Geoderma 202–203 (2013) 203–211
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Influence of rainfall and temperature on DTPA extractable nickel content of serpentine soils in Turkey İ. Ünver a,⁎, S. Madenoğlu b, A. Dilsiz b, A. Namlı a a b
Ankara University, Faculty of Agriculture, Department of Soil Science and Plant Nutrition, 06110 Dışkapı, Ankara, Turkey Ministry of Agriculture and Rural Affairs, Directorate General of Agricultural Research, Soil-Fertilizer and Water Resources Central Research Institute, P.O. Box 54, Yenimahalle, Ankara, Turkey
a r t i c l e
i n f o
Article history: Received 22 August 2012 Received in revised form 21 March 2013 Accepted 28 March 2013 Available online 25 April 2013 Keywords: Serpentine soils Nickel DTPA extraction Weathering
a b s t r a c t Influence of rainfall and temperature on DTPA (diethylene triamine pentaacetic acid) extractable nickel (DNi) and fractional (DNi / total Ni = F-DNi) concentrations of soils derived from ultramafic serpentine rock under temperate semiarid continental and Mediterranean climates were studied. All serpentinite areas in Western Anatolia and the East Thrace (ca. 400,000 km2 areas) were targeted. Meteorological data from 185 stations versus so-called phytoavailable Ni concentrations of 192 serpentine soil samples were examined. Digital elevation model (DEM), ANUSPLIN and ARC GIS 8.1 software packages for generation of climatic surfaces and analysis were employed for extrapolation of the weathering conditions in preparing comparative maps. Total Ni concentrations (TNi) were in the range of 25.7–2680 mg kg−1, whereas DNi were between 0.08 and 143 mg kg−1. The correlation between Ni extractability and the pH was weak (R2 = 0.175). This restricted effect may be attributed to the soil pH varying between neutral and slightly alkaline. Average DNi concentrations of the soil samples grouped within the province borders indicated that both precipitation and air temperature might be effective on the amount of DNi in the serpentine soils studied. The combined effect of annual precipitation and mean atmospheric temperature were significant (P b 0.01) on DNi. The differences between the climatic zones were distinct and generally increasing with the increase of annual rainfall and mean air temperature. © 2013 Elsevier B.V. All rights reserved.
1. Introduction Recent ideas about the role of nickel (Ni) as an essential nutrient in many living organisms have resulted in increased interest on this element. On the other hand, Ni is considered more likely toxic than many other metals because of its widespread existence (Burt et al., 2001; Navarro-Pedreño et al., 2003). Pedogenic or anthropogenic Ni contamination is hardly avoided as it is a basic constituent element of many soils, particularly of less silisic (ultrabasic) serpentine soils. Average Ni concentration in soils is about 16 mg kg−1 (Nriagu, 1980) varying normally between 2 and 750 mg kg−1 (Seregin and Kozhevnikova, 2006) with the highest concentrations in basic igneous rocks (McGrath, 1995). Ure and Berrow (1982) reported the average Ni concentration of 4265 soil samples as 33.7 mg kg−1. The geology and soil-forming processes strongly influence the amount of nickel in soils (Kabata-Pendias and Mukherjee, 2007). Distribution of Ni in serpentine soils depends on parent material of the soil and on pedogenetic activities that influence the weathering processes (Lee et al., 2004). Ultramafic formations can contain as much as 0.3% Ni. The extreme weathering removes most elements except the least soluble ones from the protolith. The residual soil material can average as much as 5% nickel (Marsh and Anderson, 2011).
