Spatial Distribution and Bioavailability of Some Essential Trace Elements in Southern Ondo State Nigeria

The total elemental content of soil though may give abundance of element concentration but have been found not to be suitable for prediction of environmental bioavailability and toxicity by scientific community. Surface (0-30cm) and subsurface (60-90cm) soil profile in the Southern Ondo State Nigeria were investigated for spatial distribution, bioavailability and mobility of some essential trace elements (Cu, Fe, Mn, Zn). Their spatial distribution were very similar in both surface and subsurface soil environment indicating that similar geochemical factors may be responsible for their distribution. The North was composed of basement complex while the South was largely undifferentiated sedimentary rock. Higher concentrations of Cu, Fe, Mn and Zn were recorded in the North through the centre of study area to lower concentrations in the South. The spatial concentration of the trace elements may have been influenced by the nature of underlying bedrock type. Cu was potentially bioavailable in both surface and subsurface soil environment considering the fact that >50% of its total concentration were in the nonresidual fraction. Other trace elements were not bioavailable because >60% of their total concentrations were found in residual fractions. The relative risk assessment code of Cu (surface; subsurface) indicated progressive risk (MoF1, MoF2, MoF3) from low (2-10; 1-6) through medium (12-30; 10-21) to high risk (25-40; 21-35) in both surface and subsurface soil environment while Zn (surface) shows similar trend (1-5; 11-21; 22-35) only in the surface soil environment. Other elements show some level of risk to no risk. There is likelihood that Cu and/or Mn may be associated with anthropogenic sources.


Introduction
Soil is a part of the ecosystem and it occupies a basic role for humans, because the survival of man is tied to the maintenance of its productivity (Gruhn et al, 2003).Soil functions as a filtering, buffering, storage, and transformation system; thus it protects against the effects of element pollution (Blum et al., 2006).Soil is effective in these functions only as long as the physical, chemical and its biological activities are preserved.Soil is the main source of trace elements for plants both as micronutrients and as pollutants (Kabata-Pendias & Mukherjee, 2007).It is also a direct source of these elements to humans due to soil ingestion affected by "pica-soil", geophagia, dust inhalation, and absorption through skin (Bisi-Johnson et al 2010).
It has been assumed that the behavior of elements in soils and in consequence their bioavailability differ as to their origin (Zhang et al, 2002).The element transfer from soil is a very complex process governed by several factors, both natural and affected by humans (Roivainen et al, 2012).Soil processes (Retallack, 2001) and anthropogenic factors (Mirsal, 2008) are the major factors that control the behavior of elements in soil.Several recent reports have indicated that regardless of the forms of the anthropogenic elements, their availability to plants is significantly higher than those of natural origin (Kabata-Pendias & Mukherjee, 2007;Alloway, 2013).
Elements present in soils can be associated with several reactive components.Although total element concentrations may indicate the overall level of elements in soils, they provide no information regarding the chemical nature or potential mobility and bioavailability of a particular element (Vijver et al., 2004;Jin et al., 2005;Powell et al., 2005).Sequential fractionation is a frequently used approach to evaluate element distribution into different chemical forms present in a solid phase.Conceptually, sequential fractionation categorizes elements associated with chemically homogeneous fractions that, ultimately, affect element availability (Clemente et al, 2008;Nobuntou et al, 2010;Burt et al, 2011;Cornejo-Ponce & Acarapi-Cartes, 2011).Although often criticized due to lack of specificity of extractants and possible readsorption of elements during extraction (Rao et al., 2008).Sequential fractionation can provide useful information to predict the fate of heavy metal in the environment (Michalke, 2003;Michalke, 2009;Ajmone-Marson & Biasioli, 2010;Nannoni et al, 2011;Luo et al, 2012).
The mobility of heavy metals in soil samples can be evaluated by dividing the fractions that are weakly bound to soil components with all fractions (Kabala & Singh 2001).These are usually classified according to a risk assessment code (RAC) based on the strength of the bond between the element and the different geochemical fractions in soils and the ability of the elements to be released and enter into the food chain (Rodriguez et al, 2010).The RAC expressed as a percentage, is defined by taking the ratio of the mobile fractions (water soluble and exchangeable fractions) to the total concentration of elements in the soil.However, Batjargal et al (2010) has expressed that exchangeable and carbonate bound fractions are bioavailable and additionally, fraction bound to Fe/Mn oxides could be leached by weak acidic solution.Consequently, it is therefore necessary to assess the possible contribution of these potentially leachable pools of elements to bioavailable component and thus ascertain their risk in the environment.
Generally, the extent of anthropogenic contamination can be expressed using the enrichment index and it has been widely used by several authors in order to establish the degree of contamination by elements (Rubio et al., 2000;Loska et al., 2003;Ghrefat et al., 2011;Ahiamadjie et al., 2011;Likuku et al., 2013).This index is usually computed by averaging the ratios of the concentrations of the measured element to the hazard criteria or to the soil quality guidelines for that element.It is notable that neither in Nigeria nor sub-Saharan Africa have soil quality guidelines been established.Thus, the determination of permissible levels of element concentration in soil and the application of such standards as used by other countries may not be easy as there could be varying lithography.Hence rather than expressing the enrichment index (equation 1) as an estimate of pollution, it can as well be used as an estimate of possible anthropogenic influences on the surface environment assuming that under normal conditions pedogenic process on the subsurface soil should give rise to surface soil.
where, Xi is concentration of the metal in bulk soil in surface environment, Xref is the concentration of the Ti in bulk soil in surface environment, Yi is the concentration of metal in subsurface environment", Yref is the concentration of the Ti in subsurface environment.Values>1.0indicate accumulation of metals in soils due to anthropogenic sources while values of 1.0 and <1.0 show that enrichment of metals is not detectable and loss of metals due to pedogenic processes (Acosta et al, 2011).

