Potential genetic impacts of metal content on Northern Red Oak (Quercus rubra) populations from the Greater Sudbury Region during reclamation
By
Anh Tran
Thesis submitted in partial fulfillment of the requirements for the degree of Master of Science (MSc) in Biology
School of Graduate Studies Laurentian University Sudbury, Ontario
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Abstract Genetic diversity is important for species survival and sustainability under environmental stresses and changes. The objectives of the study are to compare genetic variability in red oak populations growing in eroded and stable upland sites and to determine if there are any long term effects of liming on aspects of soil fertility and toxicity, and population variability of red oak. Total and bioavailable metals were measured in samples from different sites within the Greater Sudbury Region. The highest concentrations of metals were found in the upper organic layer, LFH. Only a small fraction of total metals were bioavailable. The level of metal content in the top soil layer was affected by both land topography and the site distance from smelters. The enrichment factor comparing the contaminated versus uncontaminated sites varied between 0.702 and
16.78 indicating environmental pollution. The translocation factors from soil to branches were low for most total elements, but high for bioavailable metals. The pH levels of limed areas were found to be higher than unlimed areas, an indication of the prolonged effect of liming on soil acidity. Genetic analysis of all the red oak populations was conducted using ISSR markers. The level of polymorphic loci in red oak populations from the
Greater Sudbury Region was moderate to high ranging from 43.97% to 64.54%. The mean values of Na, Ne, h and I were determined to be 1.54, 1.22, 0.14 and 0.22, respectively. The levels of inter-population polymorphism and population differentiation
(G s t ) were 97.87% and 34%, respectively. The estimated gene flow (Nm) value was 0.98.
The genetic distance values ranged between 0.125 and 0.611. There was no association between the level of soil metal content and the genetic variation of the red oak populations analyzed. iv Acknowledgements
I would like to take this opportunity to sincerely thank my supervisor Dr. Nkongolo for giving me the opportunity to work in his lab and for his dedication, passion and expertise throughout my research project. To my committee members Dr. Spiers and Dr. Beckett for their assistance with site selection, sample collection and metal analysis. To my labmates Ramya Narendrula, Paul Michael, Melanie Mehes and Gabriel Theriault for their valuable discussions and assistance with sample collection, processing and data analysis. I would like to express appreciation to members of the Elliott Lake Research
Field Station of Laurentian University analysts for metal analysis. I would like to thank my loving parents for their continuous support and believing in me, as well as my friend
Martin Uceda for his motivation when I needed it most. Table of Contents
ABSTRACT...... III
ACKNOWLEDGEMENTS...... V
LIST OF FIGURES...... VIII
LIST OF TABLES...... X
CHAPTER 1: LITERATURE REVIEW...... 1
1 .1 M etal C ontamination in t h e G r e a ter S u d b u r y R e g io n ( O n ta rio , C a n a d a ) ...... 1
1 .2 N u t r ie n t C o n t e n t in S o il ...... 3
1 . 3 S o il A m e n d m e n t ...... 8
1 .3 R evegetation ...... 1 0
1 .4 S pe c ie s o f In t e r e s t ...... 1 2
1 .5 O v e r v ie w o f G en etic variability ...... 1 5
1 .6 .1 M e a su r in g G en etic variability w it h M o l ec u la r M a r k e r s ...... 1 5
1 .6 .2 In t e r -S im p l e S e q u e n c e R e p e a t (ISSR)-PCR ...... 1 8
1 .6 O b je c t iv e s ...... 2 0
CHAPTER 2: METAL ANALYSIS IN RED OAK (QUERCU5 RUBRA) POPULATIONS GROWING IN LIMED AND UNLIMED AREAS IN THE GREATER SUDBURY REGION (ONTARIO, CANADA)...... 21
2 .1 Introduction ...... 2 1
2 .2 M ateria ls a n d M e t h o d s ...... 2 2
2 .2 .1 S a m p l in g ...... 2 2
2 .2 .2 M etal a n d p h a n alysis in s o i l ...... 2 5
2 .2 .3 S ta tistic a l A n a l y s is ...... 2 6
2 .3 R e s u l t s ...... 2 7
2 .3 .1 T o t a l m e t a l o f S o i l ...... 2 7
2 .3 .2 B ioavailable M etal o f S o i l ...... 2 8
2 .3 .3 S o il ph lev els ...... 2 9
2 .3 .4 E n r ic h m e n t Fa c t o r ...... 2 9
2 .3 .5 T ranslocation f a c t o r ...... 2 9
2 .3 .6 T o t a l m e t a l c o n t e n t in leaves a n d b r a n c h e s o f red o a k ...... 3 0
2 .4 D is c u s s io n ...... 4 8
CHAPTER 3: GENETIC ANALYSIS OF QUERCUS RUBRA POPULATIONS FROM METAL CONTAMINATED AND UNCONTAMINATED SITES IN THE GREATER SUDBURY REGION (ONTARIO, CANADA)...... 54
3 .1 Introduction ...... 5 4
3 .2 M a terials a n d M e t h o d s ...... 5 5
3 .2 .1 S a m p l in g ...... 5 5
3 .2 .2 M o lecu la r A n a l y s is ...... 5 6
vi 3.2.3 St a t is t ic a l A n a l y s is ...... 58
3.3 R e s u l t s ...... 58
3.3.1 D e g r a d a t io n A n a l y s is...... 58
3.3.2 ISSR-PCRA mplification a n d P olymorphism ...... 58
3.3.3 G e n e t ic V a r ia b il it y...... 59
3.3.4 G e n e t ic R elationship ...... 60
3.4 D is c u s s io n...... 71
CHAPTER 4: GENERAL CONCLUSIONS...... 75
REFERENCES...... 77
APPENDECES...... 82
vii List of Figures
Figure 1: Map of North America showing the distribution of northern red oak (Quercus rubra)...... 14
Figure 2: Location of red oak sampling sites within the Sudbury region. Site 1: Daisy Lake; Site 2: Wahnipitae Hydro Wahnapitae Hydro Dam; Site 3: Laurentian; Site 4: Kukagami; Site 5: Kingsway; Site 6: Falconbridge; Site 7: Capreol; Site 8: St. Charles; Site 9: Onaping Falls; Site 10: Airport...... 24
Figure 3: Location of red oak sampling sites within the Sudbury region. Site 1: Daisy Lake; Site 2: Wahnipitae Hydro Wahnapitae Hydro Dam; Site 3: Laurentian; Site 4: Kukagami; Site 5: Kingsway; Site 6: Falconbridge; Site 7: Capreol; Site 8: St. Charles; Site 9: Onaping Falls; Site 10: Airport...... 47
Figure 4: Degradation analysis illustrated on a 1% TBE agarose gel for DNA of red oak samples. The top band indicates intact genomic DNA. Lack of smearing is indicative of lack of degradation. Lane 1 contains lkb+ ladder; Lanes 2-21 contains red oak DNA samples...... 61
Figure 5: Dendrogram based on ISSR data for 13 Quercus rubra populations (Free Tree Program version 1.50)...... 65
Figure 6: ISSR amplification of red oak samples with primer ISSR 178 98B. Lanes 1, 22 and 33 contain lkb+ ladder; Lanes 2-21 contain red oak samples from St. Charles population; Lanes 23-32 contain red oak samples from Onaping Falls population. 66
Figure 7: ISSR amplification of red oak samples with primer ISSR UBC 825. Lanes 1, 22 and 33 contain lkb+ ladder; Lanes 2-21 contain red oak samples from Falconbridge population; Lanes 23-32 contain red oak samples from Capreol population...... 67
Figure 8: ISSR amplification of red oak samples with primer ISSR 10. Lanes 1, 22 and 33 contain lkb+ ladder; Lanes 2-11 contain red oak samples from Wahnapitae Hydro Dam Unlimed population; Lanes 13-32 contain red oak samples from Wahnapitae Hydro Dam Limed population...... 68
Figure 9: ISSR amplification of red oak samples with primer ISSR 9. Lanes 1, 22 and 35 contain lkb+ ladder; Lanes 2-21 contain red oak samples from St. Charles population; Lanes 23-35 contain red oak samples from Onaping Falls population...... 69
Figure 10: ISSR amplification of red oak samples with primer ISSR 5. Lanes 1, 20 and 31 contain lkb+ ladder; Lanes 2-9 contain red oak samples from Daisy Lake Unlimed population; Lanes 11-30 contain red oak samples from Wahnapitae Hydro Dam population...... 70 Figure 1 i: ISSR screening analysis illustrated on 2% TBE agarose gel for red oak DNA samples. Each primer amplified sample 1 from Daisy Lake, Wahnapitae Hydro Dam, Laurentian, Kukagami, Kingsway, Falconbridge, Capreol. Lanes 1, 10, 19, 28 and 37 contain lkb+ ladder; Lanes 2-9 contain amplified DNA from ISSR 10; Lanes 11-18 for ISSR UBC 809; Lanes 20-27 for ISSR 15; Lanes 29-36 for ISSR 9...... 86
ix List of Tables
Table 1: Mean total concentrations of elements in selected soil horizons from the Sudbury region unlimed sites impacted by varying degrees by smelter aerosolic fallout (concentrations are in mg kg'1, dry weight)...... 31
Table 2: Mean bioavailable concentrations of elements in selected soil horizons from the Sudbury region unlimed sites impacted by varying degrees by smelter aerosolic fallout (concentrations are in mg kg'1, dry weight)...... 32
Table 3: Mean total concentration of elements in the organic surface horizons (LFH) of soils from the Sudbury region sites (concentrations are in mg kg'1, dry weight) ..33
Table 4: Bioavailable concentration elements in the organic surface horizons (LFH) of soils from the Sudbury region sites (concentrations are in mg kg'1, dry weight) ..34
Table 5: Mean total concentration of elements in the limed and unlimed organic surface horizons (LFH) of soils from the Sudbury region sites (concentrations are in mg kg'1, dry weight)...... 35
Table 6: Mean bio-available concentration elements in the limed and unlimed organic surface horizons (LFH) of soils from the Sudbury region sites (concentrations are in mg kg'1, dry weight)...... 36
Table 7: Percentage of bioavailable relative to total elemental concentration for the LFH horizon of soils from the Sudbury region sites ...... 37
Table 8: Correlation between total and bio-available elemental concentration in soil profiles from the Sudbury region sites...... 38
Table 9: The pH levels of individual soil horizons from the Sudbury region sites 39
Table 10: Mean total concentration of elements in leaves of red oak (Quercus rubra) from the Sudbury region sites, concentrations are in mg kg'1, dry weight...... 40
Table 11: Mean total concentration of elements in branches of red oak (Quercus rubra) from the Sudbury region sites, concentrations are in mg kg1, dry weight...... 41
Table 12: Mean total concentration of elements in leaves of red oak (Quercus rubra) from the Sudbury region sites, concentrations are in mg kg'1, dry weight...... 42
Table 13: Mean total concentration of elements in branches of red oak (Quercus rubra) from the Sudbury region sites, concentrations are in mg k g 1, dry weight...... 43
Table 14: Mean total concentration of elements in leaves and branches of red oak (Quercus rubra) from the Sudbury Region sites, concentrations are in mg k g 1, dry weight...... 44
x Table 15: Summary of elemental concentrations from limed sites in soil and red oak tissues (concentrations are in mg kg'1, dry weight)...... 45
Table 16: Summary of elemental concentrations from unlimed sites in soil and red oak tissues (concentrations are in mg kg"1, dry w eight)...... 46
Table 17: The nucleotide sequence of ISSR primers used to screen DNA from red oak (Quercus rubra) populations samples...... 62
Table 18: Genetic variability parameters of red oak (Quercus rubra) populations based on ISSR data...... 63
Table 19: Distance matrix generated from ISSR data using the Jaccard’s similarity coefficient analysis for 13 red oak...... 64
Table 20: Enrichment factors of total metals with significantly different mean concentrations between Eroded/Disturbed and Control sites ...... 83
Table 21: Enrichment factors of bioavailable metals with significantly different mean concentrations between Eroded/Disturbed and Control sites ...... 83
Table 22: The translocation factors for contaminated sites from soil to branches and branches to soil ...... 84
Table 23: The translocation factors for contaminated sites from soil to branches and branches to soil ...... 85
Table 24: Mean polymorphic percentages for limed and unlimed sites...... 87
Table 25: Mean polymorphic percentages for sites less than 5km, between 5 and 15 and more than 5km from the smelter ...... 87
Table 26: Metal concentration guidelines for soil according to the Ontario Ministry of Environment and Energy (OMEE)...... 88 Chapter 1: Literature Review
1.1 Metal Contamination in the Greater Sudbury Region (Ontario, Canada)
The Greater Sudbury Region is recognized for an abundance of copper, nickel and various other metal deposits. The discovery and value of these metal deposits in the late
1880s have lead to the development of a world renowned mining and smelting industry producing up to 50 000 tonnes of ore per day (Smith, 1996) and a staggering total of 1.6 billion tones of base metal rich ores to date (Wren etal., 2012).