⁎ Corresponding author. Tel.: +90 312 5961164; fax: +90 312 3178465. E-mail address:
[email protected] (İ. Ünver). 0016-7061/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.geoderma.2013.03.025
Global distribution and total amounts of nickel in soils are well established; however, more information about their phytoavailability is still needed. Governing weathering processes and pedogenesis of serpentine soils differ from location to location with varying climatic conditions as well as the nature of the parent material and other soil forming factors due to the wide distribution and occurrence of these soils. Higher levels of Ni and/or Mg in ultramafic soils seem likely to account for vegetation change where Ni availability increases with decreasing pH and lower pH on serpentine soils may be responsible for poor forest colonization (Robinson et al., 1996), suggesting highly complex interrelations. Large number of reports on the effectiveness and reliability of extraction methods on determining phytoavailability of nickel to crop plants are now available (Aydinalp and Katkat, 2004; L'Huillier and Edighoffer, 1996; Sukkariyah et al., 2005), whereas information about the effects of soil properties on Ni bioavailability is rather limited. A series of systematic studies seem to be necessary on soils with a wide range of physicochemical properties with common plant species. Many researchers focused on Ni extraction methods so as to establish relationships between Ni concentrations of the soil and plants because a number of extraction techniques simulating metal uptake process were claimed to be useful in estimating the amounts accumulated in plants (Misra and Pande, 1974; Shewry and Peterson, 1976; Wang et al., 2004). Although superiority of any extraction method over the others seems to depend on plant species and soil types, any relevant analysis
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method might to be useful at least in comparing the test soils. The chemical used in this study was diethylene triamine pentaacetic acid (DTPA) as its ionized ligand, which has a high affinity for metal cations. Although the test is commonly used in determining so-called phytoavailable Ni contents of the soils near neutral (Lindsay and Norvell, 1978; Quantin et al., 2008; Severson et al., 1979), a number of soil properties including pH and organic matter content may influence phytoavailability (Barančíková et al., 2004; Kukier et al., 2004; Li et al., 2003). Trace metals extracted by this technique were shown to correlate with plant metal uptake if soil pH variation of test soils is small (Bidwell and Dowdy, 1987; Sukkariyah et al., 2005). On the other hand, largescale differences in uptake, translocation and accumulation of various elements indicate the importance of plant species, subspecies and genotypes on the matter suggesting that an element at the rhizosphere could be available to one plant while not applicable to some others. Superiority of any extraction technique may become controversial when considering the above mentioned multivariate factors (Kabata-Pendias, 2004). The extraction method has a predictive value if there is a correlation between the extractable pool of a metal in soil and the uptake of the metal by a plant (Kukier and Chaney, 2001). Labile pool of soil Ni could be a useful tool for the assessment of soil-to-plant transfer of Ni, based on the hypothesis that extractable Ni is well correlated with the labile pool, avoiding carrying out of time consuming experiments (Denys et al., 2002). The objective of this research was to determine the influence of rainfall and temperature on the DTPA (diethylene triamine pentaacetic acid) extractable (DNi) and fractional (DNi/TNi = F-DNi) nickel concentrations of soils derived from ultramafic serpentine rock under temperate semiarid continental and Mediterranean climates from Western Turkey and the East Thrace in about 400,000 km2 area. 2. Material and methods 2.1. Climate and vegetation Precipitation and temperature are the principle climatic variables influencing soil formation (Brady and Weil, 1999). Air and soil temperatures are functionally interrelated, and mean annual temperatures have been proven quite satisfactory in soil formation investigations. Significant quantitative correlations between soil properties and mean annual temperatures were obtained. It should be recognized that the official rainfall and temperature records deal with macroclimate (Jenny, 1994). Extensive coverage of the study area did not facilitate establishing a detailed, reliable vegetation index. Less phytodiversity and common Ni tolerant temperate climate plant species including perennial shrubbery and herbaceous members of Brassicaceae were noted. Almost no differences in relation to health degree and density between the woods grown in the serpentinites and others were obvious. 2.2. Data collection Weathering climatic agents were restricted to annual precipitation and mean temperature normal distributions, and the time span for the formation of soils developed on serpentine. The data from the continuously active stations from 1975 to 2010 (36 years) were employed in the statistical analyses. Average annual precipitation in the research area was between 321 mm (Konya) and 1147 mm (Muğla). Precipitation increases from the central plateau to the sea at the west and south. Projected average annual rainfall and mean temperature considering topographic components were required and generated for reaching more reliable conclusions. Mean temperature normal in the area was between 19.2 °C (Mersin) and 10.4 °C (Kayseri). Temperature recordings, which were historically monitored in urban areas, are generally higher on the seashore. However, extrapolation of the climatic data considering the elevation and slope aspect factors showed great temperature differences within short distances. Discrimination of the
