rhizosphere is 1.7–4.1 fold

(RN 8 B and RN 0.5 B, respectively) greater than thatof the bulk soil (Table 2). The inner rhizosphere alsocontains from 1.0 (1.5 time if weighted for the innerrhizosphere pooling) to 5.8 times more SPOC than thebulk soil for SH Bp A and RN 8 C, respectively. Onthe average, the inner rhizosphere is twice as rich inSPOC than the bulk soil. The SPOC constitutes theonly variable for which the Saint-Hippolyte soil hasthe highest content compared to Rouyn-Noranda.

In a pot experiment, Lorenz et al. (1997) showedan increase in the dissolved organic carbon (DOC)content in the rhizosphere relative to the bulk soil, al-though this increase was usually less than 50%. Basedon fieldwork, Gobran and Clegg (1996) reported val-ues for SPOC in the rhizosphere which were twicethose of the bulk soil. Similarly, Courchesne et al.(2001) showed an enrichment of the rhizosphere inSPOC of a similar magnitude to the one presentedhere.

The SPOC and the pH of the water extracts arenegatively related (Rouyn-Noranda r = –0.61; Saint-Hippolyte r = –0.44). This could be attributed to thefact that the decomposition of the organic matter isreduced under more acidic conditions prohibiting itsaccumulation in the soil (Grayston et al., 1996). Onthe other hand, a positive relationship between WEOCand pH was observed at the Rouyn-Noranda sites forthe outer rhizosphere and the bulk soil components (r= 0.77 and 0.91, respectively). This can be explainedby the increased solubility of humic substances and thedesorption of organic anions as pH increases.

It is rather well established in the literature thatthe rhizosphere is enriched in organic matter (Hin-singer, 1998). By its own presence the root contributesto the supply of organic matter in the rhizospherefor example through the release of soluble exudates,sloughed off cells and mucilage, also called rhizode-position (Nye, 1986). This supply of organic matteris a source of energy and C stimulating the activity ofmicroorganisms in the rhizosphere (Nye, 1986). Mostof the WEOC measured in this study likely comesfrom root exudates and soluble compounds (e.g. fulvicacids), while the SPOC can be attributed to morerecalcitrant organic substances (Vaughan et al., 1993).

Root-induced changes in water-extractable metalconcentrations

For the 10 metals that were over the method detec-tion limit (MDL), a clear trend emerges with the metalconcentrations decreasing from the inner rhizosphere

10

to the outer rhizosphere and the bulk soil (Tables 3 and4). Results for Li, Co and Cr are not included as theirconcentrations were all below the method detectionlimit (MDL) at all sites and for all soil components.For each metal, some exceptions exist, but they do notaffect the general trend. For Al, Cu, Mg, Ni, Pb andZn and that at all 18 sites the findings show that theinner rhizosphere is the richest soil component. ForCa and Cd, the outer rhizosphere sometimes has thehigher metal content (e.g. RN 0.5 A and SH Ab B, re-spectively), but the inner rhizosphere always containsmore Ca and Cd than the bulk soil. Only Fe (RN 8 B,RN 8 C) and Mn (RN 0.5 C) results show sites wherethe bulk soil is the richest soil component. Althoughan enrichment of the rhizosphere by a factor of two tothree is common, the inner rhizosphere can sometimescontain more than 10 times more water extractablemetals than the bulk soil. This is the case for Cd at RN8 C and Cu at RN 0.5 A. Obviously, this one order ofmagnitude difference could have been higher had theseparation of the rhizosphere component been moreselective.

Linehan et al. (1989) indicated that Cu, Co,Mn and Zn concentrations in rhizosphere solution ofHordeum vulgare L. are related to a seasonal patternwith the highest concentrations usually occurring latein the spring or in early summer. The samples for thecurrent research were collected at the end of Septem-ber and at the beginning of October. It is then probablethat the magnitude of the difference between the rhizo-sphere and the bulk soil was not as its highest level,although trees could present a behavior different fromthat of annual crops.