Along with the value of copper and nickel come the sulfur, iron and barren host rock to which they are melded. The discovery of mineral riches brought about the biggest challenge, which was to separate the copper and nickel from the unwanted bounded material. To reduce the amount of material being transported, an effective smelting process was required (Wren et al., 2012). Originally, sulfur was removed by open roast yards which contained up to a quarter of a million tonnes of ores and burnt continuously in the open for months. However, this process was extremely harmful as oxidizing the metal ores released sulfur dioxide into the environment, stripped the surrounding land of timber and increased the incidences of fires. These open roast yards were abolished in
1930. Nonetheless their long term effects have contributed significantly to Sudbury’s characteristic barren landscape (Amiro et al., 1981). The centralized smelters replaced open roast yards. Unfortunately, although smelters are safer, they have also played a detrimental effect to the landscape and vegetation of the Greater Sudbury Region. Slag and mine tailings have also greatly contributed to the dying landscape of Sudbury, but to a much lesser extent (Smith, 1996). It was the decades of sulfur dioxide and other mineral emissions from smelters combined with water vapour in the atmosphere forming sulfur acids and causing acid rain that has had such a large impact. Over 100 million tonnes of sulfur dioxide and tens of thousands tonnes of cobalt, copper, nickel and iron ores were released into the atmosphere (Freedman et al., 1980). These factors have had pervasive outcomes and the metal contaminations were seen widespread. For over 100 square kilometers of the land around Sudbury was rendered completely barren of vegetation, within 362.6 square kilometers, only shrubs and herbaceous covers were found, and vegetation as far as 4403 square kilometers was affected in some way (DeLestard, 1967).
The cause for the loss of vegetation lies within the soil which has been heavily contaminated with metal over the years. Antonovics et al. (1971) found a significant difference in soils containing high metal content compared to normal soils which contained flourishing vegetation. They also reported differences in nutrient content, organic matter content and texture. These soils were more acidic decreasing solubility of some macronutrients, yet increasing solubility in other micronutrients to toxic levels.
These outcomes lead to a decline in plant and vegetative growth causing soil erosion.
This results in loss of fine particles eradicating it of its much needed microflora and fauna. The overall topsoil is then eliminated leaving the soil deficient in available phosphorus, nitrogen, calcium, magnesium and manganese. Nutrient deficiencies have been found to cause morphological differences between plants growing on metal contaminated soils and uncontaminated soils. Plants on contaminated sites were smaller and prostrate (Antonovics et al., 1971). Antonovics et al. (1971) also reported that plants growing on slightly higher than normal metal containing soils are still affected and show increased metal concentrations within the plants themselves.
There is clear damage caused to soil and plant vegetation by the excess pollution of SO2 and metal concentrations. Dudka et al. (1995) published data on soil contamination by elements in the Sudbury mining and smelting region. The study
2 confirms that the Sudbury soils are in fact contaminated with cadmium, cobalt, copper, chromium, iron, manganese, nickel, sulphur and zinc. Copper and nickel were the primary contaminants in the area.
Studies have shown that particular metals also have genotoxic effects. Analysis of subcellular and acellular systems have shown that various metals affect DNA. For example, hexavalent chromium, trivalent chromium and nickel ions have induced genetic changes interacting with DNA. As well, cadmium ions have been found to replace zinc ions in fingerloop protein which bind to DNA and are a fundamental mechanism for regulating gene expression (Hughs et al., 1995).
The effects and studies of metal have caused massive reclamation projects within the community. In the last 40 years, Sudbury’s landscape has changed dramatically due to groups of professors, municipal employees, mining companies and dedicated local residents led by VETAC, aiming at producing restoration projects and reverse damages caused by metal contamination.
1.2 Nutrient Content in Soil
Plant nutrients are chemical elements that are essential for plant growth and reproduction. For an element to be considered a nutrient, it must satisfy three specific criteria. The principle criterion is that the element must be required for a plant to complete a normal life cycle. The second is that no other element will fully substitute the element that is being considered as a nutrient. The third criterion is the element is universal and essential to all plants. Many elements found in plants are not considered nutrients because they are not essential and do not satisfy the three criteria. Plants accumulate many elements which may actually have any critical role in metabolism or physiology. An element may also affect plant’s growth or enhance it without being considered essential. Such elements are simply beneficial to plants (Fried and Broeshart,
1967).
Plant nutrients are classified according to two groups, macronutrients and micronutrients. Macronutrients are essential elements used by plants in relatively large amounts. The major macronutrients of particular interest in this research are Nitrogen (N),
Phosphorus (P) and Potassium (K). Micronutrients are essential elements required in trace amounts and they include Boron (B), Chlorine (Cl), Copper (Cu), Iron (Fe), Manganese
(Mn), and Zinc (Zn) (Barker and Bryson, 2006).
The sources of nitrogen for plants are nitrates and ammonium. Once these products are reduced, they are important for the synthesis of proteins, nucleic acids for
DNA/RNA, and water soluble organic compounds. A shortage of nitrogen restricts growth of all plant organs, roots, stems, leaves, flowers, fruits and seeds. A nitrogen- deficient plant appears stunted, and has a pale colour of light green or yellow in leaves
(Barker and Bryson, 2006). Phosphorus in plants is utilized in the form of orthophosphate. Phosphates unique properties allow formation of water-stable anhydrides and esters such as adenosine diphosphate and triphosphate (ADP/ATP) for energy storage and transfer in plant biochemical processes. Beyond the role in energy-transferring processes, phosphate bonds serve as important linkage groups. They are structural components of phospholipids, nucleic acids, nucleotides, coenzymes and phosphoproteins. A deficiency in phosphorus suppresses and delays plant growth and maturity. Visual cues involve dark green stems and leaves as well as spots of red and purple. Some stems and leaves may also be shorter and more slender than normal
(Sanchez, 2006). The functions of potassium in plants include enzyme activation, protein
4 synthesis, ion absorption and transport as well as long distance transport and photosynthesis and respiration. A general non-specific early symptom of potassium deficiency includes growth retardation. The results of longer periods of deficiency includes chlorotic and necrotic symptoms in older leaves as small stripes along the leaf margins, beginning at the tips and enlarging along leaf margins in the basal direction.
Advanced levels of deficiencies result in chloroplast and mitochondrial collapse.
Conversely, the excess of potassium can also cause adverse effects. However, deficiency is rare because potassium uptake is regulated strictly. An excess of potassium may depress plant growth and yield, also impacting uptake of other cationic species (Mengel,
2006). Although the effects of a single macronutrient deficiency or excess is harmful to a plant, Auchmoody (1972) reported that seedling growth of red oak was significantly affected by nitrogen and phosphorus as well as nitrogen, phosphorus and potassium interactions; and that without nitrogen, phosphorus or potassium alone or in combination there is no growth increase.
Boron is one of the essential micronutrients. Some of the main functions of boron in plants are root elongation and nucleic acid metabolism, nitrogen remobilization, sugar, starch, auxin and phenol synthesis, flower formation and seed production. Boron is important in membrane function as it gives stability to cellular membranes by reacting with hydroxyl-rich compounds. Boron toxicity consists of marginal and tip chlorosis followed by necrosis.
Chlorine is taken up by plants in the electrically charged form of chloride ion
(C1-). It is required for optimal enzyme activity of asparagines synthethase, amylase and
ATPase. In photosynthesis, Chlorine is an essential cofactor for the activation of oxygen- evolving enzyme associated with photosystem II. Chloride also has an osmotic function
5 which increases tissue hydration and turgor pressure. Symptoms of chlorine deficiency include wilting of leaves, especially at the margin, curling, shriveling and necrosis of leaves and stubby clubbed tip roots. Chlorine toxicity causes curling of leaf margins, leaf necrosis and leaf drop. Severe toxicity causes dieback of the terminal axis and small branches (Heckman, 2006). The rate of copper uptake is among the lowest of all essential nutrients.
Copper deficiencies are species-specific and depend on the stage of deficiency.
Most plants will exhibit resetting, necrotic spotting, leaf distortion, terminal dieback, lack of turgor and discolouration of some species. Copper deficiency also limits the activity of enzymes and depresses carbon dioxide fixation. Conversely, the general forms of copper toxicity are stunted root growth and leaf chlorosis.
Iron is present mainly in the insoluble Fe(III) (ferric, Fe3+) form. Iron deficiency causes chlorotic leaves, yellow laminae and a fine reticulate pattern develops with the darker green veins contrasting markedly with a lighter green or yellow background. In extreme cases, leaves become almost white. Iron toxicity causes ‘Alkagare I’ or
‘bronzing’ which includes small reddish-brown spots on leaves and roots turn brown
(Kopsell and Kopsell, 2006).
Manganese is involved in many biochemical functions, primarily as an activator for enzymes involved in respiration, amino acid and lignin synthesis and hormone concentrations. Plants which are deficient in manganese have diffuse interveinal chlorosis on young expanded leaf blades and have severe necrotic spots or streaks. Symptoms often occur first on the middle leaves. If a plant contains toxic levels of manganese it will appear yellow beginning at the leaf edge of older leaves and sometimes leading to upward cupping (Humphries, 2006). Zinc is an integral component of enzyme structures and has the following three functions: catalytic, coactive or structural. Zinc deficiency in plants initially appears as intervenial chlorosis (mottling) in which lighter green to pale yellow colour appears between the midrib and secondary veins (Storey, 2006). Developing leaves are smaller and the intemodes are short. To combat low nutrient levels in soil, a plant will form root clusters (proteoid roots) (Schachtman et al., 1998).
Uptake of the nutrients is a complex concept and depending on different elements, various mechanisms are proposed. An element will move from solid phase to solution phase before being taken up at the root surface. From there, all nutrients will cross the cell membrane of epidermal and cortical cells (von Wiren et al., 1997). This transfer can occur passively or actively. Although total nutrient content in soil is high, a plant will only take up nutrients which are bioavailable such as inorganic and mobile forms. Other factors affecting uptake include temperature, water status and chemistry of rhizosphere in soil. Nitrogen is taken by two types of transporters, NRT1 and NRT2, which are low- affmity and high-affinity respectively. Phosphorus is taken up in various forms depending on the soil’s pH level. Studies have shown that most phosphorus uptake occurs at pH of
5.0 and 6.0 and therefore the monovalent form, H2P04 , dominates. It has been found that the inorganic form of phosphorus is co-transported across the plasma membrane of root cells with positively charged ions. Potassium requires a high-affinity transport mechanism
HKT1 which uses a K+-H+ co-uptake similar to Phosphorus (Schachtman et al., 1998).
The uptake of micronutrients however, is more difficult to investigate because of the low fluxes involved (Reid, 2001). Just as there are high and low-affinity transporters for macronutrients, micronutrients are also taken up by similar transporters. These transporters however have much broader substrate specificity. Boron, which was originally believed to be simply transported passively across cell membranes of roots
(Dordas et al., 2000) has now also been found to move across root surfaces actively by a
BOR transporter and facilitated by nodulin-like intrinsic protein (NIP) channel (Ashraf et al., 2000). Chlorine is thought to travel across the root by a symplastic pathway and Cl- fluxes across the plasma membrane and tonoplast of root cells have been estimated. These fluxes are regulated by the Cl-content currently in roots (White et a l, 2001). Copper is transported in plants by the COPT (copper transporter) which is similar to the CTR, a family of proteins found in eukaryotic cells which move Cu+ into the cytosol. There is up to six members of the COPT family (Pilon, 2011). Iron is taken up by plants by the uptake transporter AtlRTl. The uptake transporter occurs in the root and is induced by excess Nickel (Nishida et al., 2011). Zinc has been found to be taken up through an initial non-metabolic phase followed by a metabolically mediated absorption.
The amount of nutrients or metal taken up by plants is dependent on the form of the ions. The total metal concentration far exceeds the amount that is taken up and includes all forms of ions. Therefore, it is important to note the bioavailable amounts which represent the accessibility of a solid-bound chemical for assimilation and possibly toxicity (Alexander, 2000).
1.3 Soil Amendment
The effects of smelting have caused detrimental damage to soils around Sudbury as well. The sulphur dioxide released has caused acid rain to seep into the soils, increasing acidity and changing the overall soil chemistry. Acidic soils cause a decrease in solubility of macronutrients as well as molybdenum and an increase in solubility in micronutrients to toxic levels. The practice of liming is a form of soil amendment which increases soil pH to neutralize it. Raising pH is important for recolonization of species as it facilitates germination of existing and incoming seed banks (Winterhalder, 1996).
The various types of lime include calcitic and dolomitic aglime, quick or burnt, hydrated slaked, marl, and industrial by-products. Ions in these liming materials combine with hydrogen ions in the soil to produce water and carbon dioxide reducing the acidity.
Of these types, the Greater Sudbury Region generally applied ground dolomitic lime as well as calcitic lime to its soils. Dolomitic lime contains calcium magnesium carbonate, CaMg(C 03>2 and calcitic lime contains Ca(C0 3 >2. The mechanism behind the reaction is as follows: Soil colloid+2H+ + Ca(C03)2 -> Soil colloid+Ca2+ + CO2 + H2O
Between 1978 and 2011, 3400 ha of barren land in Sudbury was limed (Peter
Beckett, VET AC, personal communication, 2012). Ground limestone is applied by manually emptying bags over a grid. This distribution procedure causes an inevitable patchy result creating a mosaic, and the degree of liming varies from zero to optimal to excessive. This is favourable because it causes a random spacing of vegetation and creates an ecological variation of plants ensuring species diversity and genetic biotype diversity. As well, this organization decreases competition for metal-tolerant plants
(Winterhalder, 1996).
Although liming initially was thought to cancel out a single limiting factor of low pH, which alone does not occur in the environment. This single factor possesses its own dependent and interacting sub-factors making soil detoxification a complex strategy.