Mediterranean and continental climates with distinct lines seemed hardly possible due to the existence of broad transition zones. 2.3. Sampling and analyses The contact between the soil and the serpentine parent material was rarely prominent to determine the effect of climatic conditions on soil formation. Nickel concentrations show relatively little variation with increasing depth below 10 cm (Berrow and Reaves, 1986). Soil samples (0–15 cm) were collected from 192 serpentine soils in the Western Anatolia and the Eastern Thrace of Turkey. Subsamples obtained from each station were mixed on a polyethylene blanket to prepare a homogenous sample. Total research area was about 400,000 km 2, possibly covering all visible serpentine soil formations in the region. Soil samples were taken every 25–100 km2 from extensive ultramafic rocks. Geological map of 1:100,000 scale prepared by Turkish State Mineral Research & Exploration was used for spotting serpentinite locations and for designating the survey routes. The coordinates and elevation of the sampling locations were determined by using a handheld Magellan eXplorist XL receiver, with 3–6 m accuracy. Soil subsamples from a serpentine location were mixed, homogenized, passed through a 4 mm plastic sieve in situ and filled in polyethylene bags. Anthropogenic polluted lands were rejected to avoid possible interferences (Massoura et al., 2006; Němeček et al., 2001). Cultivated lands developed on serpentinites were also not sampled considering possible pH etc. interactions which may arise from agricultural chemicals. A laboratory meter was used for pH measurements of a 1:2.5 of soil: water dilution. Free carbonate contents of the soils were determined with a manometric pressure calcimeter (Loeppert and Suarez, 1996). Air dried ≤2 mm 50 g oven-dried soil was extracted with 100 mL of a DTPA solution consisting of 0.005 M diethylene triamine pentaacetic acid, 0.1 M triethanol amine, and 0.01 M CaCl2 at pH 7.3 (Lindsay and Norvell, 1978) and 25 °C ± 1, shaken for 2 h. Extracts were centrifuged at 5000 rpm and gravimetrically filtered from Whatman cellulose filter grade 42. PerkinElmer® Optima™ 7000 DV ICP optical emission spectrometer (ICP-OES) was used for determining DTPA extractable nickel (DNi) concentration (Miller, 1998). Analysis was carried out with three parallels. Total elements of acid digested samples were determined using ICP-MS (ICP-mass spectrometer) (Hossner, 1996). For total Ni, 0.1 g of the soil was digested in 3.5 mL of aqua regia (ultrapure mixture of concentrated HNO3/HCl, 1/3 (v/v)) on an aluminum block and diluted with 5 mL of 0.2% HNO3. Total Ni analyses were double-checked by another method as follows: 0.2 g of soil sample was digested with wet digestion in 8 mL of aqua regia in 60 mL standard digestion vessels. The solution was placed in a Berghof Speedwave® microwave digestion instrument, v 1.2.2 software, at 180 °C under 40 bar pressure for 20 min as was suggested by the manufacturer. Total Ni concentrations were determined by PerkinElmer® Optima™ 7000 DV ICP optical emission spectrometer. The total Ni context data obtained from the latter was used and reported where necessary. 2.4. GIS studies and mapping Climatic data (1975–2010) of 185 stations in the area studied were obtained from the Turkish State Meteorological Affairs. ANUSPLIN and ARC GIS 8.1 software packages were largely employed for generation of local climatic characteristics to prepare comparative maps using digital elevation model (DEM) (Tunçay et al., 2006). Procedures from the ANUSPLIN software were used to fit the thin plate spline functions, which were trivariate functions of longitude, latitude and elevation (Hutchinson, 1991). ANUSPLIN package allows for arbitrarily many surfaces and introduces the concept of surface independent variables, so that they may change systematically from one location to another. The DEM ready to use is a map converted from a 1:250,000 scale digital topographic map with a resolution of 0.01° covering the study area. After the small scale DEM data were used in generating climatic
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Table 1 Selected parameters of the soils studied. GPS coordinates
DNi mg kg−1
pH
EC dS m−1
Texture
Free carbonates %
OM %
N N N N N N N N N N N N N N N N N N
14.5 35.7 12.6 143 10.1 41.5 13.0 39.6 14.1 52.2 56.8 20.3 11.5 33.2 24.2 14.8 28.8 10.3
7.75 7.65 7.48 7.69 7.81 7.68 7.96 7.36 8.62 7.24 8.22 8.14 7.73 7.89 7.91 7.90 8.10 8.22
0.12 0.13 0.13 0.12 0.10 0.16 0.18 0.07 0.42 0.13 0.36 0.16 0.12 0.11 0.24 0.21 0.21 0.30
SL SCL SCL CL SCL L SCL CL SL CL CL SL SL SCL SCL CL C L
udl udl udl udl 1.14 udl 2.81 udl 1.82 1.14 udl 2.27 1.79 udl 10.1 3.25 1.00 3.14
1.11 5.04 1.31 5.34 1.21 3.53 2.12 3.88 1.26 2.55 4.25 3.19 1.49 1.79 3.80 5.82 3.18 5.08
37 37 36 36 36 36 36 36 36 36 37 37 37 38 38 38 39 39
06.786, 06.385, 51.271, 54.525, 44.682, 44.653, 46.586, 51.306, 21.519, 53.759, 39.680, 12.960, 51.594, 02.332, 36.695, 43.316, 36.219, 35.364,
E E E E E E E E E E E E E E E E E E
28 36.181 28 39.250 28 32.396 28 35.726 29 00.391 28 52.634 27 59.917 28 12.205 35 55.299 28 17.826 28 52.228 28 41.008 30 54.649 31 21.483 27 45.059 29 41.500 29 56.791 29 57.452
pH and EC: from 1:2.5 suspension, udl: under detection limit.