Most studies on element concentrations in therhizosphere were concerned with major elements,leaving trace and ultra-trace metals aside. Not sur-prisingly, there is no consensus in the literature withrespect to the soluble metal content of the rhizosphere.In most studies, the rhizosphere appears to be impov-erished in metals. For example, in a pot experiment,Lorenz et al. (1997) showed that the soil is generallydepleted in water-extractable Ca, Cd, K, Mg, Mn, Pand Zn after the growth of radish (Raphanus sativuscv. ‘Crystal Ball’). The authors attributed this deple-tion to the uptake of metals by plants, the reduction ofthe ionic strength and the subsequent changes in theredistribution of metals on exchange sites. Sarong etal. (1989) also found lower concentrations of labileZn (water extract) in the rhizosphere of oat in a potexperiment. Similar results were reported by Knight etal. (1997) for Zn in the soil solution of Thlaspi caer-

ulescens in a pot experiment. Göttlein et al. (1999)reported that in acidic soils there can be less Ca andMg in the rhizosphere solution while Al could increaseas a result of the release of H+ ion.

Other studies suggest that the rhizosphere is en-riched in metals. Wang et al. (2002) separated thesoil–root interface in four components to study theeffect of roots on metal fractionation as affected byroots. They showed that Cd, Cr, Cu, Ni, Pb and Znconcentrations (soluble-exchangeable-bound to car-bonate form) followed the order: near rhizosphere >

near bulk soil > rhizosphere > bulk soil. Youssef andChino (1989) also measured a higher Fe and Mn sol-ubility in a rhizobox despite a higher rhizosphere pH.Gahoonia (1993) measured a higher soluble Al con-tent in the rhizosphere of Lolium perenne cv Printo)associated to a decrease in pH. The enrichment of therhizosphere appeared to be larger at the beginning ofthe growth stage (Linehan et al., 1985).

Hinsinger (1998) explained the depletion or theenrichment of the rhizosphere by the capacity of thesoil to replenish the soluble or exchangeable forms ofmetals. When elements are abundant in the soil solu-tion (e.g. Ca, Mg), higher concentrations should beexpected in the rhizosphere than in the bulk soil asa consequence of mass-flow. However, when elementsupply is limited like it is often the case for K and P,the plant takes up the nutrients at a more rapid ratethan the soil can supply thus inducing a depletion inthe rhizosphere (Hinsinger, 1998).

In most cases, the main chemical variable asso-ciated with water extractable metal concentrations isWEOC. Figure 1 illustrates this positive trend for Mg.Water extractable metal concentrations are all signific-antly related to WEOC (r value between 0.50 and 0.94)with strongest relationships observed for Mg and Alon both sampling areas. Only Zn at Rouyn-Norandais not associated to WEOC. Gobran and Clegg (1996)showed a strong association between the solid phaseorganic matter content and most of the other variablesthey measured in the soil components of a forest soilfrom Sweden, including exchangeable Al, Ca, Mg,Na and K. A relationship between dissolved organiccarbon and Cd and Zn free ions was also establishedby Lorenz et al. (1997). Whereas metals in bulk soilwere mainly present in an uncomplexed form, whilethe same metals were organically-complexed in therhizosphere. Lorenz et al. (1997) also indicated thatthe rhizosphere contains less free Cd2+ and Zn2+ ionscompared to the bulk soil because metals are bound todissolved organic matter released during plant growth.

11

Figure 1. Relationship between water extractable organic carbon and water extractable Mg for the three soil components (inner and outerrhizosphere, bulk soil). Values are means of two or three replicates depending on the soil mass available. Lines represent regression equationfor all RN or SH sites, respectively. The legend is as follows: RN = Rouyn-Noranda, SH = Saint-Hippolyte; Rhi = inner rhizosphere, Rho =outer rhizosphere, Bk = bulk soil).

Accordingly, Merckx et al. (1986) showed that withinfour weeks of growth in pots, ionic forms of Co, Mnand Zn shifted towards high molecular weight forms asroot-derived materials accumulated in the rhizosphereof maize and wheat.

Dissolved organic matter can either increase theavailability to plants of elements that are only slightlysoluble or reduce the availability of elements that arereadily soluble (Vaughan et al., 1993). Zhang et al.(1989) indicated that plant can produce root exudatessuch as phytosiderophores when Zn deficiency occurs.These exudates mobilize Zn and render it available toroots. The same root exudates also bind Fe (Zhang etal., 1989). Treeby et al. (1989) also showed that theroot exudates of Hordeum vulgare L. cv. Europa underFe-deficiency can increase by an average of 20 timesthe amount of Fe, Zn, Cu and Mn in solution.