Detoxification of soil ultimately increases vegetative growth and nutrient supply and is therefore crucial to a dying environment and can be attributed to many factors. When soil is completely neutralized by ground limestone, toxic metal may be eliminated by precipitation as a carbonate of hydroxide. Another factor may be the hydroxylation of the
9 trivalent aluminum ion. The role of calcium and magnesium dolomitic lime is also an important factor. Although calcium alone has been shown to improve membrane integrity, their roles combined produce greater effects. Together they are important in the competitive exclusion of metal ions from the root-hair’s exchange complex and reduce the differential effect. This means that when calcite lime alone is applied, there is an induced magnesium deficiency due to the calcium-magnesium imbalance, as well as an antagonistic effect between magnesium and nickel (Winterhalder, 1996). (Brach et al,
1992) found that liming played a great influence on Oxalis. acetosella and Lycopodium lucidulum. O. acetosella occurs on acid to neutral soils and L.lucidulum strictly occurs on acidic soils which is a good indication of increased soil pH. They tested response in limed and non-limed treatments by measuring growth and tissue nutrient concentrations of the two species. Their results showed that liming increased overall growth of 0. acetosella in both growth chamber and field plot, while L. lucidulum compared to O. acetosella had less biomass, smaller segments, fewer bulbs, less dichotomous branching and less new growth.
1.3 Re vegetation
In order to restore Sudbury’s ecological damages, revegetation of the land was also done in conjunction with the liming. The economic recession caused thousands of employees to be laid off and hundreds of students to be unemployed. Sudbury took action and attained federal, provincial and municipal funding to start various reclamation projects including fertilizing and seeding. When barren areas are treated with limestone, fertilizer and seeds, immediate colonization of plants occurs. This was first seen in
Coniston Creek valley in 1974 (Winterhalder, 1996). Within a year of treatment, new
10 grass species, legumes and wildflower species had colonized. Herbaceous covers were applied to the land and various types of trees were planted. Over 95% were conifers and include jack pine (Pinus banksiana), red pine (Pinus resinosa), white pine (Pinus strobes), white spruce (Picea glauca), black spruce ( Picea mariana), white cedar (Thuja occidentalis), tamarack ( Larix laricina), hemlock ( Conium maculatum) and balsam fir
{Abies balsamea). Only 5% were of hardwood species and included red oak {Quercus rubra), red maple {Acer rubrum), ash (Fraxinus), Russian olive {Elaeagnus angustifolia), yellow birch {Betula alleghaniensis), bur oak {Quercus macrocarpa) and American beech
{Fagus grandifolia). There have also been exotic tree species which have been planted such as European larch {Larix deciduas) and the leguminous black locust {Robinia pseudoacacia). These trees have been found to be tolerant of poor soil and frost. Their tendency towards mortality is also a positive aspect as it may play a significant role in soil stabilization and soil humus and nitrogen buildup (Winterhalder, 1996).
The large majority of trees planted were obtained from the Ontario Ministry of
Natural Resources and were bare-root or container stocks. Seeds were also collected from local trees and shrubs which seedlings were raised in the greenhouse of Cambrian College of Applied Arts and Technology, Sudbury, Ontario. Many deciduous tree species were of nursery stock, the most successful being northern red oak, Quercus rubra (Winterhalder,
1996).
11 1.4 Species of Interest
Kingdom: Plantae
Order: Fagales
Family: Fagaceae
Genus: Quercus
Section: Lobatae
Species: Quercus rubra
The species Quercus rubra (syn. Quercus borealis) are hardwood trees commonly known as northern red oak, or simply red oak. They are part of theFagaceae family and the highly complex genusQuercus. This genus is said to be complex at both the genetic and taxonomic level due to the existence of several varieties and poor reproductive barriers leading to recurring natural hybridisations (Carvalho et al., 2009). Red oaks are large trees reaching 20-30 m tall and their barks are dark grey or black with shallowly furrowed into broad hard scaly ridges. Their leaves are deciduous, alternate, elliptic, 10-
25 cm long and 8-15 cm wide containing 7-11 shallow wavy lobes with irregular bristle- tipped teeth. In ideal conditions red oaks may live up to 500 years and are considered fast growing trees. At about 20-25 years, they bear their first fruit, the acorn. Red oaks are one of Ontario’s largest and most valuable trees for wood products and contain abundant and nutritious acoms crucial for wildlife. These large trees also provide good covers and nesting sites, including cavities for various birds and mammals. The genus Quercus is widely distributed in the northern hemisphere, in habitats ranging from temperate and tropical forests to dry thorn scrub and semi-desert (Nixon 1993).
The specific speciesQuercus rubra is commonly found in the Deciduous, Great
Lakes-St. Lawrence and Acadian Forest regions. Northern red oak is widely distributed
12 throughout much of the eastern United States and southeastern Canada. It grows from
Quebec, Ontario, Nova Scotia, and New Brunswick southward to southwestern Georgia,
Alabama, northern Mississippi, northern Arkansas, and eastern Oklahoma. Northern red oak extends westward through Minnesota and Iowa, south through eastern Nebraska and
Kansas to eastern Oklahoma. It occurs locally in eastern and southwestern Louisiana and western Mississippi. In Ontario, it grows primarily along the north shore of Lake Huron and in the areas south of Sudbury. Their optimal growing conditions are fresh sites with fine, deep soils that have a loam or silt-loam texture. As well, Quercus rubra are tolerant of porous, sandy or gravelly soils with good drainage, dry acidic soil and air pollution.
The tolerance levels of red oaks allow it to live in stressful environments and were one of the few species found in the barren sites of the Greater Sudbury Region during the ecological crisis. This may suggest its ability to contain certain genetic mechanisms against metal contaminants or sulfur dioxide concentrations, and they are able to adapt more readily. Their acclimatization techniques and evolutionary stability are dependent on their genetic adaptation to their surroundings. This is evident through their high genetic diversity, as the level of diversity determines their adaptability. The level of genetic diversity in red oaks have been documented to be relatively high especially in
Europe, North America and Eastern Asia. This phenomenon was due to hybridization and gene flow mediated by long-distance wind pollination (Chokchaichamnankit et a l, 2008) and was determined by ISSR markers. Studies have also used other marker systems such as allozymes, SSRs and AFLPs to determine genetic diversity (Gerweinet al., 2006) as well as molecular differentiation (Daubree et al., 1993), characterization (Dodd et al,
2003) and genetic structure (Aldrich et al., 2005) in red oak species.
13 Figure 1: Map of North America showing the distribution of northern red oak (Quercus rubra).
14 1.5 Overview of Genetic variability
Genetic variability is the key factor for the ability of species to survive and adapt to changing environmental conditions over time. High levels of variability in species are determined as healthy, conferring the potential to react to threats such as disease, predators, or climate change. Whereas low levels of variability will limit or even cease the ability of a species to respond to threats both short and long term (Amos et al., 1998).
The increase in genetic diversity can be caused by various factors such as gene flow or mutations resulting from a substitution of single nucleotides, insertions or deletions of DNA fragments and the decrease in diversity can occur passively through genetic drift or actively through natural selection (Amos et al., 1998). An example of natural selection is a selective environment in which the presence of a substance harms the individuals which do not contain the resistant gene. Preservation of diversity specifically within plant populations is crucial for maintenance of biodiversity in communities (Booth et al., 2003). The immobility of plants limits their capabilities to avoid threats and therefore the ability to adapt is of priority, otherwise the population size may slowly decline ultimately wiping out the species.
1.6.1 Measuring Genetic variability with Molecular Markers
Sustaining plant species is dependent on its genetic variability and the importance in determining survival potential in these species has led to dramatic advances in molecular genetics, specifically in biotechnology. These advances have made significant contributions to the improvement of molecular research. Plant biotechnology is used to solve practical problems in agriculture and horticulture, and to ultimately broaden our knowledge of the ecological environment. An approach widely employed to assess genetic variability in plants is the usage of genetic markers. The first techniques used morphological markers involving phenotype-based genetic markers used by Gregor
Mendel in the nineteenth century. Subsequent to these phenotypic markers have been biochemical-based markers such as allozymes and cytoplasmic markers (Cruzan, 1998).
These markers however show countless limitations which led to the development of more useful and direct, molecular markers (Agarwal et al., 2008). These stable molecular markers are defined as chromosomal landmarks or alleles that allows for the tracing of a specific region of DNA (Semagn et a l, 2006) used to detect or exploit DNA polymorphisms. These regions, however, are not considered a normal gene because they do not contain a biological effect (Semagn et al., 2006).
Ideal molecular markers should satisfy the following criteria: (1) be polymorphic and evenly distributed throughout the genome, (2) provide adequate resolution of genetic differences, (3) generate multiple, independent and reliable markers, (4) be simple, quick and inexpensive, (5) require small amounts of tissue and DNA samples, (6) have linkage to distinct phenotypes, and (7) require no prior information about the genome (Agarwal et al., 2008). Basic molecular marker techniques are classified by their mode of analysis and mode of gene action (Semagn et al, 2006).
The two modes of analysis are hybridization-based and PCR-based techniques.
Hybridization-based techniques hybridize the restriction enzyme-digested DNA to a labeled probe known as a DNA fragment. This reveals a pattern difference between DNA fragment sizes which occur between any individuals of a species even if they have almost identical genomes. An example of this type of marker includes Restriction Fragment
Length Polymorphism (RFLP) (Agarwalet al., 2008). RFLPs exemplify the differences in restriction enzyme digestion pattern of PCR fragments created by nucleotide polymorphisms between samples. RFLPs were first used in 1975 to identify DNA sequence polymorphisms for genetic mapping of a temperature-sensitive mutation of adeno-virus serotypes (Semagnet al., 2006).
PCR-based molecular markers depend on polymerase chain reaction technology
(PCR). PCR is a technique for enzymatically amplifying small segments of DNA without using a living organism. PCR amplifies short, usually less than 10 kb, well-defined part of a DNA strand. The protocol involves three steps in which double stranded DNA is denatured at 92-95°C, primers bind to the single stranded DNA at a lower annealing temperature and double stranded DNA is re-produced by DNA polymerase at 72°C. The newly synthesized DNA strands are once again denatured and the cycle continues.
Following the innovation of polymerase chain reaction (PCR) technology by Mulliset al.
(1986), a large number of molecular marker techniques have been generated based on
PCR and continue to be utilized due to its simplicity and high success rate (Agarwal et al., 2008). Examples include random amplified polymorphic DNA (RAPD), amplified fragment length polymorphism (AFLP), microsatellites and inter-simple sequence repeat
(ISSR) (Semagn et al., 2006).
There are numerous advantages of PCR-based markers over hybridization-based markers. These include the use of smaller DNA samples, elimination of radioisotopes, the ability to amplify DNA sequences from preserved tissues, the accessibility of methodology for small labs in terms of equipment, facilities and cost, no need for prior sequence knowledge for many applications, high polymorphism that enables generation of many genetic markers within a short time and the ability to screen many genes simultaneously for direct collection of data or as a feasibility study prior to nucleotide sequencing efforts (Semagn et al., 2006). Molecular markers are also classified according to its mode of gene action. This classification is divided into two categories which include codominant and dominant markers. A codominant marker reveals multiple alleles at a single locus (Milboume et al.,
1997). Dominant markers are considered multi-locus and cannot determine variation at a single locus. This means that alleles at a different locus cannot be distinguished if they are of equal molecular weight. However, they are valuable for initial examination of the partitioning of genetic variation within species or for locating centres of genetic diversity
(Newton et al., 1999).
1.6.2 Inter-Simple Sequence Repeat (ISSR)-PCR
Inter-Simple Sequence Repeat (ISSR) are dominant markers made up of DNA fragments ranging from 100-3000 base pairs (Kumar et a l, 2009), and are formed during
ISSR-PCR. ISSR-PCR is a technique introduced in 1994 (Zietkiewicz et al., 1994) which involves the amplification of DNA segments present between two identical, inversely located simple sequence repeats (SSR) or microsatellite repeats. Microsatellites are simple repetitive DNA sequences and are the smallest of this class. They have been defined as repeats 2-8 base pairs long, and there are approximately 500 to 300 000 microsatellites per plant genome (Condit et al., 1991). These microsatellites act as primers flanking to the single stranded DNA. In a single primer PCR reaction, the primers target multiple genomic loci to amplify mainly the inter-SSR sequences of different sizes.
These repeats are 16-25 base pairs long and can be di-nucleotide, tri-nucleotide, tetra- nucleotide or penta-nucleotide. Primers can be either unanchored or more commonly anchored at the 3’ or 5’ ends with 2-4 arbitrary often degenerate nucleotide bases (Fang et al., 1997) extended into the flanking sequences (Semagn et al., 2006). Unanchored primers increase unnecessary products because they anneal non-specifically within repeat regions on the template DNA producing a series of bands that differ in size but represent the same locus (Archibald et al., 2006). Anchoring primers, on the other hand, increases specificity and plays a factor in polymorphism. An anchored or extended primer is forced to bind to the ends of the SSR template DNA diminishing internal priming and smearing profiles. Anchors also force the primers to bind solely to a subset of the SSRs serving as priming sites (Reddyet al., 2002). The 3’ Anchored primers specifically construct clear banding patterns and avoid unnecessary complications during analysis. Amplified products of 5’ anchored primers do produce higher degrees of polymorphisms but have also been found to produce some smeared banding patterns (Archibald et al., 2006). ISSR
DNA is a reliable source of genetic marker which is very advantageous.