3. Results and discussion 3.1. Properties of the soils The basic approach in searching for the climatic effects on soil properties was that they have the common origin of the parent material, i.e. serpentinite. Selected properties of a number of soils containing more than 10 mg kg−1 DNi were identified (Table 1). Soil pH in the area studied varied between 7.24 and 8.62 with most values from 7.5 to 7.8. Those pH ranges support the view that the climatic conditions in the area were conducive for the persistence of bases in the soils. Salinity was not troublesome with any soils where their free carbonate content was normally less than 1% with a few exceptions, i.e. only one sample contained 10.1% carbonates. This dominant deficiency of free carbonates was not attributed to leaching as no acidic reaction was detected with the soil samples. Textural classes were usually around loamy groups. A few numbers of relatively high organic matter containing soils suggested that serpentine soils may be fertile under favorable environmental conditions. Studying the poor vegetation was outside of our research scope. Organic matter contents of the surface soils were generally between 1 and 4%, which is expected in arable soils under temperate climatic conditions (Bot and Benites, 2005). Comparing the samples with other regional soils, it appeared that the soils studied have relatively lower organic matter and lime contents with medium texture. 3.2. DNi concentration DNi concentration of the soils was highly variable. The DTPA extractable pool is considered to be a measure of the amount of potentially plant-available metal in the soil (Bani et al., 2009; Li et al., 2003). Numbers of arbitrarily selected ranges of the DNi concentrations are represented in Fig. 1. The highest DNi concentration among 192 soil samples, 143 mg kg−1 DNi was 5.75% (F-DNi) of total 2480 mg kg−1 (TNi) of its own soil. Many samples contained less than 0.1% DNi, correspondingly having very low F-DNi. These small ratios made it difficult to separate the roles of climatic conditions, soil genesis, topographic components, geological and vegetative history in the development of the extractable nickel concentrations.
The first conclusion to be drawn was relatively weak (positive and exponentially significant, P b 0.05) relationship between TNi and DNi in the soils (Fig. 2). Previous surveys of serpentine sites provided total nickel analysis, which were of restricted ecological value since such figures needed not directly reflect availability to plants. If DTPA extraction resembles phytoavailability to an extent, seeking or establishing correlations with the total amount in soils and the accumulation in plant body might probably be difficult. The possible causes of considerable variation in soluble and total nickel of British serpentine soils were discussed in terms of the influence of maritime conditions and weathering regimes (Slingsby and Brown, 1977). 3.3. pH dependency of DNi and F-DNi concentrations Important factors affecting Ni phytoavailability in soils are pH as well as the presence and abundance of organic materials, hydroxides, clay minerals, cations, and complexing ligands (NRCC, 1981). Soil pH has a close relationship to the phytoavailability of heavy metals controlling their solubility and their capacity to form chelates in the soil. Soil pH versus DNi was evaluated as an accepted major soil parameter controlling nickel solubility in the soil (Ge et al., 2000; Gray and Mclaren, 2006; Tye et al., 2004). However, the degree of the relationship among parameters was so formulated that site-specific modifications of values of partitioning coefficients (Kd) to input into environmental fate models should minimally be correct for pH effects especially when using an empirical approach (Sauvé et al., 2000), underlining the importance of other environmental parameters as well as pH of the soil.
80
Number of samples
surfaces, all climatic maps were re-projected to the geographic coordinates with 0.5° × 0.5° resolution. DNi data were tabulated into 6 arbitrary range classes to provide fitting in ARC GIS 8.1 software for mapping.
66
70 60 50
43
40
28
30
27
20
15
10
11
0 <1
1-5
2 5-10
10-20
20-40
40-80
Ni content range (mg kg-1)
80-150
Fig. 1. DTPA extractable nickel concentration ranges of the soils.
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120
80
100
DNi, mg kg-1
100
DNi, mg kg-1
a 120
y = 0.233e0.002x R² = 0.89 P<0.05
60 40 20
y = 83.774x2 -1327.4x + 5273.4 R² = 0.175, n.s.
80 60 40 20
0 0
500
1000
1500
2000
2500
0 7.20
3000
7.40
7.60
TNi, mg kg-1 Fig. 2. The relationship between total and DTPA extractable Ni concentrations of the soils, the curve indicates exponential relationship.
7.80
8.00
8.20
8.40
Soil pH
b
4.5 4
3.4. Influence of rainfall and temperature Meteorological data were gathered from the available centers. The soils were grouped in provinces to facilitate scrutinizing the influence
3.5
y = 7.7237x2-119.83x + 465.04 R² = 0.285, n.s.