The pH of the water extracts was not as closelyrelated to water-extractable metals as WEOC was. AtRouyn-Noranda, relationship between pH and waterextractable Al, Ca and Mg are not significant; forsignificant relationships, r-values vary between 0.44and 0.75. At Saint-Hippolyte, association between pHand water extractable Al, Mg, Mn and Zn are notsignificant while significant r-values fluctuate between

0.51 and 0.71. Perhaps the rather small differences inpH between sites and soil components cannot inducea detectable effect due to sample and site variabilityor to the role of confounding factors. Yet, Linehanet al. (1985) found that the rhizosphere acidificationwas related to the solubilization of Cu, Mn and Zn.McGrath et al. (1997) attributed to the lower pH in therhizosphere of Thlaspi ochroleucum the higher mobileZn (extracted with 1 M NH4NO3) concentrations in apot experiment. On the other hand, in a similar experi-ment using the same plant species, Knight et al. (1997)could not link Zn solution concentration with pH. Itthen appears that the intensity of the relation betweenpH and metal concentration is associated to both thetype of plant and the chemical forms of the metals.

Dividing the rhizosphere into an inner and an outerrhizosphere was expected to favour the detection ofthe ‘rhizosphere effect’. From the previous results, theusefulness of separating rhizosphere into an inner andan outer component in order to gain a more completepicture of the chemical gradient between the soil andthe root clearly emerges. For most of the variablesanalysed, the outer rhizosphere showed values that fellbetween the inner rhizosphere and the bulk. However,in some cases, the outer rhizosphere had the highest or

12

the lowest value of the three soil components insteadof showing an intermediate behaviour.

From a methodological perspective, the additionalshaking of the roots performed in the laboratory aftercollecting samples in the field constitutes a simple, lowcost technique that provides an operationally definedthird component giving interesting insights into thismicroscale environment (Gobran and Clegg, 1996). Itis otherwise difficult in fieldwork to obtain a separa-tion of the soil surrounding the roots that is as fine asit can be performed in the laboratory.

The effect of metal contamination

The Rouyn-Noranda site was selected to study the ef-fect that metal loading has on the properties of thesoil-root interface. For pH, a general trend exists thatfollows the expected gradient in metal contaminationwith soil pH increasing with distance from the smelter(Figure 2a). The bulk soil pH of the water extractsdeclines on average from 5.20 to 4.64 near the smelter.For similar sites, Dumontet et al. (1992) also observeda pH decline near the smelter associated to the emis-sion of acidic compounds (sulphuric and nitric acid)by the smelter, particularly before the 1990’s. Emis-sions were strongly reduced since and a H2SO4 plantwas built (Couture, 1997).

As for WEOC, its content is significantly andpositively related to the distance (Table 2). On thecontrary, the SPOC values present the inverse trendexcept for the inner rhizosphere of the second site,which has the highest value. Again, the effect of pH onthe decomposition of organic matter could explain theorganic carbon gradient. Soil EC decreases with dis-tance from the smelter. The EC trend probably reflectsthe soil acidity and the WEOC gradients (McBride,1994).

As for metal content, the expected gradient in con-tamination emerges only for Zn (Figure 2b). Reversetrends were observed for Fe, Mg, Pb and Al excludingthe inner rhizosphere. Moreover, most metals, like Ca,Cd, Cu, Mn and Ni, the sites at 2 km are the onespresenting the highest water extractable metal concen-trations (Figure 2c). The site at 8 km usually has thelowest Ca, Cd, Cu, Mn, Ni and Zn concentrations, buthas the highest Fe, Mg, Pb and Al content in the outerrhizosphere and bulk soil.

Many processes can explain the absence of aunique gradient in soil contamination by metals.Firstly, the existence of the metal gradient may bedifficult to document as samples were collected in

the upper B horizons. Indeed, it has been shown thatcontamination tends to concentrate in the surface or-ganic horizon of soils in mineral soils (Dumontet etal., 1992; Kabala and Singh, 2001) or at the surfaceof organic soils (Dumontet et al., 1990). However, thestudies performed by Dumontet et al. (1992) at Rouyn-Noranda did not include soils from a distance closerthan 2 km of the smelter in the same axis sampledfor the current research. Yet, these authors could onlydetect the contamination in Cd, Cu, Ni, Pb and Zn ata 15–30 cm depth for the 2 km site. Sites located ata distance of 5 km or more from the smelter were notaffected at that depth in Rouyn-Noranda.