The advantage of using ISSR-PCR is that it combines most of the benefits of SSR and amplified fragment length polymorphism (AFLP) analysis with the universality of random amplified polymorphic DNA (RAPD) method. ISSR-PCR products have high reproducibility possibly attributed by the use of long primers, 16-25 mers allowing a higher annealing temperature leading to elevated rigidity (Reddyet al., 2002). Previous studies done on ISSR-PCR’s reproducibility, show that approximately 92% to 95% of the scored bands are reproducible across the DNA of the same cultivar and across different
PCR runs using a polyacrylamide gel (Fanget al., 1997). In addition to reproducibility,
ISSR-PCR is advantageous because they are highly polymorphic and no prior sequence knowledge is required to perform this technique. A comparison experiment was done with ISSR, RAPD and RFLP primers on a common wheat species. The study found that
ISSR primers produced several times more information than RAPDs and were much more polymorphic. Band polymorphism of ISSR and RFLP were much more similar. The
19 genetic relationship of wheat between the three primers shows that there is great reliability of ISSR markers for estimating genotypes (Nagaoka et al., 1997). In addition to polymorphism, ISSR markers only necessitate a small amount of DNA to carry out this procedure. However, ISSR-PCR does include disadvantages. Since it is a multi-locus technique, there may be errors in non-homology of fragments of equal or similar size.
Despite the notable weaknesses of this technique, the advantages far outweigh them and
ISSR-PCR has been widely applied to numerous studies in plant research. These studies involve genetic identity or fingerprinting, parentage, clone and strain identification, taxonomic studies of closely related species, gene mapping (Kumaret al., 2009) and determining SSR motif frequency (Reddyet al., 2002).
1.6 Objectives
The objectives of this study were to compare genetic diversity in Northern Red
Oak (Quercus rubra) populations growing in eroded and stable upland sites and to determine long term effects of liming on soil fertility and toxicity, and on genetic variability of red oak populations.
20 Chapter 2: Metal Analysis in Red Oak(Quercus rubra) populations growing in limed and unlimed areas in the Greater Sudbury Region (Ontario, Canada)
2.1 Introduction
The Greater Sudbury region is highly known for its nickel, copper and other metal deposits. The mining, roasting and smelting of these valuable elements have caused disastrous effects on the vegetation and overall environment in Sudbury and has even been called one of the most ecologically disturbed regions of Canada (Amiro et al., 1981;
Amiro et al., 1981; Gratton et al., 2000a; Nkongolo et al., 2008; Vandeligt et al., 2011;
Narendrula et al., 2012). The effects have caused areas to become semi-barren to completely barren and studies on these outcomes have found sulfur dioxide emissions and metal particulates in soil and various plant species to be the source. Concentrations of metal, specifically nickel and copper, have been found to be higher in areas around smelters than areas further away (Amiro et al., 1981). The high metal content creates soil with high acidity and less plant growth. Ongoing damage and increased industrialization have pushed massive restoration projects including liming of soils and revegetation in the
Greater Sudbury Region (Lautenbach et al., 1995).
Liming is a form of soil amendment which has played a large role in the reclamation of land in the Greater Sudbury Region. The addition of lime was applied in efforts to neutralize the acidic soil within the barren lands. The pHs of these soils ranged from 3.0 to 5.0 with an average of approximately 4.0. The city of Greater Sudbury applied dolomitic lime to its soils in 1978, which contains calcium and magnesium carbonate (Lautenbach et al., 1995). The role of both calcium and magnesium together is crucial to metal toxicity as they create a competitive exclusion of metal ions from the root-hair’s exchange complex, that magnesium and calcium alone is unable to perform and may affect leaf and branch tissue (Winterhalder, 1996). The process of liming overall aims to neutralize soil pH and detoxifies soil from contamination. Since then, the addition of regreening of Sudbury has proved to be visually beneficial as the once barren lands now have a prominent increase in vegetation. Massive remediation projects have occurred since 1978 to rebuild a flourishing landscape. Dedicated groups such as the Vegetation
Enhancement Technical Advisory Committee (VETAC), Vale Inco, and devoted volunteers have involved themselves to bettering the city both ecologically and esthetically. Environmentally stressed areas have been restored through tree planting.
There have been various studies done on the conifers located in the Greater Sudbury
Region, but much less done on the hardwood species. This present study examined the hardwood species northern red oak, Quercus rubra.
The objective of this component of the present study was to assess the long term effects of the addition of liming materials on soil toxicity and metal and nutrient content.
The values of total and bioavailable elements and pH were determined.
2.2 Materials and Methods 2.2.1 Sampling
Ten sites were selected for metal analysis. Soil, oak leaf and branch samples were collected from each site. Paired pedon soil samples were collected from limed and adjacent unlimed areas from ten areas within the Sudbury region (Fig. 2). Three sites were within 5 km of Smelters, three between 5 km and 15 km from smelters, and three as far as 100 km from the smelter sites. These later sites were used as reference sites to enable comparisons of the effects of liming on both soil fertility and metal dynamics. The liming was previously performed up to 30 to 40 years ago through the Sudbury’s
22 Regional Land Reclamation Program using dolostone (Winterhalder, 1996). Daisy Lake site was limed aerially in 1995, Wahnapitae Hydro Dam site was limed in 1980 and
Kingsway site was limed in 1981. For each area, 10 pedons were sampled at random, with soil samples being collected from the surface humus form (LFH), as well as from the underlying mineral horizons (namely the Ae, Bm, BC, and C, if present) (Soil
Classification Working Group 1998). Soil samples were air dried and stored in sealed plastic bags prior to preparation for chemical analysis. Oak leaves and 1-2 year old branches were collected randomly from 20 individual trees, dried and combined for further analysis.
23 Site 7 Capreol
X Stead Valley East Suez Can's Landing Val Therese Parkwood Harwnet Boland's Bay Pmecrest Carol StmarO Az da t9C] ■rarer k*. Garson * Junction 5T* ■55/ V#- ! l i r a TsT 7) / ® © ^fc0rv:r, Site 4 Sudbury Vine Ra y tO ft> Ro^fjrd Site 2 Gttfch«J JnjJccppei CiiH Moonlght Baacn <0 Site 3 Site 1 * Lake Laurenban Comervaaon Area Site 8 A FieldngBad Figure 2: Location of red oak sampling sites within the Sudbury region. Site 1: Daisy Lake; Site 2: Wahnipitae Hydro Wahnapitae Hydro Dam; Site 3: Laurentian; Site 4: Kukagami; Site 5: Kingsway; Site 6: Falconbridge; Site 7: Capreol; Site 8: St. Charles; Site 9: Onaping Falls; Site 10: Airport 24 2.2.2 Metal and pH analysis in soil Soil pH was measured in de-ionized water and in a neutral salt solution pH (0.1 M CaCl2) (Carter et al. 1993). Total metal analysis was performed as described by (Abedin et al., 2012). For the estimation of total metal concentrations, a 0.5 g soil sample was treated with 10 mL of 10:1 ratio HF:HC1, heated to 110°C for 3.5 hours in open 50 mL Teflon™ tube in a programmable digestion block (Questron Inc™) to dry down samples, followed by addition of 7.5 mL of HC1 and 7.5 mL of HNO 3 and heating to 110 °C for another 4 hours to dry gently. The samples are then heated to 110 °C for 1 hour following addition of 0.5 mL of HF, 2 mL of HC1 and lOmL of HNO 3 to reduce solution volume to 8-10 mL. On cooling, the samples are made to 50mL with ultrapure water for subsequent analysis by plasma spectrometry. Bioavailable metals were estimated by extracting 5 g of soil with 20 ml of 0.01M LiN0 3 in a 50-ml centrifuge tubes in a shaker under ambient lighting conditions for 24 hours at 20 °C (Abedin et al. 2006; Abedin et al. 2012). The pH (LiNOs) of the suspension was measured prior to centrifugation at 3000 rpm for 20 minutes, with filtration of the supernatant through a 0.45 um filter into a 20 ml polyethylene tube and made to volume with deionized water. The filtrate was preserved at approximately 3 °C for analysis by ICP-MS. The quality control program completed in an ISO 17025 accredited facility (Elliot Lake Research Field Station of Laurentian University) included analysis of duplicates, Certified Reference Materials (CRM’s), Internal Reference Materials (IRM’s), procedural and calibration blanks, with continuous calibration verification and use of internal standards (Sc, Y, Bi) to correct for any mass bias. All concentrations were calculated in mass/mass dry soil basis. The data obtained for all 25 elements of interest in analyzed CRM soil samples were within ± 12% of the certified mean estimates. Metal content in leaves and branches was determined according to the protocol described by Abedin (2012) with samples digested and analyzed by plasma spectrometry. 2.2.3 Statistical Analysis The data for the metal levels in soil and tissue samples were analyzed using SPSS 7.5™ for Windows, with all data being transformed using a logio transformation to achieve a normal distribution. Variance-ratio test was done with an assumption of data normality in the underlying population distributions of the data. ANOVA, followed by Tukey’s HSD multiple comparison analysis, were performed to determine significant differences (p < 0.05) among the sites. Data from analysis of samples from limed and unlimed areas were compared using Student - T test. The enrichment factor (EF) and the translocation factor (TF) were determined according to the equations described by (Singh et al., 2010). Concentration of metals in soil or plant parts at contaminated site EF = ------Concentration of metals in soil or plant parts at uncontaminated site Concentration of metal in plant tissue (parts) TF = ------Concentration of metal in corresponding soil root area 26 2.3 Results The quantitative results of the spatial distribution of total and bioavailable metals and nutrients are described in Tables 1-16. 2.3.1 Total metal of Soil The estimated levels of total metal concentrations in the soil samples for the different sites from the Greater Sudbury Region in Canada are illustrated in Tables 1, 3 and 5 with highest concentrations consistently measured in the top organic layer (LFH). Close examination revealed that the original surface horizons (LFH and Ae) across the sites located within 5 km of smelter were commonly eroded and disturbed, whereas sites beyond 5 km of smelters were stable, had complete pedons with minimal to no evidence of erosion. Table 3 illustrates higher levels of copper, lead and nickel in samples from sites located 5 to 15 km from the smelters compared to eroded sites on hill slopes near either active or closed smelter sites. Arsenic was higher in eroded sites compared to sites located more than 5 km from smelters. According to the Ontario Ministry of Environment and Energy (OMEE) Guidelines, both copper and nickel far exceeds the accepted limits at all the sites including the control sites. The concentrations for lead and zinc ranged from 75.55 to 175.6 mg kg'1 and 54 to 101 mg kg'1, respectively (Table 3). Overall, the total, arsenic, copper, lead and nickel were significantly higher in sites within 15 km from the smelters compared to the comparison site. There were no significant differences among all the sites for the total amount of the following nutrients, calcium, carbon, cobalt, iron, potassium, phosphorus, magnesium, manganese, sulfur, nitrogen, strontium and zinc. The control concentrations were always among the least impacted for the total metals analyzed except for aluminum and calcium. All the total metal concentrations 27 obtained from the dominantly mineral horizon layers (Ae, Bm, Be, and C) were also within the OMOE guidelines with the exception of copper showing levels exceeding the guidelines for the first 3 horizons (Table 1). As well, nickel showed a higher concentration in the first two horizons (Table 1). There was only a significant difference in concentrations of arsenic between limed and unlimed sites for total metal and nutrient content. 2.3.2 Bioavailable Metal of Soil The concentrations of bioavailable metals and nutrients were estimated for the soil samples of all sites. Table 2 illustrates the data obtained for the three distances from smelters and it was found that there were significant differences in concentrations between varying distances of bioavailable potassium, manganese, strontium and zinc. The concentrations of potassium and manganese were significantly lower in eroded/disturbed sites compared to stable upland and control sites. Concentrations of bioavailable strontium and zinc were significantly lower in both eroded/disturbed and stable upland sites than control sites. When comparing metal concentrations between limed and unlimed sites (Table 6), there were significant differences of bioavailable aluminum, calcium, iron, magnesium, manganese and strontium, with all metals except occurring in higher concentrations in limed sites except calcium and magnesium. The percentage of bioavailable elemental relative to total elemental concentrations were very low (Table 7). Detectable values of metal concentrations which are phytoavailable ranged between 0.1 % for aluminum and 9.90% for magnesium. The average concentration of bioavailable copper and nickel were 0.8% and 0.7% respectively. The correlations between total and bioavailable metal and nutrient concentrations and are described in Table 8. There were 28 significant positive correlations for the following elements, calcium (r = 0.93), copper (r = 0.90), magnesium(r = 0.83), manganese (r = 0.88), and nickel (r = 0.89) in the top organic horizons (LFH). 