Sampling Description
Southern part of Ondo State lying between 6 o 15'N-5 o 10'E and 7 o 00'N-4 o 20'E, wherein lies the bitumen belt, was divided into regular grids of 12.5 X 12 sq.Km and in each of the grid, five points were sampled and pooled to represent a field composite sample (Figure 1).All samples were georeferenced using Geographic Positioning System (GPS).Each sample was air dried in the open laboratory, picked, disaggregated using mortar and pestle, sieved through 2mm nylon mesh (British Standard) and stored in poly propylene bottles prior to analysis (Patnaick, 2004).3).Tota onment (Figur in both the su han the subsu subsurface (F concentration plex while the n map for su g the highest w on of subsurfa higher values o ace environme concentration i ent is similar t nt (Figure 10).

Bioava
The results surface environment while only Cu is therefore potentially mobile in subsurface soil environment.This could be tantamount to their bioavailability considering the conclusion of Ma & Rao (1997).Rastmanesh et al., (2010) has expressed that residual fraction constitutes a significant proportion for all elements.Kaasalainen & Yli-Halla (2003), the proportion of the residual fraction reflects native metal concentration in soil.Consequently, the metal Fe in the surface and Fe, Mn, Zn in the subsurface environment of the southern part of Ondo State, Nigeria were not potentially bioavailable and they constitute probably the native concentrations in soil of the area under study.There was similar observation in the work of Agbaire & Akporhonor (2014) but the view of Aikpokpodion et al. (2012Aikpokpodion et al. ( , 2013) ) differs.Generally, the metals in the surface environment were more bioavailable than subsurface environment considering the relative larger value of residual fractions of the latter.Water soluble + Exchangeables were very low in all metals and within the surface and subsurface environment.Percentage of metals that are acid leachable or oxidisable were very high and a change in these conditions would increase the bioavailable metals in the two environment.The order is as follows for metals in surface and subsurface environment: Surface: Cu, F6>F2>F3>F4>F5>F1; Fe, F6>F5>F4>F3>F2>F1; Mn, F6>F5>F4>F2>F3>F1;

Mobility of Cu, Fe, Mn and Zn from the Soil Matrix
Three mobility factors were defined thus: (i) soluble+exchangeable, (ii) soluble+exchangeable + carbonates and (iii) soluble+exchangeable + carbonates + bound to Fe/Mn oxides to total concentrations of the element in the soil.According to Rodriguez et al (2009), there may be no risk when these fractions represent lower than 1% of the total concentrations, low risk for 1-10%, medium risk for 11-30%, a high risk for 30-50% and a very high risk for higher percentages.All the metals in this study were more mobile in the surface than the subsurface environment .Considering the mobility factor in terms of relative percent of soluble + exchangeables for the elements shows that Fe was with no risk at both surface and subsurface environment while Cu, Mn and Zn were with low risk.However, Fe was with low risk at both surface and subsurface environment; Cu was associated with medium risk in both environments, Mn was with low risk in the surface and medium risk in the subsurface; Zn was associated with medium risk in the surface and low risk in the subsurface when the relative percent of soluble + exchangeables + carbonate were considered.Moreover, the relative percent of soluble + exchangeables + carbonate + Fe/Mn oxides indicated that Cu was with high risk in both surface and subsurface environment; Fe was with low risk in both; Mn was with medium risk in both while Zn was with high risk in the surface and medium risk in the subsurface.The mobility of Cu, Fe, Mn and Zn increases progressively with severity of prevailing conditions.However, the progressive increase in the risk of Cu from low risk through medium risk to high risk in both surface and subsurface environment and similarly that of Zn in surface environment is noteworthy.

Conclusion
Total trace metal composition of soils are of little importance in determining the total trace metal uptake by plants and consequent level of risk these elements may pose to plants and the food chain.This is because different binding forms have different mobilities, bioavailabilities and potential environmental Forest areas can be prone to trace element changes when industrial and mining activities are introduced and the consequences of bioaccumulation of these elements are obvious.Southern Ondo State is prone to future industrial and bitumen exploitations and there is need to document the industrial and mining pre activities.This studies has therefore indicated that Cu and probably Zn could be very mobile in this environment and may pose some level of risk to ecosystem and underground water aquifers.This risk may be greater than predicted as future industrial and mining activities may increase total concentration load of the metals and also may have negative impact on the soil physicochemical properties most especially soil acidity.This will increase the portion that may be soluble, exchangeable and bound to carbonate including oxidisable or reducible.

Table 3 .
Percent phase fractionation of trace elements in surface and subsurface soil environment

Table 4 .
Assessment of sources of Cu, Fe, Mn and Zn in surface environment with Ti as normalizer