Secondly, the water-extractable metals may notbe the most appropriate chemical form to assess thegradient in metal contamination. In soils contamin-ated with smelter emissions, surface horizons cancontain up to 50% of mobile metals (defined as sol-uble, exchangeable-specifically sorbed and carbonatebound) while this percentage falls to less than 10%in the subsoil (Kabala and Singh, 2001) where oursamples were collected. Kabala and Singh (2001)indicated that soil characteristics are more import-ant than prevailing wind direction and distance fromsource to explain the metal fractionation.

A third explanation could be linked to acidic de-position. The general trend for all components atRouyn-Noranda indicates that, in agreement with liter-ature (Lindsay, 1979), a lower soil pH induces a higherconcentration of soluble Al (Figure 3). However, if thesoil components are considered individually, it can beseen that in the bulk soil and in the outer rhizosphereof Rouyn-Noranda, the Al content diminishes with de-creasing pH. This trend is not as clear for the innerrhizosphere. The same relationship exists for Mg, butnot for Ca. This pattern for Al, Mg and to a lesserextent for Ca could be the result of a long-term soilleaching due to acidic deposition. However, Ruarket al. (1991) showed no effect of acid rain on rhizo-spheric concentrations of Al3+, Mg2+ and Ca2+ under1 year-old, field grown Pinus taeda L. Also, in thecurrent study, it has been shown that the relationshipbetween WEOC and water extractable metal concen-trations is stronger than the relationship between pHof the water extracts and metal concentrations.

The effects of tree species

The effects of tree species on the rhizosphere chem-istry are neither very pronounced nor systematic.For most metals, there is no significant difference

13

Figure 2. Mean values of (a) pH of the water extract (b) water extractable Zn concentration and (c) water extractable Cu concentrations of thethree soil components (inner and outer rhizosphere, bulk soil) for sites at Rouyn-Noranda along a gradient in metal contamination. Values aremeans of two or three replicates depending on the soil mass available. Error bars represent standard deviation when analyses were performedin triplicates.

14

Figure 3. Relationship between pH of the water extract and water extractable Al for the three soil components (inner and outer rhizosphere,bulk soil). Values are means of two or three replicates depending on the soil mass available. Lines represent regression equation for the bulksoil and the outer rhizosphere of the Rouyn-Noranda site. The site legend is the same as in Figure 2.

between Abies balsamea, Acer saccharum and Betulapapyrifera. Moreover, the higher metal contents areassociated to different species depending on the metal.Yet, there is a slight tendency for Abies balsamea tohave a behaviour that stands out compared to the othertwo species. For example, the inner rhizosphere ofAbies balsamea contains less Al but more Cd thanthe other two tree species. The lack of difference ob-served in this study for water-extractable metals andto a lesser extent for pH, electrical conductivity, SPOCand WEOC might be indicative that the impact of vari-ous tree species is of limited extent in the soil studiedor, more probably, that the Abies balsamea, Acer sac-charum and Betula papyrifera induce similar effectson soil.

Nevertheless, significant differences can be ob-served for water extractable Ca with soils under Acersaccharum containing more of this element (Figure 4).A similar trend is also seen for Mg, while Al followsan opposite trend, although they are not significant.Studies show that Ca is of particular importance forAcer saccharum (van Breemen et al., 1997). This spe-cies is known to grow in soils with low Al levels orhigh Ca/Al ratios (Watmough, 2002). Other than waterextractable Ca, Acer saccharum is significantly asso-

ciated with higher pH values. This preference for lessacid sites is generally reported in literature and relatedto the fact that acidity affects the availability of Caand Al (Finzi et al., 1998; Watmough, 2002). In theirstudy, van Breemen et al. (1997) consider that soilcomposition influences the distribution of tree speciesrather than tree affecting soil elemental content. In thecurrent work, the parent material is the same on allthree sites. Despite this fact, Ca concentrations aregreater under Acer saccharum even in the bulk soil.This could be due the direct (e.g. litterfall, organicacids, biocycling) or indirect (e.g. mycorrhizae, mi-croorganisms) effects of the tree species (Finzi et al.,1998; Watmough, 2002). However, in the case of Mg,the bulk soil content is independent of tree specieswhile the inner rhizosphere content is greater underAcer saccharum.