2.3.3 Soil pH levels The pH values of the 10 sites were determined for the first three layers. The pH in limed areas was higher compared to unlimed areas, ranging from 4.12 to 6.75 in the top organic layer (Table 9). There were no significant differences observed among soil profiles analyzed for pH (H2O) and pH (CaCL). The liming done 30-40 years ago continues to have a significant effect on soil as demonstrated by higher pH values in samples from limed areas compared to unlimed sites. 2.3.4 Enrichment Factor The Enrichment factor (EF) was calculated for the four elements which revealed a significant difference in concentration between eroded/disturbed and control sites. For total metals, the EF values were found to be 0.702, 16.78,4.98 and 2.94 for aluminum, arsenic copper and nickel, respectively. For the bioavailable metals, the EF values were 0.28, 0.17,0.9 and 0.15 for potassium, manganese, strontium and zinc, respectively. 2.3.5 Translocation factor The translocation factors (TF) were calculated in contaminated sites from soil to branches and found to be very low for most of total metals except for the main macronutrients carbon, nitrogen and phosphorus. The TF values from soil to branches from control sites were relatively low except for calcium and manganese. The TF values were much higher for bioavailable elements compared to total metals (see appendix Table 29 23). The concentrations of elements were found to be higher in leaves than in branches of red oak populations (Table 14). 2.3.6 Total metal content in leaves and branches of red oak Table 10-14 illustrate the mean total metal and nutrient concentrations in leaves and branches. The mean concentrations of arsenic, cobalt, potassium, phosphorus and nitrogen in leaves were found to be significantly higher in eroded/disturbed sites compared to stable and control sites. The total mean concentrations of iron, potassium, magnesium and nickel in branches were found to be significantly higher in eroded/disturbed sites. The total mean concentrations of cadmium and manganese were found to be significantly different between limed and unlimed sites and the bioavailable mean concentrations of iron, lead and magnesium contained significantly different values between limed and unlimed sites. The total concentration of metals in leaves and branches of red oak are illustrated in Table 14. There were significant differences in potassium, lead and magnesium concentrations between leaves and branches. Of these metals only lead was found to be more concentrated in branches than leaves. 30 Table 1:Mean concentrations of total elements in selected soil horizons from the Sudbury region unlimed sites impacted by varying degrees by smelter aerosolic fallout (concentrations are in mg kg'1, dry weight) Horizons Elements Al As Ca C CoCu Fe K P Pb Mg Mn S Ni N Sr Zn 16445a 38.8a 5174a 142263a 42a 882a 25227a 7795b 654a 118.6a 1823a 279ab 1588a 1003a 6030a 57a 76a LFH 15368a 8.29b 2900a 16836b lib 158b 13785b 10040a 273b 11.34b 798b 329ab 922b 68b 349b 43a 36b Ae 16482a 5.96b 3128a 17760b 15b 104bc 20491a 9992a 378b 4.31c 968b 351a 1022b 44b 416b 35a 63a Bm 15118a 1.84b 2977a 14465b 12b 65c 19300a 9978a 323b 5.16c 929b 249ab 1023b 39b 304b 30a 55a BC 17466a 3.77b 3391a 17236b 12b 79c 22267a 9998a 292b 7.39c 990b 195b 1179b 41b 409b 34a 42b C Means in columns with a common subscript are not significantly different based on Tukey multiple comparison test (p > 0.05). 7 sites: Daisy Lake, Dam, Laurentian, Kukagami, Kingsway, Falconbridge, Capreol (control). 31 Table 2:Mean concentrations of bioavailable elements in selected soil horizons from the Sudbury region unlimed sites impacted by varying degrees by smelter aerosolic fallout (concentrations are in mg kg'1, dry weight) Horizons Elements Al As Ca Cd Co Cu Fe K P Pb Mg Mn Na Ni Sr Zn LFH 71.45a 0.32 162.86a Ae 28.61b 0.07 35.09b Bm 18.70b BC 15.87b C 16.9b Means in columns with a common subscript are not significantly different based on Tukey multiple comparison test (p > 0.05). 7 sites: Daisy Lake, Dam, Laurentian, Kukagami, Kingsway, Falconbridge, Capreol (control). 32 Table 3: Mean concentration of total elements in the organic surface horizons (LFH) of soils from the Sudbury region sites (concentrations are in mg kg'1, dry weight) * Sites Elements (Distance from smelter) Al As Ca c Co Cu Fe K P Pb Mg Mn s Ni N Sr Zn Eroded/ 15288b 87.07a 5760a 92483a 37.3a 661.7b 27433a 8574a 568a 75.55b 1830a 224a 1635a 602b 3811a 48a 54a Disturbed ±1495 ±64 ±1358 ±7811 ±9.4 ±98.3 ±2927 ±671 ±39 ±21.5 ±349 ± 1 0 ±192 ±97 ±409 ± 1 0 ± 6 (0-5 km) Stable 18300b 21.35b 4818a 207000a 63a 1334a 27783a 6813a 803a 175.6a 2081a 366a 1527a 1766a 9015a 64a 1 0 1 a upland ±837 ±5.33 ±900 ±28291 ± 2 2 ±481 ±7317 ±569 ±195 ±38.3 ±159 ±74 ±155 ±679 ±1921 ±7 ±25 (5-15 km) Control 21766a 5.19c 5880a 167373a 1 0 a 133c 11410a 7556a 775a 76.2b 1576a 317a 1504a 205c 6466a 83a 77a (> 15 km) ±692 ±2.32 ±608 ±74223 ±3 ±23 ±1549 ±359 ±29 . ± 1 0 ±105 ± 6 8 ±255 ±75 ±2854 ± 8 ±9 ^Results are expressed as mean values ± standard error based on three replicates (n = 3) Means in columns with a common subscript are not significantly different based on Tukey multiple comparison test (p > 0.05). Eroded/Disturbed sites: Daisy Lake, Wahnapitae Hydro Dam, Falconbridge; Stable upland sites: Laurentian, Kukagami, Kingsway; Control sites: Capreol, St. Charles, Onaping. 33 Table 4: Mean concentration of bioavailable elements in the organic surface horizons (LFH) of soils from the Sudbury region sites (concentrations are in mg kg'1, dry weight) Sites Elements* (Distance from Smelter) Al As Ca Cd Co Cu Fe K P Pb Mg Mn Na Ni Sr Zn Eroded/ 54.06a 0.42a 197.69a Stable 96.25a 0.23a 126.18a Control 169.63a 34 Table 5: Mean concentration of total elements in the limed and unlimed organic surface horizons (LFH) of soils from the Sudbury region sites (concentrations are in mg kg'1, dry weight) Sites Elementsa Al As* Ca C Co Cu Fe K P Pb Mg Mn S Ni N Sr Zn Limed 13666 1.46 6920 124267 41 952 20800 7066 571 91.23 2309 198 1290 991 5343 58 68 ±1439 ±1.28 ±2044 ±26533 ±14 ±343 ±3634 ±316 ±93 ±45 ±672 ±41 ±147 ±485 ±1170 ±12 ±21 Unlimed 17783 18.98 4106 136583 42 1021 29000 8540 600 120.3 1548 242 2001 1061 6345 62 73 ±2573 ±5.82 ±617 ±39404 ±11 ±356 ±3364 ±187 ±37 ±43 ±194 ±15 ±205 ±398 ±1860 ±10 ±16 a Results are expressed as mean values ± standard error based on three replicates (n = 3) * represents significant difference between treatments based on t-test (p < 0.05) Lime and No lime sites: Daisy Lake, Wahnapitae Hydro Dam and Kingsway. 35 Table 6: Mean concentration of bio-available elements in the limed and unlimed organic surface horizons (LFH) of soils from the Sudbury region sites (concentrations are in mg kg'1, dry weight) Sites Elements2 Al* As Ca* Cd Co Cu Fe* K P Pb Mg* Mn* Na Ni Sr* Zn Limed 43.3 0.14 252.8 Unlimed 77.8 0.10 82.3 a Results are expressed as mean values ± standard error based on three replicates (n = 3) *Represents significant difference between treatments based on t-test (p > 0.05) Limed and No limed sites: Daisy Lake, Wahnapitae Hydro Dam and Kingsway. 36 Table 7: Percentage of bioavailable relative to total elemental concentration for the LFH horizon of soils from the Sudbury region sites Sampling sites Elements* Al As Ca Cd Co Cu Fe K P Pb Mg Mn Ni Zn Daisy Lake 0.65 2.28 2.19 0.61 0.87 0.33 1.33 1 . 0 0 0.15 3.11 4.35 0.73 1.53 Wahnapitae 0.36 - 3.18 0.43 1.19 0.34 0.99 1.06 0 5.39 2.14 0.51 0.98 Hydro Dam Laurentian 0.78 - 1 . 2 2 0.56 0.70 0.19 3.71 0.47 0.18 1.40 5.38 0.35 0.99 Kukagami 0.60 - 3.77 2.61 1.96 0.84 2.75 4.68 0.78 3.06 12.59 1.39 2.97 Kingsway 0.23 - 2.38 0.48 0.95 0.18 1.99 0.94 0.14 4.56 4.19 0.49 1.40 Falconbridge 0 . 1 0 0.64 3.43 0.29 0.75 0.15 0.53 0 . 6 6 0 . 2 1 9.90 0.79 0.59 0.39 Capreol (Control) 0.28 - 3.99 1.25 1 . 1 1 0 . 2 2 4.58 0.53 0.41 4.13 0.47 1.37 0.26 St. Charles 1 . 2 1 - 2.84 4.24 0.62 0.38 3.73 1.31 0.54 2.73 9.27 2.58 5.87 Onaping Falls 0.78 - 6.55 3.02 1 . 2 0 1.06 3.21 ■ 12.08 1.41 5.84 15.49 2.80 6.67 *Values as percent (%) 37 Table 8: Correlation between total and bio-available elemental concentration in soil profiles from the Sudbury region sites Element LFH Ae Bm BC C Aluminum 0.06 -0.03 -0.23 -0.31 -0.79* Barium 0.29 -0.35 -0.19 0.01 0.09 Calcium 0.93* 0.49 0.54 -0.02 -0.10 Cobalt 0.65 0.90* 0.49 0.79* 0.51 Copper 0.90* 0.45 0.45 0.34 0.24 Iron 0.02 0.13 0.27 0.69 0.98* Potassium -0.002 0.65 0.06 0.34 -0.26 Magnesium 0.83* 0.42 0.77* 0.46 -0.21 Manganese 0.88* 0.99* 0.82* 0.95* 0.74 Sodium -0.17 -0.18 -0.31 -0.49 -0.15 Strontium 0.49 0.28 0.05 0.02 0.13 Nickel 0.89* -0.23 0.19 0.16 0.87* Phosphorus 0.21 0.01 -0.15 0 0 Zinc 0.49 -0.05 0.27 0.43 0.60 * Represents strong correlation between two variables based on the Pearson Correlation. 7 sites: Daisy Lake, Wahnapitae Hydro Dam, Laurentian, Kukagami, Kingsway, Falconbridge and Capreol (control) 38 Table 9: The pH levels of individual soil horizons from the Sudbury region sites Sampling Layer 1 Layer 2 sites Type pH pH pH pH h 2o CaCl2 h 2o CaCl2 Daisy Lake Unlimed 4.04 3.87 3.68 3.92 Limed 4.12 4.05 3.90 4.18 Wahnapitae Unlimed 3.82 3.56 3.75 3.85 Hydro Dam Limed 6.75 6.34 5.88 6.41 Laurentian Unlimed 3.84 3.54 4.18 4.19 Kukagami Not limed 3.93 3.61 4.0 3.93 Kingsway Unlimed 3.87 2.35 3.92 3.70 Limed 4.67 4.35 4.09 4.03 Falconbridge Limed 5.48 5.27 4.68 4.22 Capreol Unlimed 3.92 3.43 4.11 3.74 (control) St. Charles Unlimed 3.50 3.23 3.98 3.78 Onaping Falls Unlimed 3.79 3.46 4.87 3.75 39 Table 10: Mean concentration of total elements in leaves of red oak (Quercus rubra) from the Sudbury region sites, concentrations are in mg kg'1, dry weight. Sites Elements (Distance from smelter) A1 As Ca Cd Co Cu Fe Pb Mg Mn Ni Sr Zn Eroded/ Disturbed (0 -5 km) 1253ac 1.3a 6805a 0.15a 0.48a 18a 97a Stable upland (5 - 15 km) 1560a Control (> 15 km) 569.27bc ^Represents significant difference between treatments based on ANOVA test (p < 0.05) Eroded/Disturbed sites: Daisy Lake, Wahnapitae Hydro Dam, Falconbridge; Stable upland sites: Laurentian, Kukagami, Kingsway; Control sites: Capreol,Onaping Falls 40 Table 11: Mean concentration of total elements in branches of red oak (Quercus rubra) from the Sudbury region sites, concentrations are in mg kg'1, dry weight. Sites Elements (Distance from smelter) A1 As Ca Cd Co Cu Fe Pb Mg Mn Ni Sr Zn Eroded/ Disturbed (0 - 5 km) 1021a 0.8a 5636a 0.38a 0.82a 26a 249a 1.23a 1127a 295a 28a 18a 19a ±163 ±0.41 ±564 ±0.14 ±0.28 ±9.24 ±125 ±1.26 ±315 ±106 ±6.34 ±4.28 ±1.42 Stable upland (5 - 15 km) 670a 0.9a 6072a 0.62a 0.49b 19a 67.9a 2.08a 805a 637a 15ac 12a 22a ±162 ±0.66 ±976 ±0.10 ±0.17 ±6.5 ±25.2 ±1.38 ±160 ±242 ±2.75 ±2.00 ±2.48 Control (> 15 km) 367a 0.62b 5997a 0.55a 0.06c 6 .8a 13.7a 0.33b 1313a 311.7a 4.4bc 34.7b 22.6a ±332.19 ±0.61 ±190.52 ±0.14 ±0.06 ±1.91 ±13.75 ±0.16 ±625 ±131.72 ±2.59 ±5.06 ±3.16 *Represents significant difference between treatments based on ANOVA test (p < 0.05) Eroded/Disturbed sites: Daisy Lake, Wahnapitae Hydro Dam, Falconbridge; Stable upland sites: Laurentian, Kukagami, Kingsway; Control sites: Capreol, Onaping Falls 41 Table 12: Mean concentration of total elements in leaves of red oak (Quercus rubra) from the Sudbury region sites, concentrations are in mg kg ', dry weight. Sites Elementsa A1 As Ca Cd* Co Cu Fe KP Pb Mg Mn* Ni Sr Zn Limed 1385 0.25 6647 0.08 0.46 17.6 92.9 12435 2431 Unlimed 1401 0.97 7282 0.23 0.15 13.6 101 11690 2149 * Represents significant difference between treatments based on t-test (P < 0.05). Lime and No lime sites: Daisy lake, Wahnapitae Hydro Dam and Kingsway. 42 Table 13: Mean concentration of total elements in branches of red oak (Quercus rubra) from the Sudbury region sites, concentrations are in mg kg'1, dry weight. Sites Elements a A1 As Ca Cd Co Cu Fe* K P Pb* Mg* Mn Ni Sr Zn Limed 811 0.99 5457 0.29 0.82 33.5 269 6630 1342 3.35 1098 282 25 15.5 22 ±146 ±0.58 ±904 ±0.14 ±0.32 ±14 ±192 ±1833 ±363 ±2.0 ±517 ±126 ±9 ±6.4 ±1.3 Unlimed 942 0.99 6451 0.56 0.52 15.2 98 5655 1265 0.36 888 524 19 17.9 18 ±164 ±0.41 ±648 ±0.10 ±0.21 ±3 ±40.6 ±836 ±166 ±0.36 ±91.4 ±153 ±5 ±2.7 ±1.7 * Represents significant difference between treatments based on t-test (P < 0.05). Lime and No lime sites: Daisy lake, Wahnapitae Hydro Dam and Kingsway. 