F-DNi
3 2.5 2 1.5 1 0.5 0 7.3
7.4
7.5
7.6
7.7
7.8
7.9
8
Soil pH
c
4 3.5 3 2.5
F-DNi
The pH ranges of the soils studied were between neutral and alkaline. The relationship of pH of 1:2.5 soil suspensions versus DNi concentration indicated a negative tendency, i.e. higher pH values resulting in lower DNi concentration (Fig. 3a). Less alkaline soil reaction also resulted in higher F-DNi (Fig. 3b). However, a weak and inconsistent correlation between Ni extractability and soil pH was observed (for DNi: R2 = 0.175, n.s. and for F-DNi: R2 = 0.285, n.s.). The polynomial curve, which fitted the best, indicated a less sloping line above pH 8.03 likely suggesting less dependency of DNi with soil reaction within these small ranges. The close similarity of the graphs, one of which showed the soil pH vs. DNi (Fig. 3a) and the other pH vs. F-DNi (Fig. 3b) relationship indicates the effect of pH on Ni extractability and perhaps potential influence of other soil components on eventual soil reaction. If varying Ni release was attributed to soil pH ranges based on the similar trends of these two figures, it could be concluded that TNi content hardly influenced weathering processes and corresponding Ni release under studied conditions. Results showed a more pronounced effect of soil pH on nickel extractability with acidic conditions as documented by several studies: The amount of Ni extracted by DTPA was found dependent on pH of the soil sample, with retention dramatically increasing above pH 7.0 to 7.5 and Ni was somewhat less extractable than Pb, Cu and Zn, with that sorbed by the highest pH soils being the least extractable (Harter, 1983). Higher pH values (above 8) or organic matter content increased the amount of Ni adsorbed on the soil particles (Ge et al., 2000). Decreased Ni toxicity at 7.2 pH compared to pH 6.2 on corn (Wallace et al., 1977) was supported by similar findings with tomato and barley, where varying results from soil to soil was attributed to different cation exchange capacities of the soils (Rooney et al., 2007). Nickel concentrations in shoots of two Alyssum species were reported to increase with higher pH soil despite a decrease in water-soluble soil Ni (Kukier et al., 2004), opposite to that seen with agricultural crop plants, this result again indicating complexity of the effects of soil pH on Ni availability and plant growth. Staunton (2004), discussing these pH dependent variations, proposed a radiotracer technique to explain the changes. Soil pH is naturally expected to influence almost all weathering processes. The effect of pH on F-DNi was nonsignificant in this study, likely because of the narrow variation ranges. Then, a transcendental plotting, which could give positive relationships was also tried (Fig. 3c). The findings were interpretable enough as follows: R 2 = 0.586 and P b 0.01. This specific graph, although seems scientifically acceptable, is deliberately reported with the reservations of limited literature citation on the matter, inadequate sample numbers and limited pH ranges used for plotting.
2 1.5 1 0.5 0 7.3
7.5
7.7
7.9
Soil pH Fig. 3. pH dependency of D Ni (a) and F-DNi (b–c) concentrations of the soils.
of climatic conditions on their phytoavailable Ni concentrations. The soils developed under Mediterranean climate with hot and dry summers and rainy during the winter time had more DNi and F-DNi than those soils formed in the arid central Turkey (Table 2). If Bursa, located at a transition zone, were to be ignored, average DNi concentration of the Adana soils was the only exception and this may be explained by being mountainous. The serpentine soils of the higher rainfall regions, including Muğla (1127 mm) and Hatay (1084 mm) had the highest DNi concentrations. Partial high variation coefficients of a few provinces and positive skewness coefficients made them less reliable. Negative and low positive skewness of several groups as well as relatively small standard deviation and variation coefficients suggested higher reliability. Both annual precipitation and mean temperature gave positive correlation with DNi and F-DNi (Figs. 4 and 5) indicating that those climatic components remarkably influenced weathering processes. It was hardly possible to discriminate the roles of the temperature and rainfall due to frequent coincidence of higher temperature and more precipitation at the same stations. Higher R2 value of precipitation versus
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Table 2 The relationship between average precipitation, mean temperature and DTPA extractable nickel distribution. Climate components
Statistical components
R, mm
A
T, °C
mg kg Bursa Aksaray Adana Ankara Bolu Kayseri Niğde Eskişehir Konya Çanakkale Manisa Kütahya Isparta Antalya Mersin Burdur Denizli Hatay Muğla
674 350 657 405 550 397 327 367 321 591 702 547 494 1052 572 405 546 1084 1127
14.5 11.9 19.1 11.8 10.4 10.4 11.0 10.6 11.4 14.9 16.9 10.6 12.0 18.2 19.2 13.0 16.1 18.2 14.9
M −1
Ni
0.19 0.34 0.64 0.88 1.20 1.56 1.62 2.19 3.31 3.93 4.16 5.10 7.00 8.05 8.28 11.1 13.8 18.3 26.1
mg kg−1 Ni
SD
VC
SC
n
0.24 0.27 0.27 0.80 0.51 1.96 0.48 0.89 2.49 3.79 0.28 1.45 1.97 10.3 8.49 4.91 8.37 19.8 12.8
0.11 0.13 1.12 0.69 1.41 1.20 2.46 3.06 3.27 4.06 8.93 7.99 10.5 6.04 1.09 12.6 16.6 3.66 29.7
0.01 0.01 1.10 0.41 1.33 1.19 4.53 8.03 9.60 12.3 68.3 58.9 98.6 33.2 0.95 147 252 8.92 865
−1.58 1.73 2.81 0.85 1.68 −0.62 1.96 2.25 1.28 0.06 2.54 2.48 2.06 0.31 −0.99 1.39 1.92 −1.51 2.02
3 3 8 7 3 6 4 7 10 4 7 13 10 11 5 15 11 3 48
R: Annual rainfall (mm), Temperature normal (°C), A: Average, M: Median, SD: Standard deviation, VC: Variation coefficient, SC: Skewness coefficient, n: Number of soil samples. Bold figures for prevailing Mediterranean climate.