It could be hypothesized that tree species createdifferent environmental conditions in their respectiverhizosphere. For instance, Acer saccharum is usu-ally associated with endomycorrhizae while Abiesbalsamea and Betula papyrifera are mainly relatedwith ectomycorrhizae although association with en-domycorrhizae are possible particularly for Betula p.(Malloch and Malloch, 1981; Marschner, 1995). In

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Figure 4. Mean of water-extractable Ca concentrations under three different tree species and for the three soil components (inner and outerrhizosphere, bulk soil) at the Saint-Hippolyte site. For the inner rhizosphere, the value represents the mean of two analytical replicates. For theouter rhizosphere and the bulk soil, the value is the weighted mean of the three sampled trees.

the same way, distinct microbial populations are alsoassociated with each tree and these trees exude dis-tinct organic compounds as root grow (Grayston etal., 1996). As such, the rhizosphere of each treecould have been expected to contain metals in differentamounts. In the current study, the differences are lesspronounced than expected.

Other authors have worked with diverse plant spe-cies, mostly in the laboratory. For example, Wang etal. (2001) found differences between the rhizospheresolutions of Picea abies [L.] Karst and Fagus sylvat-ica L. in terms of metal concentrations. Merckx et al.(1986) showed that complexed forms of Co, Zn andMn were present in greater abundance in the rhizo-sphere of maize relative to wheat. Even when usingplants from the same genus such as Thlaspi caer-ulescens (J. and C. Presl) and Thlaspi ochroleucum(Boiss. Ex Heldr), McGrath et al. (1997) found op-posite trends for Zn in the rhizosphere solutions. Inmost laboratory studies on the rhizosphere, the em-phasis was usually given to herbaceous plant or shrubsand studies using tree species are rare. Yet, it is diffi-cult to establish if the absence of differences betweensoil components is specific to the environmental con-ditions used or if tree species are only a minor variableexplaining differences in the metal content of therhizosphere between sites. However, the samples inthis study were collected at a depth of ±15–20 cm.Finzi et al. (1998) indicate that the effect of species onthe soil is mainly expected in the forest floor and in thetop 7.5 cm. Moreover, the chemical forms extractedwith water may not be the ones mostly affected bythe difference in tree species. It can be hypothesizedthat the use of a solution considered to extract metals

associated with solid phase organic matter might bemore appropriate to evaluate differences between treespecies.

In conclusion, compared to the bulk soil, outerrhizosphere, but more particularly the inner rhizo-sphere present chemical characteristics that can differwidely. In most cases, the rhizosphere (inner or outer)is the most acidic soil component while the bulk soilis the least. Systematically, inner rhizosphere has ahigher content in both SPOC and in WEOC as wellas a greater EC than outer rhizosphere and even morethan the bulk soil. In the same way, water-extractablemetals also follow the trend inner rhizosphere > outerrhizosphere > bulk soil for most of the 18 sites for all10 studied metals that were found in concentration su-perior to the MDL. These results clearly indicate thatthe rhizosphere possesses different properties com-pared to the bulk soil. Soil analyses performed onlyon the bulk soil cannot be representative of the soil un-der root influence and cannot serve to assess the metalcontent available to plants. The results also reveal thatthe division of the rhizosphere into an inner and anouter component is a simple operational way whendoing fieldwork to get a better insight at the processestaking place at the microscale. The outer rhizospheredoes not have a constant behaviour, but tends to adoptan intermediate position between the inner rhizosphereand the bulk soil. This should be taken into account infuture work on the soil-root interface.

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Acknowledgements

We would like to thank Alain Dufresne, Alayn La-rouche, André G. Roy, Patrice Turcotte, Julie Turgeonand Marie-Claude Turmel for technical assistance.Comments and suggestions made by Mario Tenutaand three external referees were appreciated. Financialsupport for this research was provided by the NaturalScience and Engineering Research Council of Canada(NSERC), by the Fonds québécois de la recherche surla nature et les technologies (FQRNT) and by Metalsin the Environment – Research Network (MITE-RN).

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