43 Table 14: Mean concentration of total elements in leaves and branches of red oak (Quercus rubra) from the Sudbury Region sites, concentrations are in mg kg'1, dry weight. Type Elementsa A1 As Ca Cd Co Cu Fe K* P Pb* Mg* Mn Ni Sr Zn Leaves 1287 0.7 6801 0.174 0.2 15.0 90 11881 2316 Branches 824 0.9 6342 0.47 0.6 20.0 147 5772 1216 1.37 947 434 20.0 18.0 21 ±129 ±0.4 ±451 ±0.04 ±0.17 ±1.8 ±10 ±1441 ±341 ±244 ±177 ±3.6 ±1.3 ±2.1 * Represents significant difference between treatments based on t-test (P < 0.05). Leaves and Branches: Daisy lake, Wahnapitae Hydro Dam, Laurentian, Kukagami, Kingsway, Falconbridge, Capreol, Onaping Falls 44 Table 15: Summary of elemental concentrations from limed sites in soil and red oak tissues (concentrations are in mg kg ', dry weight) Elements A1 As Ca Co Cu Fe KP Pb Mg Mn Ni Sr Zn Total Soil 13666 15.78 6920- 41 952 20800 7066 571 105.9 2309 198 991 58 68 Bioavailable 43.3 0.14 252.8 0.12 7.21 42.07 98.13 6.14 0.21 169.1 3.71 4.2 0.07 0.48 soil Branches 811 0.99 5457 0.82 33.5 269 6630 1342 3.35 1098 282 25 15.5 22 Leaves 1385 0.25 6647 0.46 17.6 92.9 12435 2431 0 2367 677 27 9.4 26 45 Table 16: Summary of elemental concentrations from unlimed sites in soil and red oak tissues (concentrations are in mg kg'1, dry weight) Element A1 As Ca Co Cu Fe K P Pb Mg Mn Ni Sr Zn Total Soil 17783 1.46 4106 42 1021 29000 8540 600 91.23 1548 242 1061 62 73 Bioavailable 77.8 0.1 82.3 0.31 12.04 108.6 129.22 6.05 0.16 39.78 13.95 6.85 0.33 1.48 soil Branches 942 0.99 6451 0.52 15.2 98 5655 1265 0.36 888 524 19 17.9 18 Leaves 1401 0.97 7282 0.15 13.6 101 11690 2149 0 2434 1195 24 9.6 27 46 Site 7 Capreol X Skead Valley East Suez Carr's Landing Vai Therese Parkwood Hanmer Boland's Bay Pmecrest Carol Samard As at w # * r k# ... Garson Junction % T35? 1 “^ (74'I Site 4 Sudbury L tt* t!« y ^4f'croft£> Ro^'zrd Site 2 jn{copp*t Moon:jM Beech Site 1 Lake Laurenaan Conservation Area ? Site 8 » Fiektng Bad 2 in . Sanctuary V * ■d*** 1 \ © S£^ iStak Figure 3: Location of red oak sampling sites within the Sudbury region. Site 1: Daisy Lake; Site 2: Wahnipitae Hydro Wahnapitae Hydro Dam; Site 3: Laurentian; Site 4: Kukagami; Site 5: Kingsway; Site 6: Falconbridge; Site 7: Capreol; Site 8: St. Charles; Site 9: Onaping Falls; Site 10: Airport 47 2.4 Discussion Monitoring the long term consequences of metal contamination as well as the results of land remediation is important to determine ecological sustainability. The Sudbury region is a valuable area to conduct research on metal content in soil due to the century of mining and smelting activities. These activities have led to harmful sulfur dioxide emissions and copper and nickel particulate depositions which created 10 000 ha of barren land. The main factors restricting vegetative growth are the acidity and aluminum-, copper- and nickel-toxic properties of the soil (Winterhalder, 1996). Dolomitic and calcitic liming was applied to certain soils of the Sudbury region to counteract the toxic outcomes. The effects of metal contamination as well as liming are documented in this study through analysis of soil as well as red oak tissues. The highest total metal concentrations occurred in the organic-rich upper soil horizon (LFH). This indicates that the metal particulates found in soil are dominantly due to an airborne cause rather than an interior cause. There were significant differences in total metal concentrations among varying soil depths. With the exception of total potassium, the amount of total arsenic, carbon, cobalt, copper, phosphorus, lead, magnesium, manganese, sulfur, nickel and nitrogen was significantly higher in the first horizon compared to the rest of the layers. The trend remained the same for bioavailable metal content. However with bioavailable aluminum, calcium, iron, potassium, magnesium, sodium, nickel, strontium and zinc having dominantly higher concentrations in top layers. These results suggest that the vertical movement of metals in soils many not influence the availability of metals to plants in contaminated sites of the Sudbury region. The distances of sites from smelters also played a role in the amount of metal content. 48 The total amount of copper, lead and nickel were significantly highest in stable upland sites located 5-15km away from smelters compared to eroded/disturbed sites closer to smelters. Previous studies that have analyzed strictly the stable sites within 5km of smelters have shown higher concentrations of metals compared to sites located beyond 5km (Gratton et al., 2000b). This indicates that it is both the topographical location as well as the distance from smelters that affect the amount of metal accumulation in surface soil. The concentrations of bioavailable metals are dominantly higher in the control sites located greater than 15km from the smelters and significant differences occurred in concentrations of potassium, manganese, strontium and zinc in which distances closer to smelters contained lower concentrations. There was a significant association between the levels of total and bioavailable calcium, magnesium, manganese and nickel and soil. The bioavailable metal level in soil analyzed in this study was determined to be a critical aspect of phytoxicity. Although total amounts of metal content in soil of certain sites were high, the percentage of bioavailable metal relative to total metal was much lower. This indicates that the amount readily available to plants is much lower and therefore toxic levels in contaminated soils are minimal. Determining phytoxicity in plants should therefore be assessed through plant tissues directly. The decade of SO2 fumigations and metal particulate accumulations in the soil of the Sudbury Region has greatly impacted its mineral composition which in turn changed its chemistry. The soil’s high metal content in certain areas created a more acidic and hostile environment for plant growth and therefore liming was applied to neutralize and detoxify the soil. Both calcitic and dolomitic liming was applied manually as well as aerially in certain sites. The present study revealed that the soil pH in limed areas was higher than in unlimed areas. Total arsenic concentrations were significantly higher in 49 limed areas and the amount of bioavailable aluminum, iron and strontium were significantly lower in limed sites compared to unlimed sites as illustrated in table 5. This is consistent with Winterhalder (1983), who reported that aluminum also reaches toxic levels when pH of soil decreases. The antagonistic interaction between aluminum and nickel is also seen in these results as the low nickel concentration of 4.15mg/kg in limed areas and 6.85mg/kg in unlimed areas is a result of aluminum protecting the plant from increased nickel concentrations (Winterhalder, 1996). A measurable decrease in bioavailable amounts of cobalt, copper, potassium, manganese, nickel and zinc. The amounts of bioavailable calcium and magnesium is measurably higher in limed areas which reflects the addition of calcitic and dolomitic lime. The neutralizing power of the limestone may be expected to halt eventually leading to a deterioration of the plant community. However, as the present study illustrated, is not the case. This is because the detoxification of the soil causes roots to penetrate further into the soil and calcium and magnesium to cycle from lower horizons to the surface layer. This phenomenon is referred to as a cation pump (Aber, 1987). The pH of soil is an important factor in regulating metal and nutrient content. If the pH of soil is too low, the availability of nutrients to plants may be disrupted as seen in the barren lands of the Sudbury region. Increasing soil pH will increase the rate of organic matter mineralization. The present study determined that there is a measurable difference between areas which were limed and areas which have not been limed. The pHs of limed areas were found to be measurably higher than unlimed areas in the various sites and specifically between adjacent areas. The pH values found in this present study shows that the liming of soils 30-40 years ago continues to produce long term advantages. Although smelters are still currently in use, pH values were not as low as values recorded prior to 50 liming. For example extremes of soil acidity were once recorded to have been a pH of 2.4 and pH of 2.2 (Winterhalder, 1996). The high pH value is also reflected on the metal content as there were significantly lower bioavailable concentrations of aluminum, iron and strontium in limed areas. It was also found that the neutralizing effects of lime are not constrained to a specific layer of the soil as there were no significant pH differences within the layers observed. The enrichment factor (EF) was calculated to establish the degree of soil contamination and heavy metal accumulation. It is the ratio between the concentration of metals in contaminated soil and the concentration of metals in uncontaminated soils. Values greater than 1 indicate environmental pollution (Singh et a l, 2010). The EF for this present study was determined for the four elements which contained a significant difference between eroded/disturbed and control sites. The elements included aluminum, arsenic, copper and nickel. Their respective EF values were 0.702, 16.78, 4.98 and 2.94. Although aluminum did not contain a value to signify environmental pollution, arsenic, copper and nickel are far above the value of contamination resulting in high availability and distribution of metals in soil. The high EF values of copper and nickel are attributed to the mining and smelting activities which occur in Sudbury. These values may be an indication that there may ultimately be an increase in metal accumulation in plants located on contaminated sites (Gupta et al., 2008). The translocation factor (TF) was calculated as the ratio of the concentration of metal in plant tissue and the concentration of metal in corresponding soil root area. It is used to determine relative translocation of metals from the soil to branches (Singh et al, 2010). The values found were relatively low for the majority of elements. However, the 51 translocation factors for bioavailable elements from soil to branches were high. This is true for both contaminated and uncontaminated sites. It was also determined that the accumulation of metals was higher within leaves than the branches of red oak populations. The tissue analysis of this present study was important in determining the level of metal and nutrient uptake by northern red oak and the mobility of elements from the soil. The amount of metal uptake in leaves and branches is simply the total amount of metal. Total cadmium and manganese were significantly different in leaves of limed compared to unlimed areas and iron, lead, magnesium and nitrogen were significantly different in branches of limed compared to unlimed areas. There was also a significant difference in total potassium, lead, magnesium, manganese, sulfur and nitrogen between leaves and branches, in which all stated metals were dominant in leaves except lead. The amount of total metal concentrations found in the tissues is much lower than the total amount in soil. This may be explained because plants may counteract high concentrations of heavy metals by excluding potentially toxic elements entirely or by excluding them from active metabolic sites (Leavitt et al., 1979). Comparing the concentrations of bioavailable metal in soil and the metal content in leaves and branches, shows there is a measurable difference. The amount of metal in the leaves and branches of red oak is higher than the amount of bioavailable metal in soil. This may suggest red oak’s accumulation characteristic. It is able to retain metal and nutrient content taken up in its tissues and store it. A previous study found similar results for the accumulation of metals by red oaks. The study observed that Ag, Cd, Cu and Zn were accumulated in the tissues but excluded Pb in leaves and twigs (Leavitt et a l, 1979). 52 Considering that the amount of copper and nickel taken up is very small, red oaks would not be well utilized for phytoremediation of the Sudbury ecosystem. 53 Chapter 3: Genetic Analysis Quercusof rubra populations from metal contaminated and uncontaminated sites in the Greater Sudbury Region (Ontario, Canada) 3.1 Introduction The Greater Sudbury region is widely known for its nickel and copper deposits. The extractions of these valuable deposits have caused negative effects to the environment of Sudbury due to the roasting beds, mining and smelting processes. These practices have produced fumigations that are extremely toxic, such as sulfur dioxide and contamination of various metal particulates, which seep into the soil and ultimately harm the vegetative growth. The effects have been seen through 10,000 hectares of barren land and since 1978 have pushed large remediation projects. The steps of remediation involve liming of the soil to neutralize soil pH which acidify due to the metal particulates, application of fertilizer, distribution of seeds and tree planting. The tree planting has been an integral part of regreening, as it introduced new tree species and expanded native species. Of the trees planted since the start of the regreening programs, 95% were conifers and 5% were hardwood species. Many studies have been conducted on the fitness and viability of the introduced plant species. The present study will be the first to analyze the fitness and sustainability of a hardwood species, northern red oak (Quercus rubra) in the Greater Sudbury Region, since previous studies involved only conifer species. Red oaks were one of the few species found on the drier barren sites and have survived the stresses responsible for the loss of the original vegetation (Winterhalder, 1996). The understanding of their genetic diversity is critical as it is a factor in the determination of their sustainability. Genetic diversity is the key factor in species survival and adaptability to stressful environments as well as the driving force for evolution. It is defined as the allelic differences and combinations in a gene pool. High levels of diversity indicate 54 health and increased chances of survival against stress whereas low levels limit a species from surviving and responding to environmental threats. Therefore the level of genetic diversity is important in the ongoing monitoring of the remediation projects and of the long term effects of liming on plant species. This study will measure genetic diversity using the inter-simple sequence repeat- polymerase chain reaction (ISSR-PCR) technique. This technique is practical because it does not require any prior sequence information, it is quick, simple and produces ISSR markers which are highly polymorphic. It combines the advantages of SSRs and amplified fragment length polymorphism (AFLP) to the universality of random polymorphic DNA (RAPD) (Reddyet al., 2002). The objective of this component of the present study is to determine the effect of liming and metal contamination on genetic variability and sustainability of red oak (Quercus rubra) populations from the Greater Sudbury Region. 