DNi concentration suggests that weathering of nickel containing minerals in the serpentine soils could be more dependent on the rain rather than the mean temperature. The less twisted concave polynomial curve of the DNi vs. rainfall and F-DNi vs rainfall may likely indicate increasing influence of rainfall on Ni release, whereas convex curves were obtained with mean temperature recordings. The effect of mean annual temperature normal on F-DNi was statistically nonsignificant. This fact again supports prevailing role of rainfall on weathering as a climate component. Prevailing characters are highlighted to differentiate the Mediterranean from continental climatic for the sampling areas (Table 2). DNi concentrations might change considerably within short distances because standard deviation and variation coefficient were high particularly in
the Mediterranean Zone, the south and west regions of Turkey. Deviations were attributed to varying ages of the soil development. None of the Central Anatolian soils were found containing more than 10 mg kg−1 DNi (Figs. 6 and 7). As most of the meteorological stations were located in or near the towns, an additional GIS analysis was performed to provide crossing of climatic data to the sampling points, almost all of which were in rural areas. Multiple regression analyses suggest that precipitation and mean temperature altogether were responsible for 52.6% (P b 0.01) of DNi extractability (Fig. 8a). Coefficient of the standard deviation for this analysis was 21.6 and the best fitting linear equation confirms reliability of the relationship. It seems that mean temperature and the amount of annual
a 30 a
y = 4E-05x2-0.037x + 12.8 R² = 0.553, P<0.01
20
30 25
DNi, mg kg-1
DNi, mgkg-1
25
15 10 5
y =-0.33x2+ 10.4x -71.6 R² = 0.257, P<0.05
20 15 10 5
0 200
400
600
800
1000
0
1200
9
11
Annual rainfall, R, mm
3
F-DNi, %
b
4
y = 4E-06x2-0.0029x + 0.9296 R² = 0.597, P<0.01
2
17
19
21
y =-0.0469x2+ 1.4532x -10.067 R² = 0.2205, n.s.
5
3 2 1
1
0 200
15
4
F-DNi, %
b
13
Mean temp normal, T, oC
0 10 400
600
800
1000
1200
12
14
16
18
20
Mean temp normal, T, oC
Annual rainfall, R, mm Fig. 4. The relationship between its annual rainfall and DNi (a) and F-DNi (b) concentrations of 19 provinces having at least three soil samples, straight line indicates relationship.
Fig. 5. The relationship between its mean temperature normal and DNi (a) and F-DNi (b) concentrations of 19 provinces having at least three soil samples, straight line indicates relationship.
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Fig. 6. The relationship between annual rainfall (mm) and DTPA extractable Ni concentrations of the soils.
rainfall are greatly responsible for the release of Ni where its total amount in the serpentines is not considered. 3.5. Total Ni and percent DNi concentrations The ratios of DNi to TNi concentrations were between 0.05 to 3.91%, with an average F-DNi value of 0.61%. These small percentages may not be readily correlated relatively slow release of Ni from the serpentines. Ure and Berrow (1982) stated that Ni is relatively easily mobilized during weathering, due to its abundance in quick weatherability from ferromagnesian minerals. Yet, serpentine soils still have potential available sites for further Ni adsorption and the presence of hydrous Mn oxides in these soils as well as Fe oxides determine the Ni sorption capacity (Alves et al., 2011). Large variations of F-DNi suggested that the
climatic factors are the most significant factor in weathering of the serpentine soils (Table 3). The multiple regression analyses showed that 59.8% of DTPA extractability from total Ni content could be explained by combined effect of precipitation and mean temperature (Fig. 8b). The best fitting cubic relation was significant (P b 0.01) and the coefficient of standard deviation was 0.61. This combined effect, relying on previously mentioned limited effect of mean temperature on F-DNi may not completely define the historical background of study conditions. Organic matter content, texture (Siebielec et al., 2007), pH (Horak and Friesl, 2007; Weng et al., 2004), CEC, aeration degree (Kabata-Pendias, 2004) and biological activities (Díaz-Raviña and Bååth, 1997) were reported to be the main factors affecting extractable Ni concentration in the soil. The ratio of DNi to total Ni contents range could be associated with the accumulation in plant tissues.