3.2 Materials and Methods 3.2.1 Sampling Fresh Quercus rubra leaf samples were collected from 10 sites around the Greater Sudbury Region based on leaf morphology. Twenty trees representing each targeted population were selected for the study. The populations include Daisy Lake limed, Daisy Lake unlimed, Wahnapitae Hydro Dam limed, Wahnapitae Hydro Dam unlimed, Kukagami, Laurentian, Kingsway, Falconbridge, Capreol, St. Charles, Onaping Falls and Airport. Leaves were collected if they possessed an elliptical shape with 7-11 shallow waxy lobes. Leaf samples were wrapped in aluminum foil, immersed in liquid nitrogen and stored at -20°C until DNA extraction. 55 3.2.2 Molecular Analysis DNA Extraction Genomic DNA was extracted from fresh frozen leaf material using the CTAB extraction protocol as described by (Nkongolo, 1999; Mehes et al., 2007). The protocol is a modification of Doyle and Doyle’s (1987) procedure. These modifications included the addition of 1% polyvinyl pyrrolidone (PVP) and 0.2% beta mercaptanol to the cetyl trimethylammonium bromide (CTAB) buffer solution, two additional chloroform centrifugation steps of 10 minutes prior to the isopropanol spin and no addition of RNAse. After extraction, DNA was stored in a freezer at -20°C. DNA samples were then tested for quality and intactness by gel electrophoresis on 1% agarose gels in 0.5x Tris-Borate-EDTA (TBE) pre-stained with lpL of ethidium bromide. A mixture of 5pL of stock DNA and lpL of 6x loading buffer was loaded into the wells of the agarose gel and was run at 60V for 90 min. Gels were then visualized under an ultra-violet light source documented with Bio-Rad ChemiDoc XRS™ system and analyzed with Image Lab Software™. DNA, quantitation was performed using the BIO-RAD™ Quantitation Kit (catalogue# 170-2480). Concentrations were determined by fluorochrome Hoechst. To this end, 96-well microplates were spotted with 200 pL of Hoechst dye. The dye mixture contained 3.2 mL of lxTEN assay buffer, 6 pL of 4 2 pg/mL of Hoechst dye, 28.79 mL of ddH20. A standard curve was produced using known calf thymus DNA. For calf thymus concentration of 100 ng/pL the following volumes were added, 1750 ng, 1500 ng, 1250 ng, 1000 ng, 750 ng, 500 ng and 250 ng. For calf thymus concentration of 10 ng/pL the following volumes were added, 100 ng, 75 ng, 50 ng and 25 ng. 2 pL of extracted oak DNA were added to the plates in duplicates. The DNA fluorescence intensity was 56 measured using BMG LABTECH FLUOstar OPTIMA microplate multi-detection reader in fluorescence detection mode. The DNA concentration was standardized at 5 ng/pL. ISSR analysis A total of 15 ISSR primers were pre-screened for polymorphism and reproducibility. Of these, eight primers were identified. These included 178 99A, 178 99B, UBC 841, UBC 825, ISSR 5, 8, 9 and 10. Five of these eight primers that produced strong bands were selected for ISSR analysis and include 178 98B, UBC 825, ISSR 5, 9 and 10. PCR amplification was carried out as described by Mehes et al. (2007) in a 25 pL total volume containing a master mix of 11.4 pL distilled water, 2.5 pL MgS0 4 , 2.1 pL lOx buffer 0.5 pL of dNTPs (equal parts dTTP, dATP, dCTP, dGTP), 0.5 pL of ISSR primer, a Taq mix of 3.475 pL distilled water, 0.4 pL lOx buffer and 0.125 pLTaq polymerase (Applied Biosystems) and 4 pL standardized DNA. Each primer contained a negative control of master mix and Taq mix without any DNA. All samples were covered with one drop of mineral oil to prevent evaporation and amplified with the Eppendorf Mastercycler gradient. The program was set to a hot start of 5 minutes at 95 °C followed by 2 minutes at 85°C which the Taq mix was added, then 42 cycles of 1.5 minutes at 95°C, 2 minutes at 55°C and one minute of 72°C. A final extension of 7 min at 72°C after which samples were removed from thermocycler and placed in the -20°C freezer until further analysis. After the DNA samples were amplified, they were separated for analysis on a 2% agarose gel in 0.5x TBE with ethidium bromide. A total of 5 pL of lx loading buffer were added to the PCR products and 10 pL of this solution were loaded into the wells of the 57 gel. The gel was run at 64V for 120 min, documented with the Bio-Rad ChemiDoc XRS™ system and analyzed with Image Lab Software™. 3.2.3 Statistical Analysis Five primers were chosen based on polymorphism and reproducibility. The amplified ISSR bands produced were scored as either present (1) or absent (0) to determine the variations within and between populations. Popgene software version 1.32 (Yeh et al. 1997) was used to determine percentage of polymorphic loci, observed and expected number of alleles, Nei’s gene diversity and Shannon’s information index. The genetic distances were calculated using Jaccard’s similarity coefficients with Free Tree Program version 1.50. A neighbour-joining dendogram was produced from the similarity coefficients, the method starts with a starlike tree with no hierarchical structure and in a stepwise fashion finds the two operational taxonomic units that minimize the total branch length at each cycle of clustering. The unrooted tree generated by the neighbour-joining method is constructed under the principle of minimum evolution (Saitou and Nei, 1987). 3.3 Results 3.3.1 Degradation Analysis All samples of extracted genomic DNA were tested for quality. Figure 4 illustrates a gel confirming intact DNA of 20 red oak samples. Presence of a large molecular weight band at the top of the gel indicated the presence of intact DNA and viable for ISSR-PCR amplification. 3.3.2 ISSR-PCR Amplification and Polymorphism Preliminary screenings with fifteen primers (Table 17) were performed on bulk DNA from each site for northern red oak ( Q. rubra) and five most polymorphic and 58 reproducible were chosen to amplify all standardized DNA samples from the 10 populations. These included ISSR 178 98B, ISSR UBC 825, SC ISSR 10, SC ISSR 9, and SC ISSR 5. The results are illustrated in Figures 6-10. 3.3.3 Genetic Variability Genetic parameters were determined for the 13 red oak populations using the Popgene Software version 1.32 (Yeh et al. 1997). The percentage of polymorphic loci (%), the observed number of alleles (Na), the expected number of alleles (Ne), Nei’s gene diversity (h) and Shannon’s information index (I) were all generated and illustrated in Table 18. The mean values for Na, Ne, h and I were 1.54, 1.22,0.14 and 0.22. The level of inter-population polymorphism was 97.87%. The total gene diversity (Ht) and the mean gene diversity between populations (Hs) were 0.21 and 0.14, respectively. The population differentiation(G s t ) value was 0.34 (34%) and the estimated gene flow (Nm) was 0.98. The levels of polymorphism per primer were 61%, 73%, 66%, 56% and 48% for 178 98B, UBC 825, ISSR 10, ISSR 9 and ISSR 5, respectively. The levels of genetic variation in all populations were moderate to high. In fact the percentage of polymorphic loci varied between 43.97% (St. Charles) and 64.54% (Capreol). The observed number of alleles ranged from 1.44 (St. Charles) to 1.65 (Capreol) with a mean of 1.54. The expected number of alleles ranged from 1.18 (Kingsway, limed) to 1.28 (Capreol) with a mean of 1.22. Nei’s gene diversity, h, ranged from 0.12 (Kingsway, limed) to 0.17 (Capreol and Falconbridge) with a mean of 0.14. Shannon’s information index revealed a range between 0.19 (Kingsway, limed) and 0.27 (Capreol) with a mean of 0.22. The mean polymorphic indices were determined for limed and unlimed areas and between eroded/disturbed, stable upland and control sites. Neither 59 groupings resulted in significant differences. The mean levels of polymorphism were 53% and 55% for limed and unlimed populations, respectively. The mean levels of polymorphism were 56%, 53% and 55% for populations located at 5km, 5-15 km and greater than 15 km from the smelters, respectively. 3.3.4 Genetic Relationship All genetic markers were scored based on the presence or absence of amplification products observed as bands on the agarose gels. The data was used to calculate the genetic distances for the 13 populations as illustrated in Table 19. The values are based on a scale between 0 (identical) and 1 (different for all criteria). In the present study, the results of the genetic distances ranged between 0.215 (Capreol and Falconbridge) and 0.611 (Airport and Daisy Lake, limed). In general, 42% of genetic distance values were below 0.4 and three pairs of the populations analyzed were genetically closely related with distance values below 0.3. The distance matrix data was used to construct a dendrogram (Figure 5) to show the genetic relationships among the populations. The present study revealed that Daisy Lake and Kukagami form a cluster that is separate from the other population groupings with 100% degree of confidence. Data also showed that red oak populations from Onaping Falls and St. Charles clustered together with a 74% degree of confidence and the Airport population clustered with populations from these sites with 100% degree of confidence. Capreol and Falconbridge were found to cluster together with a 96% degree of confidence. But population grouping was not associated with the level of soil or plant metal content or geographical distance. 60 Figure 4: Degradation analysis illustrated on a 1% TBE agarose gel for DNA of red oak samples. The top band indicates intact genomic DNA. Lack of smearing is indicative of lack of degradation. Lane 1 contains lkb+ ladder; Lanes 2-21 contains red oak DNA samples. Table 17: The nucleotide sequence of ISSR primers used to screen DNA from red oak (Quercus rubra) populations samples ISSR Primer Nucleotide sequence (5’ 3’) Amplification Fragment size range (bp) HB 15 GTGGTGGTGGC Poor - HB 13 GAGGAGGAGGC Poor _ 17898A CACACACACACAAG Fair - 17898B CACACACACACAGT Good 200-1300 UBC 841 GAAGGAGAGAGAGAGAYC Fair - UBC 829 TGTGTGTGTGTGTGC Poor - UBC 827 ACACACACACACACACG Poor - UBC825 ACACACACACACACACT Good 320-950 CTTCXTCXXCTXCXTCCXCCXCCXCCTCCXCCTCT Good SC ISSR 10 400-2000 SC ISSR 9 GATCGATCGATCGC Good 320-2000 SC ISSR 8 AGATAGATAGATAGATAGATGY Fair - SC ISSR 7 AGGAGGAGGAGGAGGGY Poor - SC ISSR 6 TTGTTGTTGTTGTTGCB Poor - SC ISSR 5 ACGACGACGACG Good 210-1000 SC ISSR 4 CGTCGTCGTCGTC Poor - Possible nucleotides for base B are C, G or T and for base Y are C or T. 62 Table 18: Genetic variability parameters of red oak (Quercus rubra) populations based on ISSR data. Population P(%) Na Ne h I Daisy Lake Limed 51.77 1.52 1.21 0.13 0.20 Daisy Lake Unlimed 52.48 1.52 1.20 0.13 0.20 Wahnapitae Hydro Dam 54.61 1.55 1.21 0.13 0.21 Unlimed Wahnapitae Hydro Dam 51.77 1.52 1.20 0.13 0.21 Limed Laurentian 51.77 1.52 1.24 0.15 0.23 Kukagami 56.03 1.56 1.22 0.14 0.21 Kingsway Limed 54.61 ' 1.55 1.18 0.12 0.19 Kingsway Unlimed 58.87 1.59 1.22 0.14 0.23 Falconbridge 61.70 1.62 1.27 0.17 0.26 Capreol 64.54 1.65 1.28 0.17 0.27 St. Charles 43.97 1.44 1.21 0.13 0.20 Onaping Falls 51.06 1.51 1.22 0.13 0.21 Airport 48.94 1.49 1.22 0.14 0.21 Mean 1.54 1.22 0.14 0.22 Genetic diversity descriptive statistics. F: percentage of polymorphic loci; Na: observed number of alleles; Ne: expected number of alleles; h: gene diversity (Nei, 1973); I: Shannon’s information index. 63 Table 19: Distance matrix generated from ISSR data using the Jaccard’s similarity coefficient analysis for 13 red oak (Quercus rubra) populations (Free Tree Program version 1.50) Daisy Daisy Wahnapitae Wahnapitae Laurentian Kukagami KingswayKingsway Falconbridge Capreol St. Onaping Airport Lake Lake Hydro Dam Hydro Dam Limed Unlimed Charles Falls Limed Unlimed Unlimed Limed Daisy Lake 0 0.347 0.347 0.374 0.422 0.382 0.392 0.347 0.398 0.396 0.600 0.536 0.611 Limed Daisy Lake 0 0.293 0.320 0.386 0.379 0.323 0.327 0.395 0.378 0.556 0.545 0.580 Unlimed Wahnapitae 0 0.303 0.415 0.377 0.324 0.374 0.378 0.333 0.550 0.500 0.586 Hydro Dam Unlimed Wahnapitae 0 0.330 0.373 0.333 0.286 0.374 0.343 0.538 0.514 0.550 Hydro Dam Limed Laurentian 0 0.404 0.429 0.400 0.374 0.402 0.538 0.514 0.537 Kukagami 0 0.307 0.362 0.452 0.436 0.580 0.593 0.554 Kingsway 0 0.307 0.391 0.315 0.537 0.553 0.495 Limed Kingsway 0 0.349 0.333 0.563 0.473 0.509 Unlimed Falconbridge 0 0.215 0.496 0.460 0.482 Capreol 0 0.478 0.443 0.504 St. Charles 0 0.402 0.475 Onaping 0 0.481 Falls Airport 0 64 Laurentian Airport f— — Onaping ,•( t . ------S t Charles ------5 ------Capreol ■ Falconbridge _ _ _ _ Wahnapitae Hydro ------* ------; i Dam Limed Kingsway UnNmed Kingsway Limed ,x ------Daisy Lake UnHmed Wahnapitae Hydro Dam Unlimed Daisy Lake Limed — » Kukagami Figure 5: Dendrogram based on ISSR data for 13 Quercus rubra populations (Free Tree Program version 1.50) 65 1 2 3 4 5 6 7 8 9 10 U 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 Figure 6: ISSR amplification of red oak samples with primer ISSR 178 98B. Lanes 1, 22 and 33 contain lkb+ ladder; Lanes 2-21 contain red oak samples from St. Charles population; Lanes 23-32 contain red oak samples from Onaping Falls population. 66 Figure 7: ISSR amplification of red oak samples with primer ISSR UBC 825. Lanes 1, 22 and 33 contain lkb+ ladder; Lanes 2-21 contain red oak samples from Falconbridge population; Lanes 23-32 contain red oak samples from Capreol population. Figure 8: ISSR amplification of red oak samples with primer ISSR 10. Lanes 1, 22 and 33 contain lkb+ ladder; Lanes 2-11 contain red oak samples from Wahnapitae Hydro Dam Unlimed population; Lanes 13-32 contain red oak samples from Wahnapitae Hydro Dam Limed population. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 Figure 9: ISSR amplification of red oak samples with primer ISSR 9. Lanes 1, 22 and 35 contain lkb+ ladder; Lanes 2-21 contain red oak samples from St. Charles population; Lanes 23-35 contain red oak samples from Onaping Falls population. 69 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 Figure 10: ISSR amplification of red oak samples with primer ISSR 5. Lanes 1, 20 and 31 contain lkb+ ladder; Lanes 2-9 contain red oak samples from Daisy Lake Unlimed population; Lanes 11-30 contain red oak samples from Wahnapitae Hydro Dam population. 70 3.4 Discussion Determining plant sustainability is a critical component in monitoring land restoration effectiveness. Because the long term effects of the restoration process occurs over an extended period of time, continual assessment of metal content and its effects on biota is essential. The foundation for ecosystem sustainability relies on the genetic variability of its species. A decline in genetic variability may stunt the species gene pool and therefore decreases its chances of survival under environmental stressesors. In the present study, northern red oak samples from 13 populations were analyzed using ISSR markers to determine the level of genetic variability. ISSRs target microsatellite sequences found in the eukaryotic genome. These regions are known to evolve rapidly and are therefore deemed good tools for studies in genetic diversity of various organisms (Blair et a i, 1999). The sites were chosen on the basis of varying distances from smelters and thus reflected varying contaminant loadings. Data obtained from the ISSR marker system was used to calculate percentage of polymorphic loci within and among populations, observed number of alleles (Na), expected number of alleles (Ne), Nei’s gene diversity (h), Shannon’s information index (I), total gene diversity (Hj), mean gene diversity between populations (Hs), variation among populations or gene differentiation (G s t ) and the estimated gene flow (Nm). The ISSR analysis revealed levels of polymorphic loci ranging from 43.97% to 64.54%. This level of polymorphism varied with primers used. Primer UBC 825 generated the highest level of polymorphic loci at 73%, whereas primer ISSR 5 generated the lowest level of polymorphic loci at 48%. Overall the level of genetic variability within the population analyzed was moderate to high. Red oak populations are commonly known to have high hybridization 71 and introgression rates (Chokchaichamnankit et al., 2008), they maintain a high level of genetic diversity (Muller et al., 2004). There were no significant differences in polymorphisms observed between populations from limed and unlimed areas or between populations located at different distances from smelters. This confirms previous studies on conifer populations growing in Northern Ontario (Narendrula et al., 2012; Vandeligt et al., 2011; Dobrzeniecka et al., 2011). This lack of significant differences for genetic variability among populations suggests that the level of metals in plant tissue is too low to affect the allelic frequencies within the targeted population. The level of inter-population polymorphism was 97.87%. The observed number of alleles (Na) and the expected number of alleles (Ne) were calculated based on ISSR data. Na measures the number of alleles based on the raw data obtained from ISSR analysis. Ne measures the expected number of alleles that should be observed within the populations using the value of Na. Both Na and Ne have a scale of 0 to 2. Values closer to 0 indicate homozygosity and values closer to 2 indicate high heterozygosity. The mean values for Na and Ne in this present study were 1.54 and 1.22 respectively with Na being the higher value. Nei’s gene diversity (h) was also determined for each locus and for all loci, h measures the number of different alleles in a population and the value ranges between 0 and 1. Values closer to 0 indicate that the population is monomorphic and there is no allelic difference. Values closer to 1 indicate a polymorphic population where alleles of equal occurrences are found over different loci. The mean value of h for red oak was found to be 0.14. This low value and means that the red oak populations of the Sudbury area are monomorphic with alleles of equal frequencies occurring in most, or all, loci. There is very little genetic variation in the populations. 72 Shannon’s information index (I) was calculated to determine the abundance and distribution of alleles within red oaks populations. This index ranged from 0 to 1, where values closer to 0 indicate an uneven distribution of alleles and values closer to 1 indicate an even distribution of alleles and an abundance of species among the populations. The data from the present study (Shannon’s index of 0.22) indicate an uneven distribution of alleles in the populations. This suggests a low phenotypic diversity. The total gene diversity (HT) and the mean gene diversity between populations (Hs) were 0.21 and 0.14, respectively. The level of population differentiation(G s t ) was 0.34 (34%). This means that most of the total variation is attributed to within population variation. The estimated gene flow calculated from G s t was 0.98. This value indicates there is little transfer of genes among red oak populations within this region probably because of population fragmentation and isolation. The genetic distance matrix was calculated using the Jaccard’s similarity coefficient analysis. Values of this matrix range between 0 and 1, where values closer to 0 indicate that populations of interest are genetically similar and values closer to 1 indicate genetic difference. The genetic distance values in the present study ranged from 0.215 to 0.611. The red oak populations are both native to the region and were also planted during the regreening projects. The similarity of genetic variations for the targeted populations can be in part attributed to the fact that red oaks which were planted had come from nursery stocks originally growing in the Sudbury region. Most of the populations were established from seeds of northern provenance obtained from the Ontario Ministry of Natural Resources (Winterhalder, 1996). The Daisy Lake Limed and Kukagami cluster was separated from other groupings with 100% degree of confidence. Capreol and Falconbridge were also grouped together 73 with a high degree of confidence. Likewise, the Airport population clustered with Onaping Falls and St. Charles populations. Overall the genetic distance and dendrogram revealed that the red oak populations in the Greater Sudbury Region are neither very closely related nor genetically distant. But there is enough variability within and among population to sustain environmental challenges. 74 Chapter 4: General Conclusions The effects of metal toxicity in plants have been documented in numerous studies and found to be detrimental to plant health. Physiologically, excess nutrient concentrations may cause wilting or chlorosis and ultimately death. The present study aimed at monitoring the long term effects of reclamation in the Greater Sudbury region. This was done through soil and plant metal analysis and determination of genetic variability. The results of the present study revealed that the highest concentrations of metal and nutrients were observed in the topmost organic horizon, LFH. The proportion of total metals that was bioavailable and readily available to plants was very small. The level of metal content in the top soil layer was dependant of both land topography and the site distance from smelters. The concentrations of metal in plant tissue were found to be higher than the bioavailable metal in soil. The enrichment factor (EF) and translocation factor (TF) were estimated. The EF values varied between 0.702 and 16.78 indicating environmental pollution. The TF values from soil to branches were low for most elements and the accumulation of elements was found greater in leaves of red oak populations than branches. This suggests that red oak is likely not the species of choice for bioremediation. The pH of limed and unlimed areas were analyzed and compared to determine whether the soil liming 30-40 years ago still has an effect on soil toxicity and plant growth and survival. The pH levels of limed areas were found to be higher, an indication of the prolonged beneficial effect of liming 30 to 40 years ago on soil chemistry. The genetic component of the present study was determined using ISSR markers. The results showed that the polymorphism in red oak populations in the Greater Sudbury region was moderate ranging from 43.97-64.54%. There were no significant differences 75 in polymorphisms between areas that were limed and unlimed or between sites located at varying distances from smelters. The genetic variability of red oak populations were therefore not affected by geographical location or soil conditions. Likewise, there were no associations between the level of metal accumulations in soils and the levels of genetic variability in targeted populations. 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Genome fingerprinting by simple sequence repeat (ssr)-anchored polymerase chain-reaction amplification.Genomics, 20: 176-183. 81 Appendeces 82 Table 20: Enrichment factors of total metals with significantly different mean concentrations between Eroded/Disturbed and Control sites. Elements Al As Cu Ni Enrichment 0.702 16.78 4.98 2.94 Factor Table 21: Enrichment factors of bioavailable metals with significantly different mean concentrations between Eroded/Disturbed and Control sites. Elements K Mn Sr Zn Enrichment 0.278 0.174 0.087 0.149 Factor 83 Table 22: The translocation factors for contaminated sites from soil to branches and branches to soil. Translocation Al As Ca Co Cu Fe K P Pb Mg Mn Ni Sr Zn factor Total metal 0.07 0.01 0.98 0.02 0.04 0.01 0.89 2.69 0.02 0.62 1.32 0.05 0.38 0.35 concentrations from soil to branches Bioavailable 18.88 1.90 28.51 4.82 4.14 3.29 94.20 266.32 3.32 8.45 41.08 7.51 138.46 32.20 metal concentrations from soil to branches 84 Table 23: The translocation factors for contaminated sites from soil to branches and branches to soil. Translocation factor Al As Ca Co Cu Fe K P Pb Mg Mn Ni Sr Zn Total metal 0.02 0.18 1.53 - 0.04 - 0.53 0.90 0 0.4 1.4 0.01 0.36 0.29 concentrations from Soil to Branches Bioavailable metal 3.17 0 32.39 - 3.71 - 13.63 11.45 0.61 10.63 10.75 0.69 19.93 5.54 concentrations from soil to branches 85 lk h r 1 2 3 4 5 6 7 8 9 10 11 12 >3 14 15 16 17 18 19 20 2122 23 24 25 26 27 28 29 30 31 2000bp 650bp lOObp Figure 11: ISSR screening analysis illustrated on 2% TBE agarose gel for red oak DNA samples. Each primer amplified sample 1 from Daisy Lake, Wahnapitae Hydro Dam, Laurentian, Kukagami, Kingsway, Falconbridge, Capreol. Lanes 1, 10, 19, 28 and 37 contain lkb+ ladder; Lanes 2-9 contain amplified DNA from ISSR 10; Lanes 11-18 for ISSR UBC 809; Lanes 20-27 for ISSR 15; Lanes 29-36 for ISSR 9. 86 Table 24: Mean polymorphic percentages for limed and unlimed sites. Site Limed Unlimed Daisy Lake 51.77% 52.48% Dam 51.77% 54.61% Kingsway 54.61% 58.87% No significant difference between treatments based on t-test (p > 0.05) Table 25: Mean polymorphic percentages for sites less than 5km, between 5 and 15 and more than 5km from the smelter. Less than 5km 5-15km from smelter More than 15km 52.13 51.77 64.54 53.19 56.03 43.97 61.70 56.74 51.06 48.94 No significant differences between treatments based on ANOVA test (p > 0.05) 87 Table 26: Metal concentration guidelines for soil according to the Ontario Ministry of Environment and Energy (OMEE). Substances Ontario Sediment Quality Guidelines (mg/kg) Lowest Effect Level Severe Effect Level Arsenic 6 33 Cadmium 0.6 10 Cobalt 50 Copper 16 110 Iron 2% 4% Lead 31 250 Manganese 460 1100 Nickel 16 75 Zinc 120 820 88 15 km) ±53.6 ±0 ±80.6 ±0 ±0.8 ±13.9 ±37.6 ±20.9 ±0 ±9.51 ±12.2 ±94 ±1.4 ±0.6 ±1.1 ----- *------— Results are expressed as mean values ± standard error based on three replicates (n = 3) Means in columns with a common subscript are not significantly different based on Tukey multiple comparison test (p > 0.05). Eroded/Disturbed sites: Daisy Lake, Wahnapitae Hydro Dam, Falconbridge; Stable upland sites: Laurentian, Kukagami, Kingsway; Control sites: Capreol, St. Charles, Onaping Falls.