Fig. 7. The relationship between mean annual temperature normal (°C) and DTPA extractable Ni concentration of the soils.
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The highest DNi concentrations of 9 soils were found in the Mediterranean region. The highest TNi concentration was 2840 mg kg − 1. It is expected that Ni leaching process is slower in the temperate than hotter and rainy tropical regions or acidic soils. Massoura et al. (2006), reinforced the hypothesis stating that the Ni concentration was relatively limited in ultramafic primary minerals and poorly enriched in secondary neoformed phyllosilicates (generally 0.2–0.3%, with a maximum value of 0.5%) under temperate and Mediterranean environmental conditions. The highest DNi containing 3 soils (A1, A2 and A3) showed that DTPA extractability nickel concentration of the serpentine soil could be as high as 5.77% of the total under study conditions. Actually, that maximum ratio should be expected smaller, as larger particles, of which specific surface area is limited were eliminated at a couple of locations by sieving the soils to 4 mm during sampling.
3.6. Other heavy metals in the soils
Fig. 8. a. The combined effect of annual precipitation and mean temperature on DNi concentrations. b. The combined effect of annual precipitation and mean temperature on F-DNi.
Total analysis showed common properties of the serpentine soils which were high in Fe, Mn, and low in Al and Ca contents (Tables 4a and 4b). Total amounts, however, do not necessarily represent phytoavailable heavy metal concentration. Extremely low Ca/Mg ratio is most likely due to low Ca contents of the soils derived from serpentine. Iron, Cr, Co and Mn contents of the selected serpentine soils are higher than those reported in the literature (Alexander et al., 2007). These amounts may be more attractive for mining rather than for plant growth. Weak growth of normal plants on serpentine soils may be due to a number of factors including a number of nutrient deficiencies (Ca, P, N, K, and Mo) (Brady et al., 2005; Chaney et al., 2008; Chiarucci et al., 2003; Spence and Millar, 1963) and in acidic serpentine soils due to Ni phytotoxicity (Anderson et al., 1973; Brady et al., 2005; Halstead, 1968; Kazakou et al., 2008). Although many serpentine soils have anomalous levels of Co, Cr and Mn compared to average soils as the results obtained from the study soils showed (Table 5), there is no evidence that these elements actually limit plant growth on serpentine soils. Decreasing order
Table 3 DTPA extractable (DNi), total (TNi), and fractional (F-DNi) nickel concentrations of selected serpentine soils (Ni mg kg−1 soil). Location
GPS coordinates
Elevation (m)
DNi
TNi
F-DNi
32.3 37.4 49.2 566 34.1 25.7 1780 72.3 372 147 1610 1280 89.5 49.4 960 737 805 426 930 1490 344 75.2 843 142 58.7 2610 2550 2680 1970
0.87 0.21 0.53 0.14 0.32 0.54 0.71 0.71 0.16 0.05 0.76 0.9 0.31 0.57 0.27 0.3 0.36 0.07 0.37 0.07 0.34 0.32 0.46 0.34 0.47 1.26 2.05 3.91 0.27
% Adana, Kozan-Feke Adana, Saimbeyli Aksaray, Ihlara, Melendiz Ankara, Karagedik Ankara, Nallıhan Ankara, Gülhüyük Antalya, Çandır, Demirciler Bolu, Abant, Çepni Burdur-Fethiye, Karaçal Bursa, Orhaneli, Doğancı Denizli, Karacahöyükavşarı Isparta, Eğridir-Gelendost Isparta, Sütçüler, Çobanisa Isparta, Cankurtaran Kayseri, Yeşilhisar, Araplı Kırşehir, Akpınar Konya, Altınekin, Sarıtaş Konya, Beyşehir yolu Konya, Çeşmelisebil Konya, Kulu, Kandil Konya, Taşkent Kütahya, Çavdarhisar Kütahya, Seyitömer Kütahya, Tavşanlı, Andız Manisa, Doğankaya Muğla, Köyceğiz, Sultaniye Muğla, Balandağı Muğla, Marmaris, Çetibeli Niğde, Pozantı-Çamardı
N N N N N N N N N N N N N N N N N N N N N N N N N N N N N
37 38 38 39 40 39 37 40 37 40 37 37 37 38 38 39 38 37 38 38 36 39 39 39 38 36 36 36 37
34.661, E 35 50.433 00.261, E 36 05.707 24.348, E 34 07.663 25.300, E 32 52.204 06 662, E 31 36.901 05.938, E 33 33.746 02.146, E 31 03.533 35.051, E 31 16.319 33.804, E 30 04.861 05.779, E 28 56.543 32.201, E 29 26.680 51.594, E 30 54.649 29.000, E 31 01.147 14.749, E 31 20.077 15.522, E 35 04.411 21.957, E 34 00.608 18.870, E 32 54.037 51.779, E 32 23.027 37.815, E 32 32.503 58.267, E 32 31.064 55.512, E 32 29.485 16.761, E 29 56.674 33.770, E 29 53.593 29.906, E 29 53.138 59.856, E 27 57.022 54.525, E 28 35.726 53.128, E 28 18.941 59.539, E 28 19.881 39.979, E 34 59.901
385 1058 1114 1090 473 975 500 1125 927 370 936 1054 1146 1200 1395 1125 1030 1325 1077 1248 1529 1150 1134 980 574 11 706 134 1230
0.28 0.08 0.26 0.8 0.11 0.14 12.6 0.51 0.6 0.07 12.2 11.5 0.28 0.28 2.59 2.18 2.93 0.28 3.45 9.89 1.16 0.24 3.89 0.48 0.28 32.8 52.2 105 5.29
İ. Ünver et al. / Geoderma 202–203 (2013) 203–211
210
Table 4a Total macro elements metal and metalloid concentrations of the selected soils (g kg−1). Soil➔ Ni Fe Ca Mg Na K P S Al Ti
A1
A2
A3
2660 80.9 3.30 74.1 0.05 0.80 0.23 b0.50 6.80 0.10
2490 88.8 1.60 74.9 0.04 0.70 0.09 b0.50 7.00 0.12
2660 77.9 6.60 131 0.23 0.60 0.16 b0.50 5.00 0.08
of As, Co, Cr, Fe, Mn, and Pb from the soil A1 to A3, with the similar tendency of Ni, implied that weathering conditions may affect the DTPA extractable concentrations of those metals. Three soil samples were certainly not enough to draw a conclusion, but this seemed to deserve further attention.
It was confirmed that DTPA extractable nickel concentration of the soils studied could be an indication of the degree of weathering processes in serpentines. The soil pH, changing within relatively narrow ranges, between neutral and moderately alkaline had a weak immobilizing effect on the soils studied. Annual precipitation and mean air temperature have remarkable influence on the DNi and F-DNi amounts. As expected, the effect was more pronounced under Mediterranean conditions than semiarid temperate continental climate regions. DNi concentrations of the serpentine soils may change from trace to 143 mg kg −1 dry soil suggesting that the range of DTPA-extractable Ni is a poor indicator for estimating total Ni concentration in serpentine soils. Acknowledgments This study was funded by TUBITAK (The Scientific and Technological Research Council of Turkey) as project no: TOVAG-105O635. We gratefully acknowledge the cooperation and guidance of Dr. A. Table 4b Total micro elements metal and metalloid concentrations of the selected soils (mg kg−1). Soil➔
Ni As Co Cr Cu Fe Mn Pb Zn
A1
A2
A3
143 0.07 2.36 0.02 0.78 96.7 82.9 0.42 2.29
105 0.06 1.22 0.01 0.79 39.1 62.9 0.28 1.38
75.6 0.04 0.57 0.01 0.41 18.4 13.2 1.58 5.64
Karabulut Aloe and Dr. İ. Bayramin in the GIS studies and in generating the maps. We are deeply indebted to Dr. E. Başpınar and Ms E. Özgümüş for their generous knowledge-sharing and stimulating advice in statistical evaluation.
References
4. Conclusions
Mo Cu Pb Zn Ag Co Mn La As U Cr Th Sr Sb Bi V Ba B W Hg Sc Tl Ga Se Au 10−3
Table 5 DTPA extractable heavy metal concentrations of the selected soils, mg kg−1.
A1
A2
A3
0.2 11.9 13.1 63 b0.1 154 1340 4 2.1 0.3 631 1.0 13 b0.1 b0.1 29 33 b20 b0.1 0.11 7.7 b0.1 2 0.6 0.6
0.2 14.5 7.5 87 b0.1 166 1570 4 2.0 0.4 536 1.3 7 b0.1 b0.1 26 27 b20 b0.1 0.09 8.0 b0.1 2 b0.5 0.8
0.3 15.9 47.7 164 b0.1 160 1270 4 2.2 0.3 211 1.2 13 b0.1 b0.1 17 29 b20 0.1 0.10 5.7 b0.1 2 b0.5